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.

Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

Intraflagellar transport (IFT) is a core mechanism for ciliary assembly, length maintenance, ciliary proteome homeostasis and signal transduction. Most proteins required for ciliary structure and function are synthesized in the cytoplasm. Because the ciliary compartment is separated from the cell body by the selective barrier of the transition zone, these proteins cannot freely equilibrate between the cytoplasm and the cilium. Consequently, axonemal components, membrane proteins and signaling molecules must be actively imported into cilia, retrieved from the ciliary compartment, and recycled or degraded through highly ordered transport and sorting pathways. The IFT system is mainly composed of the IFT-A complex, IFT-B complex, kinesin-2, dynein-2 and the Bardet-Biedl syndrome protein complex (BBSome). Through coordinated anterograde and retrograde transport, these modules mediate the dynamic trafficking of different classes of ciliary cargoes. Anterograde transport delivers structural and membrane-associated components from the ciliary base toward the ciliary tip, whereas retrograde transport retrieves IFT components and selected cargoes back toward the ciliary base and cytoplasm. In this way, IFT not only supports the construction of the axoneme but also contributes to the maintenance of ciliary composition and the regulation of ciliary signaling activity. In recent years, advances in cryo-electron microscopy, in situ cryo-electron tomography and single-molecule imaging have greatly improved our understanding of the molecular mechanisms underlying IFT. These approaches have revealed how IFT trains are assembled at the ciliary base, how they move along axonemal microtubule tracks, how they undergo directional switching at the ciliary tip, and how cargoes are retrieved and recycled. Among the IFT modules, IFT-B acts as the major scaffold of IFT trains. It participates in cargo loading, motor coupling and initiation of anterograde transport. IFT-A is involved in retrograde transport, membrane protein adaptor function and train remodeling. The BBSome, through reversible association with the IFT system, regulates ciliary membrane protein sorting, signaling receptor clearance and renewal of the ciliary proteome. These functions indicate that the IFT machinery is not a simple linear transport pathway, but rather a dynamic and reconfigurable transport system. The conversion of transport direction is a key step in the IFT cycle. This process is closely associated with disassembly of anterograde trains, dissociation of kinesin-2, activation of dynein-2 at the ciliary tip and reassembly of retrograde trains. In terms of pathogenic mechanisms, IFT abnormalities may cause ciliopathies through four major pathways: defects in ciliary assembly and structure, abnormal localization of ciliary cargoes, dysregulation of signaling pathways, and impaired cargo unloading and retrieval. These defects can affect multiple organ systems, including the retina, kidney, skeleton, respiratory tract, reproductive system, and neuro-metabolic system. Current therapeutic strategies are still mainly based on symptomatic support and maintenance of organ function. Overall, IFT is a dynamic transport system jointly regulated by axonemal structure, motor activity, cargo selection and cellular signaling. It links ciliary architecture with protein turnover and signaling regulation, thereby playing a fundamental role in both ciliary homeostasis and ciliopathy pathogenesis. Further elucidation of IFT regulatory mechanisms and their relationships with disease phenotypes will help promote mechanism-based classification, genetic diagnosis and precision intervention for ciliopathies.

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.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

For HCQ retinopathy with CME, acupuncture combined with periocular injection can be used to improve the CME and protect the central vision. Subsequent research endeavors involving a more extensive cohort and extended observation periods are warranted to evaluate the effectiveness and safety profile of the intervention.
Humans ; Macular Edema/drug therapy* ; Acupuncture Therapy/methods* ; Hydroxychloroquine/therapeutic use* ; Female ; Retinal Diseases/chemically induced* ; Middle Aged ; Combined Modality Therapy ; Male