The activity and composition of the gut micro-biome is also affected by an individual’s attitudes, taste preference, and dietary habits that are likewise influenced by culture, the global food industry, and media. Furthermore, there is growing evidence that the human diet has undergone profound simplification since industrialization, which has occurred too recently on an evolutionary time scale for the human genome to adapt.This maladaption to the modern diet has been hypothesized to be the underlying evolutionary origin of “civilization diseases,” such as cardiovascular disease, in the 21st century.The gut micro-biome is remarkably stable and shares a high degree of functional capability across all human healthy individuals; however, intestinal bacterial communities are diverse and variable from person to person.For example, intraindividual variability of the fecal micro-biota is consistently lower than between-subject variability. Recent discoveries of greater similarities in gut micro-biota between monozygotic and dizygotic twin adults or between family members versus unrelated individuals highlight the powerful impact of shared environment, lifestyle, and diet as a whole on intestinal microbial configuration.Interestingly, in mice, genetics was shown to play less of a role than diet on the gut microbial community.Age and health are also associated with alterations to the intestinal micro-biota that might explain interindividual differences as well.In general, dietary effects on the intestinal micro-biota can occur on short and long time frames. An acute influx of energy and nutrients is assumed to induce bacterial blooms in a short time frame. As expected, short-term dietary modulation in a humanized gnotobiotic mouse model resulted in a significant shift within the micro-biome in a single day.A similar change in fecal micro-biome within a day of a dietary change was confirmed in a controlled-feeding study of 10 healthy volunteers.Likewise,nft hydroponic system in as short as 3 days, dramatic changes in the community composition of the gut micro-biome occurred with alterations in calorie content of the diet for several individuals.

Long-term, diet-driven structural and functional differences in the microbial community are apparent in populations from different geographic areas with very distinct dietary patterns. Studies employing culture-based and culture-independent methods found significant global differences in the fecal micro-biota from individuals in different cultures.For example, children from Burkino Faso practice a diet with high fiber and low animal protein and fat, consisting mainly of cereals, legumes, and vegetables. Italian children practice a typical Western-style diet characterized by high animal protein, simple sugars, starch, and fat with less vegetables and fiber than the diet in Burkina Faso. The microbial composition of children from Burkina Faso revealed higher levels of Prevotella and Xylanibacter , Treponema , and Butyrivibrio , which were absent in the Italian children.A similar observation was reported in a comparison of Bangladeshi and American children. Bangladeshi children, who consumed a diet similar to that of children from BurkinoFaso, exhibited a significantly greater bacterial diversity and distinct microbial community composition enriched in Prevotella, Butyrivibrio, and Oscillospira and depleted in Bacteroides in comparison with American children.Both children and adults from the United States have very different micro-biota from rural communities in Malawi and Venezuela. A typical U.S. diet that is rich in protein differs from the diets of Malawians and Venezuelan populations that are dominated by maize, cassava, and other plant-derived polysaccharides. The major change in macronutrient composition may contribute to the higher bacterial diversity of those in Malawi and Venezuela compared to adults living in U.S. metropolitan areas. Comparative studies between different geographic regions have been challenged with multiple dependent factors such as socioeconomic status, genetics, dietary habits, age, hygiene, food quality, pathogen exposure, history of antibiotic use, body composition , stress, physical activity, and other environmental conditions.

Despite ethnic and geographical variation, both comparative and controlled feeding studies conducted in the United States and Africa 63 revealed similar patterns of the Bacteroides−Prevotella balance based on diet. Global macro-nutrient profiles are recognized to modulate the intestinal microbial community. In a study charactering human fecal samples from 98 individuals, Wu et al. found that saturated fat and animal protein decreased microbial diversity and enriched the abundance of Bacteroidetes and Actinobacteria, whereas a plant-based diet with high carbohydrates increased microbial diversity and was linked with Firmicutes and Proteobacteria abundance.In a recent study, gnotobiotic mice colonized with 10 human intestinal bacterial species were provided diets containing various percentages of protein , fat , polysaccharides , and sucrose.Intriguingly, the authors were able to explain over half of the variation in species abundance in the fecal micro-biome depending on the food ingested, even when the mice were fed more complex diets.Recent evidence suggests that extreme changes in carbohydrate intake will lead to a shift in the composition of human gut micro-biota. Although reports of the relative proportion of Bacteroidetes and Firmicutes with respect to carbohydrate intake are contradictory in several studies,certain genera and bacterial families are associated with levels of carbohydrate consumption. For example, in human obese subjects, a declining carbohydrate intake induced a marked progressive decrease of a butyrate-producing subgroup of Clostridial cluster XIVa as well as bifidobacteria.A reduced-carbohydrate, high-protein diet resulted in decreased proportions of butyrate and total shortchain fatty acid by reducing butyrate-producing bacteria such as the Roseburia/Eubacterium rectale group.Likewise, Bifidobacterium levels decreased in mice fed a low-carbohydrate, high-fat “Atkin’s style diet” compared with their counterparts consuming a high-carbohydrate, high-fiber, and low-fat diet.More detailed documentation of diet-induced specific changes on the gut microbial relative abundance was reviewed by Krajmalnik-Brown et al.

Although many inconsistent results have been observed regarding the impact of diet on phylumwide changes in gut micro-biota composition and energyharvesting capacity, many have suggested that the complex relationship might involve the severity of obesity, microbial adaptation to diet over time and perhaps an age−microbial interaction. Notably, the high-fat, low-fiber diet has also been recognized as a well-established model of obesity;thus, the impact of differences in caloric consumption and subsequent response from host metabolic perturbations through weight change needs to be considered. Studies on experimental animals need to control for body mass and composition, which will allow a better comparison of the gut micro-biota without the confounding effects of weight/ adiposity.Although it appears that the overall macronutrient profile affects general patterns of fecal micro-biota, understanding the responses of intestinal microbial communities to major dietary composition presents an additional set of challenges. For example, a carbohydrate-rich diet is often accompanied with elevated dietary fiber intake and a low percentage of protein and fat; hence, the microbial composition should respond to the complex profile of the dietary structure instead of the shifting of a single dietary component. If not specifically controlled, dietary factors will affect the gut micro-biome in both energy intake and relative proportion of macronutrients in the diet. Recently, interest in microbial response to major dietary composition has re-emerged in many reviews.In this section, we will explore the complex influence of dietary structure on the gut micro-biome including gluten-free diet, vegetarian/vegan diet, and food restriction.To determine the effect of a gluten-free diet on the gut micro-biome, a crossover study involving 10 healthy subjects consuming a conventional diet without any restriction,hydroponic nft system except for gluten-containing products, resulted in a reduction in bacterial populations that are generally regarded as beneficial for human health such as Bifidobacterium and Lactobacillus, as well as an increase in opportunistic pathogens such as Escherichia coli and total Enterobacteriaceae.The observed changes might be explained by the associated reduction in polysaccharide intake that may have prebiotic action for certain bacteria. Provision of a gluten-free but polysaccharide- and probiotic-rich food intake could avoid this situation and provide better support to balance gut micro-biota.81Several small-scale culturebased studies examined the effect of a vegetarian diet on the composition of the human gut micro-biota.However, results from these studies offer no clear consensus.A crossover study reported that a Western-style diet high in meat facilitates the growth of Bacteroides, Bifidobacterium, Peptostreptococcus, and Lactobacillus spp. compared to a vegetarian diet.Similarly, elevated Bacteroides spp. levels were observed in a 4 week highbeef diet.Dietary modulation of 12 healthy male subjects with either mixed Western, lacto-ovo vegetarian, or vegan diet in a 20 day crossover study revealed significantly lower fecal lactobacilli and enterococci in the vegetarian diet than in the other two diets. Hayashi et al. reported a predominance of bacteria from the Clostridium cluster XVIII, in addition to high levels of bacteria from Clostridium clusters IV and XIVa in the fecal micro-biome of a strict vegetarian woman.However, Liszt et al.and Kabeerdoss et al.report that the proportions of Clostridium clusters IV and XIVa are lower in vegetarians. The inconsistent findings from these studies might be due to the use of different experimental methods, the limited number of individuals in these studies, or poorly matched control groups.The stool pH was lower among 250 subjects on strict vegan or vegetarian diets with equal numbers of age- and gender-matched control subjects compared to individuals consuming ordinary omnivorous diets, and this likely inhibited the growth of E. coli and Enterobacteriaceae in vegetarian/vegan subjects.

Furthermore, it has been established that microbial− mammalian co-metabolites may be measured in urine that may provide information concerning intestinal microbial metabolic activities.90 Clear metabolic differences in urine associated with the vegetarian and omnivorous diets have been observed, with creatine, carnitine, acetylacarnitine, and trimethylamine-N-oxide being elevated in a highmeat diet and p-hydroxyphenylacetate increased in a vegetarian diet.A 40% calorie restriction in mice for 9 weeks revealed small changes in fecal anaerobic populations using fluorescent in situ hybridization and denaturing gradient gel electrophoresis .Similarly, using conventional anaerobic culture of rat feces,small changes in fecal anaerobic bacterial populations with no significant difference in the bacterial cellular fatty acid profile were observed after caloric restriction.Patients with rheumatoid arthritis who participated in an intermittent modified 8-day fasting therapy also exhibited no changes in the fecal bacterial counts of clostridia, bifidobacteria, Candida, E. coli, Enterococcus, or Lactobacillus. Interestingly, the Lactobacillus spp. and archaeon Methanobrevibacter smithii counts were elevated in anorexia patients compared with healthy controls, and this difference was associated with the increased efficiency in removal of excess H2 from the human GI tract. In hibernating ground squirrels, the relative proportion of Firmicutes was decreased relative to Verrucomicrobia and Bacteroidetes after several months of fasting.Follow-up studies need to address the impact of food restriction in both the short- and long-term scale and the global significance of these changes in the intestinal micro-biota.In normal healthy individuals, the large intestine receives contents that escape from the terminal ileum, which are subsequently mixed and retained for 20−140 h to provide an opportunity for microbes to ferment a range of undigested dietary substances. The transition time through the colon strongly influences the gut microbial community, which has been correlated with stool weight and excretion of bacterial dry matter. Although few data exist on the nutrients that enter the colon from the small intestine, generally, about 85−90% of dietary sugar and starch, 66−95% of protein, and almost all fat are absorbed before entering the large intestine depending on genetics and other dietary factors . It is well established that dietary intake of non-digestible material, in combination with host-derived peptides,bile acids,and mucin,influences microbial anaerobic fermentation activity and microbial population in the colon. Increasing evidence supports that shifts in the microbial composition occur in response to changes in the content of the diet. Such changes can be expected to result from differential effects of substrates on stimulating or inhibiting microbial growth. Perhaps one of the greatest challenges in nutrition is to interrogate the interaction between the complex food matrices that integrate a wide range of biologically active compounds. This raises the question of whether there are specific dietary ingredients that have stronger selective forces on microbial diversity and configuration of functional communities than others. Dietary fiber and complex carbohydrates consist of nonstarch polysaccharides, such as resistant starch and oligosaccharides, as well as edible indigestible plant components that are resistant to digestion by endogenous enzymes in the small intestine and become the primary source of microbial fermentation, particularly in the large intestine.The effect of dietary fiber has long been proposed to contribute to human health through prebiotic enhancement of certain beneficial microbes that produce butyrate,absorb bile acids,decrease colon pH,112 and promote GI motility via shortening of the mean transit time.However, not all dietary fibers have the same effect, which is dependent on their physicochemical characteristics.The prebiotic effect of indigestible polysaccharides on gut micro-biota has previously been broadly discussed.

Sodium also increases the expression of the COX2 enzyme, which synthesizes oxylipins. In NP1, sodium may play a role in shifting the oxylipin profile towards LA-related oxylipins, leading to the protective association of NP1. NP1 was characteristic of a diet high in LA , and also explained more variation in oxylipin PC1 compared to oxylipin PC2. Oxylipin PC1 represented LAand ALA-related oxylipins and was associated with a decreased risk of T1D, which may explain the higher loading value for LA. In The Environmental Determinants of Diabetes in the Young study, higher levels of LA in the erythrocyte membranes was associated with a reduced risk of IA in non-breastfed infants, suggesting a role of LA in the pathogenesis of T1D. LA has been linked to other inflammatory conditions. Mendelian randomization studies demonstrate that LA may reduce inflammation in asthma and reduce the risk of autoimmune disorders. Although LA and ARA are n6 FAs, which are generally associated with promoting inflammation, LA also plays a role in resolving inflammation. LA reduces the mitochondrial damage inflicted through streptozotocin. The difference between an LA- and ARA-related oxylipin profile may be related to resiliency to stressors through the promotion and resolution of inflammation, which has been proposed as a model for health. Oxylipins have been used as markers of this resiliency to stress. LA-related oxylipins exhibit both pro-inflammatory and pro-resolving effects . The protective effect of LA-related oxylipins may represent a child’s ability to respond to a stressor through the promotion and subsequent resolution of inflammation. ARA-related oxylipins, in contrast,blueberry grow bag size do not demonstrate the same pro-resolution properties as LA-related oxylipins. NP1 explained 9.5% of the variation in genetically adjusted PC1 and 0.01% of the variation of genetically adjusted PC2, so this nutrient pattern may be measuring a diet that promotes a state of resiliency to stress.

This is a similar percent explained in other RRRs with biomarkers as response variables and similar factor loadings to other RRR-derived dietary patterns. The protective association of NP1 on the T1D risk did not replicate in the full DAISY cohort. One explanation may be limited power. There was a smaller proportion of cases of T1D to people without T1D in the cohort. NP1 may have a small impact on the oxylipin profile and, thus, on the risk of T1D. A larger sample size may be needed to capture this small difference in risk. Additionally, genetic factors and environmental triggers may have larger and more lasting impacts on the oxylipin profile, and these environmental triggers instigating inflammation may be a more potent target for reducing T1D risk. The nested case-control study may not be representative of the full cohort. There were T1D cases that were included in the analysis in the DAISY cohort, but were not included in the case-control, because these participants did not have measured oxylipins. The background characteristics of these T1D cases may be different than those in the nested case-control study. The average age of the T1D onset of the cases that were in the cohort analysis was 13.96 ± 7.25 compared to an average age of the T1D onset of 9.67 ± 4.49 in the nested case-control study. The pathophysiology of the development of T1D, as well as the serum vitamin D levels and genetic risk factors has been shown to be different in early-onset compared to late-onset T1D. Additionally, when developing the nutrient patterns in the case-control studies, we used the intercept as a summary measure, which did not incorporate the standard error of the summary measure, and a joint Cox PH model was used to test the nutrient pattern, which did incorporate the standard error. Incorporating this uncertainty when using the joint Cox PH model may have led to the inability to replicate the findings. Inflammation is also a dynamic process, as is the synthesis of oxylipins. Using the summary measures may not adequately capture these fluctuations in oxylipin synthesis in response to an inflammatory stimulus.

We utilized all the dietary measures and did not restrict them by age, but there may also be a critical time window during which an oxylipin-related diet might be effective. The strengths of this study include multiple measures of diets throughout childhood, as well as multiple measures of numerous oxylipins. An additional strength was the ability to adjust for the genetic influences on oxylipins and the oxylipin profile. The limitations include the small sample size in the nested case-control studies and a lack of the generalizability, given that DAISY is a cohort of children at an elevated risk of T1D compared to the general population, owing to a selection based on a genetic risk factor and family history of T1D. Lifestyle choices such as diet and physical activity can create risk factors for several chronic diseases including cardiovascular disease , diabetes, and certain cancers. Worldwide, chronic diseases are projected to cause USD 17.3 trillion of cumulative economic loss between 2011 and 2030 due to increased healthcare expenditures, reduced productivity, and lost capital. Prevention and risk-reduction strategies, including dietary recommendations, are crucial to stem this burden. In addition to guidelines on items to avoid, emphasis on health-promoting foods that complement current dietary strategies is key to the prevention and treatment of numerous chronic diseases. Current dietary guidelines advocate beneficial patterns that share several key characteristics, including abundant intakes of fruits, vegetables, nuts and seeds, legumes, and whole grains, as well as seafood, yogurt, and vegetable oils, while minimizing the intake of red and processed meats, refined grains, starches, and added sugars. Fruits and vegetables are rich in many essential nutrients and other bio-active compounds that can provide protection against many chronic diseases. Dietary recommendations promote the consumption of at least five to nine servings of a variety of fruits and vegetables per day in a 2000 kcal diet, which provide abundant amounts of vitamins , minerals ,fibers, and a diversity of bio-active phytochemicals such as polyphenols and carotenoids. An increased intake of polyphenols, particularly flavonoids, has been associated with a decreased risk for CVD through improved endothelial function, and a reduction in platelet reactivity, low-density lipoprotein [LDL], and blood pressure.

Date palm fruit , a species of the family Arecaceae that is rich in many essential nutrients and polyphenols, is one of the most commonly consumed fruits in the Middle East and North Africa. Date palm fruit, which is termed simply as dates in this review, is cultivated throughout the Middle East and to an increasing degree in other regions of the world including parts of Central and South America, Europe, India, and the United States. Consumer demand for dates continues to increase. The top countries produced about 3.5 million metric tons in 1990, around 6.5 million metric tons by 2000, and in excess of 7.5 million metric tons by 2014. Several biological activities, proposed mainly based on in vitro and animal models, have been described with respect to potential health effects of dates. These include support of oxidant defense, anti-inflammatory and gastroprotective effects , and anticancer activity. With the high incidence of CVD and diabetes worldwide, a comprehensive review of dates and their potential value in promoting vascular health is timely. Here, we focus on the roles of dates to affect markers of cardiovascular function, with particular attention to their beneficial actions in humans. Future research directions concerning dates are also suggested. Date trees are among the oldest in the world, and are an important fruit crop in Middle Eastern countries. Dates have significant religious importance for Muslims, where the fruit is mentioned in many sections of the Holy Quran for its nutritional and medicinal values. This fruit has been used traditionally to break the fast during the holy month of Ramadan in Arabic and Islamic countries. The earliest examples of the use of dates in the Middle East come from two sites, Sabiyah in Kuwait and the island of Dalma in the United Arab Emirates,blueberry box as evidenced by carbonized date seeds and stones. Dates have a special social status among Middle Eastern countries and with Arabs in general, as dates and date-based foods are served during most auspicious occasions and events, such as weddings, births, family gatherings, and religious holidays. Although dates are admired for their nutritional and health-promoting properties by the natives of the Middle East and northern Africa, the fruit is less recognized in other regions of the world due in part to limited scientific documentation derived from Islamic prophetic traditions. Iraqi dates also varied, ranging from 331 to 475 mg GAE/100 g, which are concentrations higher than other fruits such as apple, blueberry, orange, pomegranate, papaya, banana, and red grape. In contrast, others have reported that the polyphenol content in the earlier stages of date ripening to be similar to that in apples, but lower than that in an extract of various citrus fruits. Delineating the composition, variety, and ripening stage of dates and their bio-active fractions is important when designing and interpreting research studies. For consistent compositional reporting, standardization of extraction and analytical methods is needed. Dates are relatively rich in kilocalories and contain a substantial percentage of carbohydrates , which are predominately glucose , fructose, and sucrose. The fruit also contains a significant amount of dietary fibers including pectin, hemicellulose, lignin, resistant starch, and soluble fiber. Around 100 g of dates, equivalent to seven to nine fruits, provide 25–30 g of dietary fiber, which is 100% of the current US recommendations.

A variety of micro-nutrients are found in dates, including vitamins A, B-complex and C, and minerals such as calcium, magnesium, copper, sodium, phosphorus, zinc, selenium, fluorine, potassium, and iron. Variability in the polyphenol content of dates exists, as well as in the macro- and micro-nutrient levels, depending on the cultivar and degree of ripeness, along with geographic location and environmental conditions. Worldwide, CVD is the leading cause of death, taking an estimated 17.8 million lives in 2017, and is expected to account for more than 22.2 million deaths in 2030. An estimated 54% of deaths from noncommunicable disease in the eastern Mediterranean region are due to CVD and by 2030, an estimated 44% of the US population is projected to suffer from some form of CVD. Age-standardized prevalence rates of CVD per 100,000 for both sexes are particularly high in North Africa and the Middle East, Central Asia and North America, ranging between about 7066 to greater than 9266. A number of risk factors are associated with the development and progression of CVD. While constitutional risk factors such as family history, age and sex cannot be controlled, lifestyle factors related to hypercholesterolemia, hypertension, hyperglycemia, obesity, physical inactivity, and smoking can be modified and can significantly impact cardiovascular health. The presence of cardiac risk factors can be associated with vascular changes, and ultimately, the development of atherosclerosis, the underlying pathological process of CVD. Atherosclerotic CVD is a chronic inflammatory disease and disorder of lipid metabolism, initiated by endothelial dysfunction and damage promoted by immune-related mechanisms that interact with platelets, leukocytes and low-density lipoprotein cholesterol to initiate and propagate formation of lesions. Vascular homeostasis is maintained, in part, by the vasodilators nitric oxide , prostacyclin, endothelial derived hyperpolarizing factors, and vasoconstrictors such as thromboxane and endothelin-1. These mediators also help regulate smooth muscle cell proliferation, inflammation and platelet activation. In general, endothelial dysfunction occurs due to a disruption of the balance and regulatory function between vascular smooth muscle relaxing and contracting factors, growth promoting and inhibiting factors, and pro- and anti-atherogenic factors, characterized as a state of endothelial activation. Diet and physical activity are essential components of a healthy lifestyle, which play important roles in the primary and secondary prevention of chronic diseases such as CVD. Several bio-active dietary components are present in heart-healthy dietary patterns abundant in fruits, vegetables, nuts/seeds, and whole grains, including mono- and polyunsaturated fats, essential vitamins and minerals, phytochemicals such as polyphenols, and a variety of non-digestible carbohydrates that either aloneor through their interactive effects are thought to promote cardiovascular health. Understanding how specific plant foods may be beneficial can provide further insight for future refinements of dietary and public health recommendations, especially since fruits and vegetables vary greatly in their profile of bio-active compounds.Most studies on the vascular-related effects of dates have focused on cholesterol and lipid regulation, and oxidant defense and inflammatory responses .

Considering a lack of homogeneity among studies, several research considerations would improve the generalizability of results from randomized clinical trials. For example, dose-dependent trials are warranted to assess minimal and maximal dose effects along with identifying potential negative effects from higher doses. Additional repository databases should be developed not only to report studies, but also to archive raw data and results to allow future ancillary analyses. This would allow for comparison and merging of results, thus increasing the total sample size,13 thereby increasing statistical power. Further, standardization in biomarkers of intake and exposure to flavan-3-ols is warranted. For example, γ -valerolactones, a flavan-3-ol metabolite formed by the colonic micro-biome, can be used as markers of chronic flavan-3-ol intake . Future research should also include more diverse populations to assess interindividual variability for optimizing dietary recommendations and food product development, especially for specific population subgroups. Further, although this guideline was developed from research on the general adult population, additional research evaluating flavan-3-ol intake earlier in the lifespan is warranted because dietary habits adopted earlier in life can contribute to the magnitude of effect of flavan-3-ols on cardiometabolic health. In conclusion, when quality evidence is available to make an evidence-based intake guideline,plastic flower pots such a recommendation can inform multiple stakeholders including clinicians, policymakers, public health entities, and consumers. Evidence gaps identified in the review process can inform scientists, thereby guiding future randomized clinical trials.

In summary, upon review of data from human studies reporting effects of foods rich in flavon-3-ols, the Expert Panel found moderate evidence supporting cardiometabolic protection resulting from flavan-3-ol intake in the range of 400–600 mg/d. It should be noted that the beneficial effects were observed across a range of disease biomarkers and endpoints; furthermore, this is a food-based guideline and not a recommendation for flavan-3-ol supplements.Horticulture likely originated 20,000years ago. There are over 100 species of horticultural crops, consisting of diverse fruits, vegetables, and tubers, many of which are of high economic value with enormous production volume worldwide. The amounts of fruits, vegetables, and tubers produced in 2018 were 868, 1089, and 832 million tons respectively , and the increased demand from a growing, and a fluent global population, is predicted to drive further expansion of horticultural output. Horticultural crops not only provide basic calories , but also, are among the most crucial sources of fiber, organic acids, micro- and macro minerals, vitamins, and antioxidants in human diets. Healthy attributes, and a wide range of tastes, textures, and favors make horticultural crops attractive. Starch is the dominant energy source in the human diet, providing over 50% of our daily caloric needs. In the food industry, starch is widely used as a thickener, stabilizer, lipid replacer, defoaming agent, gelling agent, emulsifer, and dietary fiber, and in the pharmaceutical industry, starch is used as an excipient for drug delivery. In addition to these diverse uses, starch is an excellent renewable material for making ethanol bio fuels and degradable ‘bio plastic’ products. Starch is almost ubiquitous in higher plants, including horticultural crops, in ways that may or may not be noticed. For instance, potato, sweet potato, yam, and cassava are starchy, but spinach, lettuce, and ripe tomatoes, berries, and citrus are not, yet starch is likely to be important to the growth, development and fitness of all of these crops, as they are in better studied models. The widely accepted view is that starch accumulates either in a transitory state, or for long-term storage starch. Transitory starch follows a diurnal pattern: it is synthesized and accumulated directly from the products of photosynthesis in the leaf and in the stem during the daytime, and is then degraded into sugars as an energy source for the following night.

In comparison, storage starch is defined as that located in perennating organs such as seeds, grain, embryos and tubers, where it provides sustenance for the next generation during germination and sprouting in sexual and asexual propagated crops, respectively. A third class of starch: ‘transitory-storage starch’ has been proposed. It describes starch that is accumulated and degraded during development in the storage organ. Transitory-storage starch is a feature of many species including horticultural crops of economic value such as tomato, banana, kiwi, strawberry, nectarine, and apple fruit. Starch accumulates as semi-crystalline, water insoluble granules that vary in diameter from 1 to 100μm depending on species. Starch is organized into two glucan polymers: amylose and amylopectin. Amylose and amylopectin consist primarily of linear chains of glucoses joined by α-1,4-glycosidic bonds. In amylopectin, the α-1,4-glucan chains are branched more frequently through α-1,6-glycosidic bonds, compared to amylose. The branching of the amylopectin chains is such that chains of different lengths are produced: short, medium and long chains, and the frequency with which each fraction occurs influences starch functionality. Side chains of amylopectin form clusters around branching points, and two adjacent chains make up a double helix. These physical features of amylopectin polymers leads to a semi-crystalline granule; amylose with a randomly coiled conformation, fills the matrices within the granule. Amylopectin and amylose account for around 25 and 75% of the starch in major heterotrophic storage organs, respectively, while the starch in leaf tissues is approximately 5 – 10% amylose.Amylose and amylopectin are synthesized by the coordinate action of a group of four key enzymes. The core starch biosynthetic enzymes include ADP-glucose pyrophosphorylases , starch synthases , starch branching enzymes , and de-branching enzymes , of which there are many isoforms. In brief, AGPases initiate the first step of starch biosynthesis by catalyzing the formation of ADP-glucose. SSs elongate the glucan chains in amylose and amylopectin; SBEs branch the glucan chains, while the DBEs shorten and modify the starch chains which enable a higher-order semicrystalline structure to form.

SBEs, the focus of this review, hydrolyze α-1,4-linked glucan chains, and attach the newly-created ‘free’ chain to another glucan chain within the starch granule, via an α-1,6-linkage. Through this action, SBEs largely determine the proportion of the relatively unbranched amylose to the highly-branched amylopectin. Two major classes of SBEs are bio-functionally known: SBE1 and SBE2 , and they vary in terms of their substrate selectivity, whereas the function of SBE3 awaits verification across a broader set of species. SBE1 preferentially branches ‘amylose-like’ long glucan chains as the substrate, while SBE2 prefers a more branched substrate. SBEs are the key players in the regulation of the amylose-to-amylopectin proportion in plants. However, their functions in many harvested horticultural crops have been under-investigated, although evidence points to the importance of starch in determining the post harvest quality of these crops. We aimed to develop a better understanding of the role of SBEs in fruits, tubers, and leafy greens in physiological processes by exploring SBE sequence relationships, expression, and starch phenotypes in diverse crops.SBEs have three classes of isozymes including two functional SBE classes and one putative class 3 SBE . SBE1 isoforms appeared earlier than SBE2 and SBE3 in the viridiplantae, but plant SBE1 and SBE2 are more homologous to each other, than to SBE3. SBEs have been identifed and relatively well-characterized in cereal crops, tubers, and Arabidopsis thaliana over the last two decades, but, as mentioned, little attention has been paid to the diverse group of species that are classifed as horticultural crops. Within each class of SBE,plastic garden container the cereals grouped together, while most non-cereals formed another cluster . This pattern is due to the divergence of monocots from dicots around 200 million years ago. In contrast to the presence of ‘a’ and ‘b’ sub-isoforms of SBE2 in cereal crops, horticultural plant species generally have one SBE2 isoform. It was also observed that not all species have a known or predicted class 3 isoform. The SBE sequences contained within diverse organs, i.e., fruits, tubers, roots, and leafy vegetables , clustered together based on their respective plant families. The class 1 SBE is absent in Arabidopsis thaliana, and so it was not surprising that this SBE class is not present in the Brassicaceae. However, the class 1 SBE is also absent in apple , and European olive , but these species all have two class 2 SBE isoforms . In addition, banana contains at least four types of SBE2, and transcripts corresponding to these SBE2s have been identified, indicating that they are expressed.Starch Branching Enzymes belong to the α-amylase family of enzymes, specifcally the glycoside hydrolase family 13 superfamily, with multiple isoforms encoded by different genes . The overall structure of the SBE polypeptide is highly conserved: all SBEs possess a central α-amylase catalytic domain , and an NH2- terminus, and a carboxyl- terminus. The SBE NH2-terminus contains two conserved domains: a chloroplast transit peptide for plastid-targeting, and a CBM48 domain for binding to starch. The C-terminus contains the residues that determine substrate preference and catalytic activity. The central region of the enzyme contains the “A” catalytic domain, that is made up of 8–barrels. Notably, the class 3 SBE may not directly participate in starch biosynthesis in Arabidopsis, but it has a demonstrated function in mediating cesium toxicity of photosynthesis. However, the role of SBE3 is unlikely to be conserved. In potato, StSBE3 has a unique coiled-coil motif which is absent in the AtSBE3 polypeptide . Notably, the CBM48 domain is also deficient in AtSBE3 .

It is possible that the StSBE3 may interact and complex with other starch bio-synthetic enzymes through its coiled-coil domain, in a similar way to the SS4-PTST2 interaction in Arabidopsis, the GBSS-PTST1 interaction in rice or the SBE containing protein complexes in cereal endosperm, rendering an assistant function in starch biosynthesis. This species-specifc mode of action of SBE3 may reveal a novel function of SBEs generally. Indeed, although all SBEs are predicted to form complexes with starch phosphorylases , the starch synthases and isoamylase , interactions with other proteins show differences depending on the species and SBE isoform.Four conserved regions critical for catalysis, named Regions 1-4 , are found within the catalytic A-domain . Regions 1-3 are directly involved in catalysis, while Region 4 is involved in direct substrate binding. SBE1 and 2 have largely invariant residues, but the residues in the SBE3 isoform of many species have substitutions at these sites. Post-transcriptional phosphorylation of the SBE-protein complexes formed with other starch biosynthetic enzymes has been found in cereal crops and in cassav, while experimental evidence of this regulation in the majority of horticultural crops is absent. SBE1 and SBE3 have fewer possible phosphorylation amino acid sites than SBE2 . Overall, the distinctive domain features of the SBE3 predicted protein, and the implifcations for functionality may complicate current views of SBE function, but these features may also provide an opportunity to deepen our mechanistic understanding of starch biosynthesis and regulation.Starch metabolism is tightly regulated by plants’ internal clock and the external day-night shifts, especially in photosynthetic organs where transitory starch turnover occurs on a daily basis. The transcriptional response of the SBE genes follows the circadian rhythm in photosynthetic, and, in some cases, storage tissues. Cis-elements related to circadian control and light responsiveness were universally present in all the horticultural SBEs examined . Hormones, such as abscisic acid , ethylene, salicylic acid , jasmonic acid , and sugar signals have been reported to regulate SBE activity in cereal and horticulture crops. In addition, transcription factors that belong to the WRKY, MYB, bZIP, AP2/EREBP families, may bind to their cognate cis-elements in the 5′ upstream regions of SBEs to activate or suppress transcription. However, information on the transcriptional regulations of SBE is fragmented, and putative hub genes or master regulators have not been identifed. Systemwide surveys of cis-elements and TFs in combination with in vitro and in vivo experiments could shed light on, and unearth such regulatory networks.The amylose-to-amylopectin ratio influences the textural, cooking, and nutritional properties of starchy foods, and the functionality of starch-derived bio-materials. Most of this structure-function analysis has been performed on starches isolated from cereals and tubers. However, the relative proportions, and molecular structure of amylose and amylopectin in unripe fruit may have unique properties that could have specialized applications distinct from these well-characterized starches. There may be additional markets for fruit starches if premature harvest occurs, or is desirable, due to climactic events.

Ideally, we would have liked to collect queens at the beginning of April, 1–2 weeks before B. impatiens queens are normally observed; however, the timing of field work in 2020 had to be shifted due to the onset of Covid-19 pandemic restrictions to field work, and we chose to use the same timing in 2021. In the spring, we used similar methods to determine whether queens had survived over the winter, though dead queens were far more degraded in the spring than they had been in the fall . As queens began overwintering sometime between August and mid-October, there was some variability in the amount of time queens had spent overwintering. However, most queens had been overwintering for about two months when they were checked for the first time and for 6–7 months when they were checked for the second time. For simplicity, we will refer to bee fates at these time points as survival after “two” and “six” months.We estimated diapause survival rates using generalized linear models . Statistical analyses were performed in R, version 4.0.2 . Survival rates were estimated at two time points . At two months, survival was coded based on whether the queen was found live or dead ; we assumed that the site had been abandoned if no queen was recovered when the overwintering site was excavated, as queens may desert burrows if an obstruction is encountered while digging . At six months, we analyzed survival in two ways. Our first analysis used only known-fate individuals, i.e.,flower bucket we coded survival as whether or not the queen was found live in the spring or dead either during the fall or the spring ; queens that were not recovered were treated as missing data. Our second analysis included all individuals, i.e., survival was coded as surviving if found live in spring or as dead if the queen was not recovered in the spring or was found dead in either the spring or fall.

This second way of coding the data leads to a lower estimate of survival and was of interest due to the wide difference between field and lab estimates of survival . To estimate average survival, we ft an intercept-only model to each of the three response variables: survival to two months, survival to six months and survival to six months . We tested whether survival differed among aggregations by fitting a model with aggregation ID included as a categorical predictor variable to each of the three response variables. We evaluated statistical significance using Wald chi-square tests implemented with the Anova function in the package car . We tested if queen body condition and hibernaculum depth differed across aggregations using linear models. Linear models ft to each response variable included only aggregation ID as a predictor. Similarly, we tested if rates of abandonment of hibernaculum differed across aggregations using a univariate generalized linear model . We coded aggregation ID as a predictor variable and the presence/absence of queens during the first excavation of hibernacula in the fall as the response. We evaluated statistical significance using Wald chi-square tests implemented with the Anova function in the package car .To obtain estimates of bumblebee overwintering survival from other studies, we conducted a systematic literature search on January 26th, 2022, using Web of Science and Open Access Theses and Dissertations. A total of 73 research articles and 2 theses/dissertations were obtained using the search terms: AND AND . Of these, we retained 32 studies that provided direct estimates of bumblebee overwintering survival . We scanned the introduction and discussions of each of these retained manuscripts for additional relevant studies, locating an additional 9 papers. We excluded 6 of the studies we obtained that were not published in English. A few authors presented the same data sets in multiple publications; 2 studies were excluded as duplicate data. A final study was excluded because queen survival rates could not be calculated from the data as presented.

Thus, a total of 32 studies were included in our literature review, nearly all of which were conducted in the lab. Nearly all of the studies included in our meta-analysis tested several different diapause regimes and reported queen survival rates at monthly intervals. Thus, for each set of experimental conditions reported by each study, we recorded 1) the proportion of queens to survive, 2) the sample size, 3) the length of the diapause regime, 4) the species, mating status, origin , and approximate age of queens used in each study, 5) the temperature and relative humidity that the queens were exposed to during diapause, and 6) any other details related to the experimental design . We assumed that all queens were alive at the start of each experiment; thus, we recorded survival rates of 100% for each group of queens at month 0. For papers that did not report monthly survival estimates directly in the text of the manuscript, we used the digitize package in R to extract data from figures. For studies that monitored diapausing queens continually and reported the length of time queens survived rather than monthly survival rates , we estimated monthly survival rates manually. Prior to statistical analysis, we converted survival rates recorded from manuscripts to a binomial data set of the number of successes and failures from sample sizes and percent survival at each time interval. Many of the studies included in this literature review performed treatments on queens that we thought might lead to lowered rates of survival: inoculating queens with parasites, exposing queens to chemicals, starving queens, etc. We excluded all data from treatments we deemed obviously harmful, and included only measurements for queens that were overwintered in continuous darkness at constant temperatures between 1 and 5 °C . Queens from excluded treatments had lower survival than those included in our meta-analysis . We used a generalized linear mixed-effects model , with queen survival coded as the response to estimate diapause mortality rates. GLMMs were ft using the command glmer in R package lme4 .

Our model included diapause interval as a fxed effect and random slopes for both study species and paper ID . As a basic check of model ft, we used a linear model to compare the observed and the predicted values, and estimated confidence intervals for the slope and the intercept of this model. Diapause is an important and often under-studied feature of insect populations. Our study suggests that estimates of bumblebee survival during diapause in the lab are lower than survival in the wild. Specifically, past laboratory studies of bumblebee diapause indicate that many queens are unable to survive the natural length of diapause . In contrast, we observed that more than 60% of B. impatiens queens monitored in the field survived a 6-month period of diapause. This estimate is higher than predicted for any laboratory study of B. impatiens, as well as most studies of other bumblebee species. There were a handful of studies that achieved high rates of survival after 6 months , all of which obtained queens from field colonies. Unlike the other labbased studies included in our review, Holm and allowed B. terrestris and B. lapidarius queens to dig themselves into containers of soil and other substrate placed in an outdoor greenhouse. Similarly, Milliron placed B. fervidus queens in large containers of heartwood, providing an opportunity for some queens to bury themselves in the substrate. Our field estimates of survival are also comparable to those of Pouvreau ,square flower bucket who used methods similar to Holm and reported similarly high survival rates for queens after the natural length of diapause. In combination with the findings of overwintering studies under semi-natural conditions, the results of our field study suggest that surviving diapause may be less of an ecological hurdle for queen bumblebees than previously indicated. In many ways, it is surprising that we observed higher rates of diapause survival for overwintering queens in the field compared to the lab. Among other insect species, diapause can be a period of high risk . In temperate regions, bumblebees must cope with less-than ideal temperatures in the winter; some queens may encounter additional environmental challenges during hibernation, including pesticide exposure and pathogen infection . The fact that we observed generally high rates of diapause survival may be related to the location of our focal aggregations: Appleton Farms and Grassrides is located well within the geographic range of B. impatiens, which is found throughout the Eastern United States as well as parts of Southern Canada . We also measured survival only in forests, a habitat type in which colonies produced more new queens than in meadows . It is possible that the environmental stressors experienced by bumblebees during diapause are heightened in marginal habitat types. For example, in areas near the edges of their climatic ranges, bumblebee populations are more vulnerable to decline . The northward expansion of at least one other Bombus species, B. haematurus, has been linked to warmer winter temperatures . Given that we monitored aggregations at one study site, using similar methods to monitor diapause survival rates of B. impatiens in other regions of the United States could be a valuable area of future research. At this point, it is unclear why survival rates of queens overwintered in the laboratory were generally lower than our field estimates. It may be that laboratory conditions are stressful for queen bumblebees; maintaining study organism in artificial settings can be challenging, and the ability of study subjects to thrive in the lab can depend greatly on methods of husbandry implemented by researchers . Among-study variation in survival rates was high, suggesting that some researchers were better than others at maintaining queens in the artificial settings. It is also possible that study subjects used in lab and field experiments differ phenotypically. Insect populations maintained in the lab are known to adapt to artificial conditions ; among other insect taxa , laboratory rearing has been observed to disrupt the ability of other insect species to enter diapause .

Bumblebee queens used in diapause experiments are typically obtained from colonies purchased from commercial suppliers or from colonies reared in the lab . As bumblebee queens can be induced to bypass diapause using carbon dioxide narcotization , it is possible that the selection on commercial bumblebees to undergo long periods of diapause has been relaxed. To date, no study has addressed the impacts of captive rearing on the ability of queen bumblebees to complete diapause. However, other authors have noted differences in the morphologies of wild and lab reared bumblebees , which may impact their ability to undergo diapause . Understanding how outcomes of artificial diapause are impacted by the origin of study subjects and by other husbandry strategies would be a valuable area of future research. Until best practices are better defined, we recommend that researchers leverage the methods of authors who have had relatively high rates of success in maintaining diapausing queens , i.e., by obtaining queens from field colonies and providing queens an opportunity to excavate their own hibernacula. Our field observations broadly corroborate a pattern observed by the many lab-based studies of queen diapause survival , in that survival rates of queens were dependent on colony origin/ aggregation ID. For individuals that originate from the same colony, similarities in survival rates could be explained by a multitude of factors, including relatedness, environment during development, nutritional status, and body condition of adult queens . In the field, differences in environmental conditions around nests could have also contributed to differences in survival rates.Compacted soils may have limited the ability of queens to dig their hibernacula, as queens dug themselves less deeply in the soil and greater number of hibernacula were abandoned by queens at these aggregations. These aggregations also had smaller queens, as measured by both IT span and body mass. Due to low sample sizes, we were unable to statistically separate effects of colony origin and the other ecological or environmental factors which might have influenced diapause survival . In this context, our research points to at least one major advantage of monitoring queen vital rates in the lab, in that extraneous sources of variation can be controlled in the lab , making identifying the environmental factors which impact queen vital rates in the field more straightforward.

We have also seen that taking into account hyperbolic geometry produces better low-dimensional visualizations, cf. Figure 11 and Figure 12 . Accurate representation of data across scales is a very active area of research. Special attention is being devoted to developing visualization methods that can not only cluster data in a useful way but also preserve relative positions between clusters. In particular, preserving global data structure was one of the driving factors for the UMAP method. Knowing the underlying geometry helps to position clusters appropriately and robustly map them across different runs in a visualization method. For example, the t-SNE method produces random positions of the clusters across different runs of the algorithm. This problem can in part be alleviated by additional constraints on large distances. Here we find that using a combination of a hyperbolic metric for large distances and Euclidean metric for local distances offers strong improvements in this respect. It also outperforms the recent Poincar´e map method that implements hyperbolic metric only for local distances. We notice that although h-SNE is best fit for hyperbolic data, it performs similarly as g-SNE in accuracy distances preservation. It’s future direction to further optimize h-SNE algorithm.What could be the origin of hyperbolic geometry at the large scale and Euclidean at small scale? First, any curved geometry, including hyperbolic, is locally flat, i.e. Euclidean. The scale at which non-Euclidean effects become important depends on the curvature of the space. From a biological perspective,procona valencia the Euclidean aspects can arise from intrinsic noise in gene expression. This noise effectively smoothes the underlying hierarchical process that generates the data. We find that hyperbolic effects of human gene expression can be detected by including measurements on as few as ∼ 100 probes. Why do hyperbolic effects require measurements along multiple dimensions?

The reason is that hyperbolic geometry is a representation of an underlying hierarchical process, which generates correlations between variables. These correlations become detectable above the noise once a sufficient number of measurements is made. As an example, one can think of leaves in a tree-like network, and how their activity becomes correlated when it is induced by turning on and off branches of the network. Intuitively, these correlations generate the outstanding branches of a hyperbola. We observe that these correlations can be detected by monitoring even a relatively small number of probes. This makes it possible to construct a global map of genes from partial measurements, and open new ways for combining data from different experiments. Individual olfactory receptors respond to many odor ligands, and each odor ligand evokes responses from many ORs. How the activities of ORs collectively encode natural odor mixtures remains an open question. In Chapter 1 we have demonstrated that odor molecules can be mapped onto a three dimensional hyperbolic space based on the statistics of their co-occurrence within natural mixtures, and that the principal perceptual properties of odorants, e.g. pleasantness, can be well represented by the axes in the space. This indicated that the hyperbolic embedding space of natural odorants may serve as the stimuli space for olfactory receptors. To show this we use the concentration measurements of odorants from strawberry and tomato datasets used in Zhou et al., and the OR response datasets from Hallem et al.. We combined strawberry and tomato odor datasets based on their overlapping odorants, and then selected the common odorants that are available in both natural odor datasets and receptor response datasets. The similarities of odorants in terms of OR responses were defined as the Euclidean distances of available receptor activities vectors. The co-occurrence similarities were defined as the absolute values of correlation coefficients of odorant concentrations across samples. The geometric distances of odorants were calculated using both hyperbolic and Euclidean representations of natural odorants, which are achieved by hyperbolic multi-dimensional scaling used in and Euclidean multi-dimensional scaling respectively. Figure 13 shows the correlations between the OR response similarities and odorants stimuli similarities.

The correlation is significant when using co-occurrence statistics in natural fruit samples as the stimuli, compared with the shuffling results . In the geometric representations, stimuli similarities are given by the geometric distances of the embedding points. Hyperbolic representation leads to a much higher increase of correlation compared with Euclidean representation . These findings show that OR responses capture the co-occurrence statistics of natural odorants, and that a hyperbolic model is a proper representation of odorants stimuli space for OR responses. We have shown in Chapter 2 that h-SNE outperforms other algorithms qualitatively and quantitatively in 2D visualization for Lukk data. The Lukk data is a relatively small dataset and has a limited degree of complexity. In this section, we apply h-SNE to a highly complicated dataset which contains scRNAseq measurements of very large number of cells in nine mouse brain regions. The dataset came from Saunders et al in which they used Drop-seq to profile RNA expressions in 69000 cells from nine regions in mouse brain. We analyzed the data in both a global scale which considers cells from the whole brain, and a local scale which focuses on specific brain regions. We first perform t-SNE, UMAP and h-SNE to 4500 cells equally sampled from the nine regions and visualize the global mouse brain atlas in 2D map . Some of the brain regions, such as the striatum and hippocampus, are well separated from other regions in all the three algorithms; while some other regions, such as cerebellum and substantia nigra, are broken into disconnected sub-clusters in t-SNE and UMAP embedding, and only continuously represented in h-SNE . The global structures of the disconnected components in t-SNE and UAMP are hard to detect, but a branching structure is clearly shown in h-SNE map. In h-SNE map, there are two types of regions which show distinct spatial organizations in the disk. One is called “centering region”: the cells from entopedencular, cerebellum, globus pallidus, substantia nigra and thalamus locate around the center of disks; the other type is called “branching region”: cells from the frontal cortex, posterior cortex, hippocampus and striatum stretch out from the center like branches .

Next we look at each of the nine regions separately and perform h-SNE embedding for 5000 cells sampled from each region. In these regional embeddings, cells are further separated into several sub-clusters and labeled by different colors. The cell distributions in regional mapping are consistent with the distribution in global mapping: in the five “centering regions”, different sub-clusters expand in all directions from center in the disks; while in the four “branching regions”, the sub-clusters tend to branch out in a single direction . Next we study the relationship between the cell structures and cell distributions in the disk. The cells with low gene expressions tend to locate in the center of the disk ; the granule cells in CB and dentate gyrus are small neurons and form circular shapes surrounding the centers ; cells in CA1 and CA3 of hippocampus and layer 2/3 in frontal and posterior cortex are mostly pyramidal neurons, and they form “crabs” extending to the boundaries of the disks ; polydendrocytes are glial cells and distribute like a “narrow path” going from the center to the boundary . These spatial patterns of different cell types are hard to find in t-SNE and UMAP embedding . These findings show that structurally similar cell types across brain regions are characterized by similar spatial localization patterns in the 2D hyperbolic disk. The quality of the embeddings are validated by the quantitative evaluation of data distances preservation. We calculate the correlation coefficient between the pairwise distances of the low dimensional embedding points and original high dimensional data points,flower bucket and find that h-SNE best preserves the data distances with the highest correlation coefficient across all the nine brain regions in Saunders et al . From the distances plots, we notice that h-SNE not only preserves distances with less noise , but also preserves the intrinsic geometry of the data, as can be seen in the linear distance relationships in the plots, compared with the other embeddings . In Section 3.2, we show that h-SNE embedding can characterize structure-specific cell types across brain regions, here we further study whether the method can be applied to characterize region-specific cell types across brain regions in dynamic process, e.g. cell differentiation. Marques performed single cell RNAseq for 5072 cells to study the oligodendrocytes differentiation in 10 regions of mouse central nervous system. They identified 13 cell types including: vascular and leptomeningeal cells , oligodendrocyte precursors , differentiation committed oligodendrocyte precursors , two sub-types of newly-formed oligodendrocytes , two sub-types of myelin-forming oligodendrocytes , six sub-types of mature oligodendrocytes .

These cell types represent different stages of oligodendrocytes differentiation. The authors performed t-SNE and defined the 10 regions to be immature , intermediate and mature , based on the mature cells proportions in different regions of juvenile brain. However, the classification of regions was qualitative and the differences of these “mature” regions were not explored. Here we performed t-SNE, UMAP and h-SNE on the whole dataset , and find that all the three embedding methods show clear global differentiation trajectories, but in totally different ways. t-SNE mapping is similar to the result in,where the two sub-clusters MOL1-4 and MOL5-6 are mixed together . UMAP mapping shows a branch between MFOL and MOL cells, however, this branchdoes not separate MOL1-4 and MOL5-6 since they exist in both branches. h-SNE shows a narrow path before MFOL and then “explodes” to circular shape, MOL1-4 locate at the inner circle and MOL 5-6 move further to the outer circle. Next we separate the cells based on the anatomical regions and study how the mature cells distributions differ in the five regions where mature cells abound: SN-VTA, dorsal horn, hypothalamus, cortex S1 and corpus callosum. t-SNE does not show a clear structure in the mature cells distribution in these five regions . In UMAP, the mature cells in SN-VTA and corpus callosum locate in different branches, but the cells in the dorsal horn, hypothalamus and cortex S1 distribute in both branches and cannot be distinguished. In h-SNE, we find that the mature cells of the five regions locate at different radii in the hyperbolic disk. The median embedding radii of MOL5-6 cells are larger than MOL1-4 in all the five regions, and the median radii of both MOL1-4 and MOL5-6 cells increase from SN-VTA to corpus callosum . These results show the expression patterns of the same mature cells are region-dependent in an organized way, and may provide new insights of studying cell types in different regions during the differentiation. The quality of the embeddings are also evaluated by distance preservation: the h-SNE embedding performs best with the correlation of R = 0.78 in distance plots.Nitrogen is an essential element for plant growth. The application of N fertilizers has resulted in N losses from agricultural systems into groundwater, rivers, coastal waters, and the atmosphere . Nitrate leaching and nitrous oxide emissions from agricultural soils are recognized as significant environmental threats . Nitrate leaching into rivers and estuarine ecosystems is responsible for algal blooms, eutrophication and public health risk . The greenhouse gas N2O is produced mainly during nitrification and denitrification . Nitrate leaching and N2O production from orchards have not been widely studied. If an orchard is located on light-textured and free-draining soils, receiving a high input of N the potential for leaching can be high . Our objective was to evaluate the environmental impact of upland blueberry cultivation with two different soil organic amendments regarding NO3 – leaching and N2O emissions. A 40 Lcontainer was equipped with a 5 cm thick quartz grain drainage layer on the bottom and 5 cm pine bark mulch on top of the media. A completely randomized block design with three replications was arranged for the following treatments: PM – Tateyama brown forest soil + peat moss , SC- Soil + sawdust sewage sludge compost with 5 g ferrous sulfate per L soil and SO- soil only. This study used Rabbiteye blueberry cv. ’Tifblue’ . Ammonium sulfate was applied at the rate of 134 kg/ha, divided into two applications: 45 kg/ha in July 2008 and 89 kg/ha in March 2009. The soil and plant samples were collected every third decade of each month during the growing season.

Nunney et al. previously proposed that IHR-generated genetic variation facilitated invasion of new hosts, based on the observation that all isolates from blueberry were recombinant-group X. fastidiosa subsp. multiplex. This hypothesis is further supported by the invasion of mulberry by the chimeric X. fastidiosa subsp. morus. These examples raise three additional points of support. First, given the long-term geographical association of the native X. fastidiosa subsp. multiplex with these 3 native host plants, the failure to infect them suggests that the genetic variation required for successful invasion had been absent from the native subspecies. Second, contact of these plant hosts with two newly introduced subspecies has failed to lead to infection of these plants; in all known cases of natural infection, these hosts were infected only by STs that had undergone large-scale IHR. Third, in each case, the STs found on these hosts show very little variation: blackberry, 1 ST; blueberry, 2 STs; and mulberry, 4 STs. This lack of within-host variation is consistent with host plants imposing strong host-specific selection on the bacterial genome. The data also suggest that host specificity is not determined by the lateral gene transfer of novel genetic material, since this would not impose the observed constraint on the genome. In addition, a similar pattern has been found in X. fastidiosa subsp. pauca in Brazil : evidence of large-scale IHR, combined with very limited genetic variation. From a sample of 55 citrus and 23 coffee isolates, only five STs were observed, with 85% of the citrus isolates having the same ST.

The data from X. fastidiosa show that massive recombination can occur between subspecies. We see this in the creation of X. fastidiosa subsp. morus,30 litre plant pots bulk and a similar event may have been involved in the genesis of the X. fastidiosa subsp. pauca strain that infects citrus and coffee in South America . But how did this happen? It has been established that conjugative plasmids can occur in X. fastidiosa , including a candidate found in the mulberry type . Furthermore, high rates of transformation have been observed in the laboratory . Which of these processes is involved in large-scale genomic exchange is not known. These data raise a second issue: how, given the clear potential for genetic exchange, X. fastidiosa subsp. morus and also the ancestral X. fastidiosa subsp. multiplex and X. fastidiosa subsp. fastidiosa strains have not introgressed into an ill-defined network of isolates. There are two main, nonexclusive hypotheses that might explain how these taxa have remained distinct: “opportunity” and “host selection.” The opportunity hypothesis is based on the distinct and almost completely non-overlapping range of plant hosts of the subspecies , which could severely limit contact between them and hence limit opportunity for IHR. This hypothesis is strengthened if it could be established that genetic exchange typically occurs in the plant host. On the other hand, the opportunity hypothesis would be weakened if genetic exchange typically occurs in the insect vector, since different subspecies can colonize the same insect . The host selection hypothesis proposes that different plant hosts impose strong host-specific selection such that, even if IHR occurs relatively frequently, most of the bacteria resulting from such exchange are maladapted and do not survive. Even moderate levels of recombination would be expected to generate high levels of genetic variability; however, very little genetic variability was observed within the mulberry type despite evidence of large-scale IHR and a broad geographical occurrence within the United States.

This near monomorphism of the mulberry-type isolates suggests that plant host specialization places severe constraints on the genome; i.e., the shift to the new host seems to have eliminated all but a narrowly defined set of genotypes. If the host shift had been due to some other genetic change, such as the acquisition of new extrachromosomal genes,then these genes would be expected to be seen in a number of different genetic backgrounds, which they are not. Thus, in summary, X. fastidiosa subsp. morus provides an important example for understanding the role of homologous recombination in bacterial adaptive evolution. We have been able to associate a clear ecological shift with a high level of recombination. But we are left with a puzzle. The data are consistent with X. fastidiosa subsp. morus and the recombinant-group X. fastidiosa subsp. multiplex originating from a single large-scale IHR, with no unambiguous evidence of any similar events involving the strains of X. fastidiosa subsp. fastidiosa currently found in the United States. Was this initial event a conjugation, followed by DNA fragmentation within the bacterial cell which resulted in large-scale recombination, or was it associated with a period during which conditions promoted a high rate of transformation, conditions that no longer prevail or occur only rarely? At present, it is far from clear if one or both of these possibilities could account for the pattern of evolution illustrated in Fig. 2.Understanding the relationship between species diversity and ecosystem functioning is a key issue given the global decline in biodiversity . Ecosystem functions such as nutrient cycling, soil formation, and pollination are crucial to environmental stability so an understanding of how and why these functions are related to species diversity will help to predict the broader consequences of species losses . Complementarity is niche differentiation by species/taxa which increases the efficiency of resource use. Large overlap between niches can indicate functional redundancy in a system, that is different species/taxa are doing similar things.

The functional redundancy and complementarity of species has been widely discussed, as it has implications for ecosystem functioning and prioritizing species conservation . There are several examples from studies of plants that show complementarity can contribute to a positive relationship between diversity and functioning . However, little is known about the role of complementarity in ecosystem functions mediated by organisms such as pollinators. Ecosystem functions can translate into short- or long term ecological or economic benefits to humans and in such cases are referred to as ecosystem services. Pollination is an ecosystem service crucial for wild plant reproduction , food production , and human nutrition , with bees being the main service provider . Complementarity is thought to play an important role in pollination service. With greater pollinator diversity and therefore, potentially greater complementarity, an increase in pollination service and therefore, fruit set may result. Pollination success in coffee was found to be positively correlated with pollinator functional group richness . In addition, pollinator functional diversity explained more of the variance in the seed set of pumpkin than species richness . However, as yet there are only a few studies on complementarity in pollination function and, to our knowledge, no data on how spatial complementarity of pollinator communities interacts with environmental change.Diversity in an ecosystem may appear redundant under a particular set of environmental conditions or at a given time. However, different species may not respond equally or in the same way to environmental changes. The diversity of what appear to be functionally similar species under one set of environmental conditions may buffer ecosystem function against fluctuations in these conditions, a condition known as response diversity . It has been observed that some non-Apis bees such as bumble bees and Osmia cornuta are more able to forage under inclement weather conditions than honey bees . For example,wholesale plant containers in apple orchards O. cornuta and muscoid flies were observed foraging under light rain when honey bees were not active and O. cornuta was the only pollinator species observed foraging in the orchards under high wind speeds.Such complementarity could be an extremely important mechanism for ensuring stable crop production. Agriculture has become increasingly pollinator dependent and recent findings of declines in both wild and managed bees have raised concerns about the potential impact on pollination services . For a large number of crop species, pollination is provided by honey bees , but there are many examples of crop species for which non-Apis pollinator species are more effective for fruit set on a per visit basis , coffee , and blueberry.Almond is a mass flowering crop, which requires biotic pollination and flowers early in the year when high wind speeds, low temperatures, and precipitation are common.In 23 almond orchards, the percentage fruit set was positively associated with the richness of flower visitors in the orchard and the species richness of wild bees .In this study, we investigated complementarity in almond, as a potential mechanism for this positive diversity-function relationship. Using the same 23 almond orchards, we investigated whether wild flower visitors showed spatial complementarity with honey bees and how spatial complementarity altered under changing environmental conditions . Our aims were to explore if different flower visitor taxa share or partition spatial niches at the tree scale; if flower visitor taxa show differential abilities to forage at high wind speeds and if the change in environmental conditions causes those taxa that forage at high wind speeds to change their spatial niche. Information from our study is important for predicting the consequences of functional pollinator diversity loss in a changing world.

The observations in the 23 orchards in 2008 under low wind speeds were used to investigate the foraging location of flower visitors within the trees, as all orchards had been sampled equally. The flower visitor community was divided into four functional taxa . The frequencies of visits by each of the taxa were analyzed in separate models. Due to a large number of zeros, data were summed for each observation day across trees at the edge and trees in the interior of each orchard. The explanatory variables were the location within the tree and the wind speed . The number of flowers observed was included as an offset as it was a covariate known to affect the flower visit counts. The random variables were the location , nested within the observation day, nested within the orchard. For the wild bees, hover flies, and all-others the error distribution was Poisson. For honey bees, the error distribution was log normal Poisson with a subject level random variable to account for over dispersion . For all models, stepwise deletion was carried out . After the removal of an explanatory variable, the models with and without the variable were compared by analysis of variance to test the loss of explanatory power from the removal of the variable . When there was no significant difference between the models, the explanatory variable was removed.Data were collected under high wind speeds in four orchards in 2008, 2009, and 2010 . These data were analyzed with the data collected at the orchard edge in the same four orchards under low wind speeds in 2008. To isolate the impact of wind speed from other environmental variables such as temperature, we conducted observations on days with high wind speeds and sunny conditions. High wind data were collected over 3 years as windy days were often also cooler and rainy; with windy, sunny days being rarer. In 2008, observations of flower visits were carried out over three separate days, per orchard and wind category. The data were summed across all five trees at the orchard edge observed in a day, in an orchard. The frequency of flower visits was the response variable in a mixed model with a log normal Poisson error distribution. The orchard’s pollinator diversity category, wind speed, and their interaction were included as explanatory variables. The wind speed was calculated as the average of the start and end wind speed of the observation period. Year was also included as an explanatory variable and the number of flowers observed as an offset . Only the observations in the two high pollinator diversity orchards were selected to analyze the effect of wind speed on the frequency of flower visits by each taxa. The high wind observations in 2008, 2009, and 2010 and the low wind observations from the same orchards in 2008, at the orchard edge only were analyzed. The data were summed across the five trees observed on each day, in each orchard. The number of flower visits recorded by each taxa was the response variable. The explanatory variables were the wind speed, the year and an offset of the number of flowers observed . Observation day nested within the orchard and a subject level random variable were included. A Poisson error distribution was selected.

Trials were performed using slight modifications to the previously reported assay. Fifty flies were aged per vial and starved in vials with 2 Kimwipes moistened with 3ml of water. A 6mm diameter circle of Whatman #1 filter paper was placed in the bottom of a 10 cm length tube to deliver the odor. A brass screen of 8/32 inch diameter was placed 5mm from the bottom of the tube to gate off the filter paper. Approximately 100 flies were inserted into the control tube and joined to the tube with test odorant. After 30minutes exposure in the dark at 25 degrees Celsius, the apparatus was photographed. Flies 5 cm from each screen were counted. Preference index was calculated. The Two-Choice Trap Assay in a plate tests less volatile odorants. Trials were performed as described. Ten female flies are placed in a Petri dish containing two traps. Traps were made with 1.5ml micro centrifuge tubes with opening cut in the bottom of the tube. Both traps contain the fly’s normal laboratory food at the base. The neck of one trap has a filter paper with test odorant, the other trap has solvent. Five microliters of hexane and five microliters of 10% DEET or test compounds in hexane were applied to the stem part of filter paper inserted into upper part of pipette tip near entrance to trap to allow flies to walk over treated surface. Traps were placed in chemical hood for 5minutes to allow hexane to volatilize before being placed in the 1% agarose treated Petri dish chamber.Assay was performed to determine24 preference for an attractive food source in the context of a repellent odor. Briefly, ten male and ten female starved flies are placed in a cylindrical chamber containing two traps: with test odorant and lure,plants in pots ideas with solvent and lure. Apple cider vinegar is the lure for all trials except for D. virilis where liquid malt was used . To create a well for separating lure from test odorant, a single cap cut from a BioRad PCR 0.2ml Tube Flat Cap strips was inserted in a snap top lid of a micro-centrifuge tube. To run the assay, 35ul of test odorant was pipetted into inner well and 90ul of lure into the outer ring. For all trials, the control trap had paraffin oil solvent in inner well and lure in outer ring. Flies were given six hours to enter traps.

Preference index was calculated.Test odorant or solvent was added to warm standard grape juice media in Petri dishes and set to solidify. Petri dishes were placed at opposite ends of a 10 gallon closed glass chamber. A 100ml beaker containing 40ml of distilled water was placed equidistant between grape plates to add moisture to the chamber. For each trial, 15 male and 25 female un-starved Canton-S flies were lightly anesthetized with carbon dioxide and released in the chamber. Assay was run for 24hours at 25 degrees Celsius on a 12hour light: 12hour dark cycle. Preference was determined by counts of eggs on grape plate containing test odorant and control. Two-Choice Blueberry Assay in a glass chamber. Fresh blueberries were obtained from a local grocer and were soaked in distilled water for 30minutes, rinsed and dried. To prepare the chamber, 31 grams of blueberries were placed in each of 2 plastic bowls. Test compound is painted on blueberries in test bowl and solvent on blueberries in control bowl. Bowls are placed at opposite ends of a 10 gallon closed glass chamber. A 100ml beaker containing 40ml of distilled water was place equidistant between fruit to add moisture to the chamber. For each trial, 15 male and 15 female un-starved flies were lightly anesthetized with carbon dioxide and released in the chamber. Assay was run for seven days at 25 degrees Celsius on a 12hour light: 12hour dark cycle. After 7 days, each bowl was covered and set aside for an additional six days for eggs and larvae to develop after which the blueberries were dissected under microscope and number of eggs, larvae, pupae and adults were recorded. Preference was determined by inferring egg-laying from a count of eggs, larvae and pupae emerging from each set of fruit.Overweight and obesity put individuals at risk of major health problems including type 2 diabetes , nonalcoholic fatty liver disease and cardiovascular disease. Consumption of Western style diets can be a major contributing factor to the increased rates of overweight and obesity in human populations, while consumption of select fruits and vegetables could attenuate these conditions. Evidence for the latter is conflicting when considering overall intakes, types of fruits and vegetables consumed, and other variables associated with population studies.

On the other hand, a large body of evidence in experimental animals suggests a benefit of select phytochemicals present in fruits and vegetables in the development of obesity and associated pathologies triggered by consumption of high fructose and/or high fat diets. Among phytochemicals, anthocyanidins are flavonoids being actively investigated for their potential to mitigate unhealthy conditions, particularly metabolic disorders. In this regard, mounting evidence supports a potential beneficial action of AC consumption on T2D and cardiovascular health. Furthermore, AC-rich food consumption is inversely correlated with overall mortality. AC are flavonoids that exist in nature as anthocyanins, the glycosylated forms of AC. They provide color to grapes, berries, blueberries, black currants, bilberries, purple corn, and black rice, among other fruits and vegetables. With the basic three-ring structure of flavonoids, AC are characterized by double bonds in the three rings and a positive charge in the B ring on the oxygen atom. Different hydroxyl substitutions in number and position define different AC, e.g. delphinidins, malvidins, and peonidins. These differences in substitutions can have a major impact on AC biological actions in animals. In this regard, we recently observed that 3-O-glucosides of cyanidin and delphinidin were more efficient than malvidin, petunidin and peonidin 3-O-glucosides at inhibiting tumor necrosis factor alpha -induced activation of transcription factor NF-κB in Caco-2 cell. Dietary energy overload can cause tissue inflammation, oxidative stress, and insulin resistance. Excess fat consumption leads to the activation of inflammatory and redox-regulated events including: i) the IκB kinase , and downstream the transcription factor NF-κB; and ii) the mitogen activated kinase c-jun N-terminal kinase . Activation of both JNK and IKK and the increased expression of the NF-κB-regulated protein tyrosine phosphatase 1B phosphatase down regulate the insulin signaling pathway leading to insulin resistance. Inflammation, oxidative stress,container size for blueberries and chronic NF-κB activation also contribute to other major adverse consequences of obesity, e.g. NAFLD and cardiovascular disease. Identifying fruits and vegetables and their active components that can provide protection against the adverse effects of consuming Western style diets has the potential to have a major impact on human health. Moreover, understanding the mechanisms by which these components act modifying cell functions is crucial to define public recommendations in terms of diets and potential supplementation.

This work investigated the capacity of a diet enriched in the AC cyanidin and delphinidin to mitigate in mice the development of obesity, dyslipidemia, steatosis, and insulin resistance promoted by the chronic consumption of a HFD. The beneficial effects of AC were mainly associated with the attenuation of liver inflammation, oxidative stress, and down regulation of the redox sensitive JNK and IKK/NF-κB. These findings stress the concept that cyanidins and delphinidins can provide benefits against excess fat consumption and its adverse health consequences.Fecal triglyceride content was measured using a modified method to that proposed by Folch et al.. Fecal samples were collected over 24 h from single cages and dried at 37 °C for 24 h. Dried feces were ground to a fine powder using a mortar and pestle. The lipid extraction was performed by homogenizing the fecal powder with 500 ml of chloroform-methanol solution. Samples were mixed for 5 min and centrifuged at 1000×g for 10 min at room temperature and the lower liquid phase containing the extracted lipids in chloroform-methanol was collected and evaporated overnight. Analysis of triglyceride content was performed by saponification using a method described by Weber et al. with minor modifications. Briefly, the lipid residue was digested by incubation with 500 µl of a KOH :ethanol solution for 30 min at 60 °C. An aliquot was combined with 215 µl of 1 M MgCl2. After centrifugation for 15 min at 2000×g at room temperature, 2 µl of the supernatant were collected and analyzed for glycerol content using the enzymatic triglyceride kit TG Color GPO/PAP AA . Analysis of liver triglyceride content was performed after extraction and saponification, basically as previously described for feces. Briefly, a 100 µl aliquot of 10% liver homogenate was mixed with 300 µl of a KOH :ethanol solution and evaporated overnight at 55 °C. The following day, 1 ml of 50% ethanol was added and samples centrifuged for 5 min at 10,000×g at room temperature. Of the resulting supernatant, 200 µl were added with 215 µl of 1 M MgCl2 and placed on ice for 10 min. After centrifugation at 10,000×g for 5 min at room temperature, 10 µl of the supernatant were analyzed for triglyceride content as described above.The liver was removed and samples fixed overnight in 4% neutralized paraformaldehyde solution. Samples were subsequently washed twice in phosphate buffer saline solution, dehydrated, and then embedded in paraffin for histological analysis. Sections were obtained from paraffin blocks and placed on glass slides. Hematoxylin and eosin staining was performed following standard procedures. Sections were examined using an Olympus BX51 microscope . Hepatic histological examination was performed using the NAFLD activity score described by Kleiner et al.. Three randomly selected fields per animal were assessed and analyzed using Pro Plus 5.1 software .Daily food intake in the groups fed the HFD was significantly lower than in those fed the control and CA diets . However, the calorie intake was similar within groups

Weekly food intake did not significantly vary within groups . Starting at week 4 and through the following weeks, the body weight gain for C, CA, and HFA40 groups was significantly lower than for the HF group . At week 14, there was a dose-dependent decrease in body weight depending on the amount of AC in the diet . At the end of the study, consumption of the HFD caused a 31% higher body weight compared to controls, while the body weight of HFA40 mice was 14% lower than in HF mice. HFD-induced obesity was associated with an increased weight of the different fat pads . HFA40 mice showed a brown fat content similar to C mice, and 72% and 49% lower visceral and retroperitoneal fat accumulation, respectively, compared to HF mice. Brown fat weight in CA mice was 43% higher than in the C group. Consumption of the HFD also caused dyslipidemia. Plasma cholesterol and triglyceride levels were 26% and 9% higher in HF than in C mice, respectively . Supplementation of HFD-fed mice with AC prevented the increase of plasma triglyceride concentrations at all the AC concentrations tested, while plasma cholesterol increase was only prevented at the highest AC supplementation level, i.e. HFA40 group. While there were no significant differences in the amount of triglycerides excreted with the feces among the control, HF and CA groups , fecal triglyceride amount in the HFA40 group was significantly higher than in the control group . Fecal cholesterol content was significantly higher in the HF and HFA40 groups than in control and CA groups .We next investigated the levels of select hormones, which are relevant to the regulation of glucose homeostasis, and that are produced by the adipose tissue, i.e. adiponectin and leptin, and by gastrointestinal enteroendocrine cells, i.e. GIP and GLP-1. While plasma adiponectin levels were similar among groups, plasma leptin was 4 times higher in the HF compared to the C group . The increase in leptin observed in HF mice was partially prevented in HFA40 mice. Plasma GLP-1 concentration was significantly higher in HF, HFA40 and CA groups compared to the C group .Consumption of the HFD caused steatosis and liver inflammation. Liver triglyceride levels were 76% higher in the HFD-fed compared to the C group. This increase in liver triglycerides was not observed in the HFA40 group. . Lipid deposition was also assessed by histological analysis after hematoxylin-eosin staining .

Blueberries are a delightful and nutritious addition to any garden, offering a bounty of sweet, antioxidant-rich fruits. However, successful blueberry cultivation requires careful attention to specific needs and growing conditions. Many novice gardeners make common mistakes that can hinder plant growth and fruit production. This comprehensive guide will explore these common errors and provide tips on how to avoid them,plastic seedling pots ensuring a healthy and productive blueberry harvest.

1. Choosing the Wrong Blueberry Varieties

Mistake: Selecting Varieties Unsuitable for Your Climate

One of the most critical mistakes gardeners make is choosing blueberry varieties that are not suited to their local climate. Blueberries come in several types, each adapted to specific climatic conditions.

Solution:

• Northern Highbush Blueberries: Suitable for regions with cold winters and mild summers.
• Southern Highbush Blueberries: Ideal for areas with mild winters and hot summers.
• Rabbiteye Blueberries: Thrive in warm to hot climates and are drought-tolerant.
• Lowbush Blueberries: Best for cold climates and are often found in northern regions.
• Half-high Blueberries: Hybrids of Highbush and Lowbush, suitable for colder climates with good winter hardiness.

Mistake: Not Considering Chill Hours

Blueberries require a certain number of chill hours (hours below 45°F) during winter to break dormancy and ensure proper fruit set.

Solution: Research the chill hour requirements of different blueberry varieties and match them to the average chill hours in your region. For instance:

• Northern Highbush varieties typically need 800-1,000 chill hours.
• Southern Highbush varieties can require as few as 150-600 chill hours.
• Rabbiteye varieties usually need around 350-600 chill hours.

2. Planting in Poor Soil Conditions

Mistake: Incorrect Soil pH

Blueberries require acidic soil with a pH between 4.5 and 5.5. Many gardeners overlook soil testing and plant blueberries in soil that is too alkaline, leading to poor growth and nutrient deficiencies.

Solution:

• Conduct a soil test before planting to determine the soil pH.
• If the pH is too high, amend the soil with sulfur or an acidifying fertilizer to lower the pH to the desired range.
• Regularly monitor soil pH and adjust as needed to maintain optimal conditions for blueberry growth.

Mistake: Poor Soil Drainage

Blueberries are sensitive to waterlogged soil, which can lead to root rot and other issues.

Solution:

• Ensure that your planting site has well-draining soil. Avoid low-lying areas where water tends to accumulate.
• If necessary, improve drainage by incorporating organic matter such as compost or peat moss into the soil.
• Consider planting blueberries in raised beds or mounds to enhance drainage.

3. Improper Planting Techniques

Mistake: Planting Too Deep or Too Shallow

Planting blueberries at the wrong depth can stress the plants and inhibit their growth.

Solution:

• Plant blueberries so that the top of the root ball is level with the soil surface or slightly above it.
• Ensure that the roots are spread out in the planting hole and not bunched up or circling around.

Mistake: Spacing Plants Too Closely

Blueberry bushes need adequate space for air circulation and growth. Planting them too closely can lead to overcrowding, increased disease risk, and reduced fruit production.

Solution:

• Space Highbush blueberry plants 4-6 feet apart.
• Space Rabbiteye blueberry plants 6-8 feet apart.
• For Lowbush blueberries, space plants 1-2 feet apart.

4. Neglecting Watering and Mulching

Mistake: Inconsistent Watering

Blueberries require consistent moisture, especially during establishment and fruiting periods. Inconsistent watering can stress the plants and affect fruit quality.

Solution:

• Provide 1-2 inches of water per week, depending on weather conditions.
• Use drip irrigation or soaker hoses to deliver water directly to the root zone, minimizing evaporation and reducing disease risk.
• Monitor soil moisture regularly and adjust watering practices accordingly.

Mistake: Not Mulching

Mulching helps retain soil moisture, suppress weeds, and regulate soil temperature, but many gardeners overlook this practice.

Solution:

• Apply a 2-4 inch layer of organic mulch, such as pine needles, wood chips, or bark, around the base of the plants.
• Replenish mulch as needed to maintain an adequate layer and prevent weed growth.

5. Improper Fertilization Practices

Mistake: Using the Wrong Fertilizer

Blueberries require specific nutrients and are sensitive to certain fertilizers. Using general-purpose fertilizers can lead to nutrient imbalances and poor plant health.

Solution:

• Use a fertilizer formulated specifically for acid-loving plants, with an emphasis on nitrogen in the ammonium form.
• Avoid fertilizers with high levels of phosphorus, as blueberries have relatively low phosphorus requirements.

Mistake: Over-Fertilizing or Under-Fertilizing

Applying too much or too little fertilizer can harm blueberry plants, leading to nutrient deficiencies or toxicities.

Solution:

• Follow the manufacturer’s recommendations for application rates and timing.
• Fertilize blueberries in early spring as new growth begins and again in late spring or early summer.
• Avoid fertilizing in late summer or fall,big plastic pots as this can stimulate late-season growth that is susceptible to winter damage.

6. Failing to Prune Properly

Mistake: Neglecting Pruning

Regular pruning is essential for maintaining plant health, controlling size, and encouraging fruit production. Neglecting to prune can result in overgrown, unproductive bushes.

Solution:

• Prune blueberries annually during the dormant season, typically in late winter or early spring.
• Remove dead, damaged, or diseased wood, as well as weak or spindly growth.
• Thin out older canes (those older than 6 years) to encourage new growth and maintain a balance of canes of different ages.
• Shape the bushes to an open, vase-like form to improve air circulation and light penetration.

Mistake: Over-Pruning

While pruning is important, over-pruning can reduce fruit production and stress the plants.

Solution:

• Avoid removing more than 20-25% of the plant’s canopy in a single pruning session.
• Focus on removing only what is necessary to maintain plant health and productivity.

7. Ignoring Pest and Disease Management

Mistake: Not Monitoring for Pests and Diseases

Blueberries are susceptible to various pests and diseases, and failing to monitor plants regularly can lead to significant damage and yield loss.

Solution:

• Inspect plants regularly for signs of pests and diseases, such as discolored leaves, damaged fruit, or unusual growth patterns.
• Implement integrated pest management (IPM) practices, including cultural, mechanical, biological, and chemical controls as needed.

Common Pests:

1. Blueberry Maggot: Use sticky traps and insecticides if necessary to control infestations.
2. Aphids: Introduce beneficial insects like ladybugs or use insecticidal soap to manage populations.
3. Birds: Use netting or scare devices to deter birds from feeding on your crop.

Common Diseases:

1. Mummy Berry: Remove and destroy infected berries and fallen leaves to reduce the spread.
2. Botrytis Blight: Improve air circulation and avoid overhead watering.
3. Phytophthora Root Rot: Ensure good drainage and avoid overwatering.

8. Poor Harvesting and Post-Harvest Handling

Mistake: Harvesting Too Early or Too Late

Harvesting blueberries at the wrong time can affect their flavor and shelf life.

Solution:

• Harvest blueberries when they are fully blue and easily come off the bush with a gentle tug.
• Regularly check for ripeness during the harvest season and pick berries promptly.

Mistake: Mishandling Berries Post-Harvest

Improper handling of harvested blueberries can lead to bruising and reduced shelf life.

Solution:

• Handle berries gently to avoid bruising.
• Place harvested berries in shallow containers to prevent crushing.
• Cool berries as soon as possible after picking to preserve freshness.
• Store blueberries in the refrigerator at 32-40°F for up to two weeks. For longer storage, consider freezing the berries by spreading them in a single layer on a baking sheet and freezing until solid, then transferring to airtight containers or freezer bags.

Conclusion

Growing blueberries can be a rewarding experience, but it requires careful attention to detail and a commitment to proper horticultural practices. By avoiding common mistakes such as selecting unsuitable varieties, planting in poor soil conditions, improper watering and fertilization, neglecting pruning, ignoring pest and disease management, and mishandling the harvest, you can ensure a healthy and productive blueberry crop.

Successful blueberry cultivation involves understanding the specific needs of your plants and providing the optimal conditions for their growth. Regular monitoring, soil testing, and timely interventions are key to overcoming challenges and maximizing fruit production. With patience and diligence, you can enjoy the sweet rewards of homegrown blueberries for years to come.

My econometric estimates allow me to make several predictions about how rising temperatures will affect the agricultural labor sector. To do this, I develop a model of a firm choosing an optimal piece rate wage under some exogenous environmental condition .My model produces two interesting sets of comparative statics. First, I show that temperature’s effect on the optimal piece rate wage depends on how temperature affects labor productivity directly, and how temperature affects labor productivity’s responsiveness to the wage. Plugging my empirical estimates into this model, I find that an optimizing blueberry farm would pay its workers a higher piece rate wage on particularly cool days, ceteris paribus. Second, I show that temperature’s effect on overall farm profits has the same sign as temperature’s direct effect on labor productivity. In the case of California blueberry farms, where cool temperatures have meaningful negative effects on productivity, this suggests that the first-order effect of rising temperatures on profits is likely to be positive. However, in contexts where cool temperatures do not lower labor productivity, the opposite is likely to be true. The remainder of this paper is organized as follows: in section 1.2, I develop a simple theoretical model of workers’ optimal effort under a piece rate wage scheme. In section 1.3, I describe the institutional details of the two California blueberry farms I study in this paper. I then discuss my data and report summary statistics in section 1.4. Section 1.5 outlines my empirical strategy, and section 1.6 reports my results. I discuss my findings in section 1.7, giving particular attention to how rising temperatures are likely to affect the agricultural labor sector. Finally, in section 1.8, I conclude.

There has been relatively little theoretical work done on piece rate wage schemes in the past, partly because their structure is so straightforward,blackberries in containers and partly because they are so much less common than salaries or hourly wage schemes. Nonetheless, previous research has highlighted several important aspects of piece rate wages that are relevant to this paper. Prendergast and Brown both provide good summaries of when and where piece rates are likely to be effective. Specifically, in cases where firms can cheaply monitor productivity and ensure quality control, piece rates should correctly align workers’ incentives with those of their employer, maximizing labor productivity.10 Several papers have confirmed the prediction that, under the correct circumstances, piece rate wage schemes better incentivize labor productivity than do more traditional wage schemes. Lazear , studying an auto glass company, finds that a switch from hourly to piece rate wages boosts output per worker by an average of 44%. Shi , studying a tree-thinning company, estimates a more modest effect of 23%. Shearer , studying tree-planters in British Columbia, also finds an effect near 20%. Bandiera et al. study agricultural workers in the United Kingdom and come to a similar conclusion, noting that piece rates based on individual production eliminate cross-worker externalities found in relative incentive schemes. In a non-causal study from California, Billikopf and Norton also provide evidence that piece rate wages boost vine-pruners’ performance relative to hourly wages. Such increases in productivity under piece rates seem to come from increased worker effort, as Foster and Rosenzweig demonstrate by measuring workers’ net calorie expenditures under different pay schemes. None of the papers cited above, however, estimate how labor productivity responds to changes in a piece rate wage.Among the most well-known papers that have attempted to do so are Paarsch and Shearer and Haley . In both cases, the authors calibrate a structural model of worker effort in order to address piece rates’ endogeneity.

They find positive elasticities of effort with respect to wages, of 2.14 and 1.51 respectively, in line with theoretical predictionsOther papers have relied on natural experiments or natural field experiments to try and recover the effect of piece rate wage levels on productivity. For instance, Treble exploits a natural experiment from the 1890s in an English coal mine to derive a nearunit-elastic productivity response. In a more recent setting, Paarsch and Shearer implement a natural field experiment with tree-planters in British Columbia and estimate a productivity elasticity of 0.39. While the authors note that this estimate is “substantially smaller” than that of Paarsch and Shearer and Haley , it is unclear wether they think this result invalidates the earlier estimates.Finally, Guiteras and Jack conduct an experiment in rural Malawi to explore how variation in piece rate wages affects both quantity and quality of worker output. Despite the theoretical simplicity of a piece rate wage scheme, it is not immune to employees’ behavioral responses. Even though a firm may be able to set a different piece rate every day, doing so may foment unrest among employees if the changes are seen as arbitrary . In other situations, high piece rates may operate as efficiency wages – à la Yellen , Shapiro and Stiglitz , and Newbery and Stiglitz – especially if a firm is trying to retain high-quality workers . An additional consideration is that variable piece rate wages may lead to a less reliable supply of labor on the intensive margin. In other words, piece rate employees may work fewer or more hours depending on the day’s wage. Such behavior would be consistent with a reference-dependent preference model like that of Kőszegi and Rabin where workers have some internal reference point for how much money they intend to earn in a particular day.Finally, piece rate wages are much more common in seasonal specialty agriculture than in many other industries or settings. Tasks such as picking, pruning, or planting can be easily measured and tracked, making piece rates feasible. In these cases, productive workers can earn considerably higher incomes under a piece rate scheme than under an hourly wage scheme: Moretti and Perloff find that US agricultural workers paid by piece rate earn 26% more than their hourly counterparts. This number is slightly misleading, and certainly not causal, considering that workers select into particular work in part based on the compensation scheme. Rubin and Perloff note that piece rate workers tend to be disproportionately young or old: “[a]pparently, prime-age workers find that higher earnings in piece-rate jobs do not compensate for the difficulty of more intensive effort, more variable incomes, and possible greater injury risk or shortened farm-work career” . However,these selection issues are irrelevant if the goal is to understand how piece rates affect the productivity of workers who select into such work in the first place. Harvesting fresh blueberries is a labor intensive process. Berries grow in small bunches and ripen at differing times. This means that a single blueberry bush can be harvested multiple times each season. However, since each berry-bunch contains both ripe and unripe berries, pickers must harvest fruit carefully by hand. Mechanized blueberry harvesters exist, but they are imprecise and are used primarily for harvesting berries destined for the processing market.Berry-pickers collect fruit in small buckets fastened on the front of their bodies. Once the buckets are full,blackberry container the workers carry their harvest to a weigh-station at the end of a field row. Workers pour their berries into standardized bins which are then weighed, packed into trucks, and driven to a refrigerated packing plant. Because blueberries are delicate and perishable, they must be refrigerated quickly after being picked. When workers bring their berries to be weighed, a foreman closely watches the process to ensure quality control. If a picker’s fruit is intermingled with too many twigs, leaves, or unripe berries, the foreman will warn the picker that their quality must improve to keep their job.

The farms I study both utilize an automated system to track workers’ productivity and calculate payroll.Each picker is given a unique barcode that they wear as a badge, and each fruit tray is assigned its own barcode as well. When a picker brings their fruit to be weighed, the weigher scans both the picker’s barcode and the tray’s barcode to record the tray weight. The picker then receives a receipt of their weigh-in. The farmer likes the barcode system because it is quick, automatic, reliable, provides real-time data, and replaces a cumbersome paper-and-pencil system. Pickers like the barcode system because they are able to witness the fruit-weighing and are thus confident that the farmer is paying them honestly for the fruit they pick. At the beginning of each work day, around 6:00 or 6:30 a.m., the farmer sets the day’s piece rate wage and posts the wage in a public spot for all workers to see.Workers are paid the piece rate for each pound of berries they harvest, and the rate does not change throughout the day. The piece rate does, however, change over the course of the season . As fruit becomes more abundant on the bushes through May and June, picker productivity rises. Farmers therefore generally lower the piece rate wage throughout the season as more and more berries ripen. Anecdotally, farmers say they lower their piece rates “when there’s a lot of fruit in the field” with the goal of maintaining a relatively stable effective hourly wage for the average berry picker.If any one worker picks a small enough quantity of fruit that their effective hourly wage for the day falls below the legal minimum wage, the farmer pays them according to the hourly minimum wage. In these cases, the farmer often then gives the picker in question additional training and a warning that they may be fired if they do not quickly improve. Anecdotally, the hourly minimum wage is most likely to bind during a new employee’s first few days on the job as they develop their skills as a fruit picker. If a worker consistently falls below the minimum wage cutoff, they frequently quit on their own accord or are effectively fired and asked not to return the next day. Because blueberries are delicate and highly perishable, they are not bought and sold in a central commodity market. Instead, individual producers set short-term contracts with different marketers or buyers to provide a certain quantity of berries in particular packaging at a particular time. These contracts are set on a near-daily basis, and prices can change quickly throughout the season. While there is certainly some quality differentiation within the blueberry market, buyers and marketers view different producers as close substitutes. This means that individual producers have relatively little, if any, market power. I thus take California blueberry contract prices as an accurate reflection of a competitive market price for blueberries in the state. Blueberry prices in California are highly seasonal: prices are quite high at the beginning of the season in April, and much lower near the end of the season in June. This seasonality in price is largely explained by variation in aggregate production throughout California, and variation in the availability of blueberries from other global producers. In the early spring, the United States imports fresh blueberries at high prices from Mexico or other countries since domestic production is agronomically infeasible. By mid-to-late-June, farms in northern states such as Washington, Oregon, and Michigan begin to produce berries in large quantities, driving down the market price. California blueberry farmers therefore face a relatively short season when it is profitable to harvest and sell their fruit. While blueberry bushes continue to yield berries through June and into July, labor costs are too high relative to market prices at that time for California farmers to justify continued production. To summarize, the California blueberry season begins agronomically, but ends economically. Organic blueberries regularly command a price premium of around two dollars per pound. While the harvesting process is identical for conventional and organic berries, organic bushes produce fewer berries per bunch. Thus, pickers of organic berries spend more time finding and harvesting berries than do their conventional counterparts. Additionally, fruit quality is more variable in organic blueberries. This leads to a smaller proportion of berries ultimately reaching market. As described in the previous section, the farms I study use a digital fruit weigh-in system to track worker productivity and generate payroll data. I utilize data from these weigh-ins to conduct my analyses.

The successful diabetes induction was confirmed with blood glucose measurements from the tail vein with a glucometer , all the measurements were taken during fasting and postprandial periods during 3 days after injection. Values of fasting glucose higher than 200 mg/dl indicated a successful establishment of T2DM rat model. The BB extract was diluted in 1ml of water and administrated by oral gavage for 31 days. The fasting glucose levels in blood were tested every 2 days per week from the tail vein. Water and food consumption were quantified every day and body weight was monitored once a week. At the end of the treatment period, the rats were anesthetized via intraperitoneal with 3% pentobarbital sodium . Blood samples were collected by cardiac puncture, the blood was centrifuged for 15 min at 13,000 rpm and the plasma was recovered and stored in aliquots of 500 µl at −20◦C until use. Retroperitoneal adipose tissue was aliquoted, isolated, and washed with PBS and frozen immediately with liquid nitrogen. The frozen samples were stored at −80◦C. The stored serum samples were thawed at 4◦C. Insulin levels were quantified using the Rat Insulin ELISA kit RayBio R. Peachtree Corners, GA. The levels of total cholesterol, triglycerides, HDL-Cholesterol, and LDL-Cholesterol in the serum samples were measured with commercial kits for colorimetric assays. Tumor Necrosis Factor alpha was quantified with ELISA kit according to manufacturer protocols. RNA extraction from adipose tissue samples were carried out according to the protocol proposed in the RNeasy Lipid Tissue Mini Kit . The sequencing library was prepared by random fragmentation of the cDNA,raspbery container followed by the 5 ’and 3’ ligation adapters. Adapter-ligated fragments were amplified by PCR and visualized on agarose gels. Double stranded next generation sequencing RNAseq was commercially performed by MAcrogen on Illumina HiSeq4000 by triplicate in each group.

All RNAseq data are available at GEO database under accession number GSE215903. fter a low dose injection of STZ, rats in BB and DB groups showed significantly increased fasting blood glucose levels compared with animals from HE group, this tendence was observable during the 5 weeks treatment and at the end of the treatment as showed in Figure 1C. Furthermore, STZ administration resulted in decreased body weight in BB and DB groups , but no difference was observed on adipose tissue weight . These findings demonstrate the success of T2DM induction in Wistar rats.Two of the main characteristics of diabetic patients are the body weight decrease and the chronic increase of blood glucose levels. As exposed in Figure 1, the body weight of all the rats increased progressively, and their blood glucose levels were normal. However, the growth rate of the rats in the HE group was slower. Conversely, after STZ administration, the body weight of all rats started to decrease, and their blood glucose levels augmented significantly compared with rats in HE group. Moreover, rats in both the BB and DB groups tended to show a decrease in weight after STZ administration. The effect of BB on the fasting blood glucose level of the rats is shown in Figure 1A, from which it is obvious that the blood glucose levels of rats in the BB group decreased gradually after 1 week of treatment. At the end of treatment period, rats in BB group showed significant decreases in fasting blood glucose levels. The levels of insulin showed a down trend, even though the decreases were not significant between BB and DB groups . Further, TNF-α levels in the BB group exhibited a significant decrease when compared with DB group . With the aim to identify genomic impact of BB extract on genomic profile in adipose tissue, we performed global RNAseq. Following statistical analysis, we identified 566 significantly differentially expressed genes. A closer understanding into identified differentially expressed genes demonstrated that there are 406 among them that are protein coding genes , 33 are miRNA family genes, 39 are long non-coding genes, 3 are snRNAs and 85 are unidentified . The fold changes of these genes were observed to fluctuate from −1.15 to −13.45 for down regulated genes and from 1.14 to 22.91 for up-regulated genes.

These data suggest that the consumption of BB extract can considerably affect the expression of genes, not only protein coding but also protein non-coding genes in adipose tissue. The list of differentially expressed genes were then submitted to functional bio-informatic analyses.With the objective to inquire in the cellular functions of significantly moderated protein coding genes, we first conducted gene ontology enrichment analysis using Meta scape and Cytoscape tools. Gene ontology analysis by p-value indicated that black bean extract impacted numerous biological functional categories that include cell substrate junction assembly, phosphatidylinositol phosphate binding, fat pad development, regulation of cysteine-type endopeptidase activity, among others . Additionally, we performed a network analysis of over-represented gene ontologies where terms with a p-value <0.05, a minimum count of 3, and an enrichment factor >1.5 are collected and grouped into clusters based on their similarities . To obtain a more detailed understanding of the cellular functions that are regulated by protein coding genes significantly modulated by black bean extract, we then performed pathway enrichment analysis of up- and down-regulated differentially expressed genes using Metascape tool . The results showed that anthocyanin-rich BB extract changed the expression of genes up regulating important pathways in T2DM pathogenesis like insulin secretion, cell-substrate junction assembly, ER organization, phosphatidylserine binding, phosphatidylinositol 3-kinase binding, among others. On the other hand, BB extract also altered the expression of genes that down regulate signaling pathways involved with regulation of NIK/NF-kappaB, regulation of response to extracellular stimulus, positive regulation of cell junction assembly, negative regulation of cell population proliferation, cell adhesion molecules and negative regulation of actin filament polymerization.

Our next step was to use STRING database to explore the potential protein–protein interactions of genes identified as differentially expressed by black bean extract intake. The analysis revealed a network of interactions between identified proteins as presented in Figure 5A, as well as genes that form nodes in the network. The next step was to select the genes with the highest number of interactions with other genes and which potentially play an important role in multi-genomic effects. The number of interactions reached 12 for UBB , or 11 for MST1R and RRAS2 , or proteins like INS1 or INPPL1 with 5 or more interactions . Interestingly, pathway enrichment analyses of hub proteins conducted in GeneTrail revealed that these genes are involved in insulin signaling, mature onset of diabetes, insulin resistance, inositol phosphate metabolism or AMPK signaling pathway . Our next objective was to identify transcriptional regulators involved in the observed changes of genes, that is, transcription factors which could have their activity altered by black bean extract and affect the expression of identified significantly modulated genes. To this end, we used the database TRANSFAC and JASPAR using the Enrichr platform. Among the top ten transcription factors identified are GATA2, POU2AF1, IRF3, GATA1, NR2F2 or PPARA . It could be suggested that circulating polyphenol metabolites generated after BB extract intake could interact with transcription factors and/or cell signaling proteins regulating their activity. With the aim to test this hypothesis, we searched the capacity of major metabolites of black bean to interact and bind to these proteins using a 3D docking online server. We assessed the binding capacity of 3 major metabolites, delphinidin 3-glucoside, petunidin 3-glucoside and malvidin 3-glucoside: delphinidin 3-glucoside to GATA2 ; delphinidin 3-glucoside to POU2AF1 ; petunidin 3-glucoside to GATA2 ; malvidin 3-glucoside to GATA2 and malvidin 3-glucoside to POU2AF1 . We observed that petunidin 3-glucoside showed potential binding capacity of -6.4 kcal/mol to POU2AF1, as well as petunidin 3-glucoside and delphinidin 3-glucoside with GATA2 , and POU2AF1 , respectively. These results shows that anthocyanins in BB can interact with cell signaling proteins and produce changes in their kinase activity,growing raspberries in container this modulates the activity of downstream cell signaling proteins and consequently transcription factors.The described changes could result in the observed gene expression modifications. Our gene expression analysis also allowed us to surmise that BB can also lead to alterations in the expression of not only protein coding RNAs but also non-coding RNAs,such as miRNAs. We observed changes in expression of 33 miRNAs, including Mir615, Mir152, Mir219a1 or Mir384. Using existing database, we searched for target genes of the identified miRNAs, and nearly 500 target genes were identified. These target genes and identified miRNAs form a network of interactions as presented in the Figure 7A. To identify potential cellular functions affected by these miRNAs, we cross-examined the Mienturnet database to reveal over-represented pathways from both KEGG and Reactome databases, that is pathways associated with each of the miRNA recognized as differentially expressed by black bean extract. Among the pathways identified are PI3K- signaling pathway, Ras signaling pathway, type 1 diabetes mellitus, Insulin receptor substrate 1 related pathway, and regulation of insulin-like growth factor.

As we mentioned in the materials and methods section, we were not able to perform the RNA-lncRNAs interaction analysis in LncRRI research web server. However, in Supplementary Figure 1 we show the list of 39 lncRNAs with their fold changes that were modulated by the anthocyanin-rich BB extract.Together with identification of cellular mechanisms affected by different types of RNAs, we also aimed to identify diseases associated with identified differentially expressed genes. We used the Enrichr database OMIM disease tool that interconnects differentially expressed genes with diseases, revealing their possible role in prevention or development of these disorders. We observed that our genes differentially expressed between the BB and DB groups are significantly associated with metabolic disease, nutrition disorder, cardiovascular disease, and immune system disease . In this research we investigated the potential health benefits and the multigenomic mode of action of a rich-anthocyanin extract from BB on adipose tissue in the context of dietstreptozocin-induced type 2 diabetes mellitus. After 4 weeks dietary supplementation, we found that black bean extract improved the symptoms of T2DM and insulin resistance, controlled the levels of blood glucose, and pro-inflammatory cytokines. The use of RNAseq revealed a complex multigenomic mode action of these bio-active compounds in adipose tissue by modulating expression of protein coding, miRNA, transcription factors, and lncRNAs , regulating processes like inflammation, metabolism and cell signaling. In the last years, special interest was given to research on natural and non-toxic antidiabetic agents. Functional foods contain bio-active compounds that can exert health advantages beyond their natural properties when consumed in a regular and consistent manner through diet . Anthocyanins are an important class of polyphenols featured by their promising effects on T2DM acting on suppression of carbohydrate-metabolizing enzymes; decrease of glucose transporters expression or activity; inhibition of glycogenolysis and modifying the gut microbiota by anthocyanin breakdown products . In this research we found that an anthocyanin-rich BB extract improved glucose levels on diabetic rats. One of the effects of anthocyanins in T2DM is the suppression of postprandial glycaemia through the inhibition of α-amylase and α-glucosidase enzymes. In a study conducted by Törrönen et al., the authors evaluated the effect of berries, naturally rich in anthocyanins, on postprandial glucose levels in healthy volunteer adults. Another study showed that consumption of a rich-anthocyanin puree containing bilberries, blackcurrants, cranberries, strawberries, and 35 g of sucrose resulted, after 15 and 30 min, in lower levels of glucose when compared with the control group that only consumed sucrose . Using in silico and in vivo studies, pelargonidin-3-O-rutinose present in strawberries exhibited the potential to improve postprandial hyperglycemia by inhibiting α-glucosidase . Another mechanism of action of anthocyanins is their impact on glucose transporters. It was demonstrated that an anthocyaninrich berry-extract considerably decreased sodium-dependent and sodium-independent transporters in Caco-2 cells and also reduced the expression of genes encoding SGLT1 and GLUT2, suggesting that anthocyanins can regulate the rate of glucose absorption . The over-expression of glycogenolysis in the liver releases glucose into the bloodstream; glycogen synthase kinase is a key liver enzyme that inhibits glycogen synthase enzyme to convert glycogen to glucose. Herrera-Balandrano et al., investigated the hypoglycemic effects of malvidin from a blueberry anthocyanin extract and observed that BAE could improve insulin sensitivity by inhibiting GSK3β and glycogen synthase in the insulinindependent pathway . Moreover, a recent systematic review describes that anthocyanins can also exert their health effects by modulating the gut microbiota composition, particularly by increasing Bacteroidetes and decreasing Firmicutes. These changes will result in higher production of short chain fatty acids, lower intestinal permeability and pH, greater number of goblet cells and improvement of villi anatomy .