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.

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

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/.

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

Objective:The combined diagnosis models was constructed with the test indicators and its application value in the clinical evaluation of patients with interstitial lung disease was evaluated.Methods:Methodology development and validation. A total of 101 patients with idiopathic pulmonary fibrosis (IPF) and 107 patients with non-IPF interstitial lung disease admitted to China-Japan Friendship Hospital from 2022 to 2023 were collected, and 98 healthy people were collected during the same period. The population in each group was divided into modeling group (180 cases) and validation group (126 cases) by complete randomization. Serum samples and clinical test results were collected. The test indicators included white blood cell count, lymphocyte count, monocyte count, hemoglobin concentration, highly sensitive C-reactive protein, Krebs von den Lungen 6, total cholesterol, triglycerides, high density lipoprotein cholesterol, low density lipoprotein cholesterol, adenosine deaminase, neuron-specific enolase, alpha-fetoprotein, carcinoembryonic antigen, cytokeratin 19 fragment, carbohydrate antigen 15-3, gastrin releasing peptide precursor, squamous cell carcinoma antigen and interleukin 1 (IL-1), IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12p70, IL-17, tumor necrosis factor-α, interferon-α, interferon-γ. Multiple collinearity test, univariate and multivariate logistic regression were performed for the included test indicators in each group, and nomograms were established and validated by receiver operating characteristic (ROC) curves, calibration curves and clinical decision curves.Results:By comparing interstitial lung disease to healthy people, carbohydrate antigen 15-3 ( OR=1.285, 95% CI 1.178-1.402), IL-6 ( OR=1.128, 95% CI 1.011-1.258), adenosine deaminase ( OR=1.465, 95% CI 1.261-1.702), and Krebs von den Lungen-6 ( OR=1.013, 95% CI 1.008-1.017) were independent risk factors for interstitial lung disease. Based on these four indexes, the nomogram model was constructed. The AUCs of the combined diagnosis model in the modeling group and validation group were 0.967(95%CI 0.941-0.993)and 0.948(95% CI 0.911-0.984), respectively.Decision curve analysis showed that the net benefit of the combined diagnosis model in diagnosing IPF was higher than that of a single indicator within the threshold range of 0.01-1. In the comparison of IPF and non-IPF interstitial lung disease, alpha-fetoprotein ( OR=1.403, 95% CI 0.975-2.019) and squamous cell carcinoma antigen ( OR=0.531, 95% CI 0.321-0.878) were independent risk factors for IPF. The AUCs of the combined diagnosis model in the modeling group and validation group were 0.703 (95% CI 0.597-0.81) and 0.642 (95% CI 0.528-0.757), respectively. Through calibration curve and clinical decision curve verification, it was found that it had a certain value in the differential diagnosis of IPF. Conclusions:Carbohydrate antigen 15-3, IL-6, adenosine deaminase and Krebs von den Lungen 6 are risk factors of interstitial lung disease, which can be used to construct a combined diagnostic model for the diagnosis of interstitial lung disease. Alpha-fetoprotein and squamous cell carcinoma antigen are risk factors of IPF, which can be used to construct a combined diagnostic model to distinguish IPF from non-IPF interstitial lung disease and assist clinical diagnosis of IPF.

Idiopathic pulmonary fibrosis (IPF) is an interstitial lung disease that occurs mostly in the middle-aged and eldly people, with a short median survival and cannot be cured, and the etiology is still unclear. Currently, it is believed that the pathogenesis is related to cellular aging, and abnormal cellular aging leads to the failure of damaged alveolar epithelial cells that cannot be repaired normally, which promotes the occurrence of pulmonary fibrosis. Senescence-associated secretory phenotype (SASP), SASP affects pulmonary fibrosis through different signaling pathways in IPF patients, and this article reviews the expression level and mechanism of existing SASP in IPF patients.

OBJECTIVE To investigate the effects and mechanism of luteolin on osteogenic repair of bone defects. METHODS The targets and potential pathways of luteolin in the treatment of bone defects were screened by network pharmacology method， and then the top 2 targets were selected by Hub gene screening for molecular docking verification， with binding energy as the evaluation standard. In vitro experiments were conducted on rat bone mesenchymal stem cells （BMSC） and rat umbilical vein endothelial cells （RUVEC）. Phenotypic validation was performed using alkaline phosphatase staining， alizarin red S staining， and in vitro angiogenesis experiments. Western blot assay was used to detect the protein expressions of phosphatidylinositol 3 kinase （PI3K） and protein kinase 1 （Akt1）， so as to validate the mechanism of luteolin on osteogenic differentiation of BMSC and angiogenesis of RUVEC in vitro. RESULTS The results of network pharmacology showed that the effects of luteolin on vascular formation and bone repair in bone defects were mainly related to Akt1， SRC， estrogen receptor 1， epidermal growth factor receptor， cyclooxygenase 2， matrix metalloproteinase 9 targets， and were closely related to PI3K-Akt signaling pathway. The results of molecular docking showed that luteolin binding to Akt1 and SRC proteins was stable. The results of in vitro experiments showed that luteolin could significantly improve the expressions and activities of alkaline phosphatase in BMSC， increased the number of calcium salt deposits and calcified nodules， and promoted calcification of BMSC. Compared with luteolin 0 μmol/L group， the angiogenesis ability of RUVEC was enhanced significantly in luteolin 1， 10 μmol/L groups， the length of blood vessels and the protein expressions of PI3K and Akt1 were significantly increased （P＜0.05 or P＜0.01）； the higherthe concentration， the better the effect. CONCLUSIONS Luteolin may play a role in promoting angiogenesis and bone repair at the fracture site by activating PI3K/Akt signaling pathway and promoting the protein expressions of PI3K and Akt1.