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Identification of the Surface Hydrogen Functionalities on Colloidal Zinc Oxide Nanocrystals with Multinuclear Solid-State NMR Spectroscopy
SCARF1 deficiency exacerbates gut inflammation and autoimmune pathology
Terahertz Vibrational Condensation in Out-of-Equilibrium Nanoscale Reverse Micelles
Global insights into [177Lu]Lu-DOTATATE safety: a comprehensive disproportionality analysis from the WHO pharmacovigilance database
Understanding the psychological impact of the climate crisis on individuals with depression: a phenomenological study
Abstract Climate change-related weather events have profound effects on human health, including mental well-being. Research indicates that the climate crisis contributes to various psychological disorders, such as depression and anxiety. Understanding how individuals diagnosed with depression experience and interpret the impact of climate change can help in developing preventive, protective, and therapeutic interventions for this vulnerable group. This study explores the experiences of individuals with depression regarding the climate crisis, their perceptions of its effects on their illness, and their needs for possible solutions. Using a phenomenological approach, in-depth interviews were conducted with twelve participants. The data were collected through a personal information form and a semi-structured interview, focusing on participants’ views and experiences related to the climate crisis. Thematic analysis revealed five key themes: (1) Effects on Daily Life and Social Functioning, (2) Health Impacts, (3) Climate Anxiety and Future Concerns, (4) Emotional and Psychological Responses, and (5) Coping Mechanisms and Recommendations. Findings suggest that individuals with depression experience multidimensional negative effects due to the climate crisis, affecting their well-being and daily lives. There is a pressing need to develop targeted interventions that enhance psychological resilience in this group, helping them cope with the ongoing and future challenges posed by climate change.
Depolymerization-Induced Morphological Transformation
Starter feed enhances growth, antioxidant capacity, and gut microbiota in Chawula yak calves
Unconventional Mechanism in the Selective Removal of Lead and Cadmium from Acidic Media Using Na <sub> <i>x</i> +2 <i>y</i> </sub> Sn <sub> 4– <i>y</i> </sub> S <sub>8</sub> ·3H <sub>2</sub> O (NMS-7)
Correction: Antifungal properties of Eucalyptus endophytic Streptomyces strains
Suppressing loop current of shielded loops at fundamental resonance
Abstract In magnetic resonance imaging (MRI), arrays of small loop antennas/coils are extensively used for signal reception. In such arrays, the loop current must be suppressed to prevent transmit antennas or other elements in a receive array from being detuned, thereby preserving image quality. While suppressing the current in conventional loop antennas/coils is straightforward, achieving effective suppression in shielded loops has remained an unresolved challenge. In this article, we derive theoretical principles for optimally suppressing the loop current of shielded loops at fundamental resonance and verify them experimentally. Maximal current suppression is achieved by carefully selecting the electrical load at the antenna outputs. We identify a critical relationship between loop inductance and load inductance specific to shielded loops. Our results demonstrate that the optimal suppression method reduces loop current by an additional 31–36 dB compared with the straightforward yet suboptimal approach of shorting the antenna outputs. These findings can facilitate the development of more robust antenna/coil arrays for MRI applications.
Concise Synthesis of Deoxylimonin
UV-induced immune modulation in the lung niche slows cancer progression
Correction to “Conformer-Sensitive Nuclear Dynamics of the Ammonia Dimer Cation Probed by Femtosecond Time-Resolved Coulomb Explosion”
Comparison of 3D ankle kinematics between minimal inertial measurement units configuration and optical motion capture system under diverse walking conditions
Abstract Accurate assessment of three-dimensional ankle kinematics is essential for advancing biomechanical analyses and informing potential clinical applications. While optical motion capture systems (OMCs) are considered the gold standard, their high cost and limited portability restrict their use outside the laboratory. Inertial measurement units (IMUs) offer a more practical alternative; however, concerns remain regarding their validity and reliability in diverse walking conditions. This study evaluated the agreement and repeatability of IMU-derived ankle kinematics relative to OMCs across three walking surfaces: level ground, inward wedge, and outward wedge. Ankle movements in the sagittal, frontal, and transverse planes were analyzed using a minimal sensor configuration. Moderate to high agreement and consistent repeatability were observed in the sagittal and transverse planes, particularly during level and inward wedge floor walking. Conversely, the frontal plane demonstrated limited agreement under wedged conditions, likely because of complex multisegmental foot dynamics and reference frame misalignment from static calibration. Despite these limitations, consistent repeatability across conditions supports the use of IMUs for tracking ankle kinematics outside the laboratory. These findings suggest the preliminary applicability of IMUs as a functional tool for interpreting ankle kinematics outside the laboratory.
Unraveling the Mixing Entropy-Activity Relationship in High Entropy Alloy Catalysts: The More, The Better?
The contribution of phenolic endocrine-disrupting chemicals to breast cancer risk: A comprehensive bioinformatics analysis
Abstract Bisphenol A (BPA), nonylphenol (NP), and octylphenol (OP) are common environmental phenolic endocrine disruptors and widely used industrial chemicals that have garnered significant attention due to their potential to disrupt endocrine functions. These compounds are known to interfere with hormonal activities, particularly those related to estrogen, and are linked to the onset and progression of breast cancer. This study aims to systematically investigate the potential relationship between BPA, NP, and OP and breast cancer risk, along with their underlying molecular mechanisms, by synthesizing data from multiple databases. We initially acquired the chemical structures and SMILES representations of BPA, NP, and OP from the PubChem database. Subsequently, we utilized multiple databases, including the Comparative Toxicogenomics Database (CTD), SEA, and Swiss Target Prediction, t0 estimate their probable biological targets. The predicted targets were standardized and consolidated to form a comprehensive target database. Breast cancer-related targets were subsequently identified from the GeneCards and DisGeNET databases, and their overlap with the targets of BPA, NP, and OP was analyzed to pinpoint potential breast cancer risk targets. To elucidate the functional pathways involved, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses using the DAVID database. This analysis offered insights into the molecular pathways influenced by BPA, NP, and OP in the context of breast cancer. Additionally, we utilized machine learning algorithms, specifically Least Absolute Shrinkage and Selection Operator (LASSO) regression and Support Vector Machine (SVM), to identify nuclear targets linked to BPA, NP, and OP-induced breast cancer. These nuclear targets were further validated through differential expression analysis and Receiver Operating Characteristic (ROC) curve analysis using the GEO dataset GSE42568. We also performed a Single Gene Gene Set Enrichment Analysis (GSEA) to investigate the potential regulatory mechanisms of these nuclear genes in breast cancer. The infiltration of immune cells in breast cancer tissues was analyzed using single-sample gene set enrichment analysis (ssGSEA), and the correlation between nuclear targets and immune cell infiltration was examined. Finally, molecular docking and molecular dynamics simulations were conducted to assess the binding affinity and stability of BPA, NP, and OP with their nuclear targets. In this study, we integrated network toxicology, machine learning and multi-omics validation, and identified for the first time that BPA, NP and OP may induce breast cancer through 156 common targets; among them, MAOA, MGLL, ADRA2A, RPN2, GF1R and CTSD were identified as the key causative genes, with a diagnostic efficacy of 0.80–0.94 AUC. Mechanistically, these genes are concentrated in the GPCR/MAPK/JNK, sphingolipid, and prolactin signaling pathways, which regulate the Wnt/TGF-β/chemokine network and dramatically modify the immunological infiltration of nine classes of M0-M2 macrophages and CD4⁺ T cells. Molecular docking and kinetic simulations suggested the strong affinity of BPA for MGLL, and the complex was stabilized with ≥ 3 hydrogen bonds. In conclusion, phenolic endocrine disruptors may cause breast cancer through the “multi-target-immune microenvironment-metabolic reprogramming” axis, and MAOA, MGLL, ADRA2A, and RPN2 may serve as new targets for early detection and management.