AIM: To investigate variation patterns of corneal biomechanical parameters and binocular symmetry among children of different genders aged 8-16 years.METHODS:A retrospective study was conducted, and children who underwent optometric examinations at the ophthalmology department of our hospital were enrolled between January 2022 and December 2024. Measurements included the flat keratometry(K1), steep keratometry(K2), and mean curvature(Km)of the anterior corneal surface, horizontal visible iris diameter(HVID), central corneal thickness(CCT), corneal endothelial cell density(CECD), average cell size(ACS), coefficient of variation(CV), and hexagonality(HEX). Corneal parameters and binocular differences were compared between genders and across age groups.RESULTS:A total of 621 children(1 242 eyes)were enrolled in this study, including 284 males(568 eyes), 337 females(674 eyes), 528 children aged 8-12 years(1 056 eyes), and 93 children aged 13-16 years(186 eyes). In children aged 8-16 years, the K1, K2, Km and CV of both eyes, as well as the interocular CCT differences in boys were significantly lower than those in girls(all P<0.05), while the HVID and HEX of both eyes, as well as the CCT of the left eye in boys were significantly higher than those in girls(all P<0.05). Children aged 8-12 years had significantly higher K1, Km, CECD and HEX in both eyes, and significantly lower ACS in both eyes than those aged 13-16 years(all P<0.05). K1, K2, Km, CECD and HEX in both eyes were negatively correlated with age(P<0.05); ACS in both eyes was positively correlated with age(P<0.001); K1 and Km of the right eye were positively correlated with the CECD of the right eye(P<0.05), and K1 and CCT of the left eye were positively correlated with the CECD of the left eye(P<0.05).CONCLUSION:Significant gender differences exist in corneal parameters among children aged 8 to 16 years, while binocular symmetry remained stable.

Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

Objective To investigate the protective effect and underlying mechanisms of HydroMg, a novel sustained-release hydrogen donor, in a model of doxorubicin (DOX)-induced chronic cardiotoxicity. Methods H9C2 cells were treated with 1 μmol/L DOX and/or 1 μg/mL HydroMg, and mitochondrial membrane potential, reactive oxygen species (ROS) levels, and apoptosis were measured. In the animal experiment, mice were divided into control, HydroMg, DOX, and DOX＋HydroMg groups. The HydroMg group received intraperitoneal injection of HydroMg (100 mg/kg). Chronic cardiotoxicity was established by intraperitoneal injection of DOX (5 mg/kg every week) for four consecutive weeks; In the DOX＋HydroMg group, HydroMg (100 mg/kg) was administered intraperitoneally 4–5 h prior to each DOX injection. Cardiac function and remodeling were evaluated by echocardiography and heart weight index (HWI). The long-term survival of mice were analyzed. Subsequently, transcriptome sequencing was performed on myocardial tissues from the DOX group to identify key molecular alterations compared with controls. Results At the cellular level, HydroMg treatment effectively reversed DOX-induced mitochondrial dysfunction and oxidative stress, as evidenced by restored membrane potential, reductions in total ROS and mitochondrial superoxide levels by approximately 30% and 9%, respectively, and a decrease in the apoptosis rate from 34.13% to 18.27%. In the animal model, compared with the DOX group, HydroMg intervention increased left ventricular ejection fraction (LVEF) and fractional shortening (LVFS) by 9.62% and 5.82%, respectively, attenuated the reduction in HWI (4.41 mg/mm vs 3.53 mg/mm), and improved the 4-week survival rate (80% vs 60%). Transcriptomic analysis revealed that the core molecular features of DOX-induced cardiotoxicity, including widespread suppression of oxidative phosphorylation and antioxidant pathways. Conclusions HydroMg protects against DOX-induced chronic cardiotoxicity by alleviating oxidative stress and improving mitochondrial function, and provides a potential therapeutic strategy against DOX-related cardiotoxicity.

Objective To investigate the improvement effects of homogeneous fecal microbiota transplantation(FMT)on chemotherapy-induced diarrhea(CID)in mice.Methods Fifteen C57BL/6N mice were divided into control group,CID model group and CID+FMT group according to the random number distribution and remainder grouping method,with 5 mice per group.Control group received no intervention,and their feces were used to prepare fecal bacteria suspension.CID model group was injected intraperitoneally with fluorouracil(65 mg/kg)for 5 consecutive days to construct the CID mouse model,followed by gavage with 0.1 ml of saline on alternate days.CID+FMT group was given 0.1 ml fecal bacteria suspension gavage on alternate days for one week,followed by intraperitoneal injection of fluorouracil(65 mg/kg)for 5 consecutive days to construct the CID mouse model,with the experiment ending on the 14th day.During the experiment,the mice's food intake and body weight were recorded.At the end of the experiment,the mice were euthanized with deep carbon dioxide anesthesia,and the mice colonic specimens from cecum to anus were collected for hematoxylin and eosin(HE)staining and histopathological examination.Fecal samples were collected for 16S rRNA gene sequencing.Shannon index,Simpson index and Chao1 algorithm were used to analyze the α-diversity species of the intestinal flora in each group of mice.Similarity analysis(Anosim)was used to perform non-parametric on the inter-group differences of intestinal flora among the mice.Linear discriminate analysis size effect(LEfSe)and nonmetric multidimensional scaling(NMDS)were employed to analyze the intestinal dominant flora and the similarity classification relationships in each group of mice.Results The colonic specimen's length from cecum to anus in CID model group was significantly shorter than that in control group(P<0.05),while there was no significant difference between CID+FMT group and CID model group(P>0.05).The weight of mice in CID model group decreased by 42.04%,while control group mice gained 10.24%,with a significant difference between the two groups(P<0.05).The weight of mice in CID+FMT group decreased by 8.12%,which was significantly improved compared to CID model group(P<0.05).HE staining results revealed the intestinal mucosal structure in CID model group was severely damaged,with atrophy and deformation,accompanied by inflammatory cell infiltration,and the pathological score was higher than that of control group(P<0.05).Compared with CID model group,the intestinal mucosal integrity and crypt cells in the CID+FMT group were improved,with less damage,and the pathological score was lower than that of CID model group,but the difference was not statistically significant(P>0.05).The α-diversity analysis showed that there were significant differences in the Shannon,Simpson and Chao1 indices among the three groups(P<0.05).ANOSIM and NMDS analysis revealed that the intestinal flora in CID+FMT group was closer to the normal intestinal flora compared to CID model group.LEfSe analysis showed that the intestinal flora in CID model group was enriched in famliy_Bacteroidaceae,and the intestinal flora in CID+FMT group was similar to that of control group,with an enrichenment of familiy_Enterobacteriaceae.Conclusion Homogeneous FMT can improve the abundance of intestinal flora in CID mice,making it more similar to normal intestinal flora,thereby protecting intestinal mucosa,reducing damage and alleviating the severity of CID.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Alzheimer's disease(AD),a neurodegenerative disorder,manifests pathological changes in the brain even during the asymptomatic stage.As the pathological burden intensifies,patients experience functional decline in multiple cognitive domains,including memory,language,spatial perception,executive function,and calculation,and may also exhibit emotional abnormalities.Once AD progresses,treatment becomes extremely chal-lenging.Therefore,early diagnosis and accurate prediction of disease conversion are core tasks in the prevention and treatment of AD,and they are also urgent scientific research challenges to be overcome.Deep learning(DL)models demonstrate considerable advantages in the diagnosis,prediction,classification,and feature extraction of AD,offering new hope for solving this challenging problem.This research commences with a concise introduction to the outcomes of AD and the fundamental knowledge of deep learning.Subsequently,it offers an overview of the imaging studies on the utilization of deep learning for predicting disease transformation from two perspectives.Firstly,it systematically summarizes the existing DL models that have demonstrated innovation in the classification and prediction performance of AD.Secondly,it provides a comprehensive outline of the DL fusion models applied to the diagnosis,classification,and prediction of AD.Finally,this paper expounds upon the impending challenges in the research of this domain.This article demonstrates that deep learning models is cutting-edge trends in the ex-ploration of AD research.

Objective:The aim of this study is to re-evaluate the systematic reviews and meta-analyses on statins for the treat-ment of erectile dysfunction(ED)and construct an umbrella review,thereby providing robust evidence-based for the clinical applica-tion of statins in ED treatment.Methods:A comprehensive computerized search was conducted across CNKI,Wanfang Database,VIP,WOS,Embase,PubMed,and Cochrane Library databases from their inception to September 12,2024,for all systematic reviews and meta-analyses addressing statin interventions in ED.The methodological quality,reporting quality,and evidence quality of the in-cluded studies were assessed and summarized using PRISMA 2020,AMSTAR 2,and GRADE systems.Results:Four systematic re-views and meta-analyses were included.According to the AMSTAR 2 evaluation,one paper was rated as low quality,while the remai-ning three were classified as very low quality.PRISMA 2020 evaluation results indicated that the average score of the four included studies was 29,with all being of medium quality but exhibiting partial deficiencies.The proportion of fully consistent items across the four studies ranged from 52.38％to 80.95％.GRADE system tool evaluation revealed 11 outcome indicators,of which only one was rated as intermediate evidence.The remainders were categorized as low or very low evidence,with no high-quality evidence identified.Conclusion:Statins demonstrate efficacy in treating ED.However,the current quality of relevant systematic reviews is suboptimal,with notable deficiencies in methodological,reporting,and evidential quality.Further high-quality studies are warranted to provide more reliable evidence-based medical guidance for clinical practice.

Objective To explore the feasibility and corresponding implementation methods of constructing a sample resource bank based on individual-level data of completed clinical trials and using it to construct external controls for drug/device clinical trials.Methods Taking the pre-marketing clinical trial of transcatheter active valve replacement(TAVR)for the treatment of aortic valve stenosis as an example,the individual-level databases of multiple trials were standardized to form a sample bank.The original data of any trial in the sample bank were selected as the experimental group,and the remaining samples were selected as the control group.The potential confounding was handled by using the propensity score matching and stratification methods to clarify the process of constructing external controls based on the sample bank of individual-level data of clinical trials.Results This study included individual-level data of single-group trials of 4 TAVR devices,with a total of 569 subjects(59.2%male).The number of subjects in Trials 1 to 4 was 120,120,163,and 166,respectively.Propensity score matching enabled the matching of 113,117,125,and 147 subjects with comparable or similar characteristics from individual-level data from other trials,respectively,demonstrating a high matching success rate.The PS score distribution plot after stratification showed that the proportions of subjects in the experimental and control groups in strata 1 to 5 in scheme 1 were 4/103,11/103,22/92,32/87,and 51/64,respectively.For all constructed external controlled trials,a certain number of control samples with similar baseline characteristics to the experimental groups were distributed within each propensity score stratum.The results of the simulation test also reflected the potential differences between different devices in the 12-month all-cause mortality rate.Conclusions The sample bank constructed with individual-level data from clinical trials,as a high-quality data source,can serve as a source of external control for single-arm trials in the same field,and as a useful supplement to the external control scenario of real-world evidence to support drug and device development.At the same time,targeted research on research methods and bias control measures in related fields is also needed.

Objective To analyze the characteristics of methadone-related poisoning cases and provide a reference for forensic identification.Methods A total of 71 cases of methadone-related poisoning re-ported from 1998 to 2023 in China and 26 cases of methadone-related deaths reported from 2013 to 2018 in Italy were retrieved from databases including PubMed,Wanfang and CNKI.The general infor-mation,forensic pathological and toxicological characteristics were analyzed.Results Among the 71 methadone-related poisoning cases in China,there were 54 cases(76.06%)of poisoning without death and 17 cases(23.94%)of death from poisoning.There were 54 male cases(76.06%),and 51 cases(71.83%)aged 19 to 39 years old.There were 35 cases(49.30%)of poisoning caused by methadone alone,and 32 cases(45.07%)were poisoning caused by methadone combined with other substances or drugs including heroin and benzodiazepines.Most of the poisoned showed coma,respiratory depres-sion and miosis.Signs of asphyxia were often found by autopsy.The mass concentration of methadone detected in the blood of 6 deceased ranged from 0.112 to 3.000 mg/L.Among the 26 methadone-related deaths in Italy,22 cases were male(84.62%).There were 6 cases(23.08%)caused by methadone alone,and 20 cases(76.92%)died from methadone combined with other substances or drugs.The mass concentration of methadone in blood ranged from 0.181 to 4.059 mg/L.Conclusion The propor-tions of poisoning cases caused by methadone alone and methadone combined with other substances or drugs are comparable in China.The majority of deceased caused by methadone poisoning shows typi-cal triad of coma,respiratory depression and miosis,which helps forensic experts determine the cause of death related to methadone.Additionally,it is necessary to increase the routine testing of the con-centration of methadone and its combined substances or drugs in deceased,and collect data for the in-terpretation of the results of related cases.

Objective To evaluate the forensic application value of used dental floss as a source of bio-logical evidence for individual identification by analyzing the effects of dental floss sample collection methods,DNA extraction methods,preservation conditions,and sampling sites on the success rate of STR typing.Methods Dental floss samples were collected using three techniques:direct cutting,cotton swab wiping,and flocked swab wiping,respectively.DNA was extracted respectively by the Chelex,spin column-based and magnetic bead-based methods.DNA quantification and STR typing were per-formed using the Qubit kit and FGI HumDNA Typing kit(Platinum),respectively.Storage environ-ments(temperature and humidity,ultraviolet radiation)and sampling locations(the floss part,the handle part)on DNA quantity and STR typing were evaluated.Results Through conducting a statisti-cal analysis of three key indicators of average DNA mass concentration,STR locus detection rate,and typing accuracy rate,the direct cutting method demonstrated the highest efficacy,followed by cotton swab wiping mothed,and the flocked swab wiping method had the lowest efficacy.Direct cutting yielded an average DNA mass concentration greater than(4.94±1.87)ng/μL,with STR locus detection and accuracy rates of 100%.Bead-based DNA extraction method produced superior DNA concentration and quality compared to spin column-based and Chelex methods,regardless of whether the sampling technique used.Preservation conditions had a significant impact on the DNA analysis of samples.Par-ticularly,the STR typing accuracy of samples preserved at 55℃/50%RH for 35 days dropped to(81.82±12.31)%,and that of samples exposed to ultraviolet radiation for 12 h dropped to(55.46±34.31)%.DNA concentration from the handle part of dental floss was extremely low,with an STR typing accuracy of only(30.91±27.35)%.Conclusion Using cotton swabs to wipe or directly cutting the thread of dental floss samples,and combining this approach with the magnetic bead method for DNA extraction,can best guarantee the concentration and quality of DNA.In addition,samples should be stored in low-temperature,low-humidity environment,protected from light and ultraviolet radiation.