Background Gestational weight gain is closely related to maternal and infant health outcomes. Pregnant women are simultaneously exposed to four metals—lithium (Li), vanadium (V), uranium (U), and bismuth (Bi)—through inhalation of fine particulate matter and consumption of contaminated food and water. Existing studies suggest that exposure to these metals may be associated with gestational weight gain. However, no study has yet explored the complex relationships between exposure to mixtures of these four metals and weight gain at different stages of pregnancy. Objective To investigate the associations between mixed exposure to Li, V, U, and Bi in early pregnancy and the average weekly gestational weight gain during both early pregnancy and mid-to-late pregnancy. Methods This prospective study recruited eligible women in early pregnancy from an obstetrics clinic of a tertiary hospital in Jinan, China, between September 2021 and July 2023. Pre-pregnancy weight, current weight (at 11⁺⁰ to 13⁺⁶ weeks of gestation), and spot urine samples (≥5.0 mL) were collected at enrollment. Urinary concentrations of Li, V, Bi, and U were determined using inductively coupled plasma mass spectrometry. Participants were followed up in late pregnancy (≥28 weeks of gestation) to collect information on physical activity via questionnaire; weight measurements at the last antenatal visit (35⁺⁰ to 37⁺⁶ weeks of gestation) were obtained from the hospital information system. After adjusting for covariates, multiple linear regression and generalized additive models were used to assess the associations of individual metals with weekly weight gain in early pregnancy and in mid-to-late pregnancy. Bayesian kernel machine regression (BKMR) and quantile-based g-computation (Qgcomp) were applied to evaluate the joint effects of the metal mixture exposure on weekly weight gain at the two gestational stages. Results A total of 313 pregnant women were included. The geometric means of urinary Li, V, U, and Bi concentrations were 37.07, 0.20, 0.06, and 0.04 μg·L⁻¹, respectively; after creatinine adjustment, the corresponding values were 46.82, 0.25, 0.07, and 0.05 μg·g⁻¹ (Cr). The mean weekly gestational weight gain was (0.19±0.25) kg in early pregnancy and (0.53 ± 0.18) kg in mid-to-late pregnancy. Both multiple linear regression and generalized additive models showed that urinary V concentration was positively associated with average weekly gestational weight gain in early pregnancy, while no significant associations were found for other metals or for gestational weight gain in mid-to-late pregnancy. In the BKMR model with early-pregnancy weight gain as the outcome, V had the strongest association [posterior inclusion probability (PIP)=0.773]. When other metals were fixed at their medians, V showed a positive non-linear association with the outcome. A significant single-metal effect of V and its interaction with Li were observed. Compared with the 50th percentile of the metal mixture, the average weekly weight gain in early pregnancy increased by 0.016 (95%CI: 0.003, 0.029) and 0.018 (95%CI: 0.001, 0.036) at the 60th and 65th percentiles, respectively; conversely, at the 25th percentile, it decreased by 0.026 (95%CI: 0.002, 0.050). Overall, the joint effect of the metal mixture on early- pregnancy weight gain showed an upward trend. In the BKMR model for mid-to-late pregnancy gestational weight gain, all PIPs were<0.5, and no significant single-metal effects, interactions, or joint effects were identified. Qgcomp results confirmed a positive association between the metal mixture and early-pregnancy weight gain (b=0.031, 95%CI: 0.010, 0.051; P<0.01), with V contributing the highest positive weight (0.71). No significant association was found for weight gain in mid-to-late pregnancy (b=0.007, P=0.339). Conclusion Higher levels of co-exposure to the Li, V, Bi, and U metal mixture during early pregnancy may be associated with increased average weekly weight gain in early pregnancy. Among these metals, V exhibits a predominant role and appears to interact with Li. No association is observed between early-pregnancy metal mixture exposure and average weekly gestational weight gain in mid-to-late pregnancy. These findings suggest that monitoring and managing metal exposure during early pregnancy may be crucial for the rational regulation of gestational weight gain.

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.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Objective:To explore the efficacy of intensive repetitive transcranial magnetic stimulation (irTMS) in treatment-resistant depression (TRD) and its impact on cognitive function and systemic immune-inflammation index (SII).Methods:Forty-eight TRD patients were divided into observation group and control group using random number table method, with 24 patients in each group. The observation group was treated with irTMS, and the stimulation site was the left dorsolateral prefrontal lobe. The stimulation intensity was 110% of the motor threshold, and the stimulation frequency was 15 Hz. The stimulation interval was 26 s, and 3 000 pulses were stimulated each time. Stimulating 5 times per day, with an interval of 50 min, and continuous treatment for 5 days. The total stimulation amount for 5 days was 75 000 pulses. The control group was treated with pseudo stimulation. Before treatment (T0), 5 days after treatment (T1), and 1 month after treatment (T2), 17-item Hamilton depression scale (HAMD-17) was used to assess depressive mood. Evaluating cognitive function using the Wisconsin card sorting test.A fully automated blood cell analyzer was used to detect platelet count (PLT), neutrophil count (NC), and lymphocyte count (LC), calculate the systemic immune inflammation index (SII), SII=PLT × NC/LC. Statistical analysis was conducted using SPSS 20.0 software. The comparison between two sets of repeated measurement data was performed using repeated measurement analysis of variance.Simple effect analysis was performed if the interaction effect was significant.Pearson analysis was used for correlation testing.Results:The interaction effect between the time and group of HAMD-17 scores was significant ( F=121.784, P<0.05). The results of simple effects analysis showed that the HAMD-17 scores of the observation group at T1 and T2 ((12.07±4.08) and (14.78±4.99), respectively) were lower than those of the control group ((23.78±5.87) and (24.67±7.00), P<0.05). The treatment response rate and remission rate of the observation group at T1 were higher than those of the control group ( χ2=4.090, 7.378, both P<0.05).The treatment response rate and remission rate of the observation group at T2 were higher than those of the control group ( χ2=4.463, 4.547, both P<0.05). The time and group interaction effects of the percentage of correct response and conceptualization level in the Wisconsin card sorting test were significant ( F=30.087, 20.004, P<0.05). The results of simple effects analysis showed that the percentage of correct response and conceptualization level in the observation group at T1 and T2 were higher than those in the control group (all P<0.05). The time and group interaction effect of SII was significant ( F=8.173, P<0.05). The results of simple effects analysis showed that there was no statistically significant difference in SII between the two groups at T0 ( P>0.05). The SII at T1 and T2 in the observation group was lower than that in the control group ( P<0.05). In the observation group, the changes in SII from T2 to T0 was positively correlated with the change in HAMD-17 scores ( r=0.527, P<0.05), and negatively correlated with the percentage of correct responses to the Wisconsin card sorting test ( r=-0.412, P<0.05) and the percentage of conceptualization level ( r=-0.411, P<0.05). Conclusion:irTMS is effective in treating TRD and can improve patients' cognitive function and immune inflammation damage.

Objective:To analysis the influenced factors of readmission in hospital among patients with mood disorder,construct predictive models and compare the predictive performance of the models.Methods:The electron-ic medical record data of patients with mood disorder admitted to Beijing Anding Hospital from January 2010 to De-cember 2018 were retrospectively collected.Utilizing stepwise logistic regression to analyze the related factors of re-admission in patients with mood disorder.Logistic regression,support vector machine,random forest,extreme gradi-ent boosting(XGBoost)algorithms and convolutional neural networks(CNN)were used to construct a readmission prediction model and compare the predictive performances of the different models by using the accuracy,precision,recall,et.al.Results:A total of 6 234 patients with mood disorder were enrolled,24.9％(n=1 549)patients were readmitted after discharge.The stepwise logistic regression results revealed that readmissions were more likely to occur in patients with mood disorder who were female,had comorbidities,had a treatment outcome of cure,were treated with MECT and were on second-generation antipsychotics(OR=1.26,1.68,1.26,1.35,1.18).The CNN model demonstrated the highest accuracy,precision,and F1 scores,all at 0.87,with a recall of 0.86.The random forest achieved a recall of 0.86 and an AUC of 0.95.Conclusion:Readmission of patients with mood disorder is influenced by a multitude of factors.The convolutional neural networks and random forest models outperform other models in prediction.

Objective:To explore the optimization potential of clinical target volume (CTV) delineation proposed in the guidelines of the Oncology Group (RTOG), the Francophone Group of Urological Radiotherapy (GFRU), and the European Society for Radiotherapy and Oncology (ESTRO) based on prostate bed local occurrence patterns after radical prostatectomy identified using prostate-specific membrane antigen positron emission tomography (PSMA PET).Methods:A retrospective analysis was conducted on patients with local prostate bed recurrence after radical prostatectomy who underwent PSMA PET at the Department of Nuclear Medicine, Peking University First Hospital from September 2021 to February 2024. The central point of each recurrence was marked. A six-zone method was established based on prostate bed anatomy and the characteristics of cross-sectional imaging. Then, the positional relationships (within or outside) were recorded with respect to recurrences and CTV defined by the RTOG, GFRU, and ESTRO (CTV RTOG, CTV GFRU, and CTV ESTRO), followed the analysis of the recurrence rates and distribution characteristics of various zones. Results:A total of 63 patients with prostate bed recurrence after radical prostatectomy were enrolled in this study, including 97 recurrences. The recurrence rates in the six zones were as follows: 10% of zone 1, 22% of zone 2, 29% of zone 3, 2% of zone 4, 12% of zone 5a, 18% of zone 5b, and 7% of zone 6. Among these zones, zones 2 and 3 showed the highest and second-highest recurrence rates, respectively. CTV GFRU and CTV ESTRO completely covered zones 2 and 3, while CTV RTOG covered zone 2 completely and zone 3 partially. Zone 4, characterized by a low recurrence rate, was not covered by CTV GFRU and CTV ESTRO but was entirely covered by CTV RTOG. Zone 5a, with a recurrence rate of 12%, was completely covered by CTV RTOG but was partially covered by CTV GFRU and CTV ESTRO. The range of 1.3 cm in front of the posterior wall of the bladder covered all recurrences in zone 5a. Conclusions:For CTV delineation of the prostate cancer surgical bed, zone 4, the anterior half of the bladder above the pubic symphysis midpoint, should be contracted due to the low recurrence rate in this zone. In contrast, the anterior boundary above the pubic symphysis midpoint should extend to 1.3 cm in front of the posterior wall of the bladder to completely cover the recurrence zones.

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 develop and validate a nomogram prediction model for residual stone risk after flexible ureteroscopic lithotripsy(FURL)in patients with 2-3 cm renal calculi,so as to provide reference for treatment options.Methods Clinical data of 342 patients with renal calculi measuring 2-3 cm undergoing FURL in our hospital during Jun.2017 and Apr.2024 were retrospectively collected.At a 3∶1 randomization ratio,patients were allocated to the training cohort(n=257)and validation cohort(n=85).Patients in the training cohort were stratified into two subgroups based on postoperative stone-free status:residual stone group(n=63)and stone-free group(n=194).Logistic regression analysis was employed to identify factors influencing stone retention and construct the nomogram prediction model.Bootstrapped resampling was applied to validate the model internally,model performance was assessed with calibration curves,Hosmer-Lemeshow test was used to test the degree of fitting,receiver operating characteristic(ROC)curve was plotted to evaluate the predictive accuracy,and decision curve analysis was used to determine the clinical net benefit.The model's generalization capability was evaluated with 10-fold cross-validation of the training set.Results Multivariate logistic regression revealed that stone size,CT value,lower calyx stones,multiple stones,renal infundibulum length(RIL),and renal infundibulum width(RIW)were independent predictors of residual stones(P＜0.05).The nomogram based on the above mentioned parameters demonstrated excellent discrimination,with Bootstrap-validated concordance indices of 0.876(training cohort)and 0.948(validation cohort).Hosmer-Lemeshow tests showed good calibration in both cohorts(P＞0.05).ROC analysis yielded the area under the curve(AUC)of 0.876 and 0.948 for the training and validation cohorts,respectively.The optimal cutoff value was 0.253,with corresponding sensitivity of 84.13％,specificity of 78.35％,and total score of nomogram of 143.The decision curve analysis showed when the threshold probability of the training cohort and verification cohort was 0-0.81 and 0-0.97,respectively,the nomogram could obtain good clinical net benefit in predicting the risk of residual stones.The average accuracy of 10-fold cross-validation was 0.814,and the average AUC was 0.865.Conclusion The nomogram model effectively predicts residual stone risk following FURL for 2-3 cm renal calculi.It is suggested that patients with a total score of ≤143 may consider undergoing FURL.

Objective:To explore the efficacy of intensive repetitive transcranial magnetic stimulation (irTMS) in treatment-resistant depression (TRD) and its impact on cognitive function and systemic immune-inflammation index (SII).Methods:Forty-eight TRD patients were divided into observation group and control group using random number table method, with 24 patients in each group. The observation group was treated with irTMS, and the stimulation site was the left dorsolateral prefrontal lobe. The stimulation intensity was 110% of the motor threshold, and the stimulation frequency was 15 Hz. The stimulation interval was 26 s, and 3 000 pulses were stimulated each time. Stimulating 5 times per day, with an interval of 50 min, and continuous treatment for 5 days. The total stimulation amount for 5 days was 75 000 pulses. The control group was treated with pseudo stimulation. Before treatment (T0), 5 days after treatment (T1), and 1 month after treatment (T2), 17-item Hamilton depression scale (HAMD-17) was used to assess depressive mood. Evaluating cognitive function using the Wisconsin card sorting test.A fully automated blood cell analyzer was used to detect platelet count (PLT), neutrophil count (NC), and lymphocyte count (LC), calculate the systemic immune inflammation index (SII), SII=PLT × NC/LC. Statistical analysis was conducted using SPSS 20.0 software. The comparison between two sets of repeated measurement data was performed using repeated measurement analysis of variance.Simple effect analysis was performed if the interaction effect was significant.Pearson analysis was used for correlation testing.Results:The interaction effect between the time and group of HAMD-17 scores was significant ( F=121.784, P<0.05). The results of simple effects analysis showed that the HAMD-17 scores of the observation group at T1 and T2 ((12.07±4.08) and (14.78±4.99), respectively) were lower than those of the control group ((23.78±5.87) and (24.67±7.00), P<0.05). The treatment response rate and remission rate of the observation group at T1 were higher than those of the control group ( χ2=4.090, 7.378, both P<0.05).The treatment response rate and remission rate of the observation group at T2 were higher than those of the control group ( χ2=4.463, 4.547, both P<0.05). The time and group interaction effects of the percentage of correct response and conceptualization level in the Wisconsin card sorting test were significant ( F=30.087, 20.004, P<0.05). The results of simple effects analysis showed that the percentage of correct response and conceptualization level in the observation group at T1 and T2 were higher than those in the control group (all P<0.05). The time and group interaction effect of SII was significant ( F=8.173, P<0.05). The results of simple effects analysis showed that there was no statistically significant difference in SII between the two groups at T0 ( P>0.05). The SII at T1 and T2 in the observation group was lower than that in the control group ( P<0.05). In the observation group, the changes in SII from T2 to T0 was positively correlated with the change in HAMD-17 scores ( r=0.527, P<0.05), and negatively correlated with the percentage of correct responses to the Wisconsin card sorting test ( r=-0.412, P<0.05) and the percentage of conceptualization level ( r=-0.411, P<0.05). Conclusion:irTMS is effective in treating TRD and can improve patients' cognitive function and immune inflammation damage.