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IntroductionGrowing evidence exists that greenspace exposure can reduce metabolic syndrome risk, a growing public health concern with well-documented inequities across population subgroups. We capitalize on the use of g-computation to simulate the influence of multiple possible interventions on residential greenspace on nine metabolic biomarkers and metabolic syndrome in adults (N = 555) from the 2014-2017 Community of Mine Study living in San Diego County, California.MethodsNormalized difference vegetation index (NDVI) exposure from 2017 was averaged across a 400-m buffer around the participants residential addresses. Participants fasting plasma glucose, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglyceride concentrations, systolic and diastolic blood pressure, hemoglobin A1c (%), waist circumference, and metabolic syndrome were assessed as outcomes of interest. Using parametric g-computation, we calculated risk differences for participants being exposed to each decile of the participant NDVI distribution compared to minimum NDVI. Differential health impacts from NDVI exposure by sex, ethnicity, income, and age were examined.ResultsWe found that a hypothetical increase in NDVI exposure led to a decrease in hemoglobin A1c (%), glucose, and high-density lipoprotein cholesterol concentrations, an increase in fasting total cholesterol, low-density lipoprotein cholesterol, and triglyceride concentrations, and minimal changes to systolic and diastolic blood pressure, waist circumference, and metabolic syndrome. The impact of NDVI changes was greater in women, Hispanic individuals, and those under 65 years old.ConclusionsG-computation helps to simulate the potential health benefits of differential NDVI exposure and identifies which subpopulations can benefit most from targeted interventions aimed at minimizing health disparities.

Abstract Background Effective physician-patient communication is crucial to compassionate healthcare, particularly when conveying life-altering diagnoses such as those associated with congenital heart diseases. Despite its importance, medical practitioners often face challenges in communicating effectively. Because of these gaps, we aim to introduce a simulation-based training protocol to improve pediatric cardiology trainee’s communication skills. This study will be conducted in collaboration with associations supporting caregivers of children with congenital heart disease. It strives to demonstrate how specific training programs can efficiently foster humanistic, patient-centered care in standard medical practice. Methods This multicenter, open-label randomized controlled trial will be conducted in pediatric cardiac units and simulation centers of across 10 universities in France. The study population comprises pediatric cardiologists in training (including pediatric cardiac fellows or specialist assistants). The SIMUL-CHD intervention will consist of simulation-based training with standardized patients, focusing on improving communication skills for pediatric cardiology trainees during diagnostic counselling. Patients and caregivers have been recruited from a National Patient Association named “Petit Cœur de Beurre”. The primary outcome is the quality of physicians’ communication skills. The evaluation committee, which will review video recordings of the sessions, will be blinded to which participants received simulation-based training (group of interest) and which received theory-based training (control group). Secondary outcomes are the effect of SIMUL-CHD on empathy and anxiety levels in young pediatric cardiologists. Baseline scores pre and post-intervention will be compared, and skill improvement resulting from the intervention measured. Discussion Simulation-based training has proven efficacy in teaching technical skills in various scenarios however its application to communication skills in pediatric cardiology remains unexplored. The involvement of experienced parents provides a unique perspective, incorporating their profound understanding of the emotional challenges and specific hurdles faced by families dealing with congenital heart disease. Trial registration This trial is registered with the OSF registry (registered https://osf.io/ed78q ).

Abstract Synapses are organized into nanocolumns that control synaptic transmission efficacy through precise alignment of postsynaptic neurotransmitter receptors and presynaptic release sites. Recent evidence show that Leucine-Rich Repeat Transmembrane protein LRRTM2, highly enriched and confined at synapses, interacts with Neurexins through its C-terminal cap, but the role of this binding interface has not been explored in synapse formation and function. Here, we develop a conditional knock-out mouse model (cKO) to address the molecular mechanisms of LRRTM2 regulation, and its role in synapse organization and function. We show that LRRTM2 cKO specifically impairs excitatory synapse formation and function in mice. Surface expression, synaptic clustering, and membrane dynamics of LRRTM2 are tightly controlled by selective motifs in the C-terminal domain. Conversely, the N-terminal domain controls presynapse nano-organization and postsynapse AMPAR sub-positioning and stabilization through the recently identified Neurexin-binding interface. Thus, we identify LRRTM2 as a central organizer of pre- and post- excitatory synapse nanostructure through interaction with presynaptic Neurexins.

When our brains are healthy, we can memorize, pay attention, reason, move, communicate, make decisions, and complete complex tasks. As some people get older, they can no longer do those things—they suffer from cognitive disorders that could indicate the start of dementia. Many factors might play a role in the development of dementia and some of those factors, like age and education level, have been identified. We know that there are additional, unidentified factors that play a role in the development of dementia, and scientists are discovering that where we live also matters. Our living environments include buildings and other structures, green spaces, and the level of air pollution. In this article, we explain the impact of the living environment on brain health decline during aging.

A Human induced pluripotent stem cell (iPSC) line was generated from dermal fibroblasts of a patient affected with an autosomal recessive retinal dystrophy carrying the homozygous c.910-7G>A variant in UBAP1L. Three isogenic control iPSC lines derived from this affected subject line were created using CRISPR/Cas9 engineering. All iPSC lines expressing the pluripotency markers, were able to differentiate into the three germ layers, and exhibit a normal karyotype. These cellular models will provide a powerful tool to study disease mechanisms associated with the recently reported UBAP1L- associated retinal dystrophy and better understand the role of the protein in retinal physiology.

STUDY OBJECTIVES: Examining multiple dimensions of sleep health may better capture associations between sleep and health risks, including cardiometabolic disease (CMD). Hispanics have elevated risk for inadequate sleep and CMD biomarkers. Few studies have explored whether associations between sleep and CMD differ by Hispanic ethnicity. METHODS: Leveraging data from the Community of Mine (CoM) study, a cross-sectional investigation of 602 ethnically diverse participants, we derived accelerometer-measured sleep duration and efficiency, and self-reported sleep quality. Accelerometer-measured sleep exposures were analyzed both as continuous and categorical variables. Multivariate and quantile regression models were used to assess associations between sleep and CMD biomarkers (insulin resistance, systolic blood pressure, and low-density-lipoprotein cholesterol), controlling for age, sex, ethnicity, education, smoking status, and body mass index. We examined the potential effect modification of Hispanic ethnicity. RESULTS: We observed mixed results based on CMD biomarkers and sleep exposure. Increased sleep duration was significantly related to low-density lipoprotein cholesterol in adjusted models (estimate = 0.06; 95% CI: 0.02, 0.11). Poor sleep efficiency was associated with greater insulin resistance in the adjusted quantile (estimate = 0.20; 95% CI: 0.04, 0.36) model at the 90th percentile. Self-reported sleep quality was not associated with CMD outcomes. There was no evidence of effect modification by Hispanic ethnicity. CONCLUSIONS: In this cohort, sleep health measures were found to have mixed and at times opposing effects on CMD outcomes. These effects did not demonstrate an interaction with Hispanic ethnicity.

Accumulating evidence links cardiometabolic health with social and environmental neighborhood exposures, which may contribute to health inequities. We examined whether environmental characteristics were individually or jointly associated with insulin resistance, hypertension, obesity, type 2 diabetes, and metabolic syndrome in San Diego County, CA. As part of the Community of Mine Study, cardiometabolic outcomes of insulin resistance, hypertension, BMI, diabetes, and metabolic syndrome were collected in 570 participants. Seven census tract level characteristics of participants' residential environment were assessed and grouped as follows: economic, education, health care access, neighborhood conditions, social environment, transportation, and clean environment. Generalized estimating equation models were performed, to take into account the clustered nature of the data and to estimate β or relative risk (RR) and 95 % confidence intervals (CIs) between each of the seven environmental characteristics and cardiometabolic outcomes. Quantile g-computation was used to examine the association between the joint effect of a simultaneous increase in all environmental characteristics and cardiometabolic outcomes. Among 570 participants (mean age 58.8 ± 11 years), environmental economic, educational and health characteristics were individually associated with insulin resistance, diabetes, obesity, and metabolic syndrome. In the mixture analyses, a joint quartile increase in all environmental characteristics (i.e., improvement) was associated with decreasing insulin resistance (β, 95 %CI: -0.09, -0.18-0.01)), risk of diabetes (RR, 95 %CI: 0.59, 0.36-0.98) and obesity (RR, 95 %CI: 0.81, 0.64-1.02). Environmental characteristics synergistically contribute to cardiometabolic health and independent analysis of these determinants may not fully capture the potential health impact of social and environmental determinants of health.

Abstract Dual‐energy X‐ray computed tomography consists of imaging objects using two incident X‐ray beams of different energy to distinguish the different compounds within a sample based on their density (electron density, ρe) and elemental composition (effective atomic number, Zeff). The stoichiometric calibration for dual‐energy X‐ray computed tomography was already successfully implemented to identify single and homogeneous minerals easily and non‐destructively. It is here applied for the first time to a more complex and heterogeneous sample, a varved sediment core with three distinct facies. The output of dual‐energy X‐ray computed tomography was compared against elemental geochemistry obtained at the same resolution using a micro‐XRF core scanner. The three individual facies can be successfully differentiated using dual‐energy X‐ray computed tomography because their range of ρe and Zeff values allow their discrimination. Correlations with elemental geochemistry are also discussed but are less conclusive, probably because of variations in grain size and porosity, and because these high resolution analyses were not performed at the exact same location. The paper not only eventually discusses the limitations when using dual‐energy X‐ray computed tomography on sediments but also demonstrates its potential to quantitatively study sediment cores in a non‐destructive way.

IntroductionExposure to air pollution disproportionately affects racial/ethnic minorities that could contribute to health inequalities including metabolic disorders. However, most existing studies used a static assessment of air pollution exposure (mostly using the residential address) and do not account for activity space when modelling exposure to air pollution. The aim of this study is to understand how exposure to air pollution impacts metabolic disorders biomarkers, how this effect differs according to ethnicity, and for the first time compare these findings with two methods of exposure assessment: dynamic and static measures.MethodsAmong the Community of Mine study, a cross-sectional study conducted in San Diego County, insulin resistance, diabetes, hypertension, obesity, dyslipidemia, and metabolic syndrome (MetS) were assessed. Exposure to air pollution (PM2.5, NO2, traffic) was calculated using static measures around the home, and dynamic measures of mobility derived from Global Positioning Systems (GPS) traces using kernel density estimators to account for exposure variability across space and time. Associations of air pollution with metabolic disorders were quantified using generalized estimating equation models to account for the clustered nature of the data.ResultsAmong 552 participants (mean age 58.7 years, 42% Hispanic/Latino), Hispanics/Latinos had a higher exposure to PM2.5 compared to non-Hispanics using static measures. In contrast, Hispanics/Latinos had less exposure to PM2.5 using dynamic measures. For all participants, higher dynamic exposure to PM2.5 and NO2 was associated with increased insulin resistance and cholesterol levels, and increased risk of obesity, dyslipidemia and MetS (RR 1.17, 95% CI: 1.07-1.28; RR 1.21, 95% CI: 1.12-1.30, respectively). The association between dynamic PM2.5 exposure and MetS differed by Hispanic/Latino ethnicity.ConclusionThese results highlight the importance of considering people's daily mobility in assessing the impact of air pollution on health.

Summary: Inflammatory bowel diseases are characterized by the chronic relapsing inflammation of the gastrointestinal tract. While the molecular causality between endoplasmic reticulum (ER) stress and intestinal inflammation is widely accepted, the metabolic consequences of chronic ER stress on the pathophysiology of IBD remain unclear. By using in vitro, in vivo models, and patient datasets, we identified a distinct polarization of the mitochondrial one-carbon metabolism and a fine-tuning of the amino acid uptake in intestinal epithelial cells tailored to support GSH and NADPH metabolism upon ER stress. This metabolic phenotype strongly correlates with IBD severity and therapy response. Mechanistically, we uncover that both chronic ER stress and serine limitation disrupt cGAS-STING signaling, impairing the epithelial response against viral and bacterial infection and fueling experimental enteritis. Consequently, the antioxidant treatment restores STING function and virus control. Collectively, our data highlight the importance of serine metabolism to allow proper cGAS-STING signaling and innate immune responses upon gut inflammation.

The Gross Motor Function Measure is used in most studies measuring gross motor function in children with cerebral palsy. In many studies, including those evaluating the effect of hyperbaric treatment, the Gross Motor Function Measure variations were potentially misinterpreted because of the lack of control groups. The Gross Motor Function Measure Evolution Ratio (GMFMER) uses historical data from the Gross Motor Function Classification System curves and allows to re-analyze previous published studies which used the Gross Motor Function Measure by considering the natural expected evolution of the Gross Motor Function Measure. As the GMFMER is defined by the ratio between the recorded Gross Motor Function Measure score increase and the expected increase attributed to natural evolution during the duration of the study (natural evolution yields a GMFMER of 1), it becomes easy to assess and compare the efficacy of different treatments.ObjectiveThe objective of this study is to revisit studies done with different dosage of hyperbaric treatment and to compare the GMFMER measured in these studies with those assessing the effects of various recommended treatments in children with cerebral palsy.MethodsPubMed Searches were conducted to included studies that used the Gross Motor Function Measure to evaluate the effect of physical therapy, selective dorsal rhizotomy, botulinum toxin injection, hippotherapy, stem cell, or hyperbaric treatment. The GMFMER were computed for each group of the included studies.ResultsForty-four studies were included, counting 4 studies evaluating the effects of various dosage of hyperbaric treatment in children with cerebral palsy. Since some studies had several arms, the GMFMER has been computed for 69 groups. The average GMFMER for the groups receiving less than 2 h/week of physical therapy was 2.5 ± 1.8 whereas in context of very intensive physical therapy it increased to 10.3 ± 6.1. The GMFMER of stem cell, selective dorsal rhizotomy, hippotherapy, and botulinum toxin treatment was, 6.0 ± 5.9, 6.5 ± 2.0, 13.3 ± 0.6, and 5.0 ± 2.9, respectively. The GMFMER of the groups of children receiving hyperbaric treatment were 28.1 ± 13.0 for hyperbaric oxygen therapy and 29.8 ± 6.8 for hyperbaric air.ConclusionThe analysis of the included studies with the GMFMER showed that hyperbaric treatment can result in progress of gross motor function more than other recognized treatments in children with cerebral palsy.

Summary: Modeling tumor metabolism in vitro remains challenging. Here, we used galactose as an in vitro tool compound to mimic glycolytic limitation. In contrast to the established idea that high glycolytic flux reduces pyruvate kinase isozyme M2 (PKM2) activity to support anabolic processes, we have discovered that glycolytic limitation also affects PKM2 activity. Surprisingly, despite limited carbon availability and energetic stress, cells induce a near-complete block of PKM2 to divert carbons toward serine metabolism. Simultaneously, TCA cycle flux is sustained, and oxygen consumption is increased, supported by glutamine. Glutamine not only supports TCA cycle flux but also serine synthesis via distinct mechanisms that are directed through PKM2 inhibition. Finally, deleting mitochondrial one-carbon (1C) cycle reversed the PKM2 block, suggesting a potential formate-dependent crosstalk that coordinates mitochondrial 1C flux and cytosolic glycolysis to support cell survival and proliferation during nutrient-scarce conditions.

Limited previous work has identified a relationship between exposure to ambient air pollution and aggressive somatic lung tumor mutations. More work is needed to confirm this relationship, especially using spatially resolved air pollution. We aimed to quantify the association between different air pollution metrics and aggressive tumor biology. Among patients treated at City of Hope Comprehensive Cancer Center in Duarte, CA (2013-2018), three non-small cell lung cancer somatic tumor mutations, TP53, KRAS, and KRAS G12C/V, were documented. PM2.5 exposure was assessed using state-of-the art ensemble models five and ten years before lung cancer diagnosis. We also explored the role of NO2 using inverse-distance-weighting approaches. We fitted logistic regression models to estimate odds ratio (OR) and their 95% confidence intervals (CIs). Among 435 participants (median age: 67, female: 51%), an IQR increase in NO2 exposure (3.5 μg/m3) five years before cancer diagnosis was associated with an increased risk in TP53 mutation (OR, 95% CI: 1.30, 0.99-1.71). We found an association between highly-exposed participants to PM2.5 (>12 μg/m3) five and ten years before cancer diagnosis and TP53 mutation (OR, 95% CI: 1.61, 0.95-2.73; 1.57, 0.93-2.64, respectively). Future studies are needed to confirm this association and better understand how air pollution impacts somatic profiles and the molecular mechanisms through which they operate.

This study aimed to investigate the role of cardiovascular health (CVH) and vascular events as potential contributors to socioeconomic inequalities in dementia using causal mediation analyses. We used data from the Three-City Cohort, a French population-based study with 12 years of follow-up, with active search of dementia cases and validated diagnosis. Individual socioeconomic status was assessed using education, occupation and income. A CVH score as defined by the American Heart Association and incident vascular events were considered separately as mediators. We performed multi-level Cox proportional and Aalen additive hazard regression models to estimate the total effects of socioeconomic status on dementia risk. To estimate natural direct and indirect effects through CVH and vascular events, we applied two distinct weighting methods to quantify the role of CVH and vascular events: Inverse Odds Ratio Weighting (IORW) and Marginal Structural Models (MSM) respectively. Among 5581 participants, the risk of dementia was higher among participants with primary education (HR 1.60, 95%CI 1.44-1.78), blue-collar workers (HR 1.62, 95%CI 1.43-1.84) and with lower income (HR 1.23, 95%CI 1.09-1.29). Using additive models, 571 (95% CI 288-782) and 634 (95% CI 246-1020) additional cases of dementia per 100 000 person and year were estimated for primary education and blue-collar occupation, respectively. Using IORW, the CVH score mediate the relationship between education or income, and dementia (proportion mediated 17% and 26%, respectively). Yet, considering vascular events as mediator, MSM generated indirect effects that were smaller and more imprecise. Socioeconomic inequalities in dementia risk were observed but marginally explained by CVH or vascular events mediators.

Abstract Fibroblasts have a considerable functional and molecular heterogeneity and can play various roles in the tumor microenvironment. Here we identify a pro-tumorigenic IL1R1+, IL-1-high-signaling subtype of fibroblasts, using multiple colorectal cancer (CRC) patient single cell sequencing datasets. This subtype of fibroblasts is linked to T cell and macrophage suppression and leads to increased cancer cell growth in 3D co-culture assays. Furthermore, both a fibroblast-specific IL1R1 knockout and IL-1 receptor antagonist Anakinra administration reduce tumor growth in vivo. This is accompanied by reduced intratumoral Th17 cell infiltration. Accordingly, CRC patients who present with IL1R1-expressing cancer-associated-fibroblasts (CAFs), also display elevated levels of immune exhaustion markers, as well as an increased Th17 score and an overall worse survival. Altogether, this study underlines the therapeutic value of targeting IL1R1-expressing CAFs in the context of CRC.

En este trabajo se investiga la distribución de tierras raras (REE), elementos críticos de interés económico, en minerales accesorios de Pizarras Ordovícicas del Sinclinal de Truchas (Fm. Luarca, Zona Centro-Ibérica, León). Estas pizarras están formadas por cuarzo, moscovita y clorita (± albita) y minerales accesorios diversos: monacita (en parte sin-metamórfica), xenotima, allanita, zircón, apatito, óxidos (rutilo y magnetita) y sulfuros (pirita-pirrotina, calcopirita, galena, esfalerita y pentlandita). Se han realizado regresiones lineales múltiples entre la composición media de REE de las pizarras y de diferentes minerales accesorios de la literatura. Los resultados muestran que la combinación de monacita y xenotima, con abundancias modales de 0.046% y 0.013% respectivamente, explica satisfactoriamente los patrones de REE en roca total, de acuerdo con las observaciones de microscopia electrónica de barrido. Estos resultados permiten conocer el control mineralógico de la geoquímica de REE en estas pizarras Ordovícicas. Adicionalmente, la observación de monacita sin metamórfica es importante para futuros estudios geocronológicos.

In this work, a framework was developed to access and process raw data from a commercial X-ray Computed Tomography (CT) scanner for research purposes. Our method requires vendor-provided binaries to convert the data to a readable format and also to remove the effect of proprietary beam hardening preprocessing. As a result, custom reconstruction techniques, including beam-hardening corrections algorithms, can be applied. Small region-of-interest CT imaging techniques and different backprojection algorithms were investigated to improve image quality (spatial resolution, noise) with an in-house iterative reconstruction algorithm. For a reconstruction matrix of 512 pixels × 512 pixels, processing times of approximately 2.5 s per slice were obtained using a set of 8 x GPUs. With this framework, high-quality images of high density samples (e.g., minerals) can be obtained with reduced truncation-induced blurring, free of artifacts stemming from the reconstruction process and reduced beam-hardening artifacts.