Generation of functionally active resident macrophages from adipose tissue by 3D cultures.

Introduction: Within adipose tissue (AT), different macrophage subsets have been described, which played pivotal and specific roles in upholding tissue homeostasis under both physiological and pathological conditions. Nonetheless, studying resident macrophages in-vitro poses challenges, as the isolation process and the culture for extended periods can alter their inherent properties. Methods: Stroma-vascular cells isolated from murine subcutaneous AT were seeded on ultra-low adherent plates in the presence of macrophage colony-stimulating factor. After 4 days of culture, the cells spontaneously aggregate to form spheroids. A week later, macrophages begin to spread out of the spheroid and adhere to the culture plate. Results: This innovative three-dimensional (3D) culture method enables the generation of functional mature macrophages that present distinct genic and phenotypic characteristics compared to bone marrow-derived macrophages. They also show specific metabolic activity and polarization in response to stimulation, but similar phagocytic capacity. Additionally, based on single-cell analysis, AT-macrophages generated in 3D culture mirror the phenotypic and functional traits of in-vivo AT resident macrophages. Discussion: Our study describes a 3D in-vitro system for generating and culturing functional AT-resident macrophages, without the need for cell sorting. This system thus stands as a valuable resource for exploring the differentiation and function of AT-macrophages in vitro in diverse physiological and pathological contexts.

Body composition and aging: cross-sectional results from the INSPIRE study in people 20 to 93 years old.

Aging is characterized by several major changes, including altered body composition, which is associated with numerous negative clinical consequences such as sarcopenia, osteoporosis, and frailty. The study is to evaluate body composition parameters depending on age and sex in a population ranging from the young adult to the very old, and to identify break points in the association between body composition and age. In this cross-sectional study, we included the enrolment population of the French INSPIRE-T prospective cohort, accounting for 915 subjects (62% female). Age ranged from 20 to 93 years, median age (years) was 63 (IQR 27). Body composition (lean mass, fat mass, and bone mineral content) was assessed with dual-X-ray absorptiometry (DXA). Different break points in the relationship between age and body composition variables in males and females were identified using a segmented regression analysis adjusted on physical activity, nutritional status, educational level, and comorbidities. Lean mass decreased from the age of 55 years for males (CI 95% 44-66) and 31 years for females (CI 95% 23-39). For fat mass, we observed a trend towards an increase with age for males. For females, we observed an increase with age up to age 75 (CI 95% 62-86), followed by a decreasing trend. In this study, we described the relationship between body composition and age as a function of sex, establishing a foundation for further studies on predictive biomarkers of age-related body composition alteration.

A locally optimised machine learning approach to early prognostication of long-term neurological outcomes after out-of-hospital cardiac arrest.

Background: Out-of-hospital cardiac arrest (OHCA) represents a major burden for society and health care, with an average incidence in adults of 67 to 170 cases per 100,000 person-years in Europe and in-hospital survival rates of less than 10%. Patients and practitioners would benefit from a prognostication tool for long-term good neurological outcomes. Objective: We aim to develop a machine learning (ML) pipeline on a local database to classify patients according to their neurological outcomes and identify prognostic features. Methods: We collected clinical and biological data consecutively from 595 patients who presented OHCA and were routed to a single regional cardiac arrest centre in the south of France. We applied recursive feature elimination and ML analyses to identify the main features associated with a good neurological outcome, defined as a Cerebral Performance Category score less than or equal to 2 at six months post-OHCA. Results: We identified 12 variables 24 h after admission, capable of predicting a six-month good neurological outcome. The best model (extreme gradient boosting) achieved an AUC of 0.96 and an accuracy of 0.92 in the test cohort. Conclusion: We demonstrated that it is possible to build accurate, locally optimised prediction and prognostication scores using datasets of limited size and breadth. We proposed and shared a generic machine-learning pipeline which allows external teams to replicate the approach locally.

Integrative Multimodal Metabolomics to Early Predict Cognitive Decline Among Amyloid Positive Community-Dwelling Older Adults.

Alzheimer's disease is strongly linked to metabolic abnormalities. We aimed to distinguish amyloid-positive people who progressed to cognitive decline from those who remained cognitively intact. We performed untargeted metabolomics of blood samples from amyloid-positive individuals, before any sign of cognitive decline, to distinguish individuals who progressed to cognitive decline from those who remained cognitively intact. A plasma-derived metabolite signature was developed from Supercritical Fluid chromatography coupled with high-resolution mass spectrometry (SFC-HRMS) and nuclear magnetic resonance (NMR) metabolomics. The 2 metabolomics data sets were analyzed by Data Integration Analysis for Biomarker discovery using Latent approaches for Omics studies (DIABLO), to identify a minimum set of metabolites that could describe cognitive decline status. NMR or SFC-HRMS data alone cannot predict cognitive decline. However, among the 320 metabolites identified, a statistical method that integrated the 2 data sets enabled the identification of a minimal signature of 9 metabolites (3-hydroxybutyrate, citrate, succinate, acetone, methionine, glucose, serine, sphingomyelin d18:1/C26:0 and triglyceride C48:3) with a statistically significant ability to predict cognitive decline more than 3 years before decline. This metabolic fingerprint obtained during this exploratory study may help to predict amyloid-positive individuals who will develop cognitive decline. Due to the high prevalence of brain amyloid-positivity in older adults, identifying adults who will have cognitive decline will enable the development of personalized and early interventions.

Interrelationship between lymphocytes and leptin in fat depots of obese mice revealed by changes in nutritional status

The mechanisms underlying the relationships between nutritional status and immunity remain to be fully characterized. The present study was undertaken to analyze by flow cytometry, in the context of diet-induced obesity, the status of immune cells in subcutaneous, and epididymal fat depots in wild-type and immunodeficient Rag2−/− mice submitted to nutritional challenge, i.e., 48-h fasting and 1-week refeeding. In parallel, the responsiveness of mature adipocytes and immune cells in bone marrow, lymph node, and liver were also analyzed. The results show that fasting in obese wild-type mice induces a prominent lipolysis in epididymal AT and immunosuppression restricted to both subcutaneous and epididymal AT, characterized by reduced number of CD4+ T and B lymphocytes and M1/M2 macrophages associated with reduced leptin and increased FGF21 expression in mature adipocytes. One-week refeeding was sufficient to reverse the fasting-induced effects. Obese immunodeficient mice under nutritional challenge exhibited no changes in adipocyte leptin expression and no marked trafficking of AT macrophages or NK cells, while the fasted-induced upregulation of FGF21 expression was maintained as well as the lipolytic responses. The present results demonstrate that, in a context of diet-induced obesity, fasting-induced immunosuppression is restricted to fat depots in immunocompetent mice. Lack of adipocyte leptin regulation and fasting-induced immunosuppression in obese immunodeficient mice strongly suggests that lymphocytes are involved in the modulation of adipocyte leptin expression on one hand and on the other that leptin is involved in the immune changes in AT according to nutritional status