Objective To explore the relationship between the degree of compression and shape grading of the cerebral cistern ambiens in hypertensive cerebral hemorrhage(HCH)patients after neural endoscopic intracranial hematoma evacuation(NEIHE)and prognosis.Methods 246 HCH patients who underwent NEIHE surgery from January 2020 to June 2023 were selected as the research subjects.According to the postoperative 6 month Glasgow outcome score(GOS),the patients were divided into good prognosis group(n=158)and poor prognosis group(n=88).Hierarchical regression model was used to analyze the relationship between clinical pathological features and the degree of compression and shape grading of the cerebral cistern ambiens.Multivariate logistic regression model was used to analyze the independent risk factors affecting the poor prognosis of patients with HCH after NEIHE,and a prediction model was constructed.Receiver operating characteristic curve(ROC curve)was drawn with poor prognosis as the outcome variable.Area under the curve(AUC),integrated discrimination improvement(IDI)and net reclassification improvement(NRI)of different prediction models were compared.Hosmer-Lemeshow was used to test the goodness of fit.Generalized additive model(GAM)was used to analyze the relationship between GOS and related factors.Results Compared with the good prognosis group,the poor prognosis group had more preoperative blood loss,lower preoperative Glasgow coma score(GCS),and higher proportion of patients with midline deviation,hypertension history ≥10 years,hemorrhage breaking into the brain ventricle,and operation time in the late stage,the differences were statistically significant(P＜0.05).Compared with the good prognosis group,the proportions of patients with ipsilateral and contralateral cerebral cistern ambiens compression of 3 to 4 points and the morphological classification of cerebral cistern ambiens of grade V in the poor prognosis group were higher,and the differences were statistically significant(P＜0.05).The location of bleeding,midline deviation,and intracranial pressure all had an impact on the degree of compression and morphological grading of the cerebral cistern ambiens,and the differences were statistically significant(P＜0.05).Multivariate Logistic regression analysis(model 2:including the degree of compression and shape grading of the cerebral cistern ambiens)showed that midline deviation,history of hypertension ≥10 years,preoperative bleeding volume＞37 mL,bleeding into the brain ventricles,preoperative GCS＜7 points,late surgical timing,degree of compression of the cerebral cistern ambiens(3 to 4 points on the same side of hematoma,3 to 4 points on the opposite side of hematoma),and grade V morphology were all risk factors influencing the poor prognosis of patients with HCH after NEIHE(P＜0.05).After incorporating the degree of compression and morphological grading of the cerebral cistern ambiens into model 1(excluding the degree of compression and shape grading of the cerebral cistern ambiens),the AUC increased to 0.812(95％CI:0.763～0.872),and both the IDI(0.081,95％CI:0.049～0.095)and NRI(0.611,95％CI:0.510～0.674)of the model improved,with statistically significant differences(P＜0.05).Compared with model 1,model 2 showed an increase in AUC(0.826,95％CI:0.771～0.863),IDI(0.085,95％CI:0.052～0.110),and NRI(0.628,95％CI:0.510～0.709),with statistically significant differences(P＜0.05).The Hosmer-Lemeshow test showed that model 2(P=0.878)had a better fit for predicting poor prognosis than model 1(P=0.691).GAM analysis showed that the higher the degree of compression and morphological grading of the cerebral cistern ambiens,the lower the GOS,and the difference was statistically significant(P＜0.05).ROC curve analysis showed that the combined application of degree of compression and morphological grading of the cerebral cistern ambiens had a high predictive value for poor prognosis,with AUC of 0.935(95％CI:0.890～0.971),sensitivity of 70.26％,and specificity of 93.84％.Conclusion The degree of compression and shape changes of the cerebral cistern ambiens in HCH patients after NEIHE are closely related to prognosis,and the combined application has certain predictive value for poor prognosis.The location of bleeding,midline deviation,intracranial pressure,and other factors significantly affect the compression degree and shape change of the cerebral cistern ambiens.

Objective To explore the value of nomogram model based on MR T1WI enhanced radiomics features and clinical fac-tors in predicting the prognosis of gliomas.Methods A retrospective selection was conducted on 135 patients with postoperative pathologically confirmed gliomas,who were categorized into poor prognosis group(n=59)and good prognosis group(n=76)according to survival condition at 20 months postoperatively.All patients were randomly divided into training group(n=94)and validation group(n=41)in a 7︰3 ratio.Radiomics features were extracted by 3D Slicer software,and the extracted radiomics features were downscaled by intraclass correlation coefficient(ICC),t-test,least absolute shrinkage and selection operator(LASSO)regression,and a total of 1 058 features were extracted for each patient,and 10 optimal radiomics features were obtained,to finally get the Radiomics score(Radscore).After combining clinical features and Radscore,a nomogram model was constructed.Results In the training group,Radscore was significantly higher in the poor prognosis group than that in the good prognosis group(t=8.773,P<0.05).The area under the curve(AUC)of receiver operating characteristic(ROC)curve of the training and validation groups of the radiomics model were 0.751[95%confidence interval(CI)0.654-0.849]and 0.606(95%CI 0.426-0.787),respectively.The AUC of the nomogram model were 0.899(95%CI 0.839-0.960)and 0.908(95%CI 0.823-0.994)in the training and validation groups,respectively,with much better predictive efficacy of the nomogram model.Conclusion A nomogram model based on MR T1WI enhanced radiomics features and clinical factors has good predictive efficacy in the prognosis of gliomas after surgery.

Objective: To analyze the unregistered treatment situation and its influencing factors among pulmonary tuberculosis patients in Quzhou City, Zhejiang Province from 2017 to 2023, so as to provide a basis for promoting the management of tuberculosis patients and optimizing disease prevention and control strategies. Methods: Data of pulmonary tuberculosis patients including demographic information, etiological results, and mortality status were collected through the China Disease Prevention and Control Information System Infectious Disease Reporting and Surveillance System and the Tuberculosis Management Information System. Pulmonary tuberculosis patients not matched in the Tuberculosis Management Information System were defined as unregistered treatment patients, and the unregistered treatment rate was analyzed. Factors affecting unregistered treatment among pulmonary tuberculosis patients were analyzed using a multivariable logistic regression model. Results: A total of 10 779 pulmonary tuberculosis patients were reported in Quzhou City from 2017 to 2023, including 7 700 males (71.44%) and 3 079 females (28.56%). There were 5 484 cases aged <65 years, accounting for 50.88%. Among them, 630 cases were unregistered treatment, with an unregistered treatment rate of 5.84% (95%CI: 5.42%-6.38%). Multivariable logistic regression analysis showed pulmonary tuberculosis patients aged ≥65 years (OR=1.829, 95%CI: 1.512-2.212) had a higher risk of being unregistered treatment than those aged <65 years; patients with non-local household registration (OR=5.710, 95%CI: 4.724-6.901) had a higher risk than local patients; and patients engaged in housework/unemployed (OR=2.001, 95%CI: 1.421-2.818) or other occupations (OR=2.396, 95%CI: 1.789-3.137) had a higher risk than farmers. The mortality of unregistered treatment pulmonary tuberculosis patients was higher than the registered treatment patients (26.67% vs. 5.02%),with a significantly elevated mortality risk (OR=7.147, 95%CI: 5.738-8.902). Conclusions The unregistered treatment rate among pulmonary tuberculosis patients was well controlled in Quzhou City from 2017 to 2023, but the elderly, patients with non-local household registration, and those engaged in housework/unemployed had a higher risk of unregistered treatment. It is recommended to improve medical and social security policies, strengthen health education on tuberculosis prevention, enhance treatment adherence, and reduce mortality risk.

Objective To explore the relationship between the degree of compression and shape grading of the cerebral cistern ambiens in hypertensive cerebral hemorrhage(HCH)patients after neural endoscopic intracranial hematoma evacuation(NEIHE)and prognosis.Methods 246 HCH patients who underwent NEIHE surgery from January 2020 to June 2023 were selected as the research subjects.According to the postoperative 6 month Glasgow outcome score(GOS),the patients were divided into good prognosis group(n=158)and poor prognosis group(n=88).Hierarchical regression model was used to analyze the relationship between clinical pathological features and the degree of compression and shape grading of the cerebral cistern ambiens.Multivariate logistic regression model was used to analyze the independent risk factors affecting the poor prognosis of patients with HCH after NEIHE,and a prediction model was constructed.Receiver operating characteristic curve(ROC curve)was drawn with poor prognosis as the outcome variable.Area under the curve(AUC),integrated discrimination improvement(IDI)and net reclassification improvement(NRI)of different prediction models were compared.Hosmer-Lemeshow was used to test the goodness of fit.Generalized additive model(GAM)was used to analyze the relationship between GOS and related factors.Results Compared with the good prognosis group,the poor prognosis group had more preoperative blood loss,lower preoperative Glasgow coma score(GCS),and higher proportion of patients with midline deviation,hypertension history ≥10 years,hemorrhage breaking into the brain ventricle,and operation time in the late stage,the differences were statistically significant(P＜0.05).Compared with the good prognosis group,the proportions of patients with ipsilateral and contralateral cerebral cistern ambiens compression of 3 to 4 points and the morphological classification of cerebral cistern ambiens of grade V in the poor prognosis group were higher,and the differences were statistically significant(P＜0.05).The location of bleeding,midline deviation,and intracranial pressure all had an impact on the degree of compression and morphological grading of the cerebral cistern ambiens,and the differences were statistically significant(P＜0.05).Multivariate Logistic regression analysis(model 2:including the degree of compression and shape grading of the cerebral cistern ambiens)showed that midline deviation,history of hypertension ≥10 years,preoperative bleeding volume＞37 mL,bleeding into the brain ventricles,preoperative GCS＜7 points,late surgical timing,degree of compression of the cerebral cistern ambiens(3 to 4 points on the same side of hematoma,3 to 4 points on the opposite side of hematoma),and grade V morphology were all risk factors influencing the poor prognosis of patients with HCH after NEIHE(P＜0.05).After incorporating the degree of compression and morphological grading of the cerebral cistern ambiens into model 1(excluding the degree of compression and shape grading of the cerebral cistern ambiens),the AUC increased to 0.812(95％CI:0.763～0.872),and both the IDI(0.081,95％CI:0.049～0.095)and NRI(0.611,95％CI:0.510～0.674)of the model improved,with statistically significant differences(P＜0.05).Compared with model 1,model 2 showed an increase in AUC(0.826,95％CI:0.771～0.863),IDI(0.085,95％CI:0.052～0.110),and NRI(0.628,95％CI:0.510～0.709),with statistically significant differences(P＜0.05).The Hosmer-Lemeshow test showed that model 2(P=0.878)had a better fit for predicting poor prognosis than model 1(P=0.691).GAM analysis showed that the higher the degree of compression and morphological grading of the cerebral cistern ambiens,the lower the GOS,and the difference was statistically significant(P＜0.05).ROC curve analysis showed that the combined application of degree of compression and morphological grading of the cerebral cistern ambiens had a high predictive value for poor prognosis,with AUC of 0.935(95％CI:0.890～0.971),sensitivity of 70.26％,and specificity of 93.84％.Conclusion The degree of compression and shape changes of the cerebral cistern ambiens in HCH patients after NEIHE are closely related to prognosis,and the combined application has certain predictive value for poor prognosis.The location of bleeding,midline deviation,intracranial pressure,and other factors significantly affect the compression degree and shape change of the cerebral cistern ambiens.

Objective To explore the value of nomogram model based on MR T1WI enhanced radiomics features and clinical fac-tors in predicting the prognosis of gliomas.Methods A retrospective selection was conducted on 135 patients with postoperative pathologically confirmed gliomas,who were categorized into poor prognosis group(n=59)and good prognosis group(n=76)according to survival condition at 20 months postoperatively.All patients were randomly divided into training group(n=94)and validation group(n=41)in a 7︰3 ratio.Radiomics features were extracted by 3D Slicer software,and the extracted radiomics features were downscaled by intraclass correlation coefficient(ICC),t-test,least absolute shrinkage and selection operator(LASSO)regression,and a total of 1 058 features were extracted for each patient,and 10 optimal radiomics features were obtained,to finally get the Radiomics score(Radscore).After combining clinical features and Radscore,a nomogram model was constructed.Results In the training group,Radscore was significantly higher in the poor prognosis group than that in the good prognosis group(t=8.773,P<0.05).The area under the curve(AUC)of receiver operating characteristic(ROC)curve of the training and validation groups of the radiomics model were 0.751[95%confidence interval(CI)0.654-0.849]and 0.606(95%CI 0.426-0.787),respectively.The AUC of the nomogram model were 0.899(95%CI 0.839-0.960)and 0.908(95%CI 0.823-0.994)in the training and validation groups,respectively,with much better predictive efficacy of the nomogram model.Conclusion A nomogram model based on MR T1WI enhanced radiomics features and clinical factors has good predictive efficacy in the prognosis of gliomas after surgery.

OBJECTIVE To investigate the predictive value of prognostic nutritional index(PNI) and lymphocyte-monocyte ratio(LMR) in severe radiotherapy-induced oral mucositis(RIOM) during treatment of patients with head and neck cancer,and to construct a risk prediction model and test the prediction effect. METHODS A total of 502 patients with head and neck cancer who underwent radiotherapy were recruited from September 2021 to October 2023 in Xiangya Hospital Central South University. The participants were randomly divided into training group and validation group at a ratio of 7:3. According to whether severe RIOM occurred,they were divided into severe RIOM group and non-severe RIOM group. Univariate analysis and logistic regression analysis were used to screen the risk factors of severe RIOM. The receiver operating characteristic(ROC) curve was used to evaluate its prediction effect and R4.3.2 software was used to draw nomograms and decision curve. RESULTS The risk prediction model for patients with head and neck cancer during treatment had five factors,including the number of comorbidities(OR=2.221,95％CI=1.185-4.165),surgical history(OR=2.938,95％CI=1.393-6.198),the degree of tumor differentiation(OR=1.511,95％CI=1.090-2.094),PNI(OR=0.892,95％CI=0.852-0.934),LMR(OR=0.512,95％CI=0.254-1.030). Model formula:Y=2.102+0.413×degree of differentiation+0.798×number of comorbidities+1.078×surgical history-0.114×PNI-0.669×LMR. The validation results of the prediction model showed that the area under the ROC curve of the training group was 0.847(P<0.001),the area under the curve of the validation group was 0.808(P<0.001),and the P values of the Hosmer-Lemeshow test of the modeling group and the validation group were both greater than 0.05. The decision curve was above the reference line within most of the high-risk thresholds. CONCLUSION The risk prediction model constructed in this study has good effect,which can predict the risk of severe RIOM during radiotherapy in patients with head and neck cancer,providing the reference for taking preventive intervention measures for high-risk patients.

Objective To investigate the prevalence and severity of symptoms and to construct symptom networks in head and neck cancer patients during treatment to identify core symptoms and symptom clusters.Methods 366 patients who were hospitalized in 3 tertiary hospitals in Changsha were selected using convenience sampling from March to October 2022 and asked to complete the M.D.Anderson Symptom Inventory-Head & Neck.Exploratory factors analysis was used to extract the symptom clusters,and R packages were used to construct the symptom severity network and symptom clusters network.The centrality indexes of the networks,including strength,closeness,and betweenness,were analyzed to identify core symptoms and core symptom cluster.Results The most common symptoms in head and neck cancer patients during treatment were dry mouth(93.44％),fatigue(89.07％),loss of appetite(86.34％),and difficulty swallowing or chewing(85.79％),and the most severe symptoms were dry mouth,loss of appetite,oral or pharyngeal mucus,and difficulty swallowing or chewing.4 symptom clusters were extracted,namely oral-pharyngeal,gastrointestinal,emotional-sleep,and sickness-sensing behavioral,which could explain 67.415％of the total variance.In the symptom severity network,oral or pharyngeal mucus(rs=9.60)was a symptom with the highest strength.In the symptom clusters network,oral or pharyngeal mucus(rs=1.20),nausea(rs=1.00),fatigue(rs=1.10),and drowsiness(rs=0.97)were the symptoms with the highest strength across 4 symptom clusters.Conclusion Oral or pharyngeal mucus,nausea,fatigue,and drowsiness are the core symptoms of symptom clusters in head and neck cancer patients during treatment.Oral-pharyngeal symptom cluster is the core symptom cluster.It is recommended that clinical staff should develop interventions based on the core symptoms and symptom cluster to implement precise symptom management and improve symptom management efficiency.

Abstract OBJECTIVE To analyze the inflammation-related molecular targets of Pien Tze Huang in the treatment of hepatocellular carcinoma and to preliminary explore its mechanism. METHODS Obtain the ingredients and targets of Pien Tze Huang through TCMSP and BATMAN databases. Obtain the disease targets of hepatocellular carcinoma through Genecards, OMIM and TCGA databases. Take the intersection of compound targets and disease targets to get Pien Tze Huang’s target for the treatment of hepatocellular carcinoma. Obtain the related genes of inflammation pathway from the GSEA database, and then analyze the correlation between Pien Tze Huang’s therapeutic targets for hepatocellular carcinoma and inflammation-related genes to screen out inflammation-related targets, and explore the mechanism through GO and KEGG enrichment analysis. Then, single-factor cox analysis and LASSO regression were performed to construct related prognostic models. The 10 core targets were screened out through the protein-protein interaction(PPI) network. The model gene and the core target were intersected. The core compounds were screened out through the drug-compound-target network. Perform molecular docking verification between the core compound and the target. Construct a nomogram to assess the prognosis of patients. RESULTS Obtained 162 Pien Tze Huang targets, 522 hepatocellular carcinoma targets, 20 Pien Tze Huang therapeutic targets for hepatocellular carcinoma, and 16 inflammation-related targets. The enrichment analysis of GO and KEGG showed that their effects were mainly through biological functions such as monooxygenase activity, oxidoreductase activity, and chemical carcinogenesis-receptor activation. The ROC curve of the prognosis model calculated AUC as 0.780 in 1 year, 0.688 in 3 years, and 0.642 in 5 years, indicating that the model was reliable. The prognostic model intersects with the core target of PPI to get 5 targets: PON1, IGF2, NQO1, CCNB1 and IGFBP3. The nomogram was constructed using CCNB1, NQO1, and T staging, and its c-index was 0.726, indicating the reliability of the model. The drug-compound-target network suggested that quercetin was the core compound and targets the above two genes. CONCLUSION Pien Tze Huang’s treatment of hepatocellular carcinoma mainly uses quercetin to target CCNB1 and NQO1 to exert anti-inflammatory effects, and its prognostic model can be used to predict the survival of patients.

OX40 is a costimulatory receptor that is expressed primarily on activated CD4⁺, CD8⁺, and regulatory T cells. The ligation of OX40 to its sole ligand OX40L potentiates T cell expansion, differentiation, and activation and also promotes dendritic cells to mature to enhance their cytokine production. Therefore, the use of agonistic anti-OX40 antibodies for cancer immunotherapy has gained great interest. However, most of the agonistic anti-OX40 antibodies in the clinic are OX40L-competitive and show limited efficacy. Here, we discovered that BGB-A445, a non-ligand-competitive agonistic anti-OX40 antibody currently under clinical investigation, induced optimal T cell activation without impairing dendritic cell function. In addition, BGB-A445 dose-dependently and significantly depleted regulatory T cells in vitro and in vivo via antibody-dependent cellular cytotoxicity. In the MC38 syngeneic model established in humanized OX40 knock-in mice, BGB-A445 demonstrated robust and dose-dependent antitumor efficacy, whereas the ligand-competitive anti-OX40 antibody showed antitumor efficacy characterized by a hook effect. Furthermore, BGB-A445 demonstrated a strong combination antitumor effect with an anti-PD-1 antibody. Taken together, our findings show that BGB-A445, which does not block OX40-OX40L interaction in contrast to clinical-stage anti-OX40 antibodies, shows superior immune-stimulating effects and antitumor efficacy and thus warrants further clinical investigation.
Mice ; Animals ; Receptors, Tumor Necrosis Factor/physiology* ; Receptors, OX40 ; Membrane Glycoproteins ; Ligands ; Antibodies, Monoclonal/pharmacology* ; Antineoplastic Agents/pharmacology*

Herein, we designed a dual-response shape transformation and charge reversal strategy with chemo-photodynamic therapy to improve the blood circulation time, tumor penetration and retention, which finally enhanced the anti-tumor effect. In the system, hydrophobic photosensitizer chlorin e6 (Ce6), hydrophilic chemotherapeutic drug berberrubine (BBR) and matrix metalloproteinase-2 (MMP-2) response peptide (PLGVRKLVFF) were coupled by linkers to form a linear triblock molecule BBR-PLGVRKLVFF-Ce6 (BPC), which can self-assemble into nanoparticles. Then, positively charged BPC and polyethylene glycol-histidine (PEG-His) were mixed to form PEG-His@BPC with negative surface charge and long blood circulation time. Due to the acidic tumor microenvironment, the PEG shell was detached from PEG-His@BPC attributing to protonation of the histidine, which achieved charge reversal, size reduction and enhanced tumor penetration. At the same time, enzyme cutting site was exposed, and the spherical nanoparticles could transform into nanofibers following the enzymolysis by MMP-2, while BBR was released to kill tumors by inducing apoptosis. Compared with original nanoparticles, the nanofibers with photosensitizer Ce6 retained within tumor site for a longer time. Collectively, we provided a good example to fully use the intrinsic properties of different drugs and linkers to construct tumor microenvironment-responsive charge reversal and shape transformable nanoparticles with synergistic antitumor effect.