To develop and validate a nomogram incorporating postoperative blood pressure and other multifactorial predictors for the risk of delayed cerebral ischemia(DCI) following surgical clipping in patients with aneurysmal subarachnoid hemorrhage(aSAH).

This retrospective cohort study consecutively enrolled 272 aSAH patients who underwent aneurysm clipping at the Department of Neurosurgery, Second Affiliated Hospital of Chongqing Medical University from January 2018 to January 2022. Demographic, clinical, and imaging data were collected. Predictors were screened using LASSO regression, and a multifactorial logistic regression-based nomogram was constructed. The dataset was randomly divided into training(n=190) and validation(n=82) sets at a 7∶3 ratio. Model discrimination, calibration, and clinical utility were evaluated using the area under the receiver operating characteristic curve(AUC), calibration curves, and decision curve analysis(DCA), respectively.

Among 272 enrolled patients, 98(36%) developed DCI. Multivariate analysis identified age(OR=0.97; 95%CI: 0.94~0.99; P=0.036), World Federation of Neurological Surgeons(WFNS) grade(OR=1.36; 95%CI: 1.02~1.82; P=0.038), Fisher grade(OR=1.44; 95%CI: 1.01~2.05; P=0.048), and mean arterial pressure on postoperative day 2(OR=1.06; 95%CI: 1.03~1.09; P<0.001) as independent risk factors for DCI. The model achieved C-indices of 0.739 (95%CI : 0.668~0.810) in the training set and 0.760 (95%CI: 0.647~0.872) in the validation set. Calibration curves demonstrated high agreement between predicted and observed probabilities(mean absolute error=0.027), while DCA confirmed significant net clinical benefit at threshold probabilities of 15%~65%.

We successfully developed a predictive model incorporating age, WFNS grade, Fisher grade, and postoperative day 2 mean arterial pressure, with elevated postoperative blood pressure identified as an early critical indicator for DCI development.

To investigate the efficacy of low-frequency repetitive transcranial magnetic stimulation (rTMS) combined with vestibular rehabilitation training (VRT) for persistent postural-perceptual dizziness (PPPD).

In this retrospective case-control study, 48 PPPD patients admitted to our rehabilitation center (September 2023 to September 2024) were divided into control group (n=24, VRT only) and study group (n=24, VRT + rTMS). Assessments at baseline and post-treatment included Dizziness Handicap Inventory (DHI), Vestibular Symptom Index (VSI), Hamilton Depression Rating Scale (HAMD), Pittsburgh Sleep Quality Index (PSQI), Numeric PPPD Questionnaire (NPQ), and overall response rate.

After 6 weeks, the study group showed significantly higher overall response rate compared to control group (91.67% vs 66.67%, P=0.033). The study group demonstrated significantly lower scores than control group: DHI (37.85±6.46 vs 48.53±7.54, P=0.007), VSI (3.85±0.46 vs 5.53±1.54, P=0.002), HAMD (10.20±6.30 vs 15.74±7.05, P=0.006), PSQI (6.24±1.88 vs 8.89±2.79, P=0.003), and NPQ (15.44±3.26 vs 20.81±9.14, P=0.009).

‍Combined low-frequency rTMS and VRT effectively alleviates dizziness symptoms and improves treatment efficacy in PPPD patients.

To analyze clinical characteristics affecting survival outcomes in gastric adenocarcinoma (GAC) patients with second primary malignancies (SPM) and construct a predictive model with a web-based calculator.

Patients diagnosed with GAC between January 2010 and December 2017 in the SEER database (n=24 085) were analyzed, comparing non-SPM (n=22 963) and SPM cohorts (n=1 122). SPM patients were randomized (3:1) into training (n=842) and internal validation cohorts (n=280). Univariate/multivariate Cox regression identified prognostic factors for model construction. Model performance was evaluated via ROC curves, calibration plots, and decision curve analysis (DCA). A web-based calculator was deployed using DynNom (https://kunma697.shinyapps.io/dynnomapp-1/). External validation used 192 SPM patients diagnosed at Yantai Yuhuangding Hospital (2010-2017).

χ² tests revealed SPM patients had higher age (56.3%), earlier T-stage (T1:29.2%; T2:10.5%), predominant gastric cardia involvement (43.7%), fewer distant metastases (12.3%), and higher rates of radiotherapy (32.5%) and surgery (77.2%) vs. non-SPM (P<0.05). Cox analyses identified GAC primary site, T-stage, SEER stage, radiotherapy/surgery history, plus SPM grade/stage/treatment history as significant predictors (P<0.05). AUCs in the training cohort were 0.771 (95%CI:0.722~0.820), 0.839 (95%CI:0.796~0.882), and 0.836 (95%CI: 0.792~0.879) for 1-/3-/5-year survival; internal validation showed 0.751 (95%CI: 0.700~0.801), 0.746 (95%CI: 0.695~0.797), and 0.772 (95%CI: 0.723~0.821); external validation yielded 0.713 (95%CI: 0.648~0.778), 0.805 (95%CI: 0.749~0.861), and 0.851 (95%CI: 0.801~0.901). Calibration indicated high prediction-actuality concordance; DCA confirmed clinical utility.

The model and web calculator incorporating GAC/SPM characteristics effectively predict SPM patient prognosis.

To evaluate the predictive value of deep learning features from chest CT images combined with clinical and radiomics features for epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC).

This case-control study retrospectively analyzed clinical and imaging data of 1 070 NSCLC patients from radiology departments at three hospitals (January 2013 to October 2023). Patients were divided into: a training set (n=502) and internal validation set (n=217) via 7∶3 randomization of 719 cases from the First Affiliated Hospital of Army Medical University; external validation set 1 (n=173) from General Hospital of Eastern Theater Command; external validation set 2 (n=178) from Daping Hospital of Army Medical University. Deep learning features were extracted using a 2.5D convolutional neural network (CNN) with ResNet101 backbone, radiomics features were derived from CT images, and clinical risk factors were identified to construct models. An integrated model combined deep learning, clinical, and radiomics features. All four models were developed using random forest (RF) classifiers. Calibration curves assessed goodness-of-fit, and decision curve analysis (DCA) evaluated clinical utility.

The deep learning model achieved AUCs of 0.833 7 (95%CI: 0.770 6~0.884 7), 0.815 1 (0.741 6~0.882 8), and 0.810 1 (0.745 2~0.873 6) in the internal and two external validation sets, respectively. Clinical models yielded AUCs of 0.731 0 (0.660 2~0.802 1), 0.746 0 (0.666 4~0.824 9), and 0.813 4 (0.743 1~0.883 6); radiomics models showed AUCs of 0.762 4 (0.692 4~0.825 1), 0.745 4 (0.671 1~0.814 3), and 0.724 7 (0.639 7~0.801 6). The integrated model demonstrated optimal performance with AUCs of 0.905 5 (0.857 0~0.945 4), 0.832 7 (0.763 3~0.896 4), and 0.889 0 (0.834 4~0.934 3). DCA indicated significant net benefit for EGFR prediction at threshold probabilities of 0.15~0.85 using the integrated model.

Deep learning features from CT images effectively predict EGFR mutation status in NSCLC. The integrated model combining deep learning, clinical, and radiomics features further enhances predictive performance.

To develop and validate a risk prediction model for infiltration/extravasation in peripheral intravenous catheter therapy.

This retrospective study analyzed 942 patients who completed the Infiltration/Extravasation Risk Assessment Form between January and June 2023 at the First Affiliated Hospital of Army Medical University (including Departments of Neurology, Endocrinology, Gastroenterology and Hepatobiliary Surgery). Patients were allocated to a derivation cohort (n=628) and validation cohort (n=314) in a 2∶1 ratio based on catheterization chronology. The derivation cohort served for model development and internal validation, while the validation cohort underwent external validation. Logistic scoring method constructed the risk model, with Hosmer-Lemeshow (HL) test assessing goodness-of-fit and ROC curve evaluating predictive performance. Twenty-one potential risk factors were assessed, including age, gender, chronic diseases, clinician experience, treatment compliance, and total infusion volume.

Infiltration/extravasation occurred in 48 cases (5.10% incidence: 31 derivation/17 validation). Among 21 factors, 15 showed significant association (P<0.05), with 6 independent predictors: junior high school education or below (OR=5.2), chronic disease history (OR=3.1), poor compliance (OR=2.8), lower extremity venipuncture (OR=4.1), total infusion ≥1 000 mL (OR=3.5), and hyperosmotic/corrosive medications (OR=6.7). The final prediction model was: Y=2×(low education)+1×(chronic disease)+1×(poor compliance)+1×(lower extremity puncture)+1×(volume ≥1 000 mL)+2×(corrosive agents). For the derivation cohort, AUC was 0.967 (95%CI: 0.936~0.998), specificity 0.911, sensitivity 0.935, with good calibration (χ²=4.135, P=0.845). Validation cohort showed AUC 0.939 (0.853~1.000), specificity 0.919, sensitivity 0.941, and acceptable calibration (χ²=8.998, P=0.085).

This model demonstrates excellent discriminative ability and calibration, providing an effective tool for identifying high-risk patients and guiding targeted preventive strategies.

To explore the callsal association between intrahepatic cholestasis of pregnancy (ICP) and offspring attention-deficit hyperactivity disorder (ADHD) and Tourette’s syndrome (TS) and its potential mechanisms.

Genome wide association study (GWAS) in public datasets was used to extract data. Among them, exposure was ICP (n=123 579), which stems from FinnGen dataset. Outcome was defined as ADHD, TS and other tic disorders (n=23 918), which is extracted from GWAS Catalog. Among mediators, total cholesterol in high-density lipoprotein (TC in HDL) were from the genetic map of the human plasma proteinome (n=21 558), and Obg-like ATPase 1 was from whole-genome study of circulating metabolites (n=3 301). In this study, we chose instrumental variables (IVs) that meets the Mendelian randomization (MR) hypothesis. When using two-sample MR, inverse variance weighted (IVW) was adopted as the primary method, and MR-Egger regression, weighted median, weighted mode, and simple mode were also utilized to analyse the robustness. Cochran’s Q test, MR-Egger intercept test and leave-one-out sensitivity analysis were performed to verify the reliability. Significant threshold was set up as P<0.05. When using two-step MR, the first step is two-sample MR from exposure to mediator, and the second step is multivariable MR (MVMR), which is from mediator to outcome. At this time, conditional F-statistic was adopted to test the strength of IVs. At last, product distribution test was applied to determine the significance of mediation effects.

ICP was significantly related to ADHD and TS as well as other tic disorders in offspring (IVW: OR=1.003, 95%CI: 1.000~1.006, P=0.035), and sensitivity analysis verified the robustness of the results. The potential positive mediators included TC in HDL [total effect (TE) =2.855×10^-3; mediated effect (ME) =8.628×10^-4; mediated proportion (MP) =30.217%, 95%CI: 0.878%~73.954%], and Obg-like ATPase 1 (TE=2.855×10^-3; ME=1.216×10^-3; MP=42.572%, 95%CI: 6.356%~90.195%).

ICP is possible to elevate the incidence rate of ADHD and TS and other tic disorders via reducing TC in HDL and Obg-like ATPase 1.

To investigate the role of p300 in lipid metabolism disorders.

Bioinformatics analysis was performed to analyze the expression patterns of p300 in lipid metabolism disorder-related diseases and its correlation with SREBP-1c and downstream lipid metabolic enzymes. Immunofluorescence assay was used to detect the expression of p300 in the liver tissues of the patients with varying disease severity of non-alcoholic fatty liver disease (NAFLD). A mouse model of lipid metabolism disorder was established in male C57BL/6J mice by feeding high-fat diet (HFD) for 12 weeks. Western blotting was employed to assess p300 expression level in the liver tissues of HFD-fed mice. A cell model of lipid metabolism disorder was established in HepG2/AML-12 cells induced with free fatty acid (FFA). The effects of siRNA-mediated knockdown of p300 was observed to measure the levels of intracellular total cholesterol (TC) and triglyceride (TG), lipid deposition, and production of reactive oxygen species (ROS).

Clinically, p300 was highly expressed in lipid metabolism disorders, and its level was positively correlated with NAFLD severity (P<0.05). Gene Set Enrichment Analysis (GSEA) revealed that p300 expression was significantly associated with fatty acid metabolism, cholesterol homeostasis, lipogenesis, PPAR signaling pathway, and peroxisome pathway. In vivo, p300 was significantly up-regulated in the livers of HFD-fed mice (P<0.01). In vitro, FFA stimulation markedly increased p300 expression in both HepG2 and AML-12 cells (P<0.01), whereas p300 knockdown significantly reduced intracellular TG and TC levels (P<0.01), attenuated lipid droplet accumulation, and reversed FFA-induced ROS elevation (P<0.01). Furthermore, p300 expression was positively correlated with the expression of SREBP-1c and its downstream key lipid synthesis enzymes.

p300 may promote hepatic lipid accumulation by acetylating and activating SREBP-1c and regulating downstream lipid metabolic enzymes, thereby affecting lipid synthesis and oxidative stress. These findings suggest that p300 may be a potential therapeutic target for lipid metabolism disorder-related diseases.

Investigate the expression level of discs large homolog associated protein 5 (DLGAP5) in oral squamous cell carcinoma (OSCC) and analyze its effects on cell proliferation, migration, invasion capacity, and the Warburg effect.

Bioinformatics analysis was performed to identify the potential therapeutic targets for OSCC. A total of 72 OSCC tissue samples and 40 adjacent non-cancerous tissue samples collected in the First Affiliated Hospital of Shihezi University from 2013 to 2024 were included, and the clinical pathological and prognostic data were collected from patients. Immunohistochemistry assay was applied to detect the protein expression of DLGAP5, and its association with clinical pathological features was analyzed. Kaplan-Meier survival curve was plotted for survival analysis, and Cox regression model was employed to analyze the prognostic factors. The expression of DLGAP5 at mRNA and protein levels was detected in HOK, SCC-9, SCC-15, SCC-25, and CAL-27 cell lines with RT-qPCR and Western blotting, respectively. Four small interfering RNAs (siRNAs) were designed to target the DLGAP5 sequence, and then based on the transfection efficiency, the sequence with optimal silencing effect was selected for subsequent functional studies. After DLGAP5 was silenced in the CAL-27 and SCC-15 cells, Western blotting was applied to detect the expression of hexokinase 2 (HK2) and enolase 1 (ENO1), CCK-8, scratch healing and Transwell assays were conducted to assess cell proliferation, migration, and invasion capabilities, and glucose, lactate, and ATP detection kits were utilized to determine the glycolytic metabolic levels in OSCC cells.

Bioinformatics analysis indicates that DLGAP5 is a potential key therapeutic target for OSCC. Experimental validation demonstrated that DLGAP5 was highly expressed in both OSCC tissues and cells (P<0.05). Analysis of clinical pathology and prognostic data revealed that DLGAP5 expression level was significantly correlated with tumor TNM stage, lymph node metastasis, and differentiation grade in OSCC patients, and high DLGAP5 expression was associated with poor prognosis (P<0.05). DLGAP5 silencing resulted in significantly reduced expression of HK2 and ENO1, markedly decreased levels of glycolytic metabolites (P<0.05), and notably declined cell proliferation, migration, and invasion capabilities (P<0.05).

DLGAP5 is highly expressed in OSCC. Silencing DLGAP5 may inhibit OSCC cell proliferation, migration, and invasion by indirectly regulating the Warburg effect, and the molecule is associated with poor prognosis in the OSCC patients.

To determine whether an intelligerct cloud platform follow-up model demonstrates superiority over conventional methods in enhancing follow-up quality, reducing costs, and improving functional recovery following total knee arthroplasty(TKA).

A retrospective cohort study was conducted on 260 patients undergoing TKA at our hospital from October 2022 to September 2023. According to the different postoperative follow-up methods, they were divided int a cloud platform group (n=130) and a traditional group (n=130). The baseline data, pre- and postoperative knee function scores, and follow-up costs were collected and compared between the 2 groups.

The cloud platform group exhibited significantly higher rate of follow-up satisfaction, reduced resource utilization, shorter per-follow-up duration, fewer accompanying persons per visit, lower total follow-up expenditures, and decreased cumulative follow-up time when compared with the traditional group (P<0.05). At 6 weeks, 3, 6, and 12 months postoperatively, better range of motion (ROM) was observed in the cloud-based group than the traditional group (P<0.05), but no intergroup differences were seen in other knee function scores.

Cloud platform follow-up enhances early postoperative ROM (6 weeks to 12 months) and demonstrates marked cost-effectiveness when compared to the conventional mode. It represents a viable alternative for post-TKA rehabilitation surveillance.

To explore the pharmacokinetic characteristics of sufentanil in individuals with normal body mass index (BMI), overweight BMI, and different CYP3A4/5 enzyme genotypes.

The patients receiving laparoscopic surgery under general anesthesia in the First Affiliated Hospital of Army Medical University from November 2020 to September 2021 were prospectively recruited in this study. Before the operation, the oral swabs were collected from all the patients for genotyping using the human CYP3A4/5 gene kit. Based on the potential impact of combination of their polymorphisms on sufentanil metabolism and the proportion of different genotype combinations of CYP3A4/5 enzymes, the patients were divided into groups I (3A4 homozygous mutation or 3A4 heterozygous mutation+3A5 homozygous mutation), II (3A4 heterozygous mutation + 3A5 heterozygous mutation), and III (3A4 wild type or 3A4 heterozygous mutation + 3A5 wild type). According to their BMI, they were also assigned into a normal body weight group (18.5~24.0 kg/m²) and an overweight group (24~<28 kg/m²), and the differences in drug metabolism parameters were statistically analyze between the 2 groups. After routine general anesthesia induction (sufentanil 0.5 μg/kg), venous blood samples were collected to detect the changes in its concentration using high performance liquid chromatography-mass spectrometry (HPLC-MS). The pharmacokinetic data of sufentanil were calculated between the normal BMI group and overweight group in all participants and between the 2 body weight groups among those with different genotype combinations.

Among the 90 participants completing the blood drug concentration test, 8 patients had their blood samples contaminated (including 1 case with an anesthesia duration of <2 h), and 3 were excluded due to low weight or overweight. Eventually, 79 participants were included in the pharmacokinetic analysis on the normal body weight group and the overweight group. Compared with the normal body weight group, the central compartment volume of distribution in the overweight group was significantly reduced (P<0.05), while no obvious differences were observed between the 2 groups in terms of peripheral compartment volume of distribution, total clearance rate, peripheral compartment clearance rate, distribution half-life, clearance half-life, and area under the blood concentration-time curve. In group Ⅰ (n=26), the overweight patients (n=13) had significantly reduced central compartment volume of distribution, peripheral compartment volume of distribution, and peripheral compartment clearance rate when compared with the normal body weight patients (n=13) (P<0.05), while no differences were observed in other pharmacokinetic parameters. In groups Ⅱ (n=25) and Ⅲ (n=28), the overweight patients and normal body weight patients had no statistical differences in all pharmacokinetic parameters.

Among the patients with the same genotype combination of CYP3A4/5 mutations, there was no difference in the metabolism of sufentanil between the overweight and normal weight patients. Additionally, in the population of 3A4 homozygous mutation or 3A4 heterozygous mutation+3A5 homozygous mutation, the overweight patients have smaller peripheral distribution range of sufentanil, and weakened metabolic process.