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The ‘double burden of malnutrition’ is a global health challenge that increasingly affects populations in both low- and middle-income countries (LMICs). This phenomenon refers to the coexistence of undernutrition and overweight or obesity, as well as other diet-related non-communicable diseases, in the same population, household or even individual. While noteworthy progress has been made in reducing undernutrition in some parts of the world, in many of these areas, the prevalence of overweight and obesity is increasing, particularly in urban areas, resulting in greater numbers of people who were undernourished in childhood and have overweight or obesity in adulthood. This creates a complex and challenging situation for research experts and policymakers who must simultaneously address the public health burdens of undernutrition and overweight/obesity. This review identifies key challenges and limitations in the current research on the double burden of malnutrition in individuals, including the need for a more comprehensive and nuanced understanding of the drivers of malnutrition, the importance of context-specific interventions and the need for greater attention to the food environment and food systems. We advocate for the re-evaluation of research strategies and focus, with a greater emphasis on multidisciplinary and systems approaches and greater attention to the synergistic relationship between the biological, environmental, commercial and socio-economic determinants of malnutrition. Addressing these key challenges can enable us to better comprehend and tackle the multifaceted and dynamic issues of the double burden of malnutrition, particularly in individuals and work towards more effective and sustainable solutions.

Background: Mycoprotein is a fungal source of protein that is increasingly consumed as an ingredient in meat analogs. Objectives: This study aimed to systematically review and meta-analyze the effects of mycoprotein intake on selected biomarkers of human health. Methods: This study was registered in PROSPERO (CRD42022308980). We searched the PubMed, Scopus, and Embase databases to identify randomized control trials in any language until 16 August, 2022. Trials were included if they administered a mycoprotein intervention against a nonmycoprotein control arm and if reported outcomes included blood lipids, blood glucose, insulin, blood pressure, or body weight. Eligible trials were assessed for risk of bias using the Cochrane risk-of-bias tool for randomized trials. An inverse-variance-weighted, random-effects meta-analysis model was used to assess the effects of intake across each biomarker. Results: Nine trials that included 178 participants with a mean follow-up of 13 d were included, with 4 reporting on blood lipids and 5 reporting on postprandial blood glucose or insulin. The overall reduction of total cholesterol was -0.55 mmol/L (95% CI: -0.85 to -0.26; P < 0.001) in the mycoprotein group compared to control, but no clear effects on HDL cholesterol, LDL cholesterol, or TGs were found (all P > 0.05). There were no reductions in postprandial blood glucose concentrations at 30, 60, 90 or 120 min. Postprandial blood insulin concentration was reduced by -76.51 pmol/L (95% CI: -150.75 to -2.28; P = 0.043) at 30 min, with no detectable effects at 60, 90, or 120 min. Conclusions: Mycoprotein intake may have important effects on blood lipids, but the evidence base is limited by the small sample sizes and short intervention periods of the contributing trials. The protocol for this systematic review has been registered in PROSPERO as CRD42022308980.

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug–omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug–drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities., Correction in DOI 10.1038/s41587-023-01805-9QC 20230626

We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.

Background: The capacity of an individual to respond to changes in food intake so that postprandial metabolic perturbations are resolved, and metabolism returns to its pre-prandial state, is called phenotypic flexibility. This ability may be a more important indicator of current health status than metabolic markers in a fasting state. Aim: In this parallel randomized controlled trial study, an energy-restricted healthy diet and 2 dietary challenges were used to assess the effect of weight loss on phenotypic flexibility. Methods: Seventy-two volunteers with overweight and obesity underwent a 12-wk dietary intervention. The participants were randomized to a weight loss group (WLG) with 20% less energy intake or a weight-maintenance group (WMG). At weeks 1 and 12, participants were assessed for body composition by MRI. Concurrently, markers of metabolism and insulin sensitivity were obtained from the analysis of plasma metabolome during 2 different dietary challenges—an oral glucose tolerance test (OGTT) and a mixed-meal tolerance test. Results: Intended weight loss was achieved in the WLG (−5.6 kg, P < 0.0001) and induced a significant reduction in total and regional adipose tissue as well as ectopic fat in the liver. Amino acid-based markers of insulin action and resistance such as leucine and glutamate were reduced in the postprandial phase of the OGTT in the WLG by 11.5% and 28%, respectively, after body weight reduction. Weight loss correlated with the magnitude of changes in metabolic responses to dietary challenges. Large interindividual variation in metabolic responses to weight loss was observed. Conclusion: Application of dietary challenges increased sensitivity to detect metabolic response to weight loss intervention. Large interindividual variation was observed across a wide range of measurements allowing the identification of distinct responses to the weight loss intervention and mechanistic insight into the metabolic response to weight loss.

BACKGROUND: The Manual of dietetic practice ('Manual') is the core textbook for qualified and student dietitians. A survey was conducted to explore views on the scope, content and presentation of the Manual to inform the forthcoming edition. METHODS: The survey comprised of questions on demographics, structure, content, access (print/digital), missing topics, strengths and weaknesses. It was distributed to members of the British Dietetic Association (BDA) and other relevant groups in August 2022. Responses are presented as frequencies and free text as themes. RESULTS: Of 1179 responses, 91% were from professionals, of whom 72% were registered dietitians with a mean of 12.7 years (range: 1-44) in practice: 60% worked in the United Kingdom with 52% based in a clinical setting. The printed version was preferred: 59% professionals, 60% students, 94% professionals and 88% students were satisfied with the structure; however, 26% professionals and 22% students identified content that was lacking or outdated, including mental health and sustainability. The strengths were its comprehensive coverage and respected contributing authors. Weaknesses included the cost, size, lack of visual aids and currency. Professionals indicated the seventh edition should focus on more practical information required for clinical practice, whereas students wanted more emphasis on summarised information and visual formats. CONCLUSIONS: The survey proved a valuable method to engage with the readership to ensure the next edition reflected their requirements. Although nearly all respondents were satisfied with the scope and content, the results highlighted those topics lacking and/or outdated. Results also showed that the next edition should focus on practical information required for clinical practice, with more summarised and visual formats.

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug-omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug-drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities.

Conventional approaches to dietary assessment are primarily grounded in self-reporting methods or structured interviews conducted under the supervision of dietitians. These methods, however, are often subjective, potentially inaccurate, and time-intensive. Although artificial intelligence (AI)-based solutions have been devised to automate the dietary assessment process, these prior AI methodologies encounter challenges in their ability to generalize across a diverse range of food types, dietary behaviors, and cultural contexts. This results in AI applications in the dietary field that possess a narrow specialization and limited accuracy. Recently, the emergence of multimodal foundation models such as GPT-4V powering the latest ChatGPT has exhibited transformative potential across a wide range of tasks (e.g., Scene understanding and image captioning) in numerous research domains. These models have demonstrated remarkable generalist intelligence and accuracy, capable of processing various data modalities. In this study, we explore the application of multimodal ChatGPT within the realm of dietary assessment. Our findings reveal that GPT-4V excels in food detection under challenging conditions with accuracy up to 87.5% without any fine-tuning or adaptation using food-specific datasets. By guiding the model with specific language prompts (e.g., African cuisine), it shifts from recognizing common staples like rice and bread to accurately identifying regional dishes like banku and ugali. Another GPT-4V's standout feature is its contextual awareness. GPT-4V can leverage surrounding objects as scale references to deduce the portion sizes of food items, further enhancing its accuracy in translating food weight into nutritional content. This alignment with the USDA National Nutrient Database underscores GPT-4V's potential to advance nutritional science and dietary assessment techniques., Comment: 10 pages

In our recent dietary assessment field studies on passive dietary monitoring in Ghana, we have collected over 250k in-the-wild images. The dataset is an ongoing effort to facilitate accurate measurement of individual food and nutrient intake in low and middle income countries with passive monitoring camera technologies. The current dataset involves 20 households (74 subjects) from both the rural and urban regions of Ghana, and two different types of wearable cameras were used in the studies. Once initiated, wearable cameras continuously capture subjects' activities, which yield massive amounts of data to be cleaned and annotated before analysis is conducted. To ease the data post-processing and annotation tasks, we propose a novel self-supervised learning framework to cluster the large volume of egocentric images into separate events. Each event consists of a sequence of temporally continuous and contextually similar images. By clustering images into separate events, annotators and dietitians can examine and analyze the data more efficiently and facilitate the subsequent dietary assessment processes. Validated on a held-out test set with ground truth labels, the proposed framework outperforms baselines in terms of clustering quality and classification accuracy., Comment: accepted to BHI 2022

Despite the pivotal role played by elevated circulating triglyceride levels in the pathophysiology of cardio-metabolic diseases many of the indices used to quantify metabolic health focus on deviations in glucose and insulin alone. We present the Mixed Meal Model, a computational model describing the systemic interplay between triglycerides, free fatty acids, glucose, and insulin. We show that the Mixed Meal Model can capture deviations in the post-meal excursions of plasma glucose, insulin, and triglyceride that are indicative of features of metabolic resilience; quantifying insulin resistance and liver fat; validated by comparison to gold-standard measures. We also demonstrate that the Mixed Meal Model is generalizable, applying it to meals with diverse macro-nutrient compositions. In this way, by coupling triglycerides to the glucose-insulin system the Mixed Meal Model provides a more holistic assessment of metabolic resilience from meal response data, quantifying pre-clinical metabolic deteriorations that drive disease development in overweight and obesity.

OBJECTIVEWe investigated the processes underlying glycemic deterioration in type 2 diabetes (T2D).RESEARCH DESIGN AND METHODSA total of 732 recently diagnosed patients with T2D from the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) study were extensively phenotyped over 3 years, including measures of insulin sensitivity (OGIS), beta-cell glucose sensitivity (GS), and insulin clearance (CLIm) from mixed meal tests, liver enzymes, lipid profiles, and baseline regional fat from MRI. The associations between the longitudinal metabolic patterns and HbA(1c) deterioration, adjusted for changes in BMI and in diabetes medications, were assessed via stepwise multivariable linear and logistic regression.RESULTSFaster HbA(1c) progression was independently associated with faster deterioration of OGIS and GS and increasing CLIm; visceral or liver fat, HDL-cholesterol, and triglycerides had further independent, though weaker, roles (R-2 = 0.38). A subgroup of patients with a markedly higher progression rate (fast progressors) was clearly distinguishable considering these variables only (discrimination capacity from area under the receiver operating characteristic = 0.94). The proportion of fast progressors was reduced from 56% to 8-10% in subgroups in which only one trait among OGIS, GS, and CLIm was relatively stable (odds ratios 0.07-0.09). T2D polygenic risk score and baseline pancreatic fat, glucagon-like peptide 1, glucagon, diet, and physical activity did not show an independent role.CONCLUSIONSDeteriorating insulin sensitivity and beta-cell function, increasing insulin clearance, high visceral or liver fat, and worsening of the lipid profile are the crucial factors mediating glycemic deterioration of patients with T2D in the initial phase of the disease. Stabilization of a single trait among insulin sensitivity, beta-cell function, and insulin clearance may be relevant to prevent

Camera-based passive dietary intake monitoring is able to continuously capture the eating episodes of a subject, recording rich visual information, such as the type and volume of food being consumed, as well as the eating behaviours of the subject. However, there currently is no method that is able to incorporate these visual clues and provide a comprehensive context of dietary intake from passive recording (e.g., is the subject sharing food with others, what food the subject is eating, and how much food is left in the bowl). On the other hand, privacy is a major concern while egocentric wearable cameras are used for capturing. In this paper, we propose a privacy-preserved secure solution (i.e., egocentric image captioning) for dietary assessment with passive monitoring, which unifies food recognition, volume estimation, and scene understanding. By converting images into rich text descriptions, nutritionists can assess individual dietary intake based on the captions instead of the original images, reducing the risk of privacy leakage from images. To this end, an egocentric dietary image captioning dataset has been built, which consists of in-the-wild images captured by head-worn and chest-worn cameras in field studies in Ghana. A novel transformer-based architecture is designed to caption egocentric dietary images. Comprehensive experiments have been conducted to evaluate the effectiveness and to justify the design of the proposed architecture for egocentric dietary image captioning. To the best of our knowledge, this is the first work that applies image captioning for dietary intake assessment in real life settings.

Malnutrition is a major public health concern in low-and-middle-income countries (LMICs). Understanding food and nutrient intake across communities, households and individuals is critical to the development of health policies and interventions. To ease the procedure in conducting large-scale dietary assessments, we propose to implement an intelligent passive food intake assessment system via egocentric cameras particular for households in Ghana and Uganda. Algorithms are first designed to remove redundant images for minimising the storage memory. At run time, deep learning-based semantic segmentation is applied to recognise multi-food types and newly-designed handcrafted features are extracted for further consumed food weight monitoring. Comprehensive experiments are conducted to validate our methods on an in-the-wild dataset captured under the settings which simulate the unique LMIC conditions with participants of Ghanaian and Kenyan origin eating common Ghanaian/Kenyan dishes. To demonstrate the efficacy, experienced dietitians are involved in this research to perform the visual portion size estimation, and their predictions are compared to our proposed method. The promising results have shown that our method is able to reliably monitor food intake and give feedback on users' eating behaviour which provides guidance for dietitians in regular dietary assessment., Comment: 11 pages, 14 figures, submitted for publication

BACKGROUND: Dietary advice remains the cornerstone of prevention and management of type 2 diabetes (T2D). However, understanding the efficacy of dietary interventions is confounded by the challenges inherent in assessing free living diet. Here we profiled dietary metabolites to investigate glycaemic deterioration and cardiometabolic risk in people at risk of or living with T2D.METHODS: We analysed data from plasma collected at baseline and 18-month follow-up in individuals from the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohort 1 n = 403 individuals with normal or impaired glucose regulation (prediabetic) and cohort 2 n = 458 individuals with new onset of T2D. A dietary metabolite profile model (Tpred) was constructed using multivariable regression of 113 plasma metabolites obtained from targeted metabolomics assays. The continuous Tpred score was used to explore the relationships between diet, glycaemic deterioration and cardio-metabolic risk via multiple linear regression models.FINDINGS: A higher Tpred score was associated with healthier diets high in wholegrain (β=3.36 g, 95% CI 0.31, 6.40 and β=2.82 g, 95% CI 0.06, 5.57) and lower energy intake (β=-75.53 kcal, 95% CI -144.71, -2.35 and β=-122.51 kcal, 95% CI -186.56, -38.46), and saturated fat (β=-0.92 g, 95% CI -1.56, -0.28 and β=-0.98 g, 95% CI -1.53, -0.42 g), respectively for cohort 1 and 2. In both cohorts a higher Tpred score was also associated with lower total body adiposity and favourable lipid profiles HDL-cholesterol (β=0.07 mmol/L, 95% CI 0.03, 0.1), (β=0.08 mmol/L, 95% CI 0.04, 0.1), and triglycerides (β=-0.1 mmol/L, 95% CI -0.2, -0.03), (β=-0.2 mmol/L, 95% CI -0.3, -0.09), respectively for cohort 1 and 2. In cohort 2, the Tpred score was negatively associated with liver fat (β=-0.74%, 95% CI -0.67, -0.81), and lower fasting concentrations of HbA1c (β=-0.9 mmol/mol, 95% CI -1.5, -0.1), glucose (β=-0.2 mmol/L, 95% CI -0.4, -0.05) an

AIMS/HYPOTHESIS: It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435).METHODS: We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively.RESULTS: The TC and TC-PA models showed better fit than null models (TC: χ2 = 242, p = 0.004 and χ2 = 63, p = 0.001 in cohort 1 and 2, respectively; TC-PA: χ2 = 180, p = 0.041 and χ2 = 60, p = 0.008 in cohort 1 and 2, respectively). The association of physical activity with glycaemic control was primarily mediated by variables in the liver fat cycle.CONCLUSIONS/INTERPRETATION: These analyses partially

Background: Dietary advice remains the cornerstone of prevention and management of type 2 diabetes (T2D). However, understanding the efficacy of dietary interventions is confounded by the challenges inherent in assessing free living diet. Here we profiled dietary metabolites to investigate glycaemic deterioration and cardiometabolic risk in people at risk of or living with T2D. Methods: We analysed data from plasma collected at baseline and 18-month follow-up in individuals from the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohort 1 n = 403 individuals with normal or impaired glucose regulation (prediabetic) and cohort 2 n = 458 individuals with new onset of T2D. A dietary metabolite profile model (T-pred) was constructed using multivariable regression of 113 plasma metabolites obtained from targeted metabolomics assays. The continuous T-pred score was used to explore the relationships between diet, glycaemic deterioration and cardio-metabolic risk via multiple linear regression models. Findings: A higher T-pred score was associated with healthier diets high in wholegrain (beta=3.36 g, 95% CI 0.31, 6.40 and beta=2.82 g, 95% CI 0.06, 5.57) and lower energy intake (beta=-75.53 kcal, 95% CI -144.71, -2.35 and beta=-122.51 kcal, 95% CI -186.56, -38.46), and saturated fat (beta=-0.92 g, 95% CI -1.56, -0.28 and beta=-0.98 g, 95% CI -1.53, -0.42 g), respectively for cohort 1 and 2. In both cohorts a higher T-pred score was also associated with lower total body adiposity and favourable lipid profiles HDL-cholesterol (beta=0.07 mmol/L, 95% CI 0.03, 0.1), (beta=0.08 mmol/L, 95% CI 0.04, 0.1), and triglycerides (beta=-0.1 mmol/L, 95% CI -0.2, -0.03), (beta=-0.2 mmol/L, 95% CI -0.3, -0.09), respectively for cohort 1 and 2. In cohort 2, the T-pred score was negatively associated with liver fat (beta=-0.74%, 95% CI -0.67, -0.81), and lower fasting concentrations of HbA1c (beta=-0.9 mmol/mol, 95% CI -1.5, -0.1), glucose (beta=-0.2 m, QC 20201123

Aims/hypothesis: It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435). Methods: We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively. Results: The TC and TC-PA models showed better fit than null models (TC: χ2 = 242, p = 0.004 and χ2 = 63, p = 0.001 in cohort 1 and 2, respectively; TC-PA: χ2 = 180, p = 0.041 and χ2 = 60, p = 0.008 in cohort 1 and 2, respectively). The association of physical activity with glycaemic control was primarily mediated by variables in the liver fat cycle. Conclusions/interpretation: These analyses partially suppo

BackgroundNon-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning. Methods and findingsWe utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (<5% or ≥5%) available for 1,514 participants. We applied LASSO (least absolute shrinkage and selection operator) to select features from the different layers of omics data and random forest analysis to develop the models. The prediction models included clinical and omics variables separately or in combination. A model including all omics and clinical variables yielded a cross-validated receiver operating characteristic area under the curve (ROCAUC) of 0.84 (95% CI 0.82, 0.86; p < 0.001), which compared with a ROCAUC of 0.82 (95% CI 0.81, 0.83; p < 0.001) for a model including 9 clinically accessible variables. The IMI DIRECT prediction models outperformed existing noninvasive NAFLD prediction tools. One limitation is that these analyses were performed in adults of European ancestry residing in northern Europe, and it is unknown how well these findings will translate to people of other ancestries and exposed to environmental risk factors that differ from those of the present cohort. Anot

Scope A grape-seed proanthocyanidin extract (GSPE) interacts at the intestinal level, enhancing glucagon-like peptide-1 (GLP-1) and peptide YY (PYY) release, which modulate appetite and glucose homeostasis. Thus, enhancing L-cell numbers could be a strategy to promote hormone production, providing a potential strategy for obesity and type-2 diabetes mellitus (T2DM) treatment. Methods and results Mice ileum organoids are used to evaluate the long-term effects of GSPE and two of its main components, epicatechin (EC) and gallic acid (GA), on intestinal differentiation. Hormone levels are determined using RIA and ELISA kits, and gene expression of transcription factors involved in intestinal cell differentiation, as well as markers of different cell types, are assessed by real-time qPCR. GSPE upregulates enterohormone gene expression and content, as well as the pan-endocrine marker chromogranin A. GSPE also modulates the temporal gene expression profile of early and late transcription factors involved in L-cell differentiation. Furthermore, GSPE upregulates goblet cell (Muc2) and enterocyte (sucraseisomaltase) markers, while downregulating stem cell markers (Lgr5+). Although EC and GA modified enterohormone release, they do not reproduce GSPE effects on transcription factor's profile. Conclusions This study shows the potential role of GSPE in promoting enteroendocrine differentiation, effect that is not mediated by EC or GA.

BACKGROUND: Childhood overweight and obesity is a serious public health issue with an increase being observed in preschool-aged children. Treating childhood obesity is difficult and few countries use standardized treatments. Therefore, there is a need to find effective approaches that are feasible for both health care providers and families. Thus, the overall aim of this study is to assess the acceptance and effectiveness of a parent support program (the More and Less, ML) for the management of overweight and obesity followed by a mobile health (mHealth) program (the MINISTOP application) in a socially diverse population of families. METHODS/DESIGN: A two-arm, parallel design randomized controlled trial in 300 2-to 6-year-old children with overweight and obesity from Romania, Spain and Sweden (n = 100 from each). Following baseline assessments children are randomized into the intervention or control group in a 1:1 ratio. The intervention, the ML program, consists of 10-weekly group sessions which focus on evidence-based parenting practices, followed by the previously validated MINISTOP application for 6-months to support healthy eating and physical activity behaviors. The primary outcome is change in body mass index (BMI) z-score after 9-months and secondary outcomes include: waist circumference, eating behavior (Child Eating Behavior Questionnaire), parenting behavior (Comprehensive Feeding Practices Questionnaire), physical activity (ActiGraph wGT3x-BT), dietary patterns (based on metabolic markers from urine and 24 h dietary recalls), epigenetic and gut hormones (fasting blood samples), and the overall acceptance of the overweight and obesity management in young children (semi-structured interviews). Outcomes are measured at baseline and after: 10-weeks (only BMI z-score, waist circumference), 9-months (all outcomes), 15- and 21-months (all outcomes except physical activity, dietary patterns, epigenetics and gut hormones) post-baseline. DISCUSSION: This study wil, Anna Ek and Christine Delisle Nyström contributed equally to this work.

Aims/hypothesis: Here, we describe the characteristics of the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) epidemiological cohorts at baseline and follow-up examinations (18, 36 and 48 months of follow-up). Methods: From a sampling frame of 24,682 adults of European ancestry enrolled in population-based cohorts across Europe, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm (based on age, BMI, waist circumference, use of antihypertensive medication, smoking status and parental history of type 2 diabetes) and enrolled into a prospective cohort study (n = 2127) (cohort 1, prediabetes risk). We also recruited people from clinical registries with type 2 diabetes diagnosed 6-24 months previously (n = 789) into a second cohort study (cohort 2, diabetes). Follow-up examinations took place at similar to 18 months (both cohorts) and at similar to 48 months (cohort 1) or similar to 36 months (cohort 2) after baseline examinations. The cohorts were studied in parallel using matched protocols across seven clinical centres in northern Europe. Results: Using ADA 2011 glycaemic categories, 33% (n = 693) of cohort 1 (prediabetes risk) had normal glucose regulation and 67% (n = 1419) had impaired glucose regulation. Seventy-six per cent of participants in cohort 1 was male. Cohort 1 participants had the following characteristics (mean +/- SD) at baseline: age 62 (6.2) years; BMI 27.9 (4.0) kg/m(2); fasting glucose 5.7 (0.6) mmol/l; 2 h glucose 5.9 (1.6) mmol/l. At the final follow-up examination the participants' clinical characteristics were as follows: fasting glucose 6.0 (0.6) mmol/l; 2 h OGTT glucose 6.5 (2.0) mmol/l. In cohort 2 (diabetes), 66% (n = 517) were treated by lifestyle modification and 34% (n = 272) were treated with metformin plus lifestyle modification at enrolment. Fifty-eight per cent of participants in cohort 2 was male. Cohort 2 participants had the following

OBJECTIVE: Roux-en-Y gastric bypass (RYGB) augments postprandial secretion of glucagon-like peptide 1 (GLP-1), oxyntomodulin (OXM), and peptide YY (PYY). Subcutaneous infusion of these hormones ("GOP"), mimicking postprandial levels, reduces energy intake. Our objective was to study the effects of GOP on glycemia and body weight when given for 4 weeks to patients with diabetes and obesity.RESEARCH DESIGN AND METHODS: In this single-blinded mechanistic study, obese patients with prediabetes/diabetes were randomized to GOP (n = 15) or saline (n = 11) infusion for 4 weeks. We also studied 21 patients who had undergone RYGB and 22 patients who followed a very low-calorie diet (VLCD) as unblinded comparators. Outcomes measured were 1) body weight, 2) fructosamine levels, 3) glucose and insulin during a mixed meal test (MMT), 4) energy expenditure (EE), 5) energy intake (EI), and 6) mean glucose and measures of glucose variability during continuous glucose monitoring.RESULTS: GOP infusion was well tolerated over the 4-week period. There was a greater weight loss (P = 0.025) with GOP (mean change -4.4 [95% CI -5.3, -3.5] kg) versus saline (-2.5 [-4.1, -0.9] kg). GOP led to a greater improvement (P = 0.0026) in fructosamine (-44.1 [-62.7, -25.5] µmol/L) versus saline (-11.7 [-18.9, -4.5] µmol/L). Despite a smaller weight loss compared with RYGB and VLCD, GOP led to superior glucose tolerance after a mixed-meal stimulus and reduced glycemic variability compared with RYGB and VLCD.CONCLUSIONS: GOP infusion improves glycemia and reduces body weight. It achieves superior glucose tolerance and reduced glucose variability compared with RYGB and VLCD. GOP is a viable alternative for the treatment of diabetes with favorable effects on body weight.

AIMS/HYPOTHESIS: Here, we describe the characteristics of the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) epidemiological cohorts at baseline and follow-up examinations (18, 36 and 48 months of follow-up).METHODS: From a sampling frame of 24,682 adults of European ancestry enrolled in population-based cohorts across Europe, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm (based on age, BMI, waist circumference, use of antihypertensive medication, smoking status and parental history of type 2 diabetes) and enrolled into a prospective cohort study (n = 2127) (cohort 1, prediabetes risk). We also recruited people from clinical registries with type 2 diabetes diagnosed 6-24 months previously (n = 789) into a second cohort study (cohort 2, diabetes). Follow-up examinations took place at ~18 months (both cohorts) and at ~48 months (cohort 1) or ~36 months (cohort 2) after baseline examinations. The cohorts were studied in parallel using matched protocols across seven clinical centres in northern Europe.RESULTS: Using ADA 2011 glycaemic categories, 33% (n = 693) of cohort 1 (prediabetes risk) had normal glucose regulation and 67% (n = 1419) had impaired glucose regulation. Seventy-six per cent of participants in cohort 1 was male. Cohort 1 participants had the following characteristics (mean ± SD) at baseline: age 62 (6.2) years; BMI 27.9 (4.0) kg/m2; fasting glucose 5.7 (0.6) mmol/l; 2 h glucose 5.9 (1.6) mmol/l. At the final follow-up examination the participants' clinical characteristics were as follows: fasting glucose 6.0 (0.6) mmol/l; 2 h OGTT glucose 6.5 (2.0) mmol/l. In cohort 2 (diabetes), 66% (n = 517) were treated by lifestyle modification and 34% (n = 272) were treated with metformin plus lifestyle modification at enrolment. Fifty-eight per cent of participants in cohort 2 was male. Cohort 2 participants had the following characteristics at

Objective Dietary supplementation with fermentable carbohydrate protects against body weight gain. Fermentation by the resident gut microbiota produces short-chain fatty acids, which act at free fatty acid receptor 2 (FFAR2). Our aim was to test the hypothesis that FFAR2 is important in regulating the beneficial effects of fermentable carbohydrate on body weight and to understand the role of gut hormones PYY and GLP-1. Methods Wild-type or Ffar2−/− mice were fed an inulin supplemented or control diet. Mice were metabolically characterized and gut hormone concentrations, enteroendocrine cell density measurements were carried out. Intestinal organoids and colonic cultures were utilized to substantiate the in vivo findings. Results We provide new mechanistic insight into how fermentable carbohydrate regulates metabolism. Using mice that lack FFAR2, we demonstrate that the fermentable carbohydrate inulin acts via this receptor to drive an 87% increase in the density of cells that produce the appetite-suppressing hormone peptide YY (PYY), reduce food intake, and prevent diet-induced obesity. Conclusion Our results demonstrate that FFAR2 is predominantly involved in regulating the effects of fermentable carbohydrate on metabolism and does so, in part, by enhancing PYY cell density and release. This highlights the potential for targeting enteroendocrine cell differentiation to treat obesity.

Leigh P Brody,1,* Meliz Sahuri-Arisoylu,1,* James R Parkinson,1 Harry G Parkes,2 Po Wah So,3 Nabil Hajji,4 E Louise Thomas,1 Gary S Frost,5 Andrew D Miller,6,* Jimmy D Bell1,* 1Department of Life Sciences, Faculty of Science and Technology, University of Westminster, 2CR-UK Clinical MR Research Group, Institute of Cancer Research, Sutton, Surrey, 3Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 4Department of Medicine, Division of Experimental Medicine, Centre for Pharmacology & Therapeutics, Toxicology Unit, Imperial College London, 5Faculty of Medicine, Nutrition and Dietetic Research Group, Division of Diabetes, Endocrinology and Metabolism, Department of Investigative Medicine, Imperial College London, Hammersmith Hospital, 6Institute of Pharmaceutical Science, King’s College London, London, UK *These authors contributed equally to this work Abstract: Metabolic reengineering using nanoparticle delivery represents an innovative therapeutic approach to normalizing the deregulation of cellular metabolism underlying many diseases, including cancer. Here, we demonstrated a unique and novel application to the treatment of malignancy using a short-chain fatty acid (SCFA)-encapsulated lipid-based delivery system – liposome-encapsulated acetate nanoparticles for cancer applications (LITA-CAN). We assessed chronic in vivo administration of our nanoparticle in three separate murine models of colorectal cancer. We demonstrated a substantial reduction in tumor growth in the xenograft model of colorectal cancer cell lines HT-29, HCT-116 p53+/+ and HCT-116 p53-/-. Nanoparticle-induced reductions in histone deacetylase gene expression indicated a potential mechanism for these anti-proliferative effects. Together, these results indicated that LITA-CAN could be used as an effective direct or adjunct therapy to treat malignant transformation in vivo. Keywords: lipid-based nanopa

BACKGROUND: Accurate monitoring of changes in dietary patterns in response to food policy implementation is challenging. Metabolic profiling allows simultaneous measurement of hundreds of metabolites in urine, the concentrations of which can be affected by food intake. We hypothesised that metabolic profiles of urine samples developed under controlled feeding conditions reflect dietary intake and can be used to model and classify dietary patterns of free-living populations.METHODS: In this randomised, controlled, crossover trial, we recruited healthy volunteers (aged 21-65 years, BMI 20-35 kg/m(2)) from a database of a clinical research unit in the UK. We developed four dietary interventions with a stepwise variance in concordance with the WHO healthy eating guidelines that aim to prevent non-communicable diseases (increase fruits, vegetables, whole grains, and dietary fibre; decrease fats, sugars, and salt). Participants attended four inpatient stays (72 h each, separated by at least 5 days), during which they were given one dietary intervention. The order of diets was randomly assigned across study visits. Randomisation was done by an independent investigator, with the use of opaque, sealed, sequentially numbered envelopes that each contained one of the four dietary interventions in a random order. Participants and investigators were not masked from the dietary intervention, but investigators analysing the data were masked from the randomisation order. During each inpatient period, urine was collected daily over three timed periods: morning (0900-1300 h), afternoon (1300-1800 h), and evening and overnight (1800-0900 h); 24 h urine samples were obtained by pooling these samples. Urine samples were assessed by proton nuclear magnetic resonance ((1)H-NMR) spectroscopy, and diet-discriminatory metabolites were identified. We developed urinary metabolite models for each diet and identified the associated metabolic profiles, and then validated the models using

Overweight and obesity lead to changes in adipose tissue such as inflammation and reduced insulin sensitivity. The aim of this study was to assess how altered energy balance by reduced food intake or enhanced physical activity affect these processes. We studied sedentary subjects with overweight/obesity in two intervention studies, each lasting 12 weeks affecting energy balance either by energy restriction (~20% reduced intake of energy from food) in one group, or by enhanced energy expenditure due to physical exercise (combined endurance- and strength-training) in the other group. We monitored mRNA expression by microarray and mRNA sequencing from adipose tissue biopsies. We also measured several plasma parameters as well as fat distribution with magnetic resonance imaging and spectroscopy. Comparison of microarray and mRNA sequencing showed strong correlations, which were also confirmed using RT-PCR. In the energy restricted subjects (body weight reduced by 5% during a 12 weeks intervention), there were clear signs of enhanced lipolysis as monitored by mRNA in adipose tissue as well as plasma concentration of free-fatty acids. This increase was strongly related to increased expression of markers for M1-like macrophages in adipose tissue. In the exercising subjects (glucose infusion rate increased by 29% during a 12-week intervention), there was a marked reduction in the expression of markers of M2-like macrophages and T cells, suggesting that physical exercise was especially important for reducing inflammation in adipose tissue with insignificant reduction in total body weight. Our data indicate that energy restriction and physical exercise affect energy-related pathways as well as inflammatory processes in different ways, probably related to macrophages in adipose tissue.

AIMS/HYPOTHESIS: The DIRECT (Diabetes Research on Patient Stratification) Study is part of a European Union Framework 7 Innovative Medicines Initiative project, a joint undertaking between four industry and 21 academic partners throughout Europe. The Consortium aims to discover and validate biomarkers that: (1) predict the rate of glycaemic deterioration before and after type 2 diabetes onset; (2) predict the response to diabetes therapies; and (3) help stratify type 2 diabetes into clearly definable disease subclasses that can be treated more effectively than without stratification. This paper describes two new prospective cohort studies conducted as part of DIRECT. METHODS: Prediabetic participants (target sample size 2,200-2,700) and patients with newly diagnosed type 2 diabetes (target sample size ~1,000) are undergoing detailed metabolic phenotyping at baseline and 18 months and 36 months later. Abdominal, pancreatic and liver fat is assessed using MRI. Insulin secretion and action are assessed using frequently sampled OGTTs in non-diabetic participants, and frequently sampled mixed-meal tolerance tests in patients with type 2 diabetes. Biosamples include venous blood, faeces, urine and nail clippings, which, among other biochemical analyses, will be characterised at genetic, transcriptomic, metabolomic, proteomic and metagenomic levels. Lifestyle is assessed using high-resolution triaxial accelerometry, 24 h diet record, and food habit questionnaires. CONCLUSIONS/INTERPRETATION: DIRECT will yield an unprecedented array of biomaterials and data. This resource, available through managed access to scientists within and outside the Consortium, will facilitate the development of new treatments and therapeutic strategies for the prevention and management of type 2 diabetes

Increased intake of dietary carbohydrate that is fermented in the colon by the microbiota has been reported to decrease body weight, although the mechanism remains unclear. Here we use in vivo11C-acetate and PET-CT scanning to show that colonic acetate crosses the blood–brain barrier and is taken up by the brain. Intraperitoneal acetate results in appetite suppression and hypothalamic neuronal activation patterning. We also show that acetate administration is associated with activation of acetyl-CoA carboxylase and changes in the expression profiles of regulatory neuropeptides that favour appetite suppression. Furthermore, we demonstrate through 13C high-resolution magic-angle-spinning that 13C acetate from fermentation of 13C-labelled carbohydrate in the colon increases hypothalamic 13C acetate above baseline levels. Hypothalamic 13C acetate regionally increases the 13C labelling of the glutamate–glutamine and GABA neuroglial cycles, with hypothalamic 13C lactate reaching higher levels than the ‘remaining brain’. These observations suggest that acetate has a direct role in central appetite regulation.

The DIRECT (Diabetes Research on Patient Stratification) Study is part of a European Union Framework 7 Innovative Medicines Initiative project, a joint undertaking between four industry and 21 academic partners throughout Europe. The Consortium aims to discover and validate biomarkers that: (1) predict the rate of glycaemic deterioration before and after type 2 diabetes onset; (2) predict the response to diabetes therapies; and (3) help stratify type 2 diabetes into clearly definable disease subclasses that can be treated more effectively than without stratification. This paper describes two new prospective cohort studies conducted as part of DIRECT.

This study aimed to determine in obese women if endocannabinoid receptor antagonism has effects on fatty acid and triglyceride metabolism and insulin sensitivity which are independent from the metabolic effects of weight loss. Fourteen obese (BMI=33.0 +/- 0.5 kg/m(2)) (mean SEM) Caucasian post-menopausal women, aged 57.8 +/- 4.7 years were studied. The women were randomised to 2 groups, one group received the endocannabinoid receptor antagonist rimonabant (20 mg/d) for 12 weeks. A control group achieved the same weight loss by a hypocaloric dietary intervention over 12 weeks. Palmitate production rate (Ra), a measure of lipolysis, and palmitate oxidation rate, and VLDL1 and VLDL2 triglyceride (TG) kinetics, were measured using isotopic tracers before and after the intervention. Weight loss was not different in the 2 groups; 2.6 +/- 0.5 kg with rimonabant and 3.1 +/- 1.0 kg in the control group. Palmitate Ra increased with rimonabant with no change in the control group (p=0.03 between groups). Palmitate oxidation rate increased with rimonabant but decreased in the control group (p=0.005 between groups). VLDL1 TG secretion rate decreased in the control group and increased in the rimonabant group (p = 0.008 between groups). There was no significant effect on insulin sensitivity. This study suggests that endocannabinoid receptor antagonism for 12 weeks in obese women increased lipolysis and fatty acid oxidation. The increase in VLDL1 TG secretion rate may be due to the increase in lipolysis which exceeded the increase in fatty acid oxidation.

The 2006 lecture Brodsky Series held is November 3-5 was honored to host Gary Frost, one of the leaders in field of library conservation. During his visit Gary presented the annual Brodsky Lecture on the Aesthetics of Book Conservation in which he explored the subtle art and the quiet passions of book conservators as these work to craft appropriate and sympathetic conservation treatments. The lecture was followed by a two-day workshop co-hosted by Gary and Joyce Miller who together operate Iowa Book Works, a firm specializing in kits of historic structures and teaching workshops throughout the country. Gary Frost is an educator in book art and book conservation. He has taught at the School of the Art Institute of Chicago, Columbia University in New York and the University of Texas at Austin. He is currently the Conservator for the Libraries at the University of Iowa, and has been awarded the 2006 Banks/Harris Preservation Award by the ALCTS Division of the American Library Association. For more see his website Future of the Book.com, which also features many of his writings on the history of the book, reading, library preservation, and host of other issues. Together with his partner Joyce Miller, Gary also operates Iowa Book Works a firm specializing in kits of historic structures and teaching workshops throughout the country. See more on the Brodsky Series Page at: https://library.syr.edu/scrc/programs/brodsky.php

Joan Flasch Artists' Book Collection

Summary Background & aims The risk of malnutrition in people with COVID-19 is high; prevalence is reported as 37% in general medical inpatients, 53% in elderly inpatients and 67% in ICU. Thus, nutrition is a crucial element of assessment and treatment. This rapid review aimed to evaluate what evidence is available to inform evidence-based decision making on the nutritional care of patients hospitalised with COVID-19 infection. Methods Cochrane Rapid Reviews guidance was followed; the protocol was registered (CRD42020208448). Studies were selected that included patients with COVID-19, pneumonia, respiratory distress syndrome and acute respiratory failure, in hospital or the community, and which examined nutritional support. All types of studies were eligible for inclusion except non-systematic reviews, commentaries, editorials and single case studies. Six electronic databases were searched: MEDLINE, Embase, Cochrane Central Register of Controlled Trials, PubMed, CINAHL and MedRxiv. Results Twenty-six articles on COVID-19 were retrieved, including 11 observational studies, five guidelines and 10 opinion articles. Seven further articles on pneumonia included three RCTs, one unblinded trial, three observational studies, and one systematic review on rehabilitation post-ICU admission for respiratory illness. The evidence from these articles is presented narratively and used to guide the nutritional and dietetic care process. Conclusions Older patients with COVID-19 infection are at risk of malnutrition and addressing this may be important in recovery. The use of nutritional management strategies applicable to other acute conditions are recommended. However, traditional screening and implementation techniques need to be modified to ensure infection control measures can be maintained. The most effective nutritional interventions require further research and more detailed guidance on nutritional management post-discharge to support long-term recovery is needed.