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Aims/hypothesis Not all people with type 2 diabetes who undergo bariatric surgery achieve diabetes remission. Thus it is critical to develop methods for predicting outcomes that are applicable for clinical practice. The DiaRem score is relevant for predicting diabetes remission post-Roux-en-Y gastric bypass (RYGB), but it is not accurate for all individuals across the entire spectrum of scores. We aimed to develop an improved scoring system for predicting diabetes remission following RYGB (the Advanced-DiaRem [Ad-DiaRem]). Methods We used a retrospective French cohort ( n  = 1866) that included 352 individuals with type 2 diabetes followed for 1 year post-RYGB. We developed the Ad-DiaRem in a test cohort ( n  = 213) and examined its accuracy in independent cohorts from France ( n  = 134) and Israel ( n  = 99). Results Adding two clinical variables (diabetes duration and number of glucose-lowering agents) to the original DiaRem and modifying the penalties for each category led to improved predictive performance for Ad-DiaRem. Ad-DiaRem displayed improved area under the receiver operating characteristic curve and predictive accuracy compared with DiaRem (0.911 vs 0.856 and 0.841 vs 0.789, respectively; p =  0.03); thus correcting classification for 8% of those initially misclassified with DiaRem. With Ad-DiaRem, there were also fewer misclassifications of individuals with mid-range scores. This improved predictive performance was confirmed in independent cohorts. Conclusions/interpretation We propose the Ad-DiaRem, which includes two additional clinical variables, as an optimised tool with improved accuracy to predict diabetes remission 1 year post-RYGB. This tool might be helpful for personalised management of individuals with diabetes when considering bariatric surgery in routine care, ultimately contributing to precision medicine.

Sub-Saharan Africa currently experiences an unprecedented wave of urbanization, which has important consequences for health and disease patterns. This study aimed to investigate and integrate the immune and metabolic consequences of rural or urban lifestyles and the role of nutritional changes associated with urban living. In a cohort of 323 healthy Tanzanians, urban as compared to rural living was associated with a pro-inflammatory immune phenotype, both at the transcript and protein levels. We identified different food-derived and endogenous circulating metabolites accounting for these differences. Serum from urban dwellers induced reprogramming of innate immune cells with higher tumor necrosis factor production upon microbial re-stimulation in an in vitro model of trained immunity. These data demonstrate important shifts toward an inflammatory phenotype associated with an urban lifestyle and provide new insights into the underlying dietary and metabolic factors, which may affect disease epidemiology in sub-Sahara African countries. Rapid urbanization can be associated with adverse health implications. de Mast and colleagues compare urban and rural Tanzanian populations using multi-omics and observe that urbanization is associated with an elevated but reversible inflammatory state.

Blastocyst-derived stem cell lines were shown to self-organize into embryo-like structures in 3D cell culture environments. Here, we provide evidence that embryo-like structures can be generated solely based on transcription factor-mediated reprogramming of embryonic stem cells in a simple 3D co-culture system. Embryonic stem cells in these cultures self-organize into elongated, compartmentalized embryo-like structures reflecting aspects of the inner regions of the early post-implantation embryo. Single-cell RNA-sequencing reveals transcriptional profiles resembling epiblast, primitive-/visceral endoderm, and extraembryonic ectoderm of early murine embryos around E4.5–E5.5. In this stem cell-based embryo model, progression from rosette formation to lumenogenesis accompanied by progression from naïve- to primed pluripotency was observed within Epi-like cells. Additionally, lineage specification of primordial germ cells and distal/anterior visceral endoderm-like cells was observed in epiblast- or visceral endoderm-like compartments, respectively. The system presented in this study allows for fast and reproducible generation of embryo-like structures, providing an additional tool to study aspects of early embryogenesis. Synthetic embryo models have arisen as an approach to probe early development in vitro, facilitating the study of difficult to access stages. Here the authors present a simple system for generating embryo-like structures that resemble peri-implantation mouse embryos.

Heterogeneity is universally observed in all natural systems and across multiple scales. Understanding population heterogeneity is an intriguing and attractive topic of research in different disciplines, including microbiology and immunology. Microbes and mammalian immune cells present obviously rather different system-specific biological features. Nevertheless, as typically occurs in science, similar methods can be used to study both types of cells. This is particularly true for mathematical modeling, in which key features of a system are translated into algorithms to challenge our mechanistic understanding of the underlying biology. In this review, we first present a broad overview of the experimental developments that allowed observing heterogeneity at the single cell level. We then highlight how this “data revolution” requires the parallel advancement of algorithms and computing infrastructure for data processing and analysis, and finally present representative examples of computational models of population heterogeneity, from microbial communities to immune response in cells.

Non-communicable diseases (NCDs) are rising rapidly in urbanizing populations in sub-Saharan Africa. Assessment of inflammatory and metabolic characteristics of a urbanizing African population and the comparison with populations outside Africa could provide insight in the pathophysiology of the rapidly increasing epidemic of NCDs, including the role of environmental and dietary changes. Using a proteomic plasma profiling approach comprising 92 inflammation-related molecules, we examined differences in the inflammatory proteome in healthy Tanzanian and healthy Dutch adults. We show that healthy Tanzanians display a pro-inflammatory phenotype compared to Dutch subjects, with enhanced activity of the Wnt/β-catenin signalling pathway and higher concentrations of different metabolic regulators such as 4E-BP1 and fibroblast growth factor 21. Among the Tanzanian volunteers, food-derived metabolites were identified as an important driver of variation in inflammation-related molecules, emphasizing the potential importance of lifestyle changes. These findings endorse the importance of the current dietary transition and the inclusion of underrepresented populations in systems immunology studies.

High-dimensional cytometry (HDC) is a powerful technology for studying single-cell phenotypes in complex biological systems. Although technological developments and affordability have made HDC broadly available in recent years, technological advances were not coupled with an adequate development of analytical methods that can take full advantage of the complex data generated. While several analytical platforms and bioinformatics tools have become available for the analysis of HDC data, these are either web-hosted with limited scalability or designed for expert computational biologists, making their use unapproachable for wet lab scientists. Additionally, end-to-end HDC data analysis is further hampered due to missing unified analytical ecosystems, requiring researchers to navigate multiple platforms and software packages to complete the analysis. To bridge this data analysis gap in HDC we develop cyCONDOR , an easy-to-use computational framework covering not only all essential steps of cytometry data analysis but also including an array of downstream functions and tools to expand the biological interpretation of the data. The comprehensive suite of features of cyCONDOR , including guided pre-processing, clustering, dimensionality reduction, and machine learning algorithms, facilitates the seamless integration of cyCONDOR into clinically relevant settings, where scalability and disease classification are paramount for the widespread adoption of HDC in clinical practice. Additionally, the advanced analytical features of cyCONDOR , such as pseudotime analysis and batch integration, provide researchers with the tools to extract deeper insights from their data. We use cyCONDOR on a variety of data from different tissues and technologies demonstrating its versatility to assist the analysis of high-dimensional data from preprocessing to biological interpretation. High-dimensional cytometry is a powerful technology for studying single-cell phenotypes in complex biological systems. Here, the authors develop cyCONDOR , a computational framework for high-dimensional cytometry data analysis, covering a comprehensive suite of features in an easy-to-use format.

Visceral adipose tissue foam cells are increased in human obesity, and were implicated in adipose dysfunction and increased cardio-metabolic risk. In the circulation, non-classical monocytes (NCM) are elevated in obesity and associate with atherosclerosis and type 2 diabetes. We hypothesized that circulating NCM correlate and/or are functionally linked to visceral adipose tissue foam cells in obesity, potentially providing an approach to estimate visceral adipose tissue status in the non-surgical obese patient. We preformed ex-vivo functional studies utilizing sorted monocyte subclasses from healthy donors. Moreover, we assessed circulating blood monocyte subclasses and visceral fat adipose tissue macrophage (ATM) lipid content by flow-cytometry in paired blood and omental-fat samples collected from patients (n = 65) undergoing elective abdominal surgery. Ex-vivo, NCM and NCM-derived macrophages exhibited lower lipid accumulation capacity compared to classical or intermediate monocytes/-derived macrophages. Moreover, of the three subclasses, NCM exhibited the lowest migration towards adipose tissue conditioned-media. In a cohort of n = 65, increased %NCM associated with higher BMI (r = 0.250,p<0.05) and ATM lipid content (r = 0.303,p<0.05). Among patients with BMI≥25Kg/m2, linear regression models adjusted for age, sex or BMI revealed that NCM independently associate with ATM lipid content, particularly in men. Collectively, although circulating blood NCM are unlikely direct functional precursor cells for adipose tissue foam cells, their increased percentage in the circulation may clinically reflect higher lipid content in visceral ATMs.

The identification of human obesity sub-types may improve the clinical management of patients with obesity and uncover previously unrecognized obesity mechanisms. Here, we hypothesized that adipose tissue (AT) mast cells (MC) estimation could be a mark for human obesity sub-phenotyping beyond current clinical-based stratifications, both cross-sectionally and prospectively. We estimated MC accumulation using immunohistochemistry and gene expression in abdominal visceral AT (VAT) and subcutaneous (SAT) in a human cohort of 65 persons with obesity who underwent elective abdominal (mainly bariatric) surgery, and we validated key results in two clinically similar, independent cohorts (n = 33, n = 56). AT-MC were readily detectable by immunostaining for either c-kit or tryptase and by assessing the gene expression of KIT (KIT Proto-Oncogene, Receptor Tyrosine Kinase), TPSB2 (tryptase beta 2), and CMA1 (chymase 1). Participants were characterized as VAT-MClow if the expression of both CMA1 and TPSB2 was below the median. Higher expressers of MC genes (MChigh) were metabolically healthier (lower fasting glucose and glycated hemoglobin, with higher pancreatic beta cell reserve (HOMA-β), and lower triglycerides and alkaline-phosphatase) than people with low expression (MClow). Prospectively, higher MC accumulation in VAT or SAT obtained during surgery predicted greater postoperative weight-loss response to bariatric surgery. Jointly, high AT-MC accumulation may be used to clinically define obesity sub-phenotypes, which are associated with a “healthier” cardiometabolic risk profile and a better weight-loss response to bariatric surgery.

(1) Background: Sub-Saharan Africa is experiencing the fastest urbanization worldwide. People in rural areas still have a traditional and rural lifestyle, whereas the Westernization of diet and lifestyle is already evident in urban areas. This study describes dietary habits of families in Burkina Faso living at different levels of urbanization. (2) Methods: Data on lifestyle, socio-economic conditions, health status and anthropometry were collected from 30 families living in rural villages, a small town and the capital city. A food frequency questionnaire and a 24 h recall diary were used to estimate dietary habits and macronutrients intake. (3) Results: The urban cohort showed a more diversified diet, with a higher intake of animal protein and, especially in children, a higher consumption of simple sugars. Fiber intake was significantly higher in the rural and semi-urbanized cohorts. As expected, overweight and obesity gradually increased with the level of urbanization. In semi-urbanized and urban families, we observed coexistence of under- and over-nutrition, whereas in rural families, a portion of children were wasted and stunted, and adults were underweight. (4) Conclusions: These three cohorts represent a model of the effect on diet of rural-to-urban migration. Rural diet and traditional habits are replaced by a Western-oriented diet when families move to urbanized areas. This dietary transition and increased socio-economic status in newly developing urban areas have a major impact on disease epidemiology, resembling the past evolution in Western countries.

African heritage diets are increasingly being replaced by Western-style dietary patterns because of urbanization, economic development, increased access to processed foods, globalization and changing social norms. The health consequences of this nutrition transition are not well understood. We conducted a randomized controlled trial in the Kilimanjaro region in Northern Tanzania to investigate the immune and metabolic effects of switching between Kilimanjaro heritage-style and Western-style diets for 2 weeks and consuming a traditional fermented banana beverage (‘Mbege’) for 1 week. Seventy-seven young and healthy volunteers assigned male at birth, some living in urban areas and some living in rural areas, were recruited in the trial. Primary outcomes were changes in the immune and metabolic profile before and after the intervention and at the 4-week follow-up. The switch from heritage-style to Western-style diet affected different metabolic pathways associated with noncommunicable diseases and promoted a pro-inflammatory state with impaired whole-blood cytokine responses to microbial stimulation. In contrast, the switch from Western-style to heritage-style diet or consuming the fermented beverage had a largely anti-inflammatory effect. Some of the observed changes in the immune and metabolic profiles persisted at the follow-up, suggesting a sustained impact from the short-term intervention. These findings show the metabolic and immune effects of dietary transitions and the consumption of fermented beverages, underscoring the importance of preserving indigenous dietary practices to mitigate noncommunicable disease risk factors in sub-Saharan Africa. ISRCTN trial registration: ISRCTN15619939 . A randomized crossover trial showed that transition to a Western diet resulted in pro-inflammatory changes, whereas transition to an African heritage diet rich in fruits and vegetables, legumes and fermented products led to opposite effects.