Dairy products are a good source of essential nutrients and past reviews have shown associations of dairy consumption with decreased systemic inflammation. Links between dairy intake and gastrointestinal (GI) inflammation are under-investigated. Therefore, we examined associations between reported dairy intake and markers of GI inflammation in healthy adults in a cross-sectional observational study, hypothesizing a negative association with yogurt intake, suggesting a protective effect, and no associations with total dairy, fluid milk, and cheese intake. Participants completed 24-h dietary recalls and a food frequency questionnaire (FFQ) to assess recent and habitual intake, respectively. Those who also provided a stool sample (n = 295), and plasma sample (n = 348) were included in analysis. Inflammation markers from stool, including calprotectin, neopterin, and myeloperoxidase, were measured along with LPS-binding protein (LBP) from plasma. Regression models tested associations between dairy intake variables and inflammation markers with covariates: age, sex, and body mass index (BMI). As yogurt is episodically consumed, we examined differences in inflammation levels between consumers (>0 cup equivalents/day reported in recalls) and non-consumers. We found no significant associations between dairy intake and markers of GI inflammation. In this cohort of healthy adults, dairy intake was not associated with GI inflammation.

Abstract The use of cacao, in its familiar food and beverage form, dates back about 3,800 years. By the time of the discovery of America by Europeans, the Aztecs and Mayans had developed methods for drying, roasting and grinding cacao beans for use in beverages and foods. Today, the same processes are used, but have been adapted to modern machinery. The current study was conducted to compare the traditional Mesoamerican processing and modern processing methods and their impact on the antioxidant activity and flavan-3-ol content of the resulting processed cocoa mass. Two cocoa bean types were used: unfermented cocoa beans commonly produced and consumed today by the native peoples of Mesoamerica, and fermented Ivory Coast cocoa beans representing the most common country of origin for cocoa in the world today. Both bean types were processed by roasting and grinding using traditional and modern processing methods. The traditional method consisted of roasting whole beans on an earthenware comal heated with wood charcoal, de-shelling the beans, then grinding the beans to a paste using a stone metate and mano. The modern method consisted of roasting cocoa beans with pilot-scale equipment that simulates large-scale chocolate manufacturing using whole bean drum roasters, deshelling the beans followed by mechanical grinding using a ball mill producing a chocolate paste. The antioxidant capacity and flavanol content of these chocolate pastes were then determined. The data show that the antioxidant capacity and flavanol content of unprocessed Mexican Lavado cocoa beans were significantly higher than that of the unprocessed, fermented Ivory Coast cocoa beans. In unfermented Mexican Lavado cocoa beans, the traditional and modern processing revealed no clear advantage with respect to the antioxidant and flavanol contents. However, for fermented Ivory Coast beans, there were some differences in the level of flavanols between traditionally processed and modern processed fermented beans. These differences, while significant for some, but not all of the flavanol measures, were attributed to final roast temperatures achieved and to the possible lack of uniformity of bean fermentation.

Huanglongbing (HLB), also known as Citrus Greening Disease, is caused by the bacterium 'Candidatus Liberibacter asiaticus' (CLas) and is a serious threat to the citrus industry. To understand the effect of CLas infection on the citrus metabolome, juice from healthy (n = 18), HLB-asymptomatic (n = 18), and HLB-symptomatic Hamlin (n = 18), as well as from healthy (n = 18) and HLB-symptomatic (n = 18) Valencia sweet oranges (from southern and eastern Florida) were evaluated using (1)H NMR-based metabolomics. Differences in the concentration of several metabolites including phenylalanine, histidine, limonin, and synephrine between control or asymptomatic fruit and symptomatic fruit were observed regardless of the citrus variety or location. There were no clear differences between the metabolite profiles of Hamlin fruits classified by PCR as asymptomatic and control, suggesting that some of the control fruit may have been infected. Taken together, these data indicate that infection due to CLas presents a strong metabolic response that is observed across different cultivars and regions, suggesting the potential for generation of metabolite-based biomarkers of CLas infection.

Routine asymptomatic testing strategies for COVID-19 have been proposed to prevent outbreaks in high-risk healthcare environments. We used simulation modeling to evaluate the optimal frequency of viral testing. We found that routine testing substantially reduces risk of outbreaks, but may need to be as frequent as twice weekly.

The Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) is a free dietary recall system that outputs fewer nutrients than the Nutrition Data System for Research (NDSR). NDSR uses the Nutrition Coordinating Center (NCC) Food and Nutrient Database, both of which require a license. Manual lookup of ASA24 foods into NDSR is time-consuming but currently the only way to acquire NCC-exclusive nutrients. Using lactose as an example, we evaluated machine learning and database matching methods to estimate this NCC-exclusive nutrient from ASA24 reports. ASA24-reported foods were manually looked up into NDSR to obtain lactose estimates and split into training (n = 378) and test (n = 189) datasets. Nine machine learning models were developed to predict lactose from the nutrients common between ASA24 and the NCC database. Database matching algorithms were developed to match NCC foods to an ASA24 food using only nutrients ("Nutrient-Only") or the nutrient and food descriptions ("Nutrient + Text"). For both methods, the lactose values were compared to the manual curation. Among machine learning models, the XGB-Regressor model performed best on held-out test data (R2 = 0.33). For the database matching method, Nutrient + Text matching yielded the best lactose estimates (R2 = 0.76), a vast improvement over the status quo of no estimate. These results suggest that computational methods can successfully estimate an NCC-exclusive nutrient for foods reported in ASA24.

Photo-based dietary assessment is becoming more feasible as artificial intelligence methods improve. However, advancement of these methods for dietary assessment in research settings has been hindered by the lack of an appropriate dataset against which to benchmark algorithm performance. We conducted the Surveying Nutrient Assessment with Photographs of Meals (SNAPMe) study (ClinicalTrials ID: NCT05008653) to pair meal photographs with traditional food records. Participants were recruited nationally, and 110 enrollment meetings were completed via web-based video conferencing. Participants uploaded and annotated their meal photos using a mobile phone app called Bitesnap and completed food records using the Automated Self-Administered 24-h Dietary Assessment Tool (ASA24®) version 2020. Participants included photos before and after eating non-packaged and multi-serving packaged meals, as well as photos of the front and ingredient labels for single-serving packaged foods. The SNAPMe Database (DB) contains 3311 unique food photos linked with 275 ASA24 food records from 95 participants who photographed all foods consumed and recorded food records in parallel for up to 3 study days each. The use of the SNAPMe DB to evaluate ingredient prediction demonstrated that the publicly available algorithms FB Inverse Cooking and Im2Recipe performed poorly, especially for single-ingredient foods and beverages. Correlations between nutrient estimates common to the Bitesnap and ASA24 dietary assessment tools indicated a range in predictive capacity across nutrients (cholesterol, adjusted R2 = 0.85, p < 0.0001; food folate, adjusted R2 = 0.21, p < 0.05). SNAPMe DB is a publicly available benchmark for photo-based dietary assessment in nutrition research. Its demonstrated utility suggested areas of needed improvement, especially the prediction of single-ingredient foods and beverages.

Background

Human milk is the gold standard of nutrition for infants, providing both protective and essential nutrients. Although much is known about milk from mothers giving birth to term infants, less is known about milk from mothers giving birth to premature infants. In addition, little is known about the composition and diversity of small molecules in these milks and how they change over the first month of lactation.

Objective

The objective was to understand how milk metabolites vary over the first month of lactation in mothers giving birth to term and preterm infants.

Methods

(1)H nuclear magnetic resonance (NMR) metabolomics was used to characterize metabolites that were present in micromolar to molar concentrations in colostrum (day 0-5 postpartum), transition milk (day 14), and mature milk (day 28) from mothers who delivered term (n = 15) and preterm (n = 13) infants. Principal components analysis, linear mixed-effects models (LMMs), and linear models (LMs) were used to explore the relation between infant maturity and the postpartum day of collection of milk samples.

Results

By using a standard NMR metabolite library, 69 metabolites were identified in the milks, including 15 sugars, 23 amino acids and derivatives, 11 energy-related metabolites, 10 fatty acid-associated metabolites, 3 nucleotides and derivatives, 2 vitamins, and 5 bacteria-associated metabolites. Many metabolite concentrations followed a similar progression over time in both term and preterm milks, with more biological variation in metabolite concentrations in preterm milk. However, although lacto-N-neotetraose (LMM, P = 4.0 × 10(-5)) and lysine (LM, P = 1.5 × 10(-4)) significantly decreased in concentration in term milk over time, they did not significantly change in preterm milk.

Conclusion

Overall, the metabolic profile of human milk is dynamic throughout the first month of lactation, with more variability in preterm than in term milk and subtle differences in some metabolite concentrations. This trial was registered at clinicaltrials.gov as NCT01841268.

The possibility of a massive oil spill in the Red Sea is increasingly likely. The Safer, a deteriorating oil tanker containing 1.1 million barrels of oil, has been deserted near the coast of Yemen since 2015 and threatens environmental catastrophe to a country presently in a humanitarian crisis. Here, we model the immediate public health impacts of a simulated spill. We estimate that all of Yemen's imported fuel through its key Red Sea ports would be disrupted and that the anticipated spill could disrupt clean-water supply equivalent to the daily use of 9.0-9.9 million people, food supply for 5.7-8.4 million people and 93-100% of Yemen's Red Sea fisheries. We also estimate an increased risk of cardiovascular hospitalization from pollution ranging from 5.8 to 42.0% over the duration of the spill. The spill and its potentially disastrous impacts remain entirely preventable through offloading the oil. Our results stress the need for urgent action to avert this looming disaster.

Nopal is a cactus plant widely consumed in Mexico that has been used in traditional medicine to aid in the treatment of type-2 diabetes. We previously showed that chronic consumption of dehydrated nopal ameliorated hepatic steatosis in obese (fa/fa) rats; however, description of the effects on other tissues is sparse. The aim of the present study was to investigate the effects of nopal cladode consumption on intestinal physiology, microbial community structure, adipose tissue, and serum biochemistry in diet-induced obese rats. Rats were fed either a normal fat (NF) diet or a HF diet containing 4% of dietary fiber from either nopal or cellulose for 6 weeks. Consumption of nopal counteracted HF-induced adiposity and adipocyte hypertrophy, and induced profound changes in intestinal physiology. Nopal consumption reduced biomarkers of intestinal inflammation (mRNA expression of IL-6) and oxidative stress (ROS), modfied gut microbiota composition, increasing microbial diversity and cecal fermentation (SCFA), and altered the serum metabolome. Interestingly, metabolomic analysis of dehydrated nopal revealed a high choline content, which appeared to generate high levels of serum betaine, that correlated negatively with hepatic triglyceride (TAG) levels. A parallel decrease in some of the taxa associated with the production of trimethylamine, suggest an increase in choline absorption and bioavailability with transformation to betaine. The latter may partially explain the previously observed effect of nopal on the development of hepatic steatosis. In conclusion, this study provides new evidence on the effects of nopal consumption on normal and HF-diet induced changes in the intestine, the liver and systemic metabolism.

Mechanistic research suggests a unique evolutionary relationship between complex milk oligosaccharides and cognate bifidobacteria enriched in breast-fed infants. Bovine milk oligosaccharides (BMO) were recently identified as structurally and functionally similar to human milk oligosaccharides. The present single-blind three-way crossover study is the first to determine the safety and tolerability of BMO consumption by healthy human participants (n 12) and its effects on faecal microbiota and microbial metabolism. Participants consumed each supplement (placebo-control; low- and high-BMO doses) for eleven consecutive days, followed by a 2-week washout period prior to initiating the next supplement arm. Low and high BMO doses were consumed as 25 and 35 % of each individual's daily fibre intake, respectively. Safety and tolerability were measured using standardised questionnaires on gut and stomach discomfort and stool consistency. Faecal extracts were profiled for bacterial populations by next-generation sequencing (NGS) and bifidobacteria presence was confirmed using quantitative PCR. Urine was analysed for changes in microbial metabolism using nuclear magnetic resonance spectroscopy (¹H-NMR). Consumption of both the low and high BMO doses was well tolerated and did not change stool consistency from baseline. Multivariate analysis of the NGS results demonstrated no change in faecal microbiota phyla among the placebo-control and BMO supplement groups. In conclusion, BMO supplementation was well tolerated in healthy adults and has the potential to shift faecal microbiota toward beneficial strains as part of a synbiotic treatment with probiotic cultures that selectively metabolise oligosaccharides.