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Ultralight Carbon Tube Foam-Derived SiC Nanofibrous Aerogels with Arbitrary Shape, Excellent Rigidity, and Resilience for Thermal Insulation.
ACS Appl Mater Interfaces
January 2025
School of Mechanics and Aerospace Engineering, Dalian University of Technology, Dalian 116024, P. R. China.
Ceramic aerogels are promising high-temperature thermal insulation materials due to their outstanding thermal stability and oxidation resistance. However, restricted by nanoparticle-assembled network structures, conventional ceramic aerogels commonly suffer from inherent brittleness, volume shrinkage, and structural collapse at high temperatures. Here, to overcome such obstacles, 3D ultralight and highly porous carbon tube foams (CTFs) were designed and synthesized as the carbonaceous precursors, where melamine foams were used as the sacrificial templates to form the hollow and thin-wall network structures in the CTFs (density: ∼4.
View Article and Find Full Text PDFComparative analysis of Voxel-based morphometry using T1 and T2-weighted magnetic resonance imaging to explore the relationship between brain structure and cognitive abilities.
Exp Brain Res
January 2025
Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Voxel-based morphometry (VBM) of T1-weighted (T1-w) magnetic resonance imaging (MRI) is primarily used to study the association of brain structure with cognitive functions. However, in theory, T2-weighted (T2-w) MRI could also be used in VBM studies because of its sensitivity to pathology and tissue changes. We aimed to compare the T1-w and T2-w images to study brain structures in association with cognitive abilities.
View Article and Find Full Text PDF[Diabetes mellitus and obesity: risk optimization before surgical interventions].
Orthopadie (Heidelb)
January 2025
Westdeutsches Diabetes- und Gesundheitszentrum, Verbund Katholischer Kliniken Düsseldorf, Hohensandweg 37, 40591, Düsseldorf, Deutschland.
Background: The prevalence of obesity has increased significantly in recent years and is a causal risk factor for the development of type 2 diabetes. Moreover, chronic degenerative joint diseases are also triggered by obesity.
Weight Loss: Both obesity-related secondary diseases-type 2 diabetes and chronic degenerative joint disease-can be prevented or at least delayed by lifestyle intervention aimed at weight reduction.
Tailoring Exercise Prescription for Effective Diabetes Glucose Management.
J Clin Endocrinol Metab
January 2025
Department of Kinesiology and Health, Rutgers University, New Brunswick, NJ 08901, USA.
Context: Physical activity, exercise, or both are a staple of lifestyle management approaches both for type 1 diabetes mellitus (T1DM) and type 2 diabetes (T2DM). While the current literature supports both physical activity and exercise for improving glycemic control, reducing cardiovascular risk, maintaining proper weight, and enhancing overall well-being, the optimal prescription regimen remains debated.
Evidence Acquisition: We searched PubMed and Google Scholar databases for relevant studies on exercise, insulin sensitivity, and glycemic control in people with T1DM and T2DM.
Optimized machine learning approaches to combine surface-enhanced Raman scattering and infrared data for trace detection of xylazine in illicit opioids.
Analyst
January 2025
Department of Chemistry, University of Victoria, Victoria, British Columbia, V8W 3V6, Canada.
Infrared absorption spectroscopy and surface-enhanced Raman spectroscopy were integrated into three data fusion strategies-hybrid (concatenated spectra), mid-level (extracted features from both datasets) and high-level (fusion of predictions from both models)-to enhance the predictive accuracy for xylazine detection in illicit opioid samples. Three chemometric approaches-random forest, support vector machine, and -nearest neighbor algorithms-were employed and optimized using a 5-fold cross-validation grid search for all fusion strategies. Validation results identified the random forest classifier as the optimal model for all fusion strategies, achieving high sensitivity (88% for hybrid, 92% for mid-level, and 96% for high-level) and specificity (88% for hybrid, mid-level, and high-level).
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