Valorisation of Agri-Food Waste for Bioactive Compounds: Recent Trends and Future Sustainable Challenges.

Worldwide, a massive amount of agriculture and food waste is a major threat to the environment, the economy and public health. However, these wastes are important sources of phytochemicals (bioactive), such as polyphenols, carotenoids, carnitine, coenzymes, essential oils and tocopherols, which have antioxidant, antimicrobial and anticarcinogenic properties. Hence, it represents a promising opportunity for the food, agriculture, cosmetics, textiles, energy and pharmaceutical industries to develop cost effective strategies. The value of agri-food wastes has been extracted from various valuable bioactive compounds such as polyphenols, dietary fibre, proteins, lipids, vitamins, carotenoids, organic acids, essential oils and minerals, some of which are found in greater quantities in the discarded parts than in the parts accepted by the market used for different industrial sectors. The value of agri-food wastes and by-products could assure food security, maintain sustainability, efficiently reduce environmental pollution and provide an opportunity to earn additional income for industries. Furthermore, sustainable extraction methodologies like ultrasound-assisted extraction, pressurized liquid extraction, supercritical fluid extraction, microwave-assisted extraction, pulse electric field-assisted extraction, ultrasound microwave-assisted extraction and high hydrostatic pressure extraction are extensively used for the isolation, purification and recovery of various bioactive compounds from agri-food waste, according to a circular economy and sustainable approach. This review also includes some of the critical and sustainable challenges in the valorisation of agri-food wastes and explores innovative eco-friendly methods for extracting bioactive compounds from agri-food wastes, particularly for food applications. The highlights of this review are providing information on the valorisation techniques used for the extraction and recovery of different bioactive compounds from agricultural food wastes, innovative and promising approaches. Additionally, the potential use of these products presents an affordable alternative towards a circular economy and, consequently, sustainability. In this context, the encapsulation process considers the integral and sustainable use of agricultural food waste for bioactive compounds that enhance the properties and quality of functional food.

Comparison of Sales From Vending Machines With 4 Different Food and Beverage Messages: A Randomized Trial.

Importance: Point-of-sale food messaging can encourage healthier purchases, but no studies have directly compared multiple interventions in the field. Objective: To examine which of 4 food and beverage messages would increase healthier vending machine purchases. Design, Setting, and Participants: This randomized trial assessed 13 months (February 1, 2019, to February 29, 2020) of vending sales data from 267 machines and 1065 customer purchase assessments from vending machines on government property in Philadelphia, Pennsylvania. Data analysis was performed from March 5, 2020, to November 8, 2022. Interventions: Study interventions were 4 food and beverage messaging systems: (1) beverage tax posters encouraging healthy choices because of the Philadelphia tax on sweetened drinks; (2) green labels for healthy products; (3) traffic light labels: green (healthy), yellow (moderately healthy), or red (unhealthy); or (4) physical activity equivalent labels (minutes of activity to metabolize product calories). Main Outcomes and Measures: Sales data were analyzed separately for beverages and snacks. The main outcomes analyzed at the transaction level were calories sold and the health status (using traffic light criteria) of each item sold. Additional outcomes were analyzed at the monthly machine level: total units sold, calories sold, and units of each health status sold. The customer purchase assessment outcome was calories purchased per vending trip. Results: Monthly sales data came from 150 beverage and 117 snack vending machines, whereas 1065 customers (558 [52%] male) contributed purchase assessment data. Traffic light labels led to a 30% decrease in the mean monthly number of unhealthy beverages sold (mean ratio [MR], 0.70; 95% CI, 0.55-0.88) compared with beverage tax posters. Physical activity labels led to a 34% (MR, 0.66; 95% CI, 0.51-0.87) reduction in the number of unhealthy beverages sold at the machine level and 35% (MR, 0.65; 95% CI, 0.50-0.86) reduction in mean calories sold. Traffic light labels also led to a 30-calorie reduction (b = -30.46; 95% CI, -49.36 to -11.56) per customer trip in the customer purchase analyses compared to physical activity labels. There were very few significant differences for snack machines. Conclusions and Relevance: In this 13-month randomized trial of 267 vending machines, the traffic light and physical activity labels encouraged healthier beverage purchases, but no change in snack sales, compared with a beverage tax poster. Corporations and governments should consider such labeling approaches to promote healthier beverage choices. Trial Registration: ClinicalTrials.gov Identifier: NCT06260176.

The relationship between the price and demand of alcohol, tobacco, unhealthy food, sugar-sweetened beverages, and gambling: an umbrella review of systematic reviews.

BACKGROUND: The WHO highlight alcohol, tobacco, unhealthy food, and sugar-sweetened beverage (SSB) taxes as one of the most effective policies for preventing and reducing the burden of non-communicable diseases. This umbrella review aimed to identify and summarise evidence from systematic reviews that report the relationship between price and demand or price and disease/death for alcohol, tobacco, unhealthy food, and SSBs. Given the recent recognition as gambling as a public health problem, we also included gambling. METHODS: The protocol for this umbrella review was pre-registered (PROSPERO CRD42023447429). Seven electronic databases were searched between 2000-2023. Eligible systematic reviews were those published in any country, including adults or children, and which quantitatively examined the relationship between alcohol, tobacco, gambling, unhealthy food, or SSB price/tax and demand (sales/consumption) or disease/death. Two researchers undertook screening, eligibility, data extraction, and risk of bias assessment using the ROBIS tool. RESULTS: We identified 50 reviews from 5,185 records, of which 31 reported on unhealthy food or SSBs, nine reported on tobacco, nine on alcohol, and one on multiple outcomes (alcohol, tobacco, unhealthy food, and SSBs). We did not identify any reviews on gambling. Higher prices were consistently associated with lower demand, notwithstanding variation in the size of effect across commodities or populations. Reductions in demand were large enough to be considered meaningful for policy. CONCLUSIONS: Increases in the price of alcohol, tobacco, unhealthy food, and SSBs are consistently associated with decreases in demand. Moreover, increasing taxes can be expected to increase tax revenue. There may be potential in joining up approaches to taxation across the harm-causing commodities.

Trends in the contribution of greenhouse gas emissions from food and beverage purchases in Mexico: 1989-2020.

BACKGROUND: Assessing the trends in dietary GHGE considering the social patterning is critical for understanding the role that food systems have played and will play in global emissions in countries of the global south. Our aim is to describe dietary greenhouse gas emissions (GHGE) trends (overall and by food group) using data from household food purchase surveys from 1989 to 2020 in Mexico, overall and by education levels and urbanicity. METHODS: We used cross-sectional data from 16 rounds of Mexico's National Income and Expenditure Survey, a nationally representative survey. The sample size ranged from 11,051 in 1989 to 88,398 in 2020. We estimated the mean total GHGE per adult-equivalent per day (kg CO2-eq/ad-eq/d) for every survey year. Then, we estimated the relative GHGE contribution by food group for each household. These same analyses were conducted stratifying by education and urbanicity. RESULTS: The mean total GHGE increased from 3.70 (95%CI: 3.57, 3.82) to 4.90 (95% CI 4.62, 5.18) kg CO2-eq/ad-eq/d between 1989 and 2014 and stayed stable between 4.63 (95% CI: 4.53, 4.72) and 4.89 (95% CI: 4.81, 4.96) kg CO2-eq/ad-eq/d from 2016 onwards. In 1989, beef (19.89%, 95% CI: 19.18, 20.59), dairy (16.87%, 95% CI: 16.30, 17.42)), corn (9.61%, 95% CI: 9.00, 10.22), legumes (7.03%, 95% CI: 6.59, 7.46), and beverages (6.99%, 95% CI: 6.66, 7.32) had the highest relative contribution to food GHGE; by 2020, beef was the top contributor (17.68%, 95%CI: 17.46, 17.89) followed by fast food (14.17%, 95% CI: 13.90, 14.43), dairy (11.21%, 95%CI: 11.06, 11.36), beverages (10.09%, 95%CI: 9.94, 10.23), and chicken (10.04%, 95%CI: 9.90, 10.17). Households with higher education levels and those in more urbanized areas contributed more to dietary GHGE across the full period. However, households with lower education levels and those in rural areas had the highest increase in these emissions from 1989 to 2020. CONCLUSIONS: Our results provide insights into the food groups in which the 2023 Mexican Dietary Guidelines may require to focus on improving human and planetary health.

Development and testing of two tools to assess point-of-sale food and beverage marketing to children in restaurants.

OBJECTIVE: To describe the development and testing of two assessment tools designed to assess exterior (including drive-thru) and interior food and beverage marketing in restaurants with a focus on marketing to children and teens. DESIGN: A scoping review on restaurant marketing to children was undertaken, followed by expert and government consultations to produce a draft assessment tool. The draft tool was mounted online and further refined into two separate tools: the Canadian Marketing Assessment Tool for Restaurants (CMAT-R) and the CMAT-Photo Coding Tool (CMAT-PCT). The tools were tested to assess inter-rater reliability using Cohen's Kappa and per cent agreement for dichotomous variables, and intra-class correlation coefficients (ICCs) for continuous or rank-order variables. SETTING: Waterloo, Ontario, Canada. PARTICIPANTS: Restaurants of all types were assessed using the CMAT-R (n 57), and thirty randomly selected photos were coded using the CMAT-PCT. RESULTS: The CMAT-R collected data on general promotions and restaurant features, drive-thru features, the children's menu and the dollar/value menu. The CMAT-PCT collected data on advertisement features, features considered appealing to children and teens, and characters. The inter-rater reliability of the CMAT-R tool was strong (mean per cent agreement was 92·4 %, mean Cohen's κ = 0·82 for all dichotomous variables and mean ICC = 0·961 for continuous/count variables). The mean per cent agreement for the CMAT-PCT across items was 97·3 %, and mean Cohen's κ across items was 0·91, indicating very strong inter-rater reliability. CONCLUSIONS: The tools assess restaurant food and beverage marketing. Both showed high inter-rater reliability and can be adapted to better suit other contexts.

Share of food group expenditure in Mexican households according to the gender of the head of household and size of the locality.

OBJECTIVE: To evaluate differences in the percentage of expenditure on food groups in Mexican households according to the gender of the household head and the size of the locality. DESIGN: Analysis of secondary data from the National Household Income and Expenditure Survey (ENIGH) 2018. We estimated the percentage of expenditure on fifteen food groups according to the gender of the head of household and locality size and evaluated the differences using a two-part model approach. SETTING: Mexico, 2018. PARTICIPANTS: A nationally representative sample of 74 647 Mexican households. RESULTS: Female-headed households allocated a lower share of expenditure to the purchase of sweetened beverages and alcoholic beverages and higher percentages to milk and dairy, fruits and water. In comparison with metropolitan households, households in rural and urban localities spent more on cereals and tubers, sugar and honey, oil and fat and less on food away from home. CONCLUSIONS: Households allocate different percentages of expenditure to diverse food groups according to the gender of the head of the household and the size of the locality where they are located. Future research should focus on understanding the economic and social disparities related to differences in food expenditure, including the gender perspective.

Predicting the short and long term effects of food price inflation, armed conflicts, and climate variability on global acute malnutrition in Somalia.

BACKGROUND: Malnutrition poses a substantial challenge in Somalia, impacting approximately 1.8 million children. This critical issue is exacerbated by a multifaceted interplay of factors. Consequently, this study seeks to examine the long-term and short-term effects of armed conflicts, food price inflation, and climate variability on global acute malnutrition in Somalia. METHODS: The study utilized secondary data spanning from January 2015 to December 2022, sourced from relevant databases. Two distinct analytical approaches were employed to comprehensively investigate the dynamics of global acute malnutrition in Somalia. Firstly, dynamic autoregressive distributed lag (ARDL) simulations were applied, allowing for a nuanced understanding of the short and long-term effects of armed conflicts, food price inflation, and climate variability on malnutrition. Additionally, the study employed kernel-based regularized least squares, a sophisticated statistical technique, to further enhance the robustness of the findings. The analysis was conducted using STATA version 17. RESULTS: In the short run, armed conflicts and food price inflation exhibit positive associations with global acute malnutrition, particularly in conflict-prone areas and during inflationary periods. Moreover, climatic variables, specifically temperature and rainfall, demonstrate positive associations. It is important to note that temperature lacks a statistically significant relationship with global acute malnutrition in the short run. In the long run, armed conflicts and food price inflation maintain persistent impacts on global acute malnutrition, as confirmed by the dynamic ARDL simulations model. Furthermore, both temperature and rainfall continue to show positive associations with global acute malnutrition, but it is worth noting that temperature still exhibits a non-significant relationship. The results from kernel-based regularized least squares were consistent, further enhancing the robustness of the findings. CONCLUSIONS: Increased armed conflicts, food price inflation, temperature, and rainfall were associated with increased global acute malnutrition. Strategies such as stabilizing conflict-prone regions, diplomatic interventions, and peace-building initiatives are crucial, along with measures to control food price inflation. Implementing climate adaptation strategies is vital to counter temperature changes and fluctuating rainfall patterns, emphasizing the need for resilience-building. Policymakers and humanitarian organizations can leverage these insights to design targeted interventions, focusing on conflict resolution, food security, and climate resilience to enhance Somalia's overall nutritional well-being.

Wild capuchin monkeys use stones and sticks to access underground food.

Primates employ different tools and techniques to overcome the challenges of obtaining underground food resources. Humans and chimpanzees are known to tackle this problem with stick tools and one population of capuchin monkeys habitually uses stone tools. Although early hominids could have used stones as digging tools, we know little about when and how these could be useful. Here, we report a second primate population observed using stone tools and the first capuchin monkey population to habitually use the 'stick-probing' technique for obtaining underground resources. The bearded capuchin monkeys (Sapajus libidinosus) from Ubajara National Park, Brazil, use 'hands-only' and 'stone-digging' techniques for extracting underground storage organs and trapdoor spiders. Males also use 'stick-probing' and 'stone-stick' techniques for capturing trapdoor spiders. Tool use does not increase success in obtaining these resources. Stone-digging is less frequent in this population than in the only other known population that uses this technique. Females use stones in a lower proportion of their digging episodes than males in both populations. Ecological and cultural factors potentially influence technique choice and sex differences within and between populations. This population has a different pattern of underground food exploration using tools. Comparing this population with others and exploring the ecological and cultural factors under which capuchin monkeys employ different tools and techniques will allow us to better understand the pressures that may have shaped the evolution of those behaviors in primates.

Fine-grained food image classification and recipe extraction using a customized deep neural network and NLP.

Global eating habits cause health issues leading people to mindful eating. This has directed attention to applying deep learning to food-related data. The proposed work develops a new framework integrating neural network and natural language processing for classification of food images and automated recipe extraction. It address the challenges of intra-class variability and inter-class similarity in food images that have received shallow attention in the literature. Firstly, a customized lightweight deep convolution neural network model, MResNet-50 for classifying food images is proposed. Secondly, automated ingredient processing and recipe extraction is done using natural language processing algorithms: Word2Vec and Transformers in conjunction. Thirdly, a representational semi-structured domain ontology is built to store the relationship between cuisine, food item, and ingredients. The accuracy of the proposed framework on the Food-101 and UECFOOD256 datasets is increased by 2.4% and 7.5%, respectively, outperforming existing models in literature such as DeepFood, CNN-Food, Wiser, and other pre-trained neural networks.

Predicted impact of banning nonessential, energy-dense food and beverages in schools in Mexico: A microsimulation study.

BACKGROUND: Childhood obesity is a growing concern worldwide. School-based interventions have been proposed as effective means to improve nutritional knowledge and prevent obesity. In 2023, Mexico approved a reform to the General Education Law to strengthen the ban of sales and advertising of nonessential energy-dense food and beverages (NEDFBs) in schools and surroundings. We aimed to predict the expected one-year change in total caloric intake and obesity prevalence by introducing the ban of NEDFBs sales in schools, among school-aged children and adolescents (6 to 17 years old) in Mexico. METHODS AND FINDINGS: We used age-specific equations to predict baseline fat-free mass (FFM) and fat mass (FM) and then estimated total energy intake (TEI) per day. The TEI after the intervention was estimated under 4 scenarios: (1) using national data to inform the intervention effect; (2) varying law compliance; (3) using meta-analytic data to inform the intervention effect size on calories; and (4) using national data to inform the intervention effect by sex and socioeconomic status (SES). We used Hall's microsimulation model to estimate the potential impact on body weight and obesity prevalence of children and adolescents 1 year after implementing the intervention in Mexican schools. We found that children could reduce their daily energy intake by 33 kcal/day/person (uncertainty interval, UI, [25, 42] kcal/day/person), reducing on average 0.8 kg/person (UI [0.6, 1.0] kg/person) and 1.5 percentage points (pp) in obesity (UI [1.1, 1.9] pp) 1 year after implementing the law. We showed that compliance will be key to the success of this intervention: considering a 50% compliance the intervention effect could reduce 0.4 kg/person (UI [0.3, 0.5] kg/person). Our sensitivity analysis showed that the ban could reduce body weight by 1.3 kg/person (UI [0.8, 1.8] kg/person) and up to 5.4 kg/person (UI [3.4, 7.5] kg/person) in the best-case scenario. Study limitations include assuming that obesity and the contribution of NEDFBs consumed at school remain constant over time, assuming full compliance, and not considering the potential effect of banning NEDFBs in stores near schools. CONCLUSIONS: Even in the most conservative scenario, banning sales of NEDFBs in schools is expected to significantly reduce obesity, but achieving high compliance will be key to its success. WHY WAS THIS STUDY DONE?: - School-based interventions have been recognized as effective means to improve nutritional knowledge and prevent obesity-related diseases.- In December 2023, the Chamber of Representatives of Mexico approved an amendment that strengthens and updates the General Education Law (Article 75) and nutritional guidelines to ban the sales and advertising of nonessential energy-dense food and beverages (NEDFBs) in schools. WHAT DID THE RESEARCHERS DO AND FIND?: - We used age-specific equations to predict baseline fat-free mass (FFM) and fat mass (FM) and total energy intake (TEI) per day.- We used microsimulation modeling to predict body weight and obesity prevalence of children and adolescents 1 year after implementing the intervention in Mexican schools.- Our modeling study suggests that an important impact on obesity prevalence can be expected if the law is implemented and enforced as intended. WHAT DO THESE FINDINGS MEAN?: - If successful, this law could serve as an example beyond Mexico on how to achieve changes in body weight through school food regulation.- An important limitation of our main scenario is that we assumed full compliance of schools with the law, yet lower compliance will reduce its impact. We also did not consider historical trends on obesity or NEDFBs consumed in schools during our 1 year simulation, and we considered only the ban impact inside schools, excluding effects near and outside schools.

Effects of sleep deprivation on food-related Pavlovian-instrumental transfer: a randomized crossover experiment.

Recent research suggests that insufficient sleep elevates the risk of obesity. Although the mechanisms underlying the relationship between insufficient sleep and obesity are not fully understood, preliminary evidence suggests that insufficient sleep may intensify habitual control of behavior, leading to greater cue-elicited food-seeking behavior that is insensitive to satiation. The present study tested this hypothesis using a within-individual, randomized, crossover experiment. Ninety-six adults underwent a one-night normal sleep duration (NSD) condition and a one-night total sleep deprivation (TSD) condition. They also completed the Pavlovian-instrumental transfer paradigm in which their instrumental responses for food in the presence and absence of conditioned cues were recorded. The sleep × cue × satiation interaction was significant, indicating that the enhancing effect of conditioned cues on food-seeking responses significantly differed across sleep × satiation conditions. However, this effect was observed in NSD but not TSD, and it disappeared after satiation. This finding contradicted the hypothesis but aligned with previous literature on the effect of sleep disruption on appetitive conditioning in animals-sleep disruption following learning impaired the expression of appetitive behavior. The present finding is the first evidence for the role of sleep in Pavlovian-instrumental transfer effects. Future research is needed to further disentangle how sleep influences motivational mechanisms underlying eating.

Agreement between a web collaborative dataset and an administrative dataset to assess the retail food environment in Mexico.

BACKGROUND: Latin American countries are often limited in the availability of food outlet data. There is a need to use online search engines that allow the identification of food outlets and assess their agreement with field observations. We aimed to assess the agreement in the density of food outlets provided by a web collaborative data (Google) against the density obtained from an administrative registry. We also determined whether the agreement differed by type of food outlet and by area-level socioeconomic deprivation. METHODS: In this cross-sectional study, we analyzed 1,693 census tracts from the municipalities of Hermosillo, Leon, Oaxaca de Juarez, and Tlalpan. The Google service was used to develop a tool for the automatic acquisition of food outlet data. To assess agreement, we compared food outlet densities obtained with Google against those registered in the National Statistical Directory of Economic Units (DENUE). Continuous densities were assessed using Bland-Altman plots and concordance correlation coefficient (CCC), while agreement across tertiles of density was estimated using weighted kappa. RESULTS: The CCC indicated a strong correlation between Google and DENUE in the overall sample (0.75); by food outlet, most of the correlations were from negligible (0.08) to moderate (0.58). The CCC showed a weaker correlation as deprivation increased. Weighted kappa indicated substantial agreement between Google and DENUE across all census tracts (0.64). By type of food outlet, the weighted kappa showed substantial agreement for restaurants (0.69) and specialty food stores (0.68); the agreement was moderate for convenience stores/small food retail stores (0.49) and fair for candy/ice cream stores (0.30). Weighted kappa indicated substantial agreement in low-deprivation areas (0.63); in very high-deprivation areas, the agreement was moderate (0.42). CONCLUSIONS: Google could be useful in assessing fixed food outlet densities as a categorical indicator, especially for some establishments, like specialty food stores and restaurants. The data could also be informative of the availability of fixed food outlets, particularly in less deprived areas.

How frequently is alcohol advertised on television in Canada?: A cross-sectional study.

AIMS: Alcohol marketing is a commercial driver of alcohol use, including among youth. This study sought to quantify and characterize alcohol advertising on broadcast television in Canada. METHODS: Open-source television program logs for January to December 2018 submitted to the Canadian Radio-television and Telecommunications Commission by 147 stations with alcohol advertisements were analyzed. RESULTS: Overall, 501 628 alcohol advertisements were broadcast. Four companies accounted for 83% of advertisements, namely, Anheuser-Busch in Bev (33.7%), Molson Coors (22.7%), Diageo (16.1%), and Arterra Wines Canada (10.8%). On conventional stations, advertising was highest on French-language stations [Median (Mdn) = 3224; interquartile range (IQR) = 2262] followed by those with programming in foreign/mixed languages (Mdn = 2679; IQR = 219) and English-language stations (Mdn = 1955; IQR = 1563). On speciality stations, advertising was most frequent on those primarily focused on sports programming (Mdn = 8036; IQR = 7393), movies and scripted shows (Mdn = 7463; IQR = 5937), and cooking (Mdn = 5498; IQR = 4032). On weekdays, 33% of alcohol ads aired from 6 to 9 a.m. and 3 to 9 p.m. and on weekends, 52% aired from 6 a.m. to 9 p.m. when children or adolescents are more likely to be watching television. On youth-oriented stations (n = 4), 7937 alcohol advertisements were broadcast with most airing from 9 p.m. to midnight (44-45%) or 12-6 a.m. (50%) on both weekdays and weekends. CONCLUSIONS: While few alcohol advertisements were broadcast on youth-oriented stations, young people in Canada are likely exposed to such advertising on programming intended for older or general audiences (e.g. sports). More research is needed to ascertain the extent to which broadcast television constitutes a source of alcohol advertising exposure among youth and to inform policies aimed at protecting them from the influence of such exposure.

Physiopathology and Treatment of Obesity and Overweight: A Proposal for a New Anorectic.

The "new epidemic," as WHO calls obesity, is caused by overeating, which, having exceeded the body's actual needs, accumulates in the form of health-damaging fat deposits. Moving more and eating less is the main remedy, but eating belongs to vital instincts, which are beyond the control of reason. In this sense, eating is different from drinking and breathing because without food it is possible to survive for a few weeks, without water for a few days, without oxygen for a few minutes. The first part of this article provides an overview of obesity and its treatment, focusing on the new anorectic anticipated in the title. The second part focuses on compulsive obesity, typically represented by constitutional obesity and food addiction. The article concludes with a discussion of the pharmacological treatment of compulsive diseases, to which some forms of obesity belong.

Whole genome sequencing analysis of Komagataeibacter nataicola reveals its potential in food waste valorisation for cellulose production.

BACKGROUND: Komagataeibacter nataicola (K. nataicola) is a gram-negative acetic acid bacterium that produces natural bacterial cellulose (BC) as a fermentation product under acidic conditions. The goal of this work was to study the complete genome of K. nataicola and gain insight into the functional genes in K. nataicola that are responsible for BC synthesis in acidic environments. METHODS AND RESULT: The pure culture of K. nataicola was obtained from yeast-glucose-calcium carbonate (YGC) agar, followed by genomic DNA extraction, and subjected to whole genome sequencing on a Nanopore flongle flow cell. The genome of K. nataicola consists of a 3,767,936 bp chromosome with six contigs and 4,557 protein coding sequences. The maximum likelihood phylogenetic tree and average nucleotide identity analysis confirmed that the bacterial isolate was K. nataicola. The gene annotation via RAST server discovered the presence of cellulose synthase, along with three genes associated with lactate utilization and eight genes involved in lactate fermentation that could potentially contribute to the increase in acid concentration during BC synthesis. CONCLUSION: A more comprehensive genome study of K. nataicola may shed light into biological pathway in BC productivity as well as benefit the analysis of metabolites generated and understanding of biological and chemical interactions in BC production later.

Odorant Receptors Expressing and Antennal Lobes Architecture Are Linked to Caste Dimorphism in Asian Honeybee, Apis cerana (Hymenoptera: Apidae).

Insects heavily rely on the olfactory system for food, mating, and predator evasion. However, the caste-related olfactory differences in Apis cerana, a eusocial insect, remain unclear. To explore the peripheral and primary center of the olfactory system link to the caste dimorphism in A. cerana, transcriptome and immunohistochemistry studies on the odorant receptors (ORs) and architecture of antennal lobes (ALs) were performed on different castes. Through transcriptomesis, we found more olfactory receptor genes in queens and workers than in drones, which were further validated by RT-qPCR, indicating caste dimorphism. Meanwhile, ALs structure, including volume, surface area, and the number of glomeruli, demonstrated a close association with caste dimorphism. Particularly, drones had more macroglomeruli possibly for pheromone recognition. Interestingly, we found that the number of ORs and glomeruli ratio was nearly 1:1. Also, the ORs expression distribution pattern was very similar to the distribution of glomeruli volume. Our results suggest the existence of concurrent plasticity in both the peripheral olfactory system and ALs among different castes of A. cerana, highlighting the role of the olfactory system in labor division in insects.

Nourishing Conversations: Using Motivational Interviewing in a Community Teaching Kitchen to Promote Healthy Eating via a Food as Medicine Intervention.

It is well known that dietary choices impact both individual and global health. However, there are numerous challenges at the personal and systemic level to fostering sustainable healthy eating patterns. There is a need for innovative ways to navigate these barriers. Food as Medicine (FM) and Culinary Medicine (CM) are approaches to helping individuals achieve healthier diets that also recognize the potential to alleviate the burden of chronic diseases through healthy eating. Teaching kitchens, which offer an interactive environment for learning nutrition and cooking skills, are valuable educational tools for FM and CM interventions. Motivational interviewing (MI), a type of person-centered counseling, facilitates behavior change and may enhance FM and CM programs involving teaching kitchens. In this commentary, we share our experience with using MI in a community-based CM program at a teaching kitchen. In demonstrating our application of MI principles, we hope to offer an additional strategy for improving dietary quality and delivering nutrition education.

Beyond the Bowl: Understanding Amino Acid Requirements and Digestibility to Improve Protein Quality Metrics for Dog and Cat Foods.

The determination of amino acid (AA) requirements for mammals has traditionally been done through nitrogen (N) balance studies, but this technique underestimates AA requirements in adult animals. There has been a shift toward researchers using the indicator amino acid oxidation (IAAO) technique for the determination of AA requirements in humans, and recently in dogs. However, the determination of AA requirements specific to adult dogs and cats at maintenance is lacking and the current requirements outlined by the National Research Council are based on a dearth of data and are likely underreporting the requirements of indispensable AA (IAA) for the population. To ensure the physiological requirements of our cats and dogs are met, we need methods to accurately and precisely measure digestibility. In vivo methods, such as ileal cannulation, are most commonly used, however, due to ethical considerations, we are moving away from animal models and toward in vitro methods. Harmonized static digestion models have the potential to replace in vivo methods but work needs to be done to have these methods more accurately represent the gastrointestinal tract (GIT) of cats and dogs. The Digestible IAA Score (DIAAS) is one metric that can help define protein quality for individual ingredients or mixed diets that uses AA SID estimates and ideally those can be replaced with in vitro AA digestibility estimates. Finally, we need accurate and reliable laboratory AA analyses to measure the AA present in complete diets, especially those used to quantify methionine (Met) and cysteine (Cys), both often limiting AAs in cat and dog diets. Together, this will guide accurate feed formulation for our companion animals to satisfy requirements while avoiding over-supplying protein, which inevitably contributes to excess N excretion, affecting both the environment and feed sustainability.