Objective: To construct prediction models of female stress urinary incontinence (SUI), and evaluate the efficacy of each model, so as to provide reference for the early diagnosis of SUI. Methods: Female SUI patients treated in our hospital during Oct. 2019 and Oct. 2023 and healthy women undergoing physical examination during the same period were involved. Women 42 days after delivery were included in the postpartum group (n=611), and perimenopausal and postmenopausal women were included in the non-postpartum group (n=409). The number of random seeds was set and the participants were divided into the training and verification sets in a ratio of 7∶3. Relevant clinical data were collected, and meaningful variables were screened using single factor and Lasso regression, which were then incorporated into the K-nearest neighbor method (KNN), support vector machine (SVM)，decision tree (DT) and random forest (RF) algorithms. The sensitivity, specificity, accuracy and area under the receiver operating characteristic curve (AUC) of the models were calculated to screen out the optimal model. Results: There were 352 SUI patients (57.6%) in the postpartum group. According to single factor and Lasso regression, significant variables included age, body mass index (BMI), maximum rapid muscle stage, parity, bladder neck mobility (BND), urethral rotation angle (URA), lateral perineal incision, past incontinence, and constipation. In the verification set, the AUC of KNN，SVM，DT and RF models were 0.881，0.878，0.750 and 0.905,respectively; the AUC, accuracy, F1 index and Kappa value of RF model were the largest. In the non-postpartum group, there were 260 SUI patients, accounting for 63.6%. The significant variables were age，BMI, maximum value and recovery time of fast muscle stage, mean value of slow muscle stage, post-resting stage variability, vaginal delivery, past incontinence, and constipation. In the verification set, the AUC of KNN,SVM，DT and RF models were 0.819,0.805，0.603 and 0.830, respectively; the AUC, accuracy, Kappa value of the RF model were the largest. Conclusion: This study successfully established 4 prediction models for the incidence of SUI in women at 42 days postpartum, perimenopausal and postmenopausal women based on machine learning. Among them, the model adopting the RF algorithm had the best prediction efficiency.

Aging is a natural process in which tissue and organ function declines as organisms age. Aging is the inevitable outcome of the organism and is irreversible. The aging process is accompanied by degenerative changes in the morphological structure of multiple organs of the body, leading to an increase in the incidence of chronic diseases such as hypertension, cardiovascular and cerebrovascular diseases, hyperlipidemia, and diabetes year by year. In recent years, natural phytochemicals have attracted widespread attention from the public due to their advantages such as non-toxicity or low toxicity, low cost, and various biological activities. Epigallocatechin gallate (EGCG) is a dietary polyphenol extracted from green tea, which has a variety of biological functions including anti-oxidation, anti-inflammation, hypoglycemic, hypolipidemic and anti-aging activities. The EGCG-mediated anti-aging mechanism has been investigated in many studies with different aging models. This article reviews the research progress on rodents, nematodes, fruit flies, and cell aging models, focusing on summarizing the lifespan extension and physiological changes of rodents, nematodes and fruit flies after EGCG intervention from multiple angles, and exploring potential mechanism by which EGCG delays aging and extends lifespan. This review provides a theoretical reference for the study of the anti-aging mechanism of phytochemicals.

BACKGROUND: Temozolomide (TMZ) resistance is a significant challenge in treating glioblastoma (GBM). Collagen remodeling has been shown to be a critical factor for therapy resistance in other cancers. This study aimed to investigate the mechanism of TMZ chemoresistance by GBM cells reprogramming collagens. METHODS: Key extracellular matrix components, including collagens, were examined in paired primary and recurrent GBM samples as well as in TMZ-treated spontaneous and grafted GBM murine models. Human GBM cell lines (U251, TS667) and mouse primary GBM cells were used for in vitro studies. RNA-sequencing analysis, chromatin immunoprecipitation, immunoprecipitation-mass spectrometry, and co-immunoprecipitation assays were conducted to explore the mechanisms involved in collagen accumulation. A series of in vitro and in vivo experiments were designed to assess the role of the collagen regulators prolyl 4-hydroxylase subunit alpha 1 (P4HA1) and yes-associated protein (YAP) in sensitizing GBM cells to TMZ. RESULTS: This study revealed that TMZ exposure significantly elevated collagen type I (COL I) expression in both GBM patients and murine models. Collagen accumulation sustained GBM cell survival under TMZ-induced stress, contributing to enhanced TMZ resistance. Mechanistically, P4HA1 directly binded to and hydroxylated YAP, preventing ubiquitination-mediated YAP degradation. Stabilized YAP robustly drove collagen type I alpha 1 ( COL1A1) transcription, leading to increased collagen deposition. Disruption of the P4HA1-YAP axis effectively reduced COL I deposition, sensitized GBM cells to TMZ, and significantly improved mouse survival. CONCLUSION P4HA1 maintained YAP-mediated COL1A1 transcription, leading to collagen accumulation and promoting chemoresistance in GBM.
Temozolomide ; Humans ; Glioblastoma/drug therapy* ; Animals ; Mice ; Cell Line, Tumor ; Drug Resistance, Neoplasm/genetics* ; YAP-Signaling Proteins ; Hydroxylation ; Dacarbazine/pharmacology* ; Adaptor Proteins, Signal Transducing/metabolism* ; Transcription Factors/metabolism* ; Collagen/biosynthesis* ; Collagen Type I/metabolism* ; Prolyl Hydroxylases/metabolism* ; Antineoplastic Agents, Alkylating/therapeutic use*

Parkinson's disease (PD) is a common neurodegenerative disorder mainly related to mitochondrial dysfunction of dopaminergic neurons in the midbrain substantia nigra. This study aimed to investigate the effects of exercise preconditioning on motor deficits and mitochondrial function in a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mouse model. Eight-week-old male C57BL/6J mice were randomly divided into four groups: sedentary + saline (SS), sedentary + MPTP (SM), exercise + saline (ES), and exercise + MPTP (EM) groups. Mice in the ES and EM groups received 4 weeks of treadmill training, and then SM and EM groups were treated with MPTP for 5 days. Motor function was assessed by behavioral tests, and morphological and functional changes in dopaminergic neurons and mitochondria in the substantia nigra of the midbrain were evaluated using immunohistochemistry, Western blot, and transmission electron microscopy technology. The results showed that, compared with the SM group, the EM group exhibited significantly improved motor ability, up-regulated protein expression levels of tyrosine hydroxylase (TH) and dopamine transporter (DAT) in the midbrain, and down-regulated protein expression of α-synuclein (α-Syn) in the mitochondria of substantia nigra. Compared with the SM group, the EM group showed up-regulated protein expression levels of mitochondrial fusion proteins, including optical atrophy protein 1 (OPA1) and mitofusin 2 (MFN2), and biogenesis-related proteins, including peroxisome proliferator activated receptor gamma coactivator 1α (PGC-1α) and mitochondrial transcription factor A (TFAM), while the protein expression levels of dynamin-related protein 1 (DRP1) and mitochondrial fission protein 1 (FIS1) were significantly down-regulated. Compared with the SM group, the EM group showed significantly reduced damage to substantia nigra mitochondria, restored mitochondrial membrane potential and ATP production, and decreased levels of reactive oxygen species (ROS). These results suggest that 4-week treadmill pre-training can alleviate MPTP-induced motor impairments in PD mice by improving mitochondrial function, providing a theoretical basis for early exercise-based prevention of PD.
Animals ; Male ; Physical Conditioning, Animal/physiology* ; Mice ; Mice, Inbred C57BL ; Mitochondria/physiology* ; Dopaminergic Neurons ; MPTP Poisoning/physiopathology* ; Substantia Nigra ; Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha ; 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine

OBJECTIVE: To reveal the effects and potential mechanisms by which synaptic vesicle glycoprotein 2A (SV2A) influences the distribution of amyloid precursor protein (APP) in the trans-Golgi network (TGN), endolysosomal system, and cell membranes and to reveal the effects of SV2A on APP amyloid degradation. METHODS: Colocalization analysis of APP with specific tagged proteins in the TGN, ensolysosomal system, and cell membrane was performed to explore the effects of SV2A on the intracellular transport of APP. APP, β-site amyloid precursor protein cleaving enzyme 1 (BACE1) expressions, and APP cleavage products levels were investigated to observe the effects of SV2A on APP amyloidogenic processing. RESULTS: APP localization was reduced in the TGN, early endosomes, late endosomes, and lysosomes, whereas it was increased in the recycling endosomes and cell membrane of SV2A-overexpressed neurons. Moreover, Arl5b (ADP-ribosylation factor 5b), a protein responsible for transporting APP from the TGN to early endosomes, was upregulated by SV2A. SV2A overexpression also decreased APP transport from the cell membrane to early endosomes by downregulating APP endocytosis. In addition, products of APP amyloid degradation, including sAPPβ, Aβ _1-42, and Aβ _1-40, were decreased in SV2A-overexpressed cells. CONCLUSION These results demonstrated that SV2A promotes APP transport from the TGN to early endosomes by upregulating Arl5b and promoting APP transport from early endosomes to recycling endosomes-cell membrane pathway, which slows APP amyloid degradation.
Amyloid beta-Protein Precursor/genetics* ; Membrane Glycoproteins/genetics* ; Animals ; Protein Transport ; Nerve Tissue Proteins/genetics* ; Humans ; Mice ; Endosomes/metabolism* ; trans-Golgi Network/metabolism*

[Purpose]To analyze the trends of brain tumor incidence and age of onset in cancer registration areas of Jiangsu Province from 2009 to 2019.[Methods]The incidence data of brain tumors from 2009 to 2019 were obtained from 16 national cancer registration areas of Jiangsu Province.The crude incidence rate,age-standardized incidence rate by Chinese standard popula-tion(ASIRC),average age of onset,standardized age-specific incidence rate,and annual average percentage change(AAPC)by sexes and regions were calculated.[Results]The incidence rate of brain tumor in Jiangsu Province from 2009 to 2019 showed an increasing trend(AAPC=4.12％,95％CI:3.31％～4.95％),and the increase in female(AAPC=5.79％,95％CI:4.44％～7.15％)was higher than that in male(AAPC=2.31％,95％CI:1.66％～2.97％);and the increase in urban areas(AAPC=4.84％,95％CI:3.52％～6.18％)was higher than that in rural areas(AAPC=3.04％,95％CI:2.12％～3.98％).The ASIRC also showed an increasing trend(AAPC=2.14％,95％CI:1.27％～3.02％).Birth cohort analysis showed that within the same age group,the incidence rate of brain tumors increased with increasing birth years.The average age of onset for crude incidence showed a delaying trend of 0.43 years old per year(t=7.09,P＜0.001);that for ASIRC was 0.20 years old per year(t=3.33,P=0.009).The proportion of patients in the age group of 60 years old and above increased from 35.79％in 2009 to 44.18％in 2019.[Conclusion]The incidence of brain tumor in cancer registration areas of Jiangsu Province showed an increasing trend from 2009 to 2019 with a delaying trend of average age of onset.

Imaging examination is a crucial part in diagnosis and treatment of central nervous system infection(CNSI),involving complex imaging sequences and parameters.This consensus was jointly written by multiple CNSI imaging experts in China,aimed to standardize imaging examination of CNSI.

Objective:To explore the value of prenatal three-dimensional ultrasonography（3DUS）in displaying auricular morphotyping and dimensions for predicting congenital aural atresia（CAA）.Methods:A retrospective collection of 227 fetuses who underwent ultrasound scans and retained auricular 3DUS volumes from January 2018 to December 2023 at the First Affiliated Hospital of Sun Yat-sen University was conducted. Fetuses were divided into two groups：a CAA group（52 fetuses，62 auricles）and a non-CAA group（175 fetuses，202 auricles），based on the presence or absence of external auditory canal identified through postnatal examination. According to 3DUS auricular contour and presence or absence of the concha，the auricles were divided into 4 types：type Ⅰ，C-shaped auricle with a concha；type Ⅱ，Irregular auricle with a concha；type Ⅲ，C-shaped auricle without a concha；type Ⅳ，Irregular auricle without a concha. And auricular length（AL）and width（AW）were measured to calculate the product of the auricular length and width（ALW）. Normal reference ranges for ALW from the non-CAA group were developed. Differences of the auricular morphotyping and Z-score of ALW（ALWZ）were compared between the two groups. Receiver operating characteristic（ROC）curves were used to evaluate the diagnostic efficiency of auricular morphotyping，ALWZ and the regression model. A Logistic regression model for CAA based on auricular morphotyping and ALWZ were established.Results:The auricular morphotyping and ALWZ between the two groups were different statistically（both P<0.05）. The AUC of the auricular morphotyping and ALWZ predicting CAA were 0.960（95% CI = 0.923 - 0.997）and 0.975（95% CI = 0.959 - 0.991）individually. Formula for CAA prediction model combining the two indicators（5.379 × morphotyping - 2.386 × ALWZ - Conclusions:The auricular morphotyping and dimensions can effectively predict CAA.

Objective:To develop a deep learning-based artificial intelligence system for assessing image quality in early pregnancy ultrasound，and to evaluate its performance in anatomical structure identification and quality control.Methods:A retrospective study was conducted by collecting 17 910 static ultrasound images of 8 quality-control planes from fetuses at 11 to 13 +6 weeks of gestation who underwent routine first-trimester ultrasound examinations at the First Affiliated Hospital of Sun Yat-sen University from June 2018 to June 2024. The dataset was divided into a training set（12 536 images），a test set（3 582 images），and a validation set（1 792 images）in a 7∶2∶1 ratio to develop a prenatal-screening artificial intelligence system（PSAIS）and to evaluate its performance in the automatic recognition and quality control of standard planes during early pregnancy. The average precision and mean average precision（mAP）were used to measure the model's ability to recognize the anatomical structures on each plane. Intraclass correlation coefficient（ICC）and Kappa statistics were used to assess the consistency between PSAIS and expert-level sonographers in both plane image quality assessment and standardization. The efficiency of PSAIS was also compared to manual quality control. Results:In the test set，the mAP values for recognizing the anatomical structures of the 8 quality-control planes all exceeded 0.800. In the validation set，PSAIS demonstrated moderate to good agreement with two experts in image quality evaluation：the ICC ranged from 0.713 to 0.843 for one expert and 0.678 to 0.788 for the other，while the Kappa values ranged from 0.590 to 0.768 and 0.530 to 0.702，respectively. In terms of plane standardization scoring，PSAIS showed particularly high agreement with expert ratings on the transventricular view（compliance rate 94.6%，Kappa=0.860）and the four-chamber cardiac view with blood flow（compliance rate 94.1%，Kappa=0.778），with agreement above 70% for the remaining planes. Compared with manual quality-control，PSAIS significantly increased processing speed：the total processing time was only 413 seconds，markedly less than the 77 008 seconds and 94 918 seconds required for manual QC（ P<0.001）. Conclusions:The PSAIS system performs well in recognizing and controlling the quality of standard ultrasound planes in early pregnancy，demonstrating high consistency with expert evaluations and significantly improved processing efficiency. It has potential application value in enhancing the quality and efficiency of early pregnancy screening.

Objective:To investigate the incidence, clinical characteristics, and impact of spontaneous portosystemic shunt (SPSS) in patients with liver cirrhosis combined with hepatic encephalopathy (HE).Methods:The basic clinical and follow-up data were retrospectively analyzed for patients diagnosed with cirrhosis combined with HE at Mengchao Hepatobiliary Hospital of Fujian Medical University from January 2017 to December 2022. The patients were divided into large and small SPSS groups and a control group based on the results of abdominal enhanced CT or MRI.The clinical characteristics and outcome differences were compared among the three groups. Kaplan-Meier survival curves were used to compare HE-free survival time and overall survival time among the three groups. The log-rank test was used to compare the differences between groups. Cox regression analysis was used to identify the relevant risk factors affecting HE-free survival time and overall survival time.Results:A total of 223 cases with liver cirrhosis combined with HE were enrolled, including 150 in the SPSS and 73 in the control groups. The incidence rate of SPSS was 67.3% (150/223). The group was divided into small SPSS (79/150, 52.7%) and large SPSS group (71/150, 47.3%) according to the cross-sectional area of the diversion channel. The HE-free survival was shorter in the small and large SPSS groups compared with the control group (35.5 months in the small SPSS group and 21.3 months in the large SPSS group; P<0.001). The HE-free survival time was shorter in the large SPSS than with small SPSS group ( P=0.003). The overall survival time in the small SPSS group and the large SPSS group was shorter compared with the control group (small SPSS group: 39.4 months, large SPSS group: 52.9 months; P<0.001). There was no statistically significant difference in overall survival time between the small SPSS and large SPSS groups ( P=0.700). Cox regression analysis showed that SPSS was an independent risk factor affecting patients' HE-free survival time and overall survival time ( P<0.05). Conclusion:SPSS is more common in patients with liver cirrhosis combined with HE. Patients who combined with SPSS showed significant reductions in both HE-free survival time and overall survival time, especially evident in those with combined large SPSS.