Spermatogenesis is a highly ordered and spatiotemporally regulated developmental process in the male reproductive system, during which spermatogonial stem cells (SSCs), supported by the seminiferous tubule microenvironment, sequentially undergo mitosis, meiosis, and spermiogenesis to ultimately generate structurally intact spermatozoa. This complex process is accompanied by extensive transcriptional reprogramming, chromatin remodeling, and finely tuned post-transcriptional regulation. Precise control of RNA fate is therefore essential for maintaining the continuity and fidelity of spermatogenesis, and its disruption represents a major molecular basis of male infertility. N⁶-methyladenosine (m⁶A), the most abundant internal RNA modification in eukaryotes, has emerged as a critical regulator of post-transcriptional gene expression. m⁶A methyltransferases (“writers”) catalyze the addition of a methyl group to the N⁶ position of adenosine, m⁶A demethylases (“erasers”) remove the modification, and m⁶A-binding proteins (“readers”) recognize m⁶A-modified transcripts. Through the coordinated actions of these factors, m⁶A regulates transcript fate at multiple levels, including RNA splicing, nuclear export, stability, translation, and decay. Emerging evidence indicates that m⁶A-mediated regulation is essential across multiple stages of spermatogenesis, including SSC self-renewal and differentiation, meiotic progression, maintenance of chromosomal stability, and sperm morphogenesis. Beyond its intrinsic functions in germ cells, m⁶A also contributes to the regulation of the testicular microenvironment. In sertoli cells, m⁶A is involved in maintaining blood-testis barrier integrity, RNA processing, and paracrine signaling, thereby providing structural and metabolic support for germ cell development. In Leydig cells, m⁶A regulates steroidogenesis, particularly testosterone synthesis, and participates in cellular stress responses and metabolic homeostasis. Through these mechanisms, m⁶A indirectly influences spermatogenesis by modulating the functional state of testicular somatic cells, highlighting an integrated regulatory mode that combines cell-intrinsic and microenvironment-mediated effects. Notably, distinct classes of m⁶A regulators exhibit pronounced stage-specific functions and coordinated division of labor, collectively forming a multilayered and dynamic regulatory network. Writers often display dosage- and temporal window-dependent effects; erasers contribute to stage-specific demethylation and functional compensation; while readers function through a “switch-buffer” dual-layer architecture, and RNA-binding proteins (RBPs) participate in substrate selection and post-transcriptional regulation. Importantly, emerging evidence suggests that some m⁶A-related proteins can function through noncanonical mechanisms independent of m⁶A recognition, such as intrinsic RNA-binding activity, helicase function, or ribonucleoprotein complex assembly, thereby expanding the functional landscape of the m⁶A regulatory system. Dysregulation of m⁶A machinery can lead to multiple spermatogenic defects, including impaired SSC self-renewal, meiotic arrest, abnormal chromatin remodeling, and defective sperm formation, ultimately resulting in male infertility. Despite substantial advances, several critical questions remain unresolved, including the distinction between m⁶A-dependent and -independent mechanisms, the spatiotemporal dynamics of m⁶A modifications at single-cell resolution, and the coordination and antagonism among different regulatory factors. In this review, we systematically summarize the dual regulation of spermatogenesis by germ cell-intrinsic mechanisms and the testicular microenvironment, and delineate the molecular mechanisms and stage-specific functions of the dynamic m⁶A regulatory network. We further discuss the current limitations in the field and propose feasible experimental strategies for future investigation. Collectively, this work aims to provide a comprehensive framework for understanding the epitranscriptomic regulation of spermatogenesis and to offer theoretical insights into the pathogenesis and clinical management of male infertility.

Spermatogenesis is a highly ordered and spatiotemporally regulated developmental process in the male reproductive system, during which spermatogonial stem cells (SSCs), supported by the seminiferous tubule microenvironment, sequentially undergo mitosis, meiosis, and spermiogenesis to ultimately generate structurally intact spermatozoa. This complex process is accompanied by extensive transcriptional reprogramming, chromatin remodeling, and finely tuned post-transcriptional regulation. Precise control of RNA fate is therefore essential for maintaining the continuity and fidelity of spermatogenesis, and its disruption represents a major molecular basis of male infertility. N⁶-methyladenosine (m⁶A), the most abundant internal RNA modification in eukaryotes, has emerged as a critical regulator of post-transcriptional gene expression. m⁶A methyltransferases (“writers”) catalyze the addition of a methyl group to the N⁶ position of adenosine, m⁶A demethylases (“erasers”) remove the modification, and m⁶A-binding proteins (“readers”) recognize m⁶A-modified transcripts. Through the coordinated actions of these factors, m⁶A regulates transcript fate at multiple levels, including RNA splicing, nuclear export, stability, translation, and decay. Emerging evidence indicates that m⁶A-mediated regulation is essential across multiple stages of spermatogenesis, including SSC self-renewal and differentiation, meiotic progression, maintenance of chromosomal stability, and sperm morphogenesis. Beyond its intrinsic functions in germ cells, m⁶A also contributes to the regulation of the testicular microenvironment. In sertoli cells, m⁶A is involved in maintaining blood-testis barrier integrity, RNA processing, and paracrine signaling, thereby providing structural and metabolic support for germ cell development. In Leydig cells, m⁶A regulates steroidogenesis, particularly testosterone synthesis, and participates in cellular stress responses and metabolic homeostasis. Through these mechanisms, m⁶A indirectly influences spermatogenesis by modulating the functional state of testicular somatic cells, highlighting an integrated regulatory mode that combines cell-intrinsic and microenvironment-mediated effects. Notably, distinct classes of m⁶A regulators exhibit pronounced stage-specific functions and coordinated division of labor, collectively forming a multilayered and dynamic regulatory network. Writers often display dosage- and temporal window-dependent effects; erasers contribute to stage-specific demethylation and functional compensation; while readers function through a “switch-buffer” dual-layer architecture, and RNA-binding proteins (RBPs) participate in substrate selection and post-transcriptional regulation. Importantly, emerging evidence suggests that some m⁶A-related proteins can function through noncanonical mechanisms independent of m⁶A recognition, such as intrinsic RNA-binding activity, helicase function, or ribonucleoprotein complex assembly, thereby expanding the functional landscape of the m⁶A regulatory system. Dysregulation of m⁶A machinery can lead to multiple spermatogenic defects, including impaired SSC self-renewal, meiotic arrest, abnormal chromatin remodeling, and defective sperm formation, ultimately resulting in male infertility. Despite substantial advances, several critical questions remain unresolved, including the distinction between m⁶A-dependent and -independent mechanisms, the spatiotemporal dynamics of m⁶A modifications at single-cell resolution, and the coordination and antagonism among different regulatory factors. In this review, we systematically summarize the dual regulation of spermatogenesis by germ cell-intrinsic mechanisms and the testicular microenvironment, and delineate the molecular mechanisms and stage-specific functions of the dynamic m⁶A regulatory network. We further discuss the current limitations in the field and propose feasible experimental strategies for future investigation. Collectively, this work aims to provide a comprehensive framework for understanding the epitranscriptomic regulation of spermatogenesis and to offer theoretical insights into the pathogenesis and clinical management of male infertility.

Prostate cancer is one of the most common tumor, with the disease progressing from inert to aggressive tumors, and rapidly progressing to castration-resistant prostate cancer. Early-stage prostate cancer is usually asymptomatic. And by the time that symptoms appear, the disease has progressed to an incurable stage. Therefore, early diagnosis and treatment is especially important to control prostate cancer, which prolongs the survival period of patients. Digital rectal examination and prostate-specific antigen have been widely used in the diagnosis of prostate cancer. However, there are certain limitations that lead to overdiagnosis and overtreatment. Although prostate needle biopsy is still the gold standard for diagnosing prostate cancer, with the wide application of multiparametric magnetic resonance examination and PSMA-PET/CT and other technologies in recent years, as well as the emergence of new biomarkers with higher sensitivity and specificity, its status as the gold standard has been challenged. And the diagnostic mode of prostate cancer has also undergone great changes. On this basis, the radical prostatectomy without prostate needle biopsy has been attempted clinically to treat prostate cancer, which gains the good clinical results. This article provides a review of the latest research advances in early screening and diagnostic models for prostate cancer.
Humans ; Male ; Benzhydryl Compounds/adverse effects* ; Drugs, Chinese Herbal/therapeutic use* ; Infertility, Male/chemically induced* ; Medicine, Chinese Traditional ; Phenols/adverse effects* ; Testis/drug effects* ; Bisphenol A Compounds

OBJECTIVES: To explore the underlying pharmacological mechanisms and its potential effects of Chinese medicine herbal formula Sini Powder (SNP) on hepatocellular carcinoma (HCC). METHODS: The active components of SNP and their in vivo distribution were identified using ultraperformance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Construction of component-target-disease networks, protein-protein interaction network, Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and molecular docking were employed to analyze the active components and anti-HCC mechanisms of SNP. Cell viability assay and wound healing assay were utilized to confirm the effect of SNP-containing serum (2.5%, 5.0%, 10%, 20%, and 40%), isoprenaline or propranolol (both 10, 100, and 1,000 µ mol/L) on proliferation and migration of HepG 2 or Huh7 cells. Meanwhile, the effect of isoprenaline or propranolol on the β 2 adrenergic receptor (ADRB2) mRNA expression on HepG2 cells were measured by real-time quantitative reverse transcription (RT-qPCR). Mice with subcutaneous tumors were either subjected to chronic restraint stress (CRS) followed by SNP administration (364 mg/mL) or directly treated with SNP (364 mg/mL). These two parallel experiments were performed to validate the effects of SNP on stress responses. Stress-related proteins and hormones were quantified using RT-qPCR, enzyme-linked immunosorbent assay, and immunohistochemistry. Metagenomic sequencing was performed to confirm the influence of SNP on the gut microbiota in the tumor-bearing CRS mice. RESULTS: The distribution of the 12 active components of SNP was confirmed in various tissues and feces. Network pharmacology analysis confirmed the anti-HCC effects of the 5 active components. The potential anti-HCC mechanisms of SNP may involve the epidermal growth factor receptor (EGFR), proto-oncogene tyrosine-protein kinase Src (SRC) and signal transducer and activator of transcription 3 (STAT3) pathways. SNP-containing serum inhibited the proliferation of HepG2 and Huh7 cells at concentrations of 2.5% and 5.0%, respectively, after 24 h of treatment. Furthermore, SNP suppressed tumor progression in tumor-bearing mice exposed to CRS. SNP treatment also downregulated the expressions of stress-related proteins and pro-inflammatory cytokines, primarily by modulating the gut microbiota. Specifically, the abundance of Alistipes and Prevotella, which belong to the phylum Bacteroidetes, increased in the SNP-treated group, whereas Lachnospira, in the phylum Firmicutes, decreased. CONCLUSION SNP can combat HCC by alleviating stress responses through the regulation of gut microbiota.
Animals ; Gastrointestinal Microbiome/drug effects* ; Liver Neoplasms/microbiology* ; Carcinoma, Hepatocellular/microbiology* ; Humans ; Drugs, Chinese Herbal/therapeutic use* ; Powders ; Cell Proliferation/drug effects* ; Mice ; Molecular Docking Simulation ; Cell Line, Tumor ; Hep G2 Cells ; Receptors, Adrenergic, beta-2/genetics* ; Stress, Physiological/drug effects* ; Cell Movement/drug effects* ; Male ; Protein Interaction Maps/drug effects* ; Cell Survival/drug effects* ; Proto-Oncogene Mas

Objective To study the medication law of Professor Wang Zhongyi in the treatment of tic disorder(TD)based on data mining technology.Methods From January 1,2022 to December 31,2023,the cases treated for TD in Professor Wang Zhongyi's outpatient clinic,which participated in the real-world study were collected.A comprehensive database has been established,screening information related to effective case diagnosis and treatment.Utilizing Excel 2021,R 4.4.2,Origin 2024 and Cytoscape 3.9.1,this study conducted medication frequency analysis,property-flavor-meridian tropism analysis,efficacy analysis,association rule analysis,clustering analysis and co-occurrence network analysis to summarize medication law.Results Totally 640 effective prescriptions were included,involving 208 kinds of Chinese materia medica.The properties were mainly warm,cold,and neutral.The flavors were mainly pungent,bitter and sweet.The meridians were mainly liver meridians.The therapeutic categories were primarily composed of liver-calming and endogenous wind-stopping drugs,along with exterior-resolving prescriptions.Correlation analysis obtained 17 strongly correlated rules.Clustering analysis obtained 5 types of medicinal combinations.The therapeutic categories were primarily composed of liver-calming and endogenous wind-stopping drugs,along with exterior-resolving prescriptions.Conclusion According to the comprehensive statistical analysis,Uncariae Ramulus cum Uncis,Gastrodiae Rhizoma,Haliotidos Concha,Paeoniae Radix alba,Bupleuri Radix,Puerariae Lobatue Radix and Scorpio are the core drugs used by Professor Wang Zhongyi to treat TD.Professor Wang Zhongyi believes that the core pathogenesis of TD is the internal movement of liver wind,and the treatment mainly focuses on calming the liver,calming the wind and stopping spasms,while also nourishing the heart,calming the mind,harmonizing blood and relieving qi.Based on different clinical symptoms of TD,modifications and adjustments are made to the core prescription to treat children with TD.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To evaluate the clinical efficacy, safety and treatment persistence of upadacitinib in Crohn's disease (CD) patients.Methods:The single-center retrospective cohort study was conducted. The patients with moderate-to-severe active CD initiating upadacitinib therapy from November 2023 to November 2024 in Nanjing Drum Tower Hospital were collected through searching the electronic medical records and paper-based patient databases. The primary outcome was the clinical remission rate at week 12. Secondary outcomes included the clinical response rate at week 12; clinical response and remission rates at weeks 4, 24 and 48; biomarker (fecal calprotectin or C-reactive protein) remission rates at all time points; as well as endoscopic remission and response rates, treatment persistence and safety evaluation.Results:A total of 44 CD patients were included, comprising 24 males (54.5%) and 20 females (45.5%). The median age was 33 (25, 40) years. The baseline Crohn's disease activity index (CDAI) score was 260.5 (225.9, 550.0) points. Patients had previously received a median of 2 (1, 2) biologic treatments. All 44 patients completed the 12-week induction therapy. With a median follow-up of 30.00 (16.25, 46.25) weeks, the clinical remission rate was 50.0% (22/44) at week 12. The clinical remission rate, clinical response rate, and biomarker remission rate were 52.3% (23/44), 88.6% (39/44) and 72.7% (32/44) respectively at week 4, and the clinical response rate and biomarker remission rate were 88.6% (39/44) and 77.2% (34/44) respectively at week 12. The clinical remission rates, clinical response rates and biomarker remission rates evolved to 43.3% (13/30), 86.7% (26/30) and 80.0% (24/30) at week 24, and further to 44.4% (4/9), 77.8% (7/9) and 77.8% (7/9) at week 48. During the follow-up period, 13 CD patients completing endoscopic evaluation, endoscopic remission and response rates were 30.8% and 23.1% respectively. CD-related surgery rate was 4.5% (2/44). Safety analysis demonstrated that the overall adverse events rate was 56.8% (25/44) including 7 patients with serious adverse events. A total of 8 patients discontinued treatment, among which 3 were due to primary loss of response, 1 due to secondary loss of response, 2 due to drug-related adverse events alone, and 2 due to concurrent primary loss of response and adverse events. The Kaplan-Meier curve for treatment persistence showed that among 39 CD patients who achieved clinical response at week 12, the continued treatment rates were 90.3% at week 12 and 85.3% at week 24 of follow-up. Two patients (5.6%) received dose escalation of upadacitinib, both of whom achieved clinical remission.Conclusion:Real-world research data demonstrate that upadacitinib exhibits significant clinical efficacy and a favorable safety profile in the treatment of moderate-to-severe active CD patients with prior biologic exposure, and no new unexpected adverse events are identified.

Objective To study the medication law of Professor Wang Zhongyi in the treatment of tic disorder(TD)based on data mining technology.Methods From January 1,2022 to December 31,2023,the cases treated for TD in Professor Wang Zhongyi's outpatient clinic,which participated in the real-world study were collected.A comprehensive database has been established,screening information related to effective case diagnosis and treatment.Utilizing Excel 2021,R 4.4.2,Origin 2024 and Cytoscape 3.9.1,this study conducted medication frequency analysis,property-flavor-meridian tropism analysis,efficacy analysis,association rule analysis,clustering analysis and co-occurrence network analysis to summarize medication law.Results Totally 640 effective prescriptions were included,involving 208 kinds of Chinese materia medica.The properties were mainly warm,cold,and neutral.The flavors were mainly pungent,bitter and sweet.The meridians were mainly liver meridians.The therapeutic categories were primarily composed of liver-calming and endogenous wind-stopping drugs,along with exterior-resolving prescriptions.Correlation analysis obtained 17 strongly correlated rules.Clustering analysis obtained 5 types of medicinal combinations.The therapeutic categories were primarily composed of liver-calming and endogenous wind-stopping drugs,along with exterior-resolving prescriptions.Conclusion According to the comprehensive statistical analysis,Uncariae Ramulus cum Uncis,Gastrodiae Rhizoma,Haliotidos Concha,Paeoniae Radix alba,Bupleuri Radix,Puerariae Lobatue Radix and Scorpio are the core drugs used by Professor Wang Zhongyi to treat TD.Professor Wang Zhongyi believes that the core pathogenesis of TD is the internal movement of liver wind,and the treatment mainly focuses on calming the liver,calming the wind and stopping spasms,while also nourishing the heart,calming the mind,harmonizing blood and relieving qi.Based on different clinical symptoms of TD,modifications and adjustments are made to the core prescription to treat children with TD.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.