Kirsten rat sarcoma viral oncogene homolog(KRAS)protein inhibitors are a promising class of thera-peutics,but research on molecules that effectively penetrate the blood-brain barrier(BBB)remains limited,which is crucial for treating central nervous system(CNS)malignancies.Although molecular generation models have recently advanced drug discovery,they often overlook the complexity of bio-logical and chemical factors,leaving room for improvement.In this study,we present a structure-constrained molecular generation workflow designed to optimize lead compounds for both drug effi-cacy and drug absorption properties.Our approach utilizes a variational autoencoder(VAE)generative model integrated with reinforcement learning for multi-objective optimization.This method specifically aims to enhance BBB permeability(BBBp)while maintaining high-affinity substructures of KRAS in-hibitors.To support this,we incorporate a specialized KRAS BBB predictor based on active learning and an affinity predictor employing comparative learning models.Additionally,we introduce two novel metrics,the knowledge-integrated reproduction score(KIRS)and the composite diversity score(CDS),to assess structural performance and biological relevance.Retrospective validation with KRAS inhibitors,AMG510 and MRTX849,demonstrates the framework's effectiveness in optimizing BBBp and highlights its potential for real-world drug development applications.This study provides a robust framework for accelerating the structural enhancement of lead compounds,advancing the drug development process across diverse targets.

Osteoporotic fractures are characterized by reduced bone mass and microstructural abnormalities, leading to differences in the healing process compared to traumatic fractures. The fracture healing process is generally divided into the inflammatory phase, the repair phase and the remodeling phase. In patients with osteoporotic fractures, due to factors such as decreased bone density, reduced bone quality and aging, there are partial alterations in inflammatory cells and osteoimmunity associated with those three healing phases, ultimately affecting fracture healing. This article focuses on the differences in fracture healing between non-osteoporotic fractures and osteoporotic fractures, reviewing relevant research literature and consensus. It analyzes and discusses changes in bone marrow mesenchymal stem cells and bone metabolism during osteoporosis, the effects of inflammatory aging, underlying diseases, and anti-osteoporosis medications on fracture healing, as well as the changes observed after pharmacological intervention. The aim is to emphasize personalized treatment approaches that account for individual and bone-specific factors in managing osteoporotic fractures, striving to promote better fracture healing outcomes and improving patients' quality of life.

Objective:To explore the genotype and the clinical phenotype of SCN2A-related developmental delay in children. Methods:A case series study was adopted. Collect clinical data from 10 cases of children with SCN2A gene variants diagnosed with global developmental delay/intellectual disability who were admitted to the Children′s Hospital between July 2019 and March 2023. Summarize the clinical phenotype and genotype based on clinical data such as general information, clinical manifestations, imaging examinations, laboratory tests, genetic testing results, and comprehensive pediatric neuropsychological development assessment. Results:A total of 10 patients were recruited, including 7 males and 3 females, with an age range of 27 days to 5 years and 9 months. 9 patients underwent children′s neuropsychological and behavioral assessments, and the results were consistent with global developmental delay, including 2 mild cases, 4 moderate cases, and 3 severe cases. 3 cases had autism spectrum disorder, and 2 cases had epilepsy. 6 patients underwent complete head MRI examination, and 4 of them showed abnormalities, including delayed myelination, widening of the local extra brain space in the frontal lobe, and abnormal frontal lobe morphology. All 10 cases had point variants. Among them, 9 cases are de novo and 1 case is maternal inheritance. Out of 10 cases, there were 5 cases with copy number variations, but all of them were of unknown significance. Among the 10 variants, 8 have been reported and 2 have not been reported, namely c.4145A>T(p.N1382I) and c.4937T>A(p.I1646N). In this study, 4 out of 10 patients with SCN2A variants had variation sites located in the S4 segment of domain which constitute Nav1.2, the sodium ion channel encoded by SCN2A. The developmental quotient level was lower when the variation sites were located in the S4 segment of domain, and the difference was statistically significant ( t=-3.101, P=0.017), indicating that the severity of developmental delay may be related to the localization of amino acids corresponding to variant sites within the protein domain. Conclusion:SCN2A mutations are strongly associated with diverse neurodevelopmental disorders. In this study, the phenotypic spectrum of SCN2A variants encompassed epilepsy, global developmental delay, and autism spectrum disorder. Affected individuals exhibited early-onset developmental delays, predominantly moderate to severe in severity. Voltage-sensing domain dysfunction in sodium channels may constitute a critical pathomechanism underlying neurodevelopmental impairments. Further electrophysiological characterization and molecular mechanistic studies are warranted todelineate the genotype-phenotype correlations between specific variant loci and clinical severity.

Objective Melatonin has been shown to have neuroprotective effects.This study is aimed at observing the effects of copper deposition on cognitive function in a toxic milk(TX)mouse model of Wilson disease(WD),and investigating the effects and mechanisms of action of Gandou Bushen Decoction(GDBSD)on melatonin synthesis and pineal function in the WD model mice.Methods A total of 30 homozygous TX mice were randomly assigned to 3 groups(n=10 in each group),including a WD group,a GDBSD group,and a dimercaptosuccinic acid(DMSA)group.A total of 10 DL mice were included in the normal control(NC)group.The structure and copper content of pineal gland tissues,oxidative stress and apoptosis-related markers,and serum melatonin levels were evaluated using hematoxylin-eosin(HE)staining,enzyme-linked immunosorbent assay(ELISA),flow cytometry,and Western blot.Results Compared with the NC group,the WD group exhibited decreased learning and cognitive abilities(P＜0.05),damaged pineal gland structure,increased copper content,reactive oxygen species(ROS)levels,and mitochondrial damage rate in the pineal gland(P＜0.01),altered levels of melatonin and oxidative stress-related markers(P＜0.05),upregulated expression levels of pro-apoptotic proteins Bax and Caspase-3,and decreased expression of the anti-apoptotic protein Bcl-2(P＜0.01).After treatment with GDBSD and DMSA,the SIRT3/FOXO3α signaling pathway was activated,the copper content in the pineal gland was reduced,and oxidative stress and apoptosis-related damages were improved,leading to an improvement in learning and memory abilities(P＜0.05).Conclusion GDBSD can alleviate cognitive impairments in WD mice caused by pineal gland copper deposition by inhibiting oxidative stress and apoptosis in the pineal gland.The underlying molecular mechanism is associated with the regulation of the SIRT3/FOXO3α signaling pathway.

Phages, as obligate bacterial and archaeal parasites, constitute a virus group of paramount ecological significance due to their exceptional abundance and genetic diversity. These biological entities serve as critical regulators in Earth's ecosystems, driving biogeochemical cycles, energy fluxes, and ecosystem services across terrestrial and marine environments. Within soil microbiomes, phages function as microbial "dark matter," maintaining the soil-plant system balance through precise modulation of the microbial community structure and functional dynamics. Despite the growing research interests in soil phages in recent years, the proportion of such studies in environmental virology remains disproportionately low, which is primarily attributed to researchers' limited familiarity with the research methodologies for phage microecology, incomplete technical frameworks, and inherent challenges posed by soil environmental complexity. To address these challenges, this review synthesizes cutting-edge methodologies for soil phage investigation from four aspects: (1) tangential flow filtration (TFF)-based phage enrichment strategies; (2) integrated quantification approaches combining double-layer agar plating, epifluorescence microscopy, and flow cytometry; (3) multi-omics analytical pipelines leveraging metagenomics and viromics datasets; and (4) computational frameworks merging machine learning algorithms with eco-evolutionary theory for deciphering phage-host interaction networks. Through comparative analysis of methodological principles, technical merits, and application scopes, we establish a comprehensive workflow for soil phage research. Future research in this field should prioritize: (1) construction of soil phage resource libraries, (2) exploration of RNA phages based on transcriptomes, (3) functional characterization of unknown genes, and (4) deep integration and interaction validation of multi-omics data. This systematic methodological synthesis provides critical technical references for addressing fundamental challenges in characterizing soil phages regarding the community structure, functional potential, and interaction mechanisms with hosts.
Bacteriophages/physiology* ; Soil Microbiology ; Ecosystem ; Microbiota ; Metagenomics/methods*

Background: Autoimmune mechanisms have important roles in the pathogenesis of alopecia areata (AA). Objective: This study aimed to evaluate the exact biological and clinical importance of immunogenes in AA patients using bioinformatic methods. Methods: Five AA scalp gene expression profiles were obtained from the Gene Expression Omnibus database. Differentially-expressed genes (DEGs) between AA and control groups were identified. An immune-related gene diagnostic signature (IRGDS) was established by protein-protein interaction network analysis, least absolute shrinkage and selection operator and logistic regression analysis. Results: A total of 102 immune-related DEGs were identified. We developed an IRGDS composed of CD8A, CSF1R and CXCL10 for AA molecular pathological assessment and diagnosis (area under the receiver operating characteristic curve [AUC]=0.962). We also validated the diagnostic value of the IRGDS in an external cohort (AUC=0.955). Patients with high IRGDS scores presented with a higher abundance of immune cell infiltration and expression of genes associated with immune recruitment and immune activation, suggesting adverse biological alterations. Conclusion In our study, an IRGDS model with accurately diagnostic capacity for AA was established, and biological alterations were deciphered in AA. The IRGDS may be used as an auxiliary diagnostic marker for AA.

Alzheimer's disease is a neurodegenerative disorder characterized by complex and not fully understood pathogenesis.Recent research has revealed that abnormalities in lipid metabolism and inflammatory responses play a crucial role in the development and progression of Alzheimer's disease.This review aims to explore the modulatory effects of lipid metabolism on inflammatory responses and their subsequent influence on the pathological processes of Alzheimer's disease from the aspects of the relationship between dysregulated lipid metabolism,increased inflammatory responses,and Alzheimer's disease,the regulatory effects of lipid mediators,and the role of microglia in these processes.

Cuproptosis, a recently identified form of regulated cell death triggered by excess intracellular copper, has emerged as a promising cytotoxic strategy for cancer therapy. However, the therapeutic efficacy of copper ionophores such as elesclomol (ES) is often hindered by cellular copper homeostasis mechanisms that limit copper influx and cuproptosis induction. To address this challenge, we developed a nanoagent utilizing outer membrane vesicle (OMV) derived from Akkermansia muciniphila (Akk) for co-delivery of antioxidant 1 copper chaperone (Atox1)-targeting siRNA and ES (siAtox1/ES@OMV) to tumors. In vitro, we demonstrated that Atox1 knockdown via siRNA significantly disrupted copper export mechanisms, resulting in elevated intracellular copper levels. Simultaneously, ES facilitated efficient copper influx and mitochondrial transport, leading to Fe-S cluster depletion, increased proteotoxic stress, and robust cuproptosis. In vivo, siAtox1/ES@OMV achieved targeted tumor delivery and induced pronounced cuproptosis. Furthermore, leveraging the immunomodulatory properties of OMVs, siAtox1/ES@OMV promoted T-cell infiltration and the activation of tumor-reactive cytotoxic T cells, enhancing tumor immune responses. The combination of siAtox1/ES-induced cuproptosis and immunogenic cell death synergistically suppressed tumor growth in both subcutaneous breast cancer and orthotopic rectal cancer mouse models. This study highlights the potential of integrating copper homeostasis disruption with a copper ionophore using an immunomodulatory OMV-based vector, offering a promising combinatorial strategy for cancer therapy.

Kirsten rat sarcoma viral oncogene homolog (KRAS) protein inhibitors are a promising class of therapeutics, but research on molecules that effectively penetrate the blood-brain barrier (BBB) remains limited, which is crucial for treating central nervous system (CNS) malignancies. Although molecular generation models have recently advanced drug discovery, they often overlook the complexity of biological and chemical factors, leaving room for improvement. In this study, we present a structure-constrained molecular generation workflow designed to optimize lead compounds for both drug efficacy and drug absorption properties. Our approach utilizes a variational autoencoder (VAE) generative model integrated with reinforcement learning for multi-objective optimization. This method specifically aims to enhance BBB permeability (BBBp) while maintaining high-affinity substructures of KRAS inhibitors. To support this, we incorporate a specialized KRAS BBB predictor based on active learning and an affinity predictor employing comparative learning models. Additionally, we introduce two novel metrics, the knowledge-integrated reproduction score (KIRS) and the composite diversity score (CDS), to assess structural performance and biological relevance. Retrospective validation with KRAS inhibitors, AMG510 and MRTX849, demonstrates the framework's effectiveness in optimizing BBBp and highlights its potential for real-world drug development applications. This study provides a robust framework for accelerating the structural enhancement of lead compounds, advancing the drug development process across diverse targets.