Search Results (4,328)

The prevention and treatment of cardiovascular disease (CVD) are undergoing a paradigm shift from a lipid-centric approach to a holistic metabolic perspective. Central to this evolution is the gut–fat–heart axis, a sophisticated three-dimensional communication network that integrates neural, endocrine, and immunometabolic signaling to regulate systemic lipid homeostasis. This manuscript systematically explores how the gut microbiota acts as a “metabolic organ” to remotely control host health through the production of bioactive metabolites and the modulation of molecular communication networks. At the physiological level, microbial products such as short-chain fatty acids (SCFAs) and modified bile acids regulate energy balance and lipid synthesis via the FXR-FGF15/19 axis and G protein-coupled receptors. Furthermore, gut hormones like GLP-1 and neuro-reflex pathways involving the vagus nerve provide rapid control over postprandial lipid clearance and feeding behavior. Conversely, pathological dysbiosis triggers the accumulation of harmful metabolites, such as trimethylamine N-oxide (TMAO) and lipopolysaccharides (LPS), which drive lipotoxicity, vascular inflammation, and “dysfunctional HDL” formation. These processes accelerate the progression of atherosclerosis, heart failure, and metabolic syndrome. Finally, the article outlines promising clinical translation strategies, including the development of TMA lyase inhibitors, next-generation probiotics, and the use of phytochemicals to reshape the microbial landscape. By decoding the molecular dialogues within the gut–fat–heart axis, this research provides a novel strategic vantage point for the integrated management of cardiovascular–kidney–metabolic (CKM) syndrome. Full article

H9N2 avian influenza viruses inherently carry cross-species transmission potential, making continuous surveillance critical for pandemic prevention. This study focused on monitoring the 2024 H9N2 epidemic in Jiangsu Province’s external environment, analyzing its molecular evolution and receptor binding properties, assessing cross-species transmission and pandemic risks, and investigating serological antibody levels across different human populations. Environmental samples were collected from live poultry markets, farms, slaughterhouses, and bird habitats across Jiangsu, screened via quantitative PCR (qPCR), with positive samples used for virus isolation and whole-genome sequencing. Receptor binding properties were tested by hemagglutination assay, and H9N2 antibody levels were measured in 370 occupationally exposed individuals and 240 non-exposed individuals using hemagglutination inhibition (HI) assays. Among the 5779 collected samples, 6.89% tested H9N2-positive, and 12 strains belonging to the Eurasian lineage Y280-like clade G57 genotype were successfully isolated. All strains carried the HA-Q226L mutation, with 11 showing preferential binding to human α-2,6 receptors and one strain possessing dual receptor binding capability. Internal genes harbored mammalian adaptation mutations, and M2 proteins contained mutations conferring complete resistance to amantadine-class antiviral drugs. Serological tests revealed antibody positive rates of 4.05% in exposed populations and 2.5% in non-exposed populations, with no statistically significant difference between groups. These findings confirm that Jiangsu’s circulating H9N2 viruses have acquired human receptor preference and mammalian adaptation, posing silent infection and pandemic risks. Enhanced surveillance and the development of candidate vaccine stockpiles are strongly recommended. Full article

Methicillin-resistant Staphylococcus aureus (MRSA) remains a significant multidrug-resistant pathogen, frequently associated with persistent infections and biofilm formation, underscoring the urgent need for alternative antimicrobial strategies. Bioactive compounds derived from fungi have attracted considerable attention due to their structural diversity and demonstrated antibacterial activity against MRSA. This study employed a scientometric approach to assess global research trends, thematic evolution, and collaborative networks concerning fungi-derived anti-MRSA compounds. Bibliographic data were collected from the Scopus database, and a total of 1666 English-language articles and reviews published up to 2025 were analyzed using Bibliometrix/Biblioshiny and VOSviewer. The findings indicate a marked increase in research output after 2010, reflecting heightened scientific interest in fungal natural products for MRSA management. China and the United States emerged as leading contributors in terms of publication volume and international collaboration. Thematic analysis revealed a shift from broad antimicrobial screening to more specialized investigations, including antibiofilm activity, secondary metabolites, endophytic fungi, molecular docking, and antimicrobial resistance. Nonetheless, several challenges persist, such as insufficient mechanistic validation, limited toxicity and pharmacokinetic assessments, and a lack of clinically relevant in vivo studies. Overall, the field is increasingly multidisciplinary, integrating microbiology, natural product chemistry, and computational methodologies to advance the discovery of anti-MRSA agents. Full article

Appendiceal mucinous neoplasms (AMNs) are a rare but clinically significant category of gastrointestinal tumors, ranging from low-grade appendiceal mucinous neoplasm (LAMN), the main precursor of pseudomyxoma peritonei (PMP), to high-grade appendiceal mucinous neoplasm (HAMN), poorly differentiated and signet-ring-cell adenocarcinomas, and goblet cell adenocarcinoma. Although current WHO and PSOGI classifications provide well established diagnostic criteria, controversies persist regarding the biological behavior and prognostic significance of the most aggressive subtypes and the relationship between HAMN and mucinous adenocarcinoma. While appendectomy is sufficient for localized LAMN, cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (CRS/HIPEC) is the treatment of choice for peritoneal dissemination This review integrates the histopathological and molecular classification of AMN and PMP with the evolution of intraperitoneal chemotherapy. Key findings indicate that KRAS and GNAS mutations are central drivers of mucin overproduction and peritoneal spread, that tumor grade and mucin cellularity remain the strongest prognostic determinants, and that the evidence supporting HIPEC and PIPAC derives largely from observational rather than randomized data. As a novel insight, we highlight the emerging role of patient-derived organoids as translational models for functional drug testing. Progress will depend on integrating molecular characterization, critical appraisal of intraperitoneal therapies, and organoid-based testing to advance individualized treatment for peritoneal surface malignancies. Full article

Prior to this study, knowledge on the evolutionary lineage of Garra remained inadequate, as previous phylogenetic investigations were primarily based on partial gene sequences. Although several mitogenomes of Garra species have been reported, their structural organization and comprehensive genomic characteristics have not been thoroughly evaluated. In this study, Garra manipurensis, endemic to the Indo-Burma biodiversity hotspot, was identified based on its detailed morphology and meristic counts. The circular mitogenome of G. manipurensis is 16,776 bp in length and contains the canonical set of 37 genes, along with duplicated control regions separated by tRNA-Proline. The comparative assessments across Garra species indicate predominantly conserved GTG start codons, occasional alternative ATA initiation codons, and incomplete stop codons. The selection pressure examinations within Garrini taxa reveal a purifying selection across all protein-coding genes. The control region comprises four conserved sequence blocks and species-specific tandem repeats, reflecting a balance between functional constraint and lineage-dependent evolutionary dynamics. The phylogenetic inference supports the monophyly of Garra and places G. manipurensis in close affinity with Garra flavatra, which is native to the western slope of Rakhine Yoma in Myanmar and Mizoram State in northeastern India. The genetic diversity analyses revealed haplotype differentiation, with shallow intraspecific genetic distances (0.000–0.011) observed samples between two distinct drainage systems in Manipur and Mizoram, northeastern India. The observed pattern of haplotype divergence in G. manipurensis may reflect the historical or seasonal hydrological connectivity among the western-slope drainages of the Chin Hills, with the subsequent geographic isolation potentially contributing to the emergence of distinct genetic lineages. Nevertheless, the extent and evolutionary significance of this differentiation remain uncertain and warrant further investigation through expanded geographic sampling and the incorporation of additional molecular data. Collectively, these findings provide in-depth insights into the mitogenomic architecture, comparative gene arrangements, phylogenetic patterns, and matrilineal evolutionary history of G. manipurensis and other congeners, thereby improving our understanding of the systematics and genetic diversity of this important cyprinid fish lineage. Full article

Silicone rubber is an important external insulating material for composite bushings, composite insulators, and other power equipment. During long-term service, it is inevitably exposed to coupled environmental and electrical stresses, such as elevated temperature, moisture ingress, strong electric fields, and partial discharge, which may lead to hydrophobicity loss, surface chalking, crack propagation, and particle shedding. To reveal the microscopic degradation mechanism of silicone rubber under complex operating conditions, a molecular model of methyl vinyl silicone rubber was constructed using Materials Studio. A stable silicone rubber molecular structure was obtained through crosslinking, geometry optimization, and ensemble relaxation. Subsequently, a reactive molecular dynamics simulation system under coupled temperature–humidity–electric field conditions was established using LAMMPS and the ReaxFF reactive force field. Different temperature gradients, electric field intensities, and aging–recovery stages were designed to investigate the degradation behavior of silicone rubber. The evolution of the maximum carbon content, maximum silicon content, carbon-containing decomposition products, and typical small-molecule products, including H₂, H₂O, CH₄, C₂H₂, C₂H₄, and C₂H₆, was statistically analyzed. In addition, atomic trajectory tracking was performed to clarify the processes of methyl group detachment, Si-O bond cleavage, water molecule participation, and molecular chain reconstruction. The results show that high temperature mainly promotes methyl group detachment from side chains and fracture of the siloxane main chain, while a strong electric field accelerates the decomposition process and induces the transformation of long siloxane chains into shorter chains. Water molecules can react with broken siloxane chains to form hydroxyl-containing structures, making the structural degradation partially irreversible. The degradation process of silicone rubber under coupled temperature–humidity–electric field stress can be summarized as side-chain detachment, main-chain scission, water-assisted reactions, free-radical recombination, and local molecular aggregation. This study provides a molecular-level theoretical basis for aging mechanism analysis, condition assessment, and lifetime prediction of composite external insulating materials. Full article

Synergistically optimizing electronic structure and exposing abundant active sites is a promising route to enhance electrocatalytic activity, yet remains challenging. Herein, a hierarchical tubular structure of vanadium-incorporated molybdenum phosphide (V-MoP) was successfully constructed for highly effectively alkaline hydrogen evolution. Molecular self-assembly of a V-substituted Keggin-type polyoxometalate (POM) with a simple organic ligand was exploited to induce a hollow tubular precursor and trigger precise V doping by virtue of the intrinsic structural features of POMs, thereby realizing simultaneous morphology engineering and electronic structure modulation. The unique open-ended hollow tubular structure, which furnishes both internal and external surfaces and superhydrophilicity, increases the exposure of electrochemical active sites, promotes rapid electrolyte penetration and shortens mass transfer pathways. Moreover, V doping effectively modulates the electronic structure of MoP, further renders Mo and P sites more electron-rich, meanwhile triggering the coexistence of V³⁺ and V⁵⁺, which further promotes water dissociation and hydrogen evolution. Consequently, the V-MoP catalyst exhibits significantly enhanced activity, far beyond that of pristine bulk MoP and bulk V-MoP, and even surpasses that of commercial 20% Pt/C at high current densities. This work provides a feasible strategy for designing advanced electrocatalysts with tailored morphology and tunable electronic structures. Full article

Melanoma incidence rates have also been steadily increasing, emphasizing the need for improved prognostic and diagnostic tools with the goal of enhancing patients’ outcomes. Biomarkers in melanoma have emerged as an important component of melanoma management, offering insight into disease progression, tumor biology, and the potential for judging treatment responses. Traditionally, blood and immunohistochemical markers such as lactate dehydrogenase (LDH), S100 calcium-binding protein (S100B), human melanoma black-45 (HMB-45), and SRY-box transcription factor 10 (SOX10) have been widely used in melanoma diagnosis, staging, and monitoring. However, their clinical use has been limited because of their low specificity, especially in patients with early-stage disease. This has led to the development of molecular and genetic biomarkers, including BRAF, NRAS, and KIT mutations, which improved patients’ risk stratification and enabled targeted therapies, and gene expression signature assays such as DecisionDx (Castle Biosciences) and SkylineDx (Merlin) that are already used in clinics to help with surgical decisions and to assess patients’ prognosis. Other circulating biomarkers, including microRNAs, circulating tumor DNA and circulating tumor cells, have been developed to provide minimally invasive approaches to monitor tumor evolution and detect recurrence. However, none of these new approaches are used in clinics due to their low specificity and/or sensitivity. Additionally, nomograms or predictive models have been created using biomarkers and clinicopathologic data to assess patients’ outcomes and survival. While significant progress has been made, the integration of melanoma biomarkers into routine clinical practice remains limited. This review summarizes current advancements in melanoma biomarkers, including traditional serum and immunohistochemical markers, as well as developments in molecular, genetic, circulating, and predictive biomarker approaches. Full article

Molecular dynamics simulations were conducted to investigate the thermal stability and structural evolution of Li-Mg alloys subjected to thermal cycling between 100 K and 400 K. Alloy compositions containing 0, 5, 10, and 20 at.% Mg were analyzed using a modified embedded-atom method interatomic potential. Structural characterization was performed through radial distribution functions, Polyhedral Template Matching (PTM), and mean squared displacement (MSD) calculations. The results showed that heating promoted the temporary formation of HCP, FCC, and other local atomic environments, indicating partial loss of crystalline ordering even below the melting temperature of Li. Nevertheless, the BCC structure remained dominant for all compositions, and the structural changes were reversible during cooling. Increasing Mg concentration improved the thermal stability of the alloys by reducing the formation of non-BCC atomic structures and decreasing atomic mobility during thermal cycling. In particular, the 20 at.% Mg alloy preserved more than 90% of the BCC population throughout the simulations. In addition, the energy variations between cycles remained very small, indicating stable thermodynamic behavior during heating and cooling. These findings provide atomistic insight into the temperature-dependent behavior of Li-Mg alloys that may be useful in works related to lithium-metal battery applications. Full article

Cystic fibrosis (CF) is a genetic disorder caused by dysfunction of the CFTR chloride ion channel. Progress in molecular understanding and therapy development relies on advanced cellular models and robust assays for evaluating CFTR function. This review traces the evolution of in vitro models, from primary and immortalized cell lines to patient-specific induced pluripotent stem cells (iPSCs) and complex three-dimensional systems. These advanced models, including air-liquid interface (ALI) cultures, organoids, and microfluidic organ-on-a-chip platforms, enable recapitulation of tissue architecture, cellular heterogeneity, and key pathological features such as impaired mucociliary clearance and chronic inflammation. A critical component of CF research is the accurate functional assessment of CFTR activity. We compare established high-resolution techniques (patch-clamp, Ussing chamber) with high-throughput screening assays, including fluorescence quenching of halide-sensitive YFP assay and organoid swelling tests. The article provides a framework for choosing the most appropriate CFTR functional assay tailored to specific research goals. Full article

Temperature and pressure are critical controlling parameters in the in situ conversion process (ICP) of oil shale. Clarifying the mechanisms governing organic matter pyrolysis is essential for reliably extrapolating laboratory findings to geological conditions. This review systematically summarizes the effects of temperature and pressure on shale pyrolysis and on hydrocarbon generation kinetics. Temperature is the primary factor controlling pyrolysis rates and product distribution, with an optimal temperature window enhancing shale oil yield while suppressing secondary cracking. Low heating rates favor thorough pyrolysis, although their influence on reaction pathways is generally overlooked in current kinetic models. Pressure effects are stage-dependent: during organic matter conversion, they are minor, whereas, in the product expulsion stage, high pressure inhibits hydrocarbon expulsion, prolongs residence time, and promotes secondary cracking, thereby reducing overall oil yield while increasing light fractions. Discrepancies in reported pressure effects arise from variations in experimental systems, sample forms, and medium conditions. The coupling of temperature and pressure is synergistic rather than additive. Given that current kinetic models largely neglect pressure and heating-rate effects, and that temperature–pressure coupling mechanisms remain unclear, future research should focus on thermal simulation experiments across wide ranges of pressures and heating rates, complemented by ReaxFF molecular dynamics to elucidate reaction pathways and guide kinetic model development. Further in situ experiments under high-temperature and high-pressure conditions are needed to characterize coupled pore evolution and fluid migration. Ultimately, integrated thermo-hydro-mechanical-chemical (THMC) models should be developed to capture hydrocarbon generation, retention, and expulsion, providing a robust theoretical framework for optimizing ICP technology. Full article

The chemical evolution of simple molecules into higher-order structures, such as amino acids, is a fundamental process occurring throughout the cosmos. Methane (CH₄) serves as a key precursor in this evolutionary sequence and is prevalent on planetary bodies like Mars and Saturn. In these environments, CH₄ is frequently ionized by cosmic radiation, forming the methane radical cation (CH₄⁺). In this study, the ion-molecule reactions between CH₄⁺ and neutral CH₄ (CH₄⁺ + CH₄ → products) were investigated using direct ab initio molecular dynamics (AIMD) simulations to elucidate the underlying reaction mechanisms. Our calculations demonstrate that proton transfer (PT) occurs efficiently, yielding the methanium ion (CH₅⁺) and the highly reactive methyl radical (CH₃): CH₄⁺ + CH₄ → CH₅⁺ + CH₃. Furthermore, the reaction outcomes exhibit a strong dependence on the impact parameter (b). Collisions at very low impact parameters (b = 0–0.2 Å) resulted in non-reactive, billiard-ball-like scattering. Within the range of b = 0.2–3.0 Å, the formation of a long-lived complex, [CH₅-CH₃]⁺, was observed. In the intermediate range of b = 3.0–5.0 Å, a proton-stripping mechanism predominated in PT channel, while collisions at b > 5.0 Å were exclusively non-reactive. The reaction mechanism was qualitatively discussed. These findings provide a detailed atomistic picture of the collision dynamics governing methane-derived molecular evolution in celestial environments. Full article

Aqueous zinc–iodine batteries (AZIBs) are emerging as highly promising candidates for next-generation, grid-scale energy storage due to the intrinsic safety of water-based electrolytes, the high theoretical capacity of the zinc anode, and the rapid conversion kinetics of the iodine cathode. However, the practical commercialization of AZIBs is severely impeded by formidable interfacial instabilities, including the uncontrollable growth of zinc dendrites, parasitic hydrogen evolution reactions (HER), and the notorious polyiodide (I₃⁻, I₅⁻) shuttle effect. These macroscopic degradation modes are fundamentally rooted in the robust [Zn(H₂O)₆]²⁺ primary solvation sheath and the immense thermodynamic driving force for polyiodide dissolution in highly polar aqueous media. To address these interconnected challenges, electrolyte engineering has evolved into the most potent, holistic strategy. This comprehensive review systematically evaluates the latest advancements in electrolyte engineering for AZIBs. We first deeply decipher the fundamental thermodynamic mechanisms governing Zn²⁺ desolvation and iodine multiphase conversion. Subsequently, we critically analyze cutting-edge regulation paradigms, including water-in-salt (WIS) and localized high-concentration electrolytes (LHCE), cosolvent networks, functional molecular additives, deep eutectic solvents (DES), and quasi-solid-state hydrogels. By integrating in situ/operando spectroscopic characterizations with multiscale theoretical computations (such as MD and DFT), we elucidate the structure–activity relationships at the atomic level. Finally, we provide strategic perspectives on the future trajectories of the field, emphasizing the stabilization of multi-electron (I⁻/I⁰/I⁺) halogen chemistry, AI-driven high-throughput screening, and the rigorous standardization of Ah-level pouch cell engineering for extreme-environment applications. Full article

Fibroblast activation protein (FAP) has emerged as a promising target for the development of cancer radiotheranostics due to its selective overexpression in cancer-associated fibroblasts (CAFs) within the tumor stroma. Affinity and selectivity refer to the binding affinities of FAP inhibitors toward FAP and related family members, whereas the accumulation of radiolabeled-FAP inhibitors varies by tumor type. Although monomeric FAP inhibitors (FAPIs) have shown extraordinary utility in diagnostic imaging, their clinical application in radiotherapy has been limited by short tumor retention times and heterogeneous uptake. To address these challenges, homomultimeric FAPI ligands—featuring two or more identical FAP-targeting motifs—have been developed with the aim of enhancing binding avidity and prolonging tumor residence. This review comprehensively examines the evolution of homomultimeric FAPI ligands, from molecular design and preclinical validation to early clinical implementation. We highlight how dimeric and higher-order multimeric constructs improve tumor retention and therapeutic efficacy compared to monomers, while also discussing the impact of linker chemistry, valency, and scaffold architecture on pharmacokinetics and targeting efficiency. Preclinical studies demonstrate that optimized dimers and trimers achieve superior tumor-to-background ratios and sustained tumor uptake, whereas excessive multimerization can lead to steric hindrance and reduced efficacy. Clinical data from pioneering studies using agents such as [¹⁷⁷Lu]Lu-DOTAGA.(SA.FAPi)₂ and [¹⁷⁷Lu]Lu-DOTAGA.Glu.(FAPi)₂ confirm prolonged tumor retention, encouraging therapeutic responses and a favorable safety profile in advanced cancers. However, translational challenges remain, including the need for better preclinical models that reflect stromal FAP heterogeneity, optimized radiometal–chelator pairs, and standardized dosing protocols for comparative clinical trials. Overall, homomultimeric FAPI ligands represent a significant advance in FAP-targeted theranostics, offering a robust platform for personalized cancer management. Full article

Small-molecule drug development faces high attrition rates driven by complex pharmacokinetics and unforeseen toxicities. While deep learning offers high predictive accuracy, its opaque “black-box” nature hinders mechanistic transparency, clinical trust, and regulatory approval. This review synthesizes how Interpretable Machine Learning, synergized with systems pharmacology, advances this paradigm by enhancing mechanistic transparency in drug development. By providing insights into algorithmic decisions, Interpretable Machine Learning helps researchers identify molecular features that are statistically associated with absorption, distribution, metabolism, and excretion optimization and preemptively mitigate toxicophores, while noting that these associations require experimental validation to establish genuine causality. Furthermore, integrating multi-omics data via Interpretable Machine Learning guides rational polypharmacology, bridging in silico target identification with “dry-wet loop” validations. Crucially, Interpretable Machine Learning accelerates clinical translation by discovering causal biomarkers, refining patient stratification, and generating transparent “Model Cards” to satisfy U.S. Food and Drug Administration/ European Medicines Agency regulations. We also discuss future challenges: data heterogeneity, out-of-distribution generalizability, and the evolution toward Causal Artificial Intelligence. Ultimately, the integration of Interpretable Machine Learning provides a framework for more transparent and evidence-based drug design, realizing the promise of precision medicine. Full article