AIM: To investigate expression differences and mechanism of action of serine/threonine kinase 1(AKT1), ATP synthase F1 subunit(ATP5F1), and Bcl-2-associated anti-apoptotic gene 3(BAG3)in the occurrence and progression of pterygium.METHODS:Pterygium-related gene expression data were retrieved from GEO database to screen differentially expressed genes(DEGs). String and Cytoscape were used to construct protein-protein interaction(PPI)networks and identify core targets. GO/KEGG enrichment analyzed mitochondrial metabolic pathways. The pterygium samples(head/body)were collected; pathological features were evaluated by HE staining, and the expression of AKT1, ATP5F1, and BAG3 was detected via immunohistochemistry(IHC).RESULTS:A total of 1 264 DEGs were identified(585 upregulated, 679 downregulated). GO analysis showed significant enrichment of mitochondrial pathways regarding to biological processes, cell components and molecular functions; KEGG analysis highlighted oxidative phosphorylation and chemical carcinogenesis-reactive oxygen species(ROS)pathways. The head and body pterygium samples were collected from 28 cases(28 eyes)that received pterygium surgery, including 7 males(7 eyes)and 21 females(21 eyes), with a mean age of 69.32±8.98 years. HE staining showed more severe dysplasia, disordered stroma, and inflammation in the pterygium head versus the body. IHC detection confirmed significantly lower AKT1, ATP5F1, and BAG3 expression in the head compared with the body(all P<0.05).CONCLUSION:GEO-based bioinformatics and experiments confirmed that AKT1/ATP5F1/BAG3(mitochondrial genes)had significant differential expression in pterygium, correlating with pathological progression. They may regulate mitochondrial metabolism to mediate pterygium progression, offering new insights for targeted therapy.

Objective To observe the value of MRI radiomics model for predicting postoperative prognosis of moderate carpal tunnel syndrome(CTS).Methods A total of 126 patients with moderate CTS who underwent endoscopic release and fat-suppressed proton density weighted imaging(PDWI)before operation were retrospectively enrolled.The patients were divided into good prognosis group(n=80)and poor prognosis group(n=46)based on postoperative functional evaluation,also randomly divided into training set and validation set at a ratio of 7∶3.Volume of interest(VOI)of the median nerve was obtained through delineating ROI of the affected wrist on fat suppressed PDWI.Radiomics features were extracted,and those associated with postoperative prognosis of CTS were screened in training set.Clinical prediction model,radiomics model and combined model of these two were established,and the predictive efficacy of the models were evaluated and compared according to the area under the curve(AUC)of receiver operating characteristic(ROC)curve.Results Patients in poor prognosis group were older than in good prognosis group(P＜0.05).A clinical model was constructed based on age.The radiomics model was constructed based on 6 radiomics features associated with postoperative prognosis of CTS,with predictive efficacy(AUC=0.872)higher than that of clinical model(AUC=0.604,P＜0.05)but not significantly different with that of the combined model(AUC=0.905,P＞0.05).Conclusion MRI radiomics model could be used to effectively predict postoperative prognosis of moderate CTS.

Objective To explore the diagnostic value of MRI radiomics analysis in mild carpal tunnel syndrome(CTS).Methods Seventy patients with mild CTS and 86 healthy volunteers who underwent wrist MRI examination were retrospectively selected.MRI fat-suppressed proton density weighted imaging(PDWI)were imported into 3D Slicer software,and the region of interest(ROI)delineation was performed by two radiologists independently.The 830 radiomics parameters were extracted,including first-order fea-tures,shape features,texture features,and wavelet-transform features.Radiomics parameter selection was performed through observer intraclass correlation coefficient(ICC),correlation analysis,and multivariate logistic regression.Five diagnostic models were estab-lished,including logistic regression,support vector machine,naive Bayes,decision tree,and random forest.Receiver operating charac-teristic(ROC)curve was used to analyze the diagnostic efficiency of the models.Results Seven radiomics features were selected for inclusion in the diagnostic models.The logistic regression model demonstrated the best performance,with an area under the curve(AUC)of 0.91[95%confidence interval(CI)0.86-0.96],a sensitivity of 88.63%,and a specificity of 89.00%in the training group.In the test group,the AUC was 0.92(95%CI 0.85-0.97),with a sensitivity of 90.48%and a specificity of 84.62%.Conclusion MRI radiomics analysis can be used to diagnose mild CTS,and the logistic regression model demonstrates superior diagnostic per-formance.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Objective To evaluate the clinical value of a modified Cancer and Aging Research Group(CARG)model in guiding anticancer drug dose adjustments for elderly cancer patients in China.Methods This prospective study enrolled patients aged≥65 years with solid tumors at the Department of Oncology,Peking Union Medical College Hospital from September 1,2022 to October 29,2023.All patients underwent comprehensive geriatric assessment(CGA)and CARG risk scoring,and were stratified into low-,intermediate-,and high-risk groups.Anti-cancer drug doses(including chemotherapy,targeted therapy or immunotherapy)were reduced proportionally based on CARG risk stratification and treatment intent(curative vs.palliative).Treatment outcomes and adverse events(AEs)were recorded regularly.Fisher's Exact Test compared AE incidence between the CARG-guided dose adjust-ment group(experimental)and the physician-experience-guided dose adjustment group(control).Receiver operating characteristic(ROC)curve analysis was used to assess the predictive value of the CARG model for severe toxicity.Results Among 166 enrolled patients(median age:71 years[range:65-90];78.3%were male;68.7%had gastro-intestinal cancers;69.3%had stageⅣ),95 were assigned to the experimental group(CARG low-risk:24[25.3%],intermediate-risk:51[53.7%],high-risk:20[21.0%])and 71 were included into the control group.By December 31,2024,81 patients experienced disease progression and 10 patients died.Overall AE rates was 92.6%in the ex-perimental group and 94.4%in the control group,while grade≥3 AEs were recorded in 45.3%vs.43.7%,respec-tively(both P＞0.05).Conclusions The modified CARG model-guided dose adjustment strategy achieved comparable safety to empirical dose adjustment,which is in line with the individualized treatment paradigm for elderly cancer pa-tients,representing a structured framework for optimizing therapeutic decision-making in geriatric oncology.

Objective To explore the diagnostic value of MRI radiomics analysis in mild carpal tunnel syndrome(CTS).Methods Seventy patients with mild CTS and 86 healthy volunteers who underwent wrist MRI examination were retrospectively selected.MRI fat-suppressed proton density weighted imaging(PDWI)were imported into 3D Slicer software,and the region of interest(ROI)delineation was performed by two radiologists independently.The 830 radiomics parameters were extracted,including first-order fea-tures,shape features,texture features,and wavelet-transform features.Radiomics parameter selection was performed through observer intraclass correlation coefficient(ICC),correlation analysis,and multivariate logistic regression.Five diagnostic models were estab-lished,including logistic regression,support vector machine,naive Bayes,decision tree,and random forest.Receiver operating charac-teristic(ROC)curve was used to analyze the diagnostic efficiency of the models.Results Seven radiomics features were selected for inclusion in the diagnostic models.The logistic regression model demonstrated the best performance,with an area under the curve(AUC)of 0.91[95%confidence interval(CI)0.86-0.96],a sensitivity of 88.63%,and a specificity of 89.00%in the training group.In the test group,the AUC was 0.92(95%CI 0.85-0.97),with a sensitivity of 90.48%and a specificity of 84.62%.Conclusion MRI radiomics analysis can be used to diagnose mild CTS,and the logistic regression model demonstrates superior diagnostic per-formance.

Objective To observe the value of MRI radiomics model for predicting postoperative prognosis of moderate carpal tunnel syndrome(CTS).Methods A total of 126 patients with moderate CTS who underwent endoscopic release and fat-suppressed proton density weighted imaging(PDWI)before operation were retrospectively enrolled.The patients were divided into good prognosis group(n=80)and poor prognosis group(n=46)based on postoperative functional evaluation,also randomly divided into training set and validation set at a ratio of 7∶3.Volume of interest(VOI)of the median nerve was obtained through delineating ROI of the affected wrist on fat suppressed PDWI.Radiomics features were extracted,and those associated with postoperative prognosis of CTS were screened in training set.Clinical prediction model,radiomics model and combined model of these two were established,and the predictive efficacy of the models were evaluated and compared according to the area under the curve(AUC)of receiver operating characteristic(ROC)curve.Results Patients in poor prognosis group were older than in good prognosis group(P＜0.05).A clinical model was constructed based on age.The radiomics model was constructed based on 6 radiomics features associated with postoperative prognosis of CTS,with predictive efficacy(AUC=0.872)higher than that of clinical model(AUC=0.604,P＜0.05)but not significantly different with that of the combined model(AUC=0.905,P＞0.05).Conclusion MRI radiomics model could be used to effectively predict postoperative prognosis of moderate CTS.

Objective:To summarize the clinical features, electroencephalogram (EEG) and magnetoencephalogram (MEG) of patients with pure paroxysmal kinesigenic dyskinesia (PKD) and PKD with epilepsy, so as to better distinguish them and guide the treatments.Methods:The clinical data of 200 patients diagnosed with PKD in the Outpatient Department of Xuanwu Hospital, Capital Medical University from 2000 to 2023 were analyzed retrospectively. The patients were divided into 2 groups: pure PKD (174 cases) and PKD with epilepsy (26 cases) according to whether accompanied by epilepsy. The differences in clinical features, drug therapy, EEG and MEG were compared between the 2 groups.Results:The clinical features of the 2 groups were essentially similar, and the proportion of PKD dyskinesia induced by emotional stress in the pure PKD group (54/174, 31.03%) was higher than that in the PKD with epilepsy group (2/26, 7.69%; χ 2=5.010, P=0.025). In terms of pharmacological response, carbamazepine was the most commonly used medication in both groups, but patients with PKD with epilepsy may need a higher therapeutic dosages (0.2-0.4 g/d, and gradually increased to 0.8 g/d) to effectively manage both dyskinesia and seizures. Regarding the EEG and MEG, the proportion of EEG abnormalities was higher in PKD patients with epilepsy, mainly manifested as focal spikes [1/70(1.43%) vs 9/21(42.86%), χ 2=24.268, P<0.001], together with aberrant MEG discharge (4/18 vs 3/5, χ 2=1.155, P=0.282). The MEG dipoles were mainly distributed in the brain regions close to the frontal lobe and central region. Conclusions:The clinical manifestations of motor symptoms of pure PKD and PKD with epilepsy are similar, and carbamazepine remains the most effective treatment. PKD patients with epilepsy have a higher proportion of abnormal EEG, mainly manifested as focal spikes, and are more likely to show abnormal discharge of MEG, which could be used to distinguish them.

Pulmonary blast injury has become the main type of trauma in modern warfare, characterized by externally mild injuries but internally severe injuries, rapid disease progression, and a high rate of early death. The injury is complicated in clinical practice, often with multiple and compound injuries. Currently, there is a lack of effective protective materials, accurate injury detection instrument and portable monitoring and transportation equipment, standardized clinical treatment guidelines in various medical centers, and evidence-based guidelines at home and abroad, resulting in a high mortality in clinlcal practice. Therefore, the Trauma Branch of Chinese Medical Association and the Editorial Committee of Chinese Journal of Trauma organized military and civilian experts in related fields such as thoracic surgery and traumatic surgery to jointly develop the Clinical treatment guideline for pulmonary blast injury ( version 2023) by combining evidence for effectiveness and clinical first-line treatment experience. This guideline provided 16 recommended opinions surrounding definition, characteristics, pre-hospital diagnosis and treatment, and in-hospital treatment of pulmonary blast injury, hoping to provide a basis for the clinical treatment in hospitals at different levels.