Objective: To analyze the association of mother-child interaction and screen exposure of preschool children with psychological and behavioural problems, so as to provide guidance for promoting the psychological development of preschool children. Methods: From November to December 2024, a convenience cluster sampling method was used to survey 2 977 mothers of preschool children in Daguan and Yingjiang districts of Anqing City. The Chinese Parent-Child Interaction Scale (CPCIS) was applied to evaluate the quality of mother-child interaction, and the Conners Parent Symptom Questionnaire (PSQ) was used to assess the psychological and behavioral problems of preschool children. Binary Logistic regression was applied to analyze the association of mother-child interaction, screen exposure and their combined effect on psychological and behavioral problems among preschool children. Results: The detection rate of psychological and behavioral problems among preschool children was 13.9%. Binary Logistic regression results showed that low scores of mother-child interaction ( OR=2.31, 95%CI =1.72-3.11) and high screen exposure ( OR= 1.52 , 95%CI =1.23-1.88) were higher risks for psychological and behavioral problems in preschool children; the results of the combined effect showed that preschool children in low scores of mother-child interaction and low screen exposure group ( OR=2.18, 95%CI =1.46-3.28), low scores of mother-child interaction and high screen exposure group ( OR=3.13, 95%CI =2.10- 4.65 ) had significantly higher risks of abnormal detection in psychological and behavioral problems, compared to those in the high scores of mother-child interaction and low screen exposure group respectively (all P <0.05). Conclusions Both screen exposure and mother- child interaction are associated with psychological and behavioral problems in preschool children. High quality mother-child interaction can relieve the adverse effects of screen exposure on preschool children s psychological and behavioral development.

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

OBJECTIVE: To explore the role of the natural compound hesperidin in glycolysis, the key ratelimiting enzyme, in colorectal cancer (CRC) cell lines. METHODS: In vitro, HCT116 and SW620 were treated with different doses of hesperidin (0-500 µmol/L), cell counting kit-8 and colone formation assays were utilized to detected inhibition effect of hesperidin on CRC cell lines. Transwell and wound healing assays were performed to detect the ability of hesperidin (0, 25, 50 and 75 µmol/L) to migrate CRC cells. To confirm the apoptotic-inducing effect of hesperidin, apoptosis and cycle assays were employed. Western blot, glucose uptake, and lactate production determination measurements were applied to determine inhibitory effects of hesperidin (0, 25 and 50 µmol/L) on glycolysis. In vivo, according to the random number table method, nude mice with successful tumor loading were randomly divided into vehicle, low-dose hesperidin (20 mg/kg) and high-dose hesperidin (60 mg/kg) groups, with 6 mice in each group. The body weights and tumor volumes of mice were recorded during 4-week treatment. The expression of key glycolysis rate-limiting enzymes was determined using Western blot, and glucose uptake and lactate production were assessed. Finally, protein interactions were probed with DirectDIA Quantitative Proteomics, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. RESULTS: Hesperidin could inhibit CRC cell line growth (P<0.05 or P<0.01). Moreover, hesperidin presented an inhibitory effect on the migrating abilities of CRC cells. Hesperidin also promoted apoptosis and cell cycle alterations (P<0.05). The immunoblotting results manifested that hesperidin decreased the levels of hexokinase 2, glucose transporter protein 1 (GLUT1), GLUT3, L-lactate dehydrogenase A, 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 2 (PFKFB2), PFKFB3, and pyruvate kinase isozymes M2 (P<0.01). It remarkably suppressed tumor xenograft growth in nude mice. GO and KEGG analyses showed that hesperidin treatment altered metabolic function. CONCLUSION Hesperidin inhibits glycolysis and is a potential therapeutic choice for CRC treatment.
Hesperidin/therapeutic use* ; Colorectal Neoplasms/metabolism* ; Glycolysis/drug effects* ; Animals ; Humans ; Apoptosis/drug effects* ; Mice, Nude ; Cell Movement/drug effects* ; Cell Line, Tumor ; Cell Proliferation/drug effects* ; Glucose/metabolism* ; Cell Cycle/drug effects* ; Mice, Inbred BALB C ; Mice ; HCT116 Cells ; Lactic Acid

This study aimed to comprehensively examine the association of gallstones, cholecystectomy, and cancer risk. Multivariable logistic regressions were performed to estimate the observational associations of gallstones and cholecystectomy with cancer risk, using data from a nationwide cohort involving 239 799 participants. General and gender-specific two-sample Mendelian randomization (MR) analysis was further conducted to assess the causalities of the observed associations. Observationally, a history of gallstones without cholecystectomy was associated with a high risk of stomach cancer (adjusted odds ratio (aOR)=2.54, 95% confidence interval (CI) 1.50-4.28), liver and bile duct cancer (aOR=2.46, 95% CI 1.17-5.16), kidney cancer (aOR=2.04, 95% CI 1.05-3.94), and bladder cancer (aOR=2.23, 95% CI 1.01-5.13) in the general population, as well as cervical cancer (aOR=1.69, 95% CI 1.12-2.56) in women. Moreover, cholecystectomy was associated with high odds of stomach cancer (aOR=2.41, 95% CI 1.29-4.49), colorectal cancer (aOR=1.83, 95% CI 1.18-2.85), and cancer of liver and bile duct (aOR=2.58, 95% CI 1.11-6.02). MR analysis only supported the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer. This study added evidence to the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer, highlighting the importance of cancer screening in individuals with gallstones.
Humans ; Mendelian Randomization Analysis ; Gallstones/complications* ; Female ; Male ; Cholecystectomy/statistics & numerical data* ; Middle Aged ; Risk Factors ; Aged ; Adult ; Neoplasms/etiology* ; Stomach Neoplasms/epidemiology*

Objective:To construct an evaluation indicator system for accessories of patient monitor,so as to provide a basis for clinical management,equipment procurement,and technical improvement for accessories of medical monitor.Methods:The initial selection indicators of corresponding accessories of three types of monitoring of medical monitors,including electrocardiogram(ECG),blood oxygen saturation(SpO2)and non-invasive blood pressure(NIBP),were determined through literature research,expert consultation,and actual investigation.The Delphi method was adopted to conduct two rounds of questionnaire consultation for experts from clinical medicine,biomedical engineering and other fields in medical institutions included Sichuan Provincial People's Hospital,The Affiliated Hospital of Southwest Medical University and Medical Institute of Chengdu Institute of Metrology Verification and Testing.The evaluation indicators were screened and optimized,and the Analytic Hierarchy Process(AHP)was used to calculate the weights of each indicator.The consistency test was conducted to verify the rationality of the evaluation indicator system.Results:The evaluation indicator system for accessories of medical monitor included three first-level indicators:clinical value,cost value,and management value.The number of second-level indicators about ECG,SpO2 and NIBP of evaluation indicator system were respectively 10,9 and 8,and the number of third-level indicators of that were respectively 20,19,and 14.In the first-level indicators,the clinical value had the highest weight,with 72.49%for ECG,70.88%for SpO2 and 70.32%for NIBP.In the second-level indicators,the accuracy(28.70%for ECG,38.13%for SpO2 and 43.03%for NIBP)and safety(27.47%for ECG,26.48%for SpO2 and 23.06%for NIBP)were the core indicators.The weights of cost value and management value were between 14.62%and 17.41%,and between 12.27%and 12.89%,respectively.Conclusion:The evaluation indicator system for accessories of medical monitor integrates multi-dimensional expert opinions and quantitative analysis,highlights the priority principle for clinical performance.It can provide theoretical support for optimizing selection about accessory for medical institutions,and improving quality of monitoring,and promoting standardized management in the industry.

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 investigate the mechanism by which lycopene prevents and alleviates ionizing radiation-induced intestinal injury.Methods:Forty specific pathogen-free male C57BL/6 mice were randomly divided into 4 groups: control group (gavage with an equal volume of corn oil), radiation group (gavage with an equal volume of corn oil and exposed to a single dose of 12 Gy X-ray irradiation on day 3), lycopene group (gavage with lycopene), and lycopene + radiation group (gavage with lycopene and irradiated with 12 Gy X-ray on day 3). All gavage treatments continued for 7 days after irradiation. On day 7 post-irradiation, intestinal tissues were collected. Hematoxylin and eosin (HE), Masson's trichrome, and Sirius red staining were used to assess intestinal injury and fibrosis. Immunohistochemistry was used to detect the expression of α-smooth muscle actin (α-SMA). Immunofluorescence staining was performed to assess the expression of transforming growth factor-β (TGF-β) and connective tissue growth factor (CTGF) in intestinal tissues. Serum levels of malondialdehyde (MDA), total superoxide dismutase (T-SOD), total antioxidant capacity (T-AOC), and glutathione peroxidase (GSH-PX) were measured to evaluate oxidative stress. mRNA expression of tumor necrosis factor-α (TNF-α), interleukin (IL)-6, IL-1β, and CD68 in intestinal tissue was quantified using real-time quantitative PCR (RT-qPCR). Western blot was used to detect the expression of apoptosis-related proteins. One-way ANOVA was used to compare differences among groups.Results:Compared with the radiation group, the lycopene + radiation group showed significantly reduced radiation-induced intestinal injury index, fibrosis, and expression of α-SMA, TGF-β, and CTGF (all P<0.05). Oxidative stress assays showed that serum MDA levels were decreased, while T-SOD, T-AOC, and GSH-PX activities were significantly increased in the lycopene + radiation group (all P<0.05). The mRNA expression of inflammatory cytokines such as TNF-α and IL-6 was significantly downregulated (all P<0.05), while pro-apoptotic protein expression was reduced and anti-apoptotic protein expression was upregulated (all P < 0.05) in the lycopene + radiation group. Conclusions:Lycopene significantly alleviates ionizing radiation-induced intestinal injury through its antioxidant, anti-inflammatory, and anti-apoptotic effects, making it a promising agent for the prevention and treatment of radiation-induced intestinal injury.

Objective:To investigate the effect of aucubin(AU)on mitochondrial autophagy in the hippocampus of ischemic stroke(IS)rats by regulating the pten-induced kinase protein 1(PINK1)/cytoplasmic E3-ubiquitin ligase(Parkin)signaling pathway.Methods:The IS rat model was established by middle cerebral artery occlusion(MCAO),and was randomly divided into IS group,low-dose AU group(AU-L),medium-dose AU group(AU-M),high-dose AU group(AU-H),and high-dose AU combined with 3-MA group(AU-H+3-MA).The rats without liga-tion were used as the Sham surgery group.Zea Longa score was used to evaluate the neurological function of rats.TTC staining was used to detect the percentage of cerebral infarction volume.The microstructures of mitochondria were observed by transmission electron microscopy,and the changes of autophagy protein-microtubule associated protein light chain 3B(LC3B)and p62 were detected by immunohistochemistry.Hippocampal apoptosis was detected by TUNEL.PINK1/Parkin-related protein expression in hippocampus was detected by Western blot.Results:Neurological function score of IS rats was increased(P＜0.05),cerebral infarction was observed by TTC staining,the expression of mito-chondrial autophagy protein p62 in hippocampus was up-regulated(P＜0.05),the expression of LC3B was down-regu-lated(P＜0.05),the number of autophagosomes was decreased(P＜0.05),and apoptosis in hippocampus was in-creased(P＜0.05),the expression of PINK1 and ARKIN protein in hippocampus was down-regulated(P＜0.05).After AU intervention,the neural function score of rats was decreased,the percentage of cerebral infarction volume was reduced,the positive expression of p62 in hippocampus was down-regulated(P＜0.05),the positive expression of LC3B was up-regulated(P＜0.05),and the number of autophagosomes was increased(P＜0.05),the apoptosis of hippocampus was decreased(P＜0.05),and the expression of PINK1 and ARKIN protein in hippocampus was in-creased(P＜0.05).3-MA blocked the therapeutic effect of AU and aggravated the nerve injury in rats.Conclusion:AU promotes hippocampal mitochondrial autophagy and improves neurological damage in IS rats by activating the PINK1/Parkin signaling pathway.

Objective:To use machine learning to predict the efficacy of accelerated corneal collagen cross-linking (A-CXL) surgery, identify prognostic factors, and construct models to predict postoperative disease progression.Methods:A single-center retrospective study was conducted.A total of 82 keratoconus patients (112 eyes) who underwent A-CXL surgery at the West China Hospital of Sichuan University between March and December 2021 were enrolled.Preoperative and follow-up examinations included anterior segment evaluation by slit-lamp microscopy, corneal topography using Pentacam, and corneal biomechanical indices using Corvis ST.Disease progression was defined as an increase in maximum keratometry (Kmax) of ≥1 D from the preoperative level at the last follow-up.Various machine learning algorithms were employed to analyze corneal topography, biomechanical parameters and corneal densitometry values to identify prognostic factors and construct models for predicting postoperative disease progression.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of West China Hospital, Sichuan University (No.2023496).Written informed consent was obtained from each subject.Results:During follow-up, 15.1% (17/112) of the eyes showed progression after A-CXL.The preoperative astigmatism and stress-strain index (SSI) in the progression group were (-5.41±2.72)D and 1.41±0.78, respectively, which were significantly higher than (-3.30±2.54)D and 0.95±0.98 in the non-progression group ( t=2.80, 2.03; both P<0.05).Cox regression analysis identified preoperative astigmatism (hazard ratio [HR]=1.20), SSI (HR=1.10), and anterior corneal densitometry of 2-6 mm (CDA6) (HR=2.10) as significant risk factors for post-A-CXL progression.Among various machine learning models developed and validated, the area under the curve (AUC) values for logistic regression, multilayer perceptron (MLP) model, and random forest (RF) exceeded 0.700.For F1-score, the AUC values for logistic regression, MLP, and RF were 0.870, 0.880, and 0.880, respectively.The network structure of the visualized MLP was a single-layer, 24-neurons neural network with 80% accuracy in predicting whether progression occurred after A-CXL.The clinical nomogram developed in conjunction with astigmatism, SSI, and CDA6 predicted the cumulative probability of progression at 0.5, 1, and 2 years postoperatively based on the sum of the specified values for each variable, and based on the optimal cutoff value, keratoconus corneas could be classified into high-, intermediate-, and low-risk groups, respectively.The time-dependent subject operating characteristic curves of the nomogram showed AUCs of 0.734, 0.685, and 0.935 at 0.5, 1, and 2 years postoperatively, respectively, all of which performed well in predicting progression. Conclusions:Preoperative astigmatism, SSI, and CDA6 are significant risk factors for post-A-CXL progression in keratoconus.The MLP model can accurately predict postoperative disease progression, and the clinical nomogram combining preoperative astigmatism, SSI, and CDA6 can effectively differentiate between low-, medium-, and high-risk postoperative progression outcomes.

Objective:To use machine learning to predict the efficacy of accelerated corneal collagen cross-linking (A-CXL) surgery, identify prognostic factors, and construct models to predict postoperative disease progression.Methods:A single-center retrospective study was conducted.A total of 82 keratoconus patients (112 eyes) who underwent A-CXL surgery at the West China Hospital of Sichuan University between March and December 2021 were enrolled.Preoperative and follow-up examinations included anterior segment evaluation by slit-lamp microscopy, corneal topography using Pentacam, and corneal biomechanical indices using Corvis ST.Disease progression was defined as an increase in maximum keratometry (Kmax) of ≥1 D from the preoperative level at the last follow-up.Various machine learning algorithms were employed to analyze corneal topography, biomechanical parameters and corneal densitometry values to identify prognostic factors and construct models for predicting postoperative disease progression.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of West China Hospital, Sichuan University (No.2023496).Written informed consent was obtained from each subject.Results:During follow-up, 15.1% (17/112) of the eyes showed progression after A-CXL.The preoperative astigmatism and stress-strain index (SSI) in the progression group were (-5.41±2.72)D and 1.41±0.78, respectively, which were significantly higher than (-3.30±2.54)D and 0.95±0.98 in the non-progression group ( t=2.80, 2.03; both P<0.05).Cox regression analysis identified preoperative astigmatism (hazard ratio [HR]=1.20), SSI (HR=1.10), and anterior corneal densitometry of 2-6 mm (CDA6) (HR=2.10) as significant risk factors for post-A-CXL progression.Among various machine learning models developed and validated, the area under the curve (AUC) values for logistic regression, multilayer perceptron (MLP) model, and random forest (RF) exceeded 0.700.For F1-score, the AUC values for logistic regression, MLP, and RF were 0.870, 0.880, and 0.880, respectively.The network structure of the visualized MLP was a single-layer, 24-neurons neural network with 80% accuracy in predicting whether progression occurred after A-CXL.The clinical nomogram developed in conjunction with astigmatism, SSI, and CDA6 predicted the cumulative probability of progression at 0.5, 1, and 2 years postoperatively based on the sum of the specified values for each variable, and based on the optimal cutoff value, keratoconus corneas could be classified into high-, intermediate-, and low-risk groups, respectively.The time-dependent subject operating characteristic curves of the nomogram showed AUCs of 0.734, 0.685, and 0.935 at 0.5, 1, and 2 years postoperatively, respectively, all of which performed well in predicting progression. Conclusions:Preoperative astigmatism, SSI, and CDA6 are significant risk factors for post-A-CXL progression in keratoconus.The MLP model can accurately predict postoperative disease progression, and the clinical nomogram combining preoperative astigmatism, SSI, and CDA6 can effectively differentiate between low-, medium-, and high-risk postoperative progression outcomes.