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Older populations with underlying medical conditions are at higher risk of COVID-19 severity and mortality once infected. OUL232 ic50 Intersectional gerontology considers the compounding effects of multiple forms of social inequity. This study explores how racial-nativity status, family income, education level and the intersecting profile of these three social standings stratify differential patterns of chronic conditions among Canadians aged 45 years and older.

Using the baseline Canadian Longitudinal Study on Aging (n = 29,748), multinomial logistic regression analyses were conducted to estimate multivariable-adjusted odds of having one and/or two (≤ 2) or multiple (≥3) medical conditions (i.e., diabetes, asthma, cancer, previous heart attack, cardiovascular disease, kidney disease, hypertension, chronic obstructive pulmonary disease, and obesity) based on socio-demographic characteristics.

There were significant racial-nativity disparities and social-class gradients in multimorbidity. The odds of having ≥3 medicth COVID-19 severe illness and mortality. Upstream health policy and social care tackling intersecting structural inequities should be undertaken to prevent increasing multimorbidity among underserved aging populations.

A better patient's knowledge on their Inflammatory Bowel Disease (IBD) could improve its outcome and quality of life. The aim of this study was to assess if an education program improves IBD patients' skills as regards to their disease.

The GETAID group conducted a prospective multicenter randomized controlled study. IBD patients were included at diagnosis, or after a significant event in the disease course. Patients were randomized between "educated" or control groups for 6 months. Education was performed by trained healthcare professionals. A psycho-pedagogic score (ECIPE) was evaluated by a "blinded" physician at baseline and after 6 and 12 months (M6 and M12). The primary endpoint was the increase of ECIPE score at M6 of more than 20%.

263 patients were included in 19 centers (Male40%; Median age30.8; CD73%). 133 patients were randomized in the educated group, and 130 in the control group. The median relative increase of the ECIPE score at M6 was higher in the educated group as compared to the control group (16.7%(0-42.1%) vs 7%(0-18.8%) respectively p=0.0008). The primary endpoint was met in 46% vs 24% of the patients in the educated and control groups respectively (p=0.0003). A total of 92 patients met the primary endpoint. In multivariate analysis, predictors of an increase of at least 20% of the ECIPE score were randomization in the educated group (OR=2.59) and no previous surgery (OR=1.92).

These findings support the set-up of education programs in centers involved in the management of IBD patients.

These findings support the set-up of education programs in centers involved in the management of IBD patients.Laughter is a complex motor behavior occurring in both emotional and nonemotional contexts. Here, we investigated whether the different functions of laughter are mediated by distinct networks and, if this is the case, which are the white matter tracts sustaining them. We performed a multifiber tractography investigation placing seeds in regions involved in laughter production, as identified by previous intracerebral electrical stimulation studies in humans the pregenual anterior cingulate (pACC), ventral temporal pole (TPv), frontal operculum (FO), presupplementary motor cortex, and ventral striatum/nucleus accumbens (VS/NAcc). The primary motor cortex (M1) and two subcortical territories were also studied to trace the descending projections. Results provided evidence for the existence of two relatively distinct networks. A first network, including pACC, TPv, and VS/NAcc, is interconnected through the anterior cingulate bundle, the accumbofrontal tract, and the uncinate fasciculus, reaching the brainstem throughout the mamillo-tegmental tract. This network is likely involved in the production of emotional laughter. A second network, anchored to FO and M1, projects to the brainstem motor nuclei through the internal capsule. It is most likely the neural basis of nonemotional and conversational laughter. The two networks interact throughout the pre-SMA that is connected to both pACC and FO.

Despite the prominent development of medical technology in recent years, the prognosis of non-small cell lung cancer (NSCLC) is still not optimistic. It is crucial to identify more reliable diagnostic biomarkers for the early diagnosis and personalized therapy of NSCLC and clarify the molecular mechanisms underlying NSCLC progression.

In the present study, bioinformatics analysis was performed on three datasets obtained from the Gene Expression Omnibus to identify the NSCLC-associated differentially expressed genes (DEGs). Immunohistochemistry-based tissue microarray of human NSCLC was used to experimental validating the potential targets obtained from bioinformatics analysis.

By using protein-protein interaction (PPI) network analysis, Kaplan-Meier plotter, and Gene Expression Profiling Interactive Analysis, we selected 40 core DEGs for further study. Then, a re-analysis of 40 selected genes via Kyoto Encyclopedia of Genes and Genomes pathway enrichment showed that nine key genes involved in the cell cvidualized therapeutic targets for NSCLC.

With up to 200 published contributions, the GreenLab mathematical model of plant growth, developed since 2000 under Sino-French co-operation for agronomic applications, is descended from the structural models developed in the AMAP unit that characterize the development of plants and encompass them in a conceptual mathematical framework. The model also incorporates widely recognized crop model concepts (thermal time, light use efficiency and light interception), adapting them to the level of the individual plant.

Such long-term research work calls for an overview at some point. That is the objective of this review paper, which retraces the main history of the model's development and its current status, highlighting three aspects. (1) What are the key features of the GreenLab model? (2) How can the model be a guide for defining relevant measurement strategies and experimental protocols? (3) What kind of applications can such a model address? This last question is answered using case studies as illustrations, and through the Discussion.