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Cold exposure induces the constitutively active thermogenic receptor, GPR3, via ERRα and ERRγ
No full textObjectives: Despite transformative advances in obesity pharmacotherapy, safely increasing energy expenditure remains a key unmet need. Exploiting thermogenic adipocytes represents a promising target given their capacity for significant catabolic activity. We previously showed that G protein-coupled receptor 3 (GPR3) can drive energy expenditure in brown and white mouse and human adipocytes. GPR3 is a unique GPCR because it displays high intrinsic activity and leads to constitutive cAMP signaling upon reaching the cell surface. Therefore, the transcriptional induction of GPR3 is analogous to ligand-binding activation of most GPCRs. Gpr3 expression is physiologically induced in thermogenic adipocytes by cold exposure, and mimicking this event through overexpression in mice is fully sufficient to increase energy expenditure and counteract metabolic disease. Yet the factors mediating physiological Gpr3 expression remain unknown. Methods: Here, we apply ATAC-Seq to identify cold-induced promoter elements of Gpr3. We uncover a role for the estrogen-related receptors, ERRα and ERRγ, in the physiological transcriptional control of Gpr3 using adipose-specific double knock-out mice with and without adeno-associated virus (AAV)-mediated rescue. Results: We show that ERRα directly binds the cold-induced promoter element of Gpr3 and that ERRα, ERRβ, and ERRγ each activate the Gpr3 promoter in vitro when co-transfected with PGC-1α. Adipocyte ERRα and ERRγ are required for the in vivo transcriptional induction of Gpr3 during cold exposure. Importantly, deficient Gpr3 cold-inducibility in adipose-specific ERRα and ERRγ KO mice is fully rescued by delivery of AAVs re-expressing either ERRα or ERRγ directly into brown adipose tissue. Conclusions: ERRα and ERRγ are critical regulators of cold-induced transcription of Gpr3 and represent a targetable strategy for pharmacologically unlocking GPR3-induced energy expenditure.</p
Automobility, planet, and humans:Pathways linking car use to environmental, societal, and individual well-being
No full textAmidst the climate crisis, global car ownership continues to rise. Scholarly literature often emphasizes negative impacts, while under-examining the varied effects on society, car users, and non-users, as well as the benefits that help sustain car dependence. This conceptual paper introduces a new conceptual model that organizes pathways linking automobility to environmental, societal, and individual well-being. Automobility exerts a profound influence on climate change and environmental sustainability, while it has far-reaching implications for human well-being. The effects on human well-being largely depend on contextual factors, such as the degree of car dependency in the built environment, and personal circumstances, including socioeconomic status. Automobility's influence operates at both collective and individual levels, shaping collective societal outcomes as well as individual experiences. Collective outcomes are mostly negative, including traffic fatalities, consumption of public space, and harmful effects on public health. Individual outcomes are unevenly distributed: individuals who rely on cars often derive important benefits such as flexibility, comfort, accessibility to destinations, and job opportunities, whereas non-users face serious mobility disadvantages particularly in car-oriented systems, thus deepening existing inequalities. The paper calls for global reflection and new empirical research that build upon or enhance the model and pathways proposed here
Reflection of serum PCB concentrations in silicone wristbands, hand wipes, indoor air, and dust and the associations between exposure and thyroid hormone homeostasis
No full textPolychlorinated biphenyls (PCBs) are legacy contaminants that are enduring indoor environmental problems due to historical applications. Among residents living in PCB-contaminated and reference apartments, we compared the effectiveness of personal and environmental samples for determining exposure through associations with 14 serum PCBs and explored potential effects on thyroid biomarkers. Silicone wristband PCBs were strongly correlated with serum measurements, particularly for lower chlorinated PCBs (rs = 0.59–0.82), and showed for the first time that wristbands are effective indicators of internal dose for PCBs. Similar correlations were observed for indoor air and dust, and hand wipes were significantly associated with serum for all congeners (rs = 0.44–0.73). Stratified analyses, which accounted for some participant characteristics, demonstrated that significant relationships were specific to those living in contaminated apartments and most focused among lower chlorinated congeners. Here, residents had lived in their homes for many years (mean > 10 years) and spent most of their time at home, due in part to being a majority aging population. As such, the four external exposure measures were strongly inter-correlated across the congeners. We also observed associations with free triiodothyronine (T3) and ratio between T3 and thyroxine (T4) in the exposed population. T3 and PCB−28 shared a significant, inverse dose-response relationship, with 13 and 17 % decreases in T3 for the second and third serum PCB−28 tertiles, respectively. Our results suggest that any of the four sample types collected in this exposure scenario accurately pointed to elevated PCB exposure and that this exposure was associated with a change in thyroid hormone homeostasis.Polychlorinated biphenyls (PCBs) are legacy contaminants that are enduring indoor environmental problems due to historical applications. Among residents living in PCB-contaminated and reference apartments, we compared the effectiveness of personal and environmental samples for determining exposure through associations with 14 serum PCBs and explored potential effects on thyroid biomarkers. Silicone wristband PCBs were strongly correlated with serum measurements, particularly for lower chlorinated PCBs (rs = 0.59–0.82), and showed for the first time that wristbands are effective indicators of internal dose for PCBs. Similar correlations were observed for indoor air and dust, and hand wipes were significantly associated with serum for all congeners (rs = 0.44–0.73). Stratified analyses, which accounted for some participant characteristics, demonstrated that significant relationships were specific to those living in contaminated apartments and most focused among lower chlorinated congeners. Here, residents had lived in their homes for many years (mean > 10 years) and spent most of their time at home, due in part to being a majority aging population. As such, the four external exposure measures were strongly inter-correlated across the congeners. We also observed associations with free triiodothyronine (T3) and ratio between T3 and thyroxine (T4) in the exposed population. T3 and PCB−28 shared a significant, inverse dose-response relationship, with 13 and 17 % decreases in T3 for the second and third serum PCB−28 tertiles, respectively. Our results suggest that any of the four sample types collected in this exposure scenario accurately pointed to elevated PCB exposure and that this exposure was associated with a change in thyroid hormone homeostasis.</p
Adding comprehensive geriatric assessment to standard of care in older patients with frailty and hematological cancer:A pilot and feasibility study
No full textGridded precipitation and temperature products performance over Afghanistan:from simple bias correction to advanced data fusion
No full textThe reliability of gridded precipitation and temperature products as alternatives to ground observations remains a matter of debate, particularly in data-sparse regions with complex terrain, such as Afghanistan. Bias correction is often essential; however, selecting between simple and advanced methods is challenging. We evaluated 13 precipitation products spanning satellite, reanalysis, merged, and gauge-based datasets (CHIRPS, CMORPH, CPC, ERA5, GLDAS, GMCP, GPCP, GPM calibrated/uncalibrated, GSMaP calibrated/uncalibrated, MERRA-2, MSWEP, and PERSIANN) and 6 temperature products (CPC, ERA5, GLDAS, MERRA-2, MODIS, and NCEP) against 82 observation stations covering Afghanistan’s diverse topography and climate zones. The temperature products showed consistently high accuracy without the need for bias correction, with CPC and GLDAS exhibiting the best performance. Among the precipitation datasets, the merged satellite–gauge–reanalysis products GMCP and MSWEP exhibited the best performance, followed by the calibrated satellite product GPM; however, bias correction was required for all precipitation products. Subsequently, simple, moderate, and complex statistical and machine learning (ML) models were applied to correct for precipitation bias. A representative subset was first used to analyse ML hyperparameter behaviour and to test combinations of meteorological features and elevation; the optimal feature set was used to optimize ML models across the full dataset for each product. The Kling–Gupta Efficiency, Root Mean Square Error, Percentage Error in Volume, and the coefficient of determination were used as the main evaluation metrics. Statistically bias-corrected precipitation data were suitable for monthly applications, with deviations of approximately 10–20% of total water volume compared with observed data. However, for daily applications and gap-filling of station observations, ML methods enriched with additional meteorological features yielded improved accuracy, reducing volume error by approximately 5–10%. Overall, the models demonstrated better performance at the monthly scale than at the daily scale. Therefore, the choice of bias-correction method heavily depends on the intended application.</p
MSCANet:Multi-Scale Spatial-Channel Attention Network for Urbanization Intelligent Monitoring
No full textRapid urbanization drives economic growth but also brings complex environmental and social issues, highlighting the urgent need for efficient urbanization monitoring techniques. However, datasets for urbanization monitoring are often lacking in rapidly developing urban areas. At the methodological level, Convolutional Neural Networks (CNNs) andTransformer-based models for urbanization monitoring exhibit limitations in balancing computational efficiency and global modeling. The recently emerging parallel large kernel convolutional networks partially alleviate the conflict between global modeling and computational efficiency, but they employ simple element-wise addition to fuse multiscale features. This crude mechanism struggles to fully leverage multi-scale information. To address this, this paper takes Accra, the capital of Ghana, as a case study and proposes an urbanization monitoring framework covering both dataset construction and model design. Methodologically, we propose the Multi-Scale Spatial-Channel AttentionNetwork (MSCANet). Its core component, the Multi-Scale Spatial-Channel Attention Module (MSCAM), jointly models spatial and channel dimensions to mitigate the common confusion problem in parallel large kernel convolutional architectures. Furthermore, we adaptively modified the MSCAM to propose the Multi-Scale Spatial-Channel Attention Feature Fusion Module (MSCA-FFM) module for effectively integrating multi-modal information during the fusion stage. Experimental results show that MSCANet achievesoptimal performance on the self-built Accra dataset, with a mean intersection over union(mIoU) of 95.02%, an overall accuracy (OA) of 98.70%, and a mean F1 Score (mF1) of 97.43%. To further validate the model’s generalization capability, supplementary experiments were conducted on the public ISPRS Potsdam dataset. The results demonstrate that the MSCANet series of models remain competitive, achieving an overall mIoU of 80.92%, with particularly strong performance in the “Building” (mIoU 92.26%) and “Impervious surface” (mIoU 84.63%) categories.<br/
Influence of sample size and spatial resolution on quantifying Mozzarella cheese microstructural properties:An X-ray tomography case study
No full textMicroscopic imaging techniques (2D and 3D) are widely employed to investigate structured food systems. However, the practical limitations of these imaging methods often restrict analyses to a small number of samples, which may be acquired under loosely defined imaging conditions and parameters. Assessing the representativeness of these measurements is further complicated by the fundamental properties of food matrices, such as their inherent heterogeneity, disordered nature, and microstructural complexity. To address this in a practical setting, a comprehensive dataset of high-resolution synchrotron X-ray tomography scans of Mozzarella cheese is analyzed. Representative Elementary Volume (REV) analysis is applied to key structural descriptors — such as anisotropy, width, and orientation — to determine the volume and resolution thresholds required for reliable local characterization. Additionally, macroscale heterogeneity is quantified by evaluating descriptor variability in samples from the same Mozzarella cheese formulation, followed by comparison to inter-cheese distances in descriptor space. These findings offer methodological guidance for designing reliable imaging protocols not only for Mozzarella but also for other structurally similar food matrices, supporting broader adoption of image-based structural measurements in both research and industrial applications.</p
Cardiogenic Shock
No full textCardiogenic shock is characterized by depression of cardiac function that leads to low blood pressure, coronary ischemia, and further decreased cardiac contractility resulting in tissue hypoxemia. The condition is associated with high early mortality, approaching 50%, which is largely influenced by the underlying etiologic factors. In infarct-related cardiogenic shock, rapid restoration of coronary blood flow substantially reduces mortality. Mechanical circulatory support devices offer hemodynamic stabilization and improved outcomes in carefully selected patients, although optimal patient selection and timing of initiation of mechanical circulatory support remain areas of active investigation. Although there have been advances in coronary revascularization techniques and mechanical circulatory support devices, overall survival in cardiogenic shock has improved only modestly. Therefore, future research should focus on refining treatment algorithms, optimizing device use, and developing new strategies to address the high mortality associated with cardiogenic shock.</p