Objective: To characterize longitudinal trajectories of testicular development in boys and breast development in girls, so as to provide reference data for understanding patterns of pubertal sexual maturation. Methods: Based on the Shanghai Pudong New Area Cohort Study on Growth, Development and Health in Children and Adolescents, a baseline survey was conducted in 2020 using a mult stage cluster random sampling method. A total of 2 184 children who completed all follow ups during the primary school period from 13 elementary schools in Pudong New Area,Shanghai,with annual follow ups during 2021-2025. Testicular volume and Tanner stage of breast development were assessed by professional physicians using standardized visual inspection and palpation. The age distribution of testicular volume and breast development was fitted by using cumulative link mixed models and Turnbull s nonparametric maximum likelihood estimation method. Results: Median ages for testicular volumes of 2, 3, 4 and 5 mL in boys were 7.07, 9.24, 10.29, and 11.57 years old, respectively. Median ages for Tanner breast stages Ⅱ, Ⅲ, Ⅳ, and Ⅴ in girls were 8.55 , 10.17, 11.18, and 13.78 years old, respectively. Based on overweight and obesity, stratified analysis showed that earlier pubertal onset among overweight/obesity children, and the key milestones for pubertal initiation were testicular volume reaching 4 mL in boys and breast Tanner II in girls for 10.29, 10.83; 8.18, 9.00 years. Conclusion Overweight and obesity are associated with earlier pubertal initiation,but there are certain gender and developmental stage specific patterns.

Objective: To determine the potential genetic causal relationship between sleep related phenotypes and female pubertal onset using the two sample Mendelian randomization approach. Methods: Genetic instrumental variables for sleep and age at menarche were sourced from FinnGen, IEU Open GWAS and GWAS Catalog three publicly available Genome Wide Association Study databases. Causal effects were estimated using the inverse variance weighted method, supplemented by sensitivity analyses and tests for heterogeneity, pleiotropy, and direction. Results: Genetically predicted sleep duration was positively associated with age at menarche ( β =0.61, 95% CI =0.30-0.91, P <0.01). Conversely, overall sleep problems ( β =-0.13, 95% CI =-0.20 to -0.07 ), two specific types of sleep disorders (sleep apnea: β =-0.10, 95% CI =-0.16 to -0.03; insomnia: β =-0.40, 95% CI = -0.69 to -0.11) were causally associated with earlier age at menarche (all P <0.01). Sensitivity analyses confirmed the robustness of these findings with consistent effect directions and no evidence of significant directional pleiotropy. Conclusions The study reveales a genetic causal relationship between sleep and pubertal onset. Adequate sleep duration appears to have a protective effect. These findings suggest that sleep may have a critical regulatory role in the initiation of pubertal development.

Advancements in artificial intelligence (AI) and emerging technologies are rapidly expanding the exploration of chemical space, facilitating innovative drug discovery. However, the transformation of novel compounds into safe and effective drugs remains a lengthy, high-risk, and costly process. Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development. Despite this need, no comprehensive tool currently supports systematic evaluation and efficient screening. Here, we present druglikeFilter, a deep learning-based framework designed to assess drug-likeness across four critical dimensions: 1) physicochemical rule evaluated by systematic determination, 2) toxicity alert investigated from multiple perspectives, 3) binding affinity measured by dual-path analysis, and 4) compound synthesizability assessed by retro-route prediction. By enabling automated, multidimensional filtering of compound libraries, druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates, which can be freely accessed at https://idrblab.org/drugfilter/.

Advancements in artificial intelligence(AI)and emerging technologies are rapidly expanding the exploration of chemical space,facilitating innovative drug discovery.However,the transformation of novel compounds into safe and effective drugs remains a lengthy,high-risk,and costly process.Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development.Despite this need,no comprehensive tool currently supports systematic evaluation and efficient screening.Here,we present druglikeFilter,a deep learning-based framework designed to assess drug-likeness across four critical dimensions:1)physicochemical rule evaluated by systematic determination,2)toxicity alert investigated from multiple perspectives,3)binding affinity measured by dual-path analysis,and 4)compound synthesizability assessed by retro-route prediction.By enabling automated,multidimensional filtering of compound libraries,druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates,which can be freely accessed at https://idrblab.org/drugfilter/.

Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, treatment, and prognosis prediction of PCa. The introduction of the foundation model has revolutionized the application of AI in medical treatment and facilitated its integration into clinical practice. This review emphasizes the clinical application of AI in PCa by discussing recent advancements from both pathological and imaging perspectives. Furthermore, it explores the current challenges faced by AI in clinical applications while also considering future developments, aiming to provide a valuable point of reference for the integration of AI and clinical applications.
Humans ; Prostatic Neoplasms/diagnosis* ; Male ; Artificial Intelligence ; Deep Learning ; Prognosis

Objective:To evaluate the long-term effectiveness of lingual mucosal graft ureteroplasty (LMGU) for managing long-segment (≥5 cm) ureteral strictures in a multi-institutional cohort of patients.Methods:A multi-center retrospective case series study was conducted on clinical data from 42 patients undergoing LMGU for long-segment ureteral strictures (≥5 cm) across five institutions between February 2017 and June 2024. The cohort comprised 31 males and 11 females, with an age of (43.4±12.0) years (range: 15 to 64 years) and a body mass index of (24.6±2.6) kg/m2 (range: 16.0 to 30.0 kg/m2). Strictures involved the left ureter in 24 cases and right ureter in 18 cases, demonstrating a stricture length of (6.4±1.5) cm (range: 5.0 to 11.5 cm). Surgical interventions included either onlay ureteroplasty or augmented anastomotic ureteroplasty, selected according to intraoperative findings. Intraoperative parameters, postoperative complications, and follow-up outcomes were analyzed.Results:Laparoscopic surgery was performed in 22 cases and robot-assisted surgery in 20 cases. Among the 42 patients, 22 underwent onlay ureteroplasty while 20 received augmented anastomotic ureteroplasty. The graft length was (5.9±1.8) cm (range: 3.0 to 12.0 cm), operative time (191.5±55.6) minutes (range: 105.0 to 350.0 minutes), and intraoperative estimated blood loss (86.7±73.6) ml (range: 10.0 to 400.0 ml). All procedures were successfully completed without conversion to open surgery. The postoperative hospital stay was (7.6±2.0) days (range: 4.0 to 15.0 days), with double-J stent removal at 6 to 8 weeks postoperatively. During a follow-up of (49.1±25.0) months (range: 12.0 to 99.0 months), no stricture recurrence was observed in any patient.Conclusion:LMGU is a safe, feasible, and effective long-term technique for managing long-segment (≥5 cm) ureteral strictures.

Objective:To evaluate the long-term effectiveness of lingual mucosal graft ureteroplasty (LMGU) for managing long-segment (≥5 cm) ureteral strictures in a multi-institutional cohort of patients.Methods:A multi-center retrospective case series study was conducted on clinical data from 42 patients undergoing LMGU for long-segment ureteral strictures (≥5 cm) across five institutions between February 2017 and June 2024. The cohort comprised 31 males and 11 females, with an age of (43.4±12.0) years (range: 15 to 64 years) and a body mass index of (24.6±2.6) kg/m2 (range: 16.0 to 30.0 kg/m2). Strictures involved the left ureter in 24 cases and right ureter in 18 cases, demonstrating a stricture length of (6.4±1.5) cm (range: 5.0 to 11.5 cm). Surgical interventions included either onlay ureteroplasty or augmented anastomotic ureteroplasty, selected according to intraoperative findings. Intraoperative parameters, postoperative complications, and follow-up outcomes were analyzed.Results:Laparoscopic surgery was performed in 22 cases and robot-assisted surgery in 20 cases. Among the 42 patients, 22 underwent onlay ureteroplasty while 20 received augmented anastomotic ureteroplasty. The graft length was (5.9±1.8) cm (range: 3.0 to 12.0 cm), operative time (191.5±55.6) minutes (range: 105.0 to 350.0 minutes), and intraoperative estimated blood loss (86.7±73.6) ml (range: 10.0 to 400.0 ml). All procedures were successfully completed without conversion to open surgery. The postoperative hospital stay was (7.6±2.0) days (range: 4.0 to 15.0 days), with double-J stent removal at 6 to 8 weeks postoperatively. During a follow-up of (49.1±25.0) months (range: 12.0 to 99.0 months), no stricture recurrence was observed in any patient.Conclusion:LMGU is a safe, feasible, and effective long-term technique for managing long-segment (≥5 cm) ureteral strictures.

OBJECTIVE To investigate the mechanism of Cichorium glandulosum in the treatment of liver fibrosis by using network pharmacology and experimental validation. METHODS A "component-target-pathway" network was constructed with the help of TCMSP, Pubchem, SwissTargetPrediction and Genecards databases, and the STRING database was used to predict the targets of Cichorium glandulosum against liver fibrosis. KEGG and GO enrichment analysis was performed in the DAVID database, and molecular docking of active ingredients and key targets was docked in AUTODOCK. PDGF-BB was used to induce activation of cells and verify the effects of six compounds, including quercetin, quercetin, chicoric acid, caffeic acid, chlorogenic acid, and isochlorogenic acid, on the proliferation, apoptosis, and liver fibrosis indicators of HSC-T6 cells. Western blotting was used to detect the expression of Ras, ERK1, ERK2, C-fos, and JNK proteins in HSC-T6 cells. RESULTS Network pharmacology screened 239 common targets between the components and liver fibrosis, PPI analysis showed that SRC, STAT3, HSP90AA1 and other targets were key targets, KEGG analysis showed that the pathways affected by Cichorium glandulosum included cancer pathways, metabolic pathways, etc. GO analysis predicted that Cichorium glandulosum mainly affected processes such as signal transduction. The molecular docking results showed that the target that could bind well with the components MAPK1, and the components that could bind well with the target aesculetin, caffeic acid and chlorogenic acid. Compared with the model group, the inhibition effect of the six compounds on PDGF-BB-induced HSC-T6 cell activation was stronger, and all 6 compounds had the effects to reverse the index of liver fibrosis, in which aesculetin had the strongest activity(P<0.01). The expression of Ras, ERK1, ERK2, C-fos, and JNK in HSC-T6 cells decreased after the interventions of 6 compounds. CONCLUSION Each component of Cichorium glandulosum has different anti liver fibrosis effects, which are related to the inhibition of ERK/RAS pathway activation.

OBJECTIVE To screen out the pharmacodynamic substances of Cistanches Herba aqueous extracts, explore the basis of the pharmacodynamic substances and their mechanism of action in the treatment of diabetic nephropathy(DN), based on the spectral relationship between the mass spectral peak areas of different elution sites of Cistanches Herba aqueous extracts and their anti-DN effects. METHODS UPLC-Orbitrap-MS/MS technique was used to characterise the chromatographic peaks; MTT method was used to detect the effects of different elution sites of Cistanches Herba aqueous extract on the proliferation of high glucose and high fat HK-2 cells; grey correlation analysis and partial least squares method were used to analyse the spectral relationship between mass spectrometry peak area and anti-DN activity. MTT method was used to determine the anti-DN activities of the individual components of Cistanches Herba aqueous extract; biochemical kit and ELISA were used to determine the levels of oxidative indicators(SOD, GSH-P) and inflammatory factors(IL-1β, TNF-α, TGF-β); Western blotting was used to detect the expression of apoptosis-related proteins. RESULTS UPLC-Orbitrap-MS/MS technique speculated and identified 72 common compounds; In Cistanches Herba aqueous extracts, water, 20% ethanol, and 40% ethanol-eluted sites differentially increased the proliferation rate of HK-2 cells in a high-sugar, high-fat environment; Partial least squares and grey correlation analyses showed that the constituents of the aqueous extracts of Cistanches Herba with greater anti-DN contributions were 8-epideoxymatricinic acid, geniposidic acid, pinoresinol, betaine and syringin, et al. MTT assay reveals that 8-epi-deoxystrychnic acid and geniposidic acid had significant proliferative effects on HK-2 cells in a high glucose and high fat environment; Biochemical kit and ELISA showed that 8-epideoxystrychnic acid and geniposidic acid were able to up-regulate the activity of SOD and GSH-Px, and at the same time they had an inhibitory effect on the expression of inflammatory factors IL-1β, TNF-α and TGF-β. Western blotting results showed that 8-epideoxystrychnic acid and geniposidic acid were able to down-regulate and up-regulate the markers of dermal mesenchymal transition: α-SMA, Collagen Ⅰ and E-cadherin, and they could exert anti-DN effects by inhibiting the PI3K-Akt pathway. CONCLUSION The two compounds, 8-epideoxystrychnic acid and geniposidic acid, which are screened by the spectroeffective relationship of anti-DN among the many chemical constituents contained in Cistanches Herba, can affect oxidative stress, inflammation and epithelial-mesenchymal transformation of renal tubular cells by inhibiting the PI3K-Akt signalling pathway, and improve renal pathology, degree of fibrosis and renal function, which will be useful for the in-depth study of aqueous extracts of Cistanches Herba in the treatment of DN.

Idiopathic pulmonary fibrosis (IPF) is an interstitial lung disease that is difficult to diagnose clinically, and finding appropriate biomarkers to assist in the diagnosis and prognosis monitoring of IPF can improve the proportion of early diagnosis and timely treatment of these patients and improve the quality of life of patients