Objective:To analyze the risk factors for postoperative intra-abdominal pressure(IAP) elevation in patients with abdominal trauma and retroperitoneal tumors, and to evaluate the clinical value of continuous dynamic IAP monitoring.Methods:A total of 196 patients with abdominal trauma or retroperitoneal tumors admitted at Peking University People's Hospital from April 2024 to April 2025 were retrospectively enrolled. Postoperative IAP monitoring data were collected, and risk factors for IAP elevation were analyzed.Results:Postoperative IAP in patients with abdominal trauma and retroperitoneal tumors exhibited a peak-shaped pattern, reaching its maximum at 24 hours and returning to baseline by 72 hours. In both the abdominal trauma and retroperitoneal tumor groups, patients with poor outcomes showed significantly higher IAP peak values, longer durations of intra-abdominal hypertension (IAH), higher incidences of IAP>12 mmHg at 6 and 24 hours postoperatively, and longer durations of abdominal perfusion pressure (APP)<60 mmHg ( P<0.05).Multivariate analysis revealed that injury severity score (ISS)≥25, shock index≥1.0, and intraoperative blood transfusion≥2 000 ml were independent risk factors for IAP elevation in patients with abdominal trauma. In patients with retroperitoneal tumors, tumor diameter≥10 cm, intraoperative blood loss≥1 500 ml, peritoneal defect area≥20 cm2, and BMI≥28 kg/m2 were identified as significant risk factors for postoperative IAP elevation. Conclusions:Postoperative IAP in patients with abdominal trauma and retroperitoneal tumors exhibits a similar common dynamic pattern. Continuous dynamic monitoring of IAP can facilitate early identification of high-risk patients, with IAP>12 mmHg at 24 hours postoperatively showing the highest predictive value for adverse outcomes. For such patients, it is recommended to implement goal-directed monitoring for 72 hours to improve clinical prognosis.

Objective To identify causal effects and potential mechanisms of oxidative stress (OS)-related genes in lung cancer. Methods OS-related genes were extracted from the GeneCards database. Integration analysis of genome-wide association study (GWAS) data for lung cancer with gene expression and DNA methylation quantitative trait locus (QTL), including eQTL and mQTL in blood was performed using the summary data-based Mendelian randomization (SMR) approach to determine the causal relationship between OS-related genes and lung cancer risk. Colocalization analysis of OS-related gene QTL and lung cancer risk locus was performed to gain insight into the potential regulatory mechanisms of lung cancer risk. Results A total of 1 188 OS-related genes were obtained from the GeneCards database. A potential causal relationship between OS-related genes and lung cancer was identified by SMR analysis. AGER expression level [OR=1.944, 95%CI (1.431, 2.640), P<0.001], and ATF6B expression level [OR=1.508, 95%CI (1.287, 1.767), P<0.001] were associated with lung cancer risk. Meanwhile, ATF6B methylation level was also associated with lung cancer risk. Conclusion OS-related genes are associated with lung cancer, which may be a potential target of anti-cancer drugs.

Ursodeoxycholic acid(UDCA)is a naturally occurring,low-toxicity,and hydrophilic bile acid(BA)in the human body that is converted by intestinal flora using primary BA.Solute carrier family 7 member 11(SLC7A11)functions to uptake extracellular cystine in exchange for glutamate,and is highly expressed in a variety of human cancers.Retroperitoneal liposarcoma(RLPS)refers to liposarcoma originating from the retroperitoneal area.Lipidomics analysis revealed that UDCA was one of the most significantly down-regulated metabolites in sera of RIPS patients compared with healthy subjects.The augmentation of UDCA concentration(≥25 μg/mL)demonstrated a suppressive effect on the proliferation of liposarcoma cells.[15N2]-cystine and[13Cs]-glutamine isotope tracing revealed that UDCA impairs cystine uptake and glutathione(GSH)synthesis.Mechanistically,UDCA binds to the cystine transporter SLC7A11 to inhibit cystine uptake and impair GSH de novo synthesis,leading to reactive oxygen species(ROS)accumulation and mitochondrial oxidative damage.Furthermore,UDCA can promote the anti-cancer effects of ferroptosis inducers(Erastin,RSL3),the murine double minute 2(MDM2)inhibitors(Nutlin 3a,RG7112),cyclin dependent kinase 4(CDK4)inhibitor(Abemaciclib),and glutaminase inhibitor(CB839).Together,UDCA functions as a cystine exchange factor that binds to SLC7A11 for antitumor activity,and SLC7A11 is not only a new transporter for BA but also a clinically applicable target for UDCA.More importantly,in combination with other antitumor chemotherapy or physiotherapy treatments,UDCA may provide effective and promising treatment strategies for RLPS or other types of tumors in a ROS-dependent manner.

Ursodeoxycholic acid (UDCA) is a naturally occurring, low-toxicity, and hydrophilic bile acid (BA) in the human body that is converted by intestinal flora using primary BA. Solute carrier family 7 member 11 (SLC7A11) functions to uptake extracellular cystine in exchange for glutamate, and is highly expressed in a variety of human cancers. Retroperitoneal liposarcoma (RLPS) refers to liposarcoma originating from the retroperitoneal area. Lipidomics analysis revealed that UDCA was one of the most significantly downregulated metabolites in sera of RLPS patients compared with healthy subjects. The augmentation of UDCA concentration (≥25 μg/mL) demonstrated a suppressive effect on the proliferation of liposarcoma cells. [¹⁵N₂]-cystine and [¹³C₅]-glutamine isotope tracing revealed that UDCA impairs cystine uptake and glutathione (GSH) synthesis. Mechanistically, UDCA binds to the cystine transporter SLC7A11 to inhibit cystine uptake and impair GSH de novo synthesis, leading to reactive oxygen species (ROS) accumulation and mitochondrial oxidative damage. Furthermore, UDCA can promote the anti-cancer effects of ferroptosis inducers (Erastin, RSL3), the murine double minute 2 (MDM2) inhibitors (Nutlin 3a, RG7112), cyclin dependent kinase 4 (CDK4) inhibitor (Abemaciclib), and glutaminase inhibitor (CB839). Together, UDCA functions as a cystine exchange factor that binds to SLC7A11 for antitumor activity, and SLC7A11 is not only a new transporter for BA but also a clinically applicable target for UDCA. More importantly, in combination with other antitumor chemotherapy or physiotherapy treatments, UDCA may provide effective and promising treatment strategies for RLPS or other types of tumors in a ROS-dependent manner.

Objective To analyze the relationship between neuroticism and gastroesophageal reflux disease (GERD) using the Mendelian randomization (MR) method. Methods Exposure and outcome data were downloaded from the Integrative Epidemiology Unit (IEU) database in August 2023, including summary statistics from genome-wide association studies (GWAS) for neuroticism (n=374 323) and GERD (n=602 604). MR was conducted using the weighted median method, MR-Egger method, inverse variance weighted method, weighted mode method, and simple mode method. The causal relationship between the two was assessed using odds ratio (OR), and sensitivity analyses were performed to ensure the accuracy of the results. Results Neuroticism was associated with an increased risk of GERD [OR=1.229, 95%CI (1.186, 1.274), P<0.001]. Similarly, GERD was associated with an increased risk of neuroticism [OR=1.786, 95%CI (1.623, 1.965), P<0.001]. Conclusion There is a bidirectional causal relationship between neuroticism and gastroesophageal reflux disease.

Objective:To analyze the risk factors for postoperative intra-abdominal pressure(IAP) elevation in patients with abdominal trauma and retroperitoneal tumors, and to evaluate the clinical value of continuous dynamic IAP monitoring.Methods:A total of 196 patients with abdominal trauma or retroperitoneal tumors admitted at Peking University People's Hospital from April 2024 to April 2025 were retrospectively enrolled. Postoperative IAP monitoring data were collected, and risk factors for IAP elevation were analyzed.Results:Postoperative IAP in patients with abdominal trauma and retroperitoneal tumors exhibited a peak-shaped pattern, reaching its maximum at 24 hours and returning to baseline by 72 hours. In both the abdominal trauma and retroperitoneal tumor groups, patients with poor outcomes showed significantly higher IAP peak values, longer durations of intra-abdominal hypertension (IAH), higher incidences of IAP>12 mmHg at 6 and 24 hours postoperatively, and longer durations of abdominal perfusion pressure (APP)<60 mmHg ( P<0.05).Multivariate analysis revealed that injury severity score (ISS)≥25, shock index≥1.0, and intraoperative blood transfusion≥2 000 ml were independent risk factors for IAP elevation in patients with abdominal trauma. In patients with retroperitoneal tumors, tumor diameter≥10 cm, intraoperative blood loss≥1 500 ml, peritoneal defect area≥20 cm2, and BMI≥28 kg/m2 were identified as significant risk factors for postoperative IAP elevation. Conclusions:Postoperative IAP in patients with abdominal trauma and retroperitoneal tumors exhibits a similar common dynamic pattern. Continuous dynamic monitoring of IAP can facilitate early identification of high-risk patients, with IAP>12 mmHg at 24 hours postoperatively showing the highest predictive value for adverse outcomes. For such patients, it is recommended to implement goal-directed monitoring for 72 hours to improve clinical prognosis.

Objective To observe the value of follicular thyroid imaging reporting and data system(F-TIRADS)for differentiating benign and malignant follicular thyroid lesions.Methods Totally 502 patients with follicular thyroid lesions were retrospectively enrolled,including 104 patients with single malignant lesion(malignant group,containing 77 follicular thyroid carcinomas[FTC]and 27 follicular variant of papillary thyroid carcinomas[FVPTC])and 398 patients with 416 benign lesions(benign group,containing 197 follicular thyroid adenomas[FTA]and 219 thyroid adenomatous hyperplasia).Ultrasonic features of lesions were recorded,and F-TIRADS scores were assigned by 1 junior and 1 senior ultrasound physicians.Taken histopathology results as gold standard,receiver operating characteristic curve was drawn,the area under the curve(AUC)was calculated to evaluate the efficacy for differentiating benign and malignant follicular thyroid lesions using F-TIRADS.Results Significant differences of composition,internal echo,boundary,calcification and trabecular structure of lesions were found between groups(all P＜0.001).Taken F-TIRADS score≥ 7 as the optimal cut-off value,the sensitivity,specificity,accuracy,positive predictive value and negative predictive value for differentiating benign and malignant follicular thyroid lesions by the junior physician was 76.92％,77.40％,77.31％,93.06％and 45.98％,while by the senior physician was 78.84％,81.25％,80.76％,93.89％and 51.25％,respectively.The efficacy of the latter was higher than of the former(AUC was 0.827 and 0.859,respectively,P＜0.05).Conclusion F-TIRADS could effectively identifying benign and malignant follicular thyroid lesions.

Objective To explore the value of improved ResNet18 lightweight deep learning(DL)models for automatically detecting gouty arthritis(GA)based on ultrasonogram of the first metatarsophalangeal joint(MTP1).Methods A total of 2 401 ultrasonograms obtained from 260 patients with suspected gout who underwent MTP1 ultrasound examination were included and divided into training set(1 910 ultrasonograms from 209 cases)and test set(491 ultrasonograms from 51 cases)at the ratio of 4∶1.GA lesions on ultrasonograms were manually labeled.After preprocessing,ResNet18 lightweight network was used to construct DL models for identifying the ultrasonogram category was normal or abnormal(with any manifestation of GA).Five-fold cross-validation method was adopted to evaluate the efficacy of the DL models constructed with 2,3,4 or 6 residual blocks,i.e.model 1,2,3 and 4,respectively,and the computational cost and the amount of parameters of each model were recorded.The efficacy of the models were verified using test set,and the best DL model was screened.Results The computational cost of model 1,2,3 and 4 was 7 558.27,2 963.73,4 012.33 and 6 093.39 M,respectively,while the amount of parameters was 4.61,4.91,4.91 and 5.28 M,respectively.Model 2 had the least computational cost with parameters only slightly more than model 1.In test set,no significant difference of accuracy nor the area under the curve was found among 4 models(all P＞0.05).The sensitivity of model 2 was higher than that of model 3,while its specificity was lower only than that of model 3(both P＜0.05),hence model 2 was the best DL model.Conclusion Improved ResNet18 lightweight DL models could be used for automatically detecting GA based on ultrasonogram of MTP1,among which model 2 was the best one.

Objective To observe the value of follicular thyroid imaging reporting and data system(F-TIRADS)for differentiating benign and malignant follicular thyroid lesions.Methods Totally 502 patients with follicular thyroid lesions were retrospectively enrolled,including 104 patients with single malignant lesion(malignant group,containing 77 follicular thyroid carcinomas[FTC]and 27 follicular variant of papillary thyroid carcinomas[FVPTC])and 398 patients with 416 benign lesions(benign group,containing 197 follicular thyroid adenomas[FTA]and 219 thyroid adenomatous hyperplasia).Ultrasonic features of lesions were recorded,and F-TIRADS scores were assigned by 1 junior and 1 senior ultrasound physicians.Taken histopathology results as gold standard,receiver operating characteristic curve was drawn,the area under the curve(AUC)was calculated to evaluate the efficacy for differentiating benign and malignant follicular thyroid lesions using F-TIRADS.Results Significant differences of composition,internal echo,boundary,calcification and trabecular structure of lesions were found between groups(all P＜0.001).Taken F-TIRADS score≥ 7 as the optimal cut-off value,the sensitivity,specificity,accuracy,positive predictive value and negative predictive value for differentiating benign and malignant follicular thyroid lesions by the junior physician was 76.92％,77.40％,77.31％,93.06％and 45.98％,while by the senior physician was 78.84％,81.25％,80.76％,93.89％and 51.25％,respectively.The efficacy of the latter was higher than of the former(AUC was 0.827 and 0.859,respectively,P＜0.05).Conclusion F-TIRADS could effectively identifying benign and malignant follicular thyroid lesions.

Objective To explore the value of improved ResNet18 lightweight deep learning(DL)models for automatically detecting gouty arthritis(GA)based on ultrasonogram of the first metatarsophalangeal joint(MTP1).Methods A total of 2 401 ultrasonograms obtained from 260 patients with suspected gout who underwent MTP1 ultrasound examination were included and divided into training set(1 910 ultrasonograms from 209 cases)and test set(491 ultrasonograms from 51 cases)at the ratio of 4∶1.GA lesions on ultrasonograms were manually labeled.After preprocessing,ResNet18 lightweight network was used to construct DL models for identifying the ultrasonogram category was normal or abnormal(with any manifestation of GA).Five-fold cross-validation method was adopted to evaluate the efficacy of the DL models constructed with 2,3,4 or 6 residual blocks,i.e.model 1,2,3 and 4,respectively,and the computational cost and the amount of parameters of each model were recorded.The efficacy of the models were verified using test set,and the best DL model was screened.Results The computational cost of model 1,2,3 and 4 was 7 558.27,2 963.73,4 012.33 and 6 093.39 M,respectively,while the amount of parameters was 4.61,4.91,4.91 and 5.28 M,respectively.Model 2 had the least computational cost with parameters only slightly more than model 1.In test set,no significant difference of accuracy nor the area under the curve was found among 4 models(all P＞0.05).The sensitivity of model 2 was higher than that of model 3,while its specificity was lower only than that of model 3(both P＜0.05),hence model 2 was the best DL model.Conclusion Improved ResNet18 lightweight DL models could be used for automatically detecting GA based on ultrasonogram of MTP1,among which model 2 was the best one.