Objective:To explore the value of predicting new-onset heart failure events in patients with hypertrophic cardiomyopathy (HCM) using clinical and cardiac magnetic resonance (CMR) features based on machine learning algorithms.Methods:The study was a retrospective cohort study. Patients with a confirmed diagnosis of HCM who underwent CMR examinations at Beijing Anzhen Hospital from May 2017 to March 2021 were selected and randomly divided into the training set and the validation set in a ratio of 7∶3. Clinical data and CMR parameters (including conventional parameters and radiomics features) were collected. The endpoint events were heart failure hospitalization and heart failure death, with follow-up ending in January 2023. Features with high stability and P value<0.05 in univariate Cox regression analysis were selected. Subsequently, three machine learning algorithms—random forest, decision tree, and XGBoost—were used to build heart failure event prediction models in the training set. The model performance was then evaluated using the independent validation set, with the performance assessed based on the concordance index. Results:A total of 462 patients were included, with a median age of 51 (39, 62) years, of whom 332 (71.9%) were male. There were 323 patients in the training set and 139 in the validation set. The median follow-up time was 42 (28, 52) months. A total of 44 patients (9.5% (44/462)) experienced endpoint events (8 cases of heart failure death and 36 cases of heart failure hospitalization), with 31 events in the training set and 13 in the validation set. Univariate Cox regression analysis identified 39 radiomic features, 4 conventional CMR parameters (left ventricular end-diastolic volume index, left ventricular end-systolic volume index, left ventricular ejection fraction, and late gadolinium enhancement ratio), and 1 clinical feature (history of non-sustained ventricular tachycardia) that could be included in the machine learning model. In the prediction models built with the training set, the concordance indices for the random forest, decision tree, and XGBoost models were 0.966 (95% CI 0.813-0.995), 0.956 (95% CI 0.796-0.992), and 0.973 (95% CI 0.823-0.996), respectively. In the validation set, the concordance indices for the random forest, decision tree, and XGBoost models were 0.854 (95% CI 0.557-0.964), 0.706 (95% CI 0.399-0.896), and 0.703 (95%CI 0.408-0.890), respectively. Conclusion:Integrating clinical and CMR features of HCM patients through machine learning aids in predicting heart failure events, with the random forest model showing superior performance.

Humans ; Parkinson Disease/diagnosis* ; Machine Learning

Developing new therapeutic agents for cancer immunotherapy is highly demanding due to the low response ratio of PD-1/PD-L1 blockade in cancer patients. Here, we discovered that the novel immune checkpoint VISTA is highly expressed on a variety of tumor-infiltrating immune cells, especially myeloid derived suppressor cells (MDSCs) and CD8⁺ T cells. Then, peptide C1 with binding affinity to VISTA was developed by phage displayed bio-panning technique, and its mutant peptide VS3 was obtained by molecular docking based mutation. Peptide VS3 could bind VISTA with high affinity and block its interaction with ligand PSGL-1 under acidic condition, and elicit anti-tumor activity in vivo. The peptide DVS3-Pal was further designed by d-amino acid substitution and fatty acid modification, which exhibited strong proteolytic stability and significant anti-tumor activity through enhancing CD8⁺ T cell function and decreasing MDSCs infiltration. This is the first study to develop peptides to block VISTA/PSGL-1 interaction, which could act as promising candidates for cancer immunotherapy.

Abstract: Objective To analyze the accuracy and feasibility of GeneXpert MTB/RIF (GeneXpert) detection in the detection of Mycobacterium tuberculosis and the characteristics of rifampicin-resistant rpoB gene mutations. Methods A total of 4 234 sputum samples from suspected tuberculosis patients diagnosed in Sanya tuberculosis designated hospitals from 2015 to 2021 were selected and subjected to sputum smear, solid culture, drug sensitivity test by solid proportion method and GeneXpert detection. Results The positive detection rates of sputum smear, solid culture and GeneXpert of 4 234 sputum samples were 29.24% (1 238/4 234), 32.17% (1 362/4 234) and 35.40% (1 499/4 234), respectively. The positive detection rate of GeneXpert was higher than that of sputum smear, and the difference was statistically significant (χ2=36.775, P<0.01). It was slightly higher than solid culture, and the difference was not statistically significant (χ2=9.908, P=0.02). Taking solid culture results as the gold standard, the sensitivity and specificity of GeneXpert for detecting MTB were 91.04% (1 240/1 362) and 90.98% (2 613/2 872), respectively. According to the proportional drug susceptibility test results as the gold standard, the sensitivity and specificity of GeneXpert in detecting rifampicin resistance were 96.96% (96/99) and 98.86% (1 128/1 141), respectively, with the consensus rate of 98.71%. The accuracy of rifampicin resistance in GeneXpert group without probe mutation was significantly lower than that in group with probe mutation. There was a statistical difference in probe mutation frequency between newly treated and retreated cases. The analysis of rpoB gene mutation frequency characteristics showed: Probe E (50.00%) > Probe A (22.12%) > Probe D (14.42%) > Probe B (6.73%) > combined probe (5.77%) > Probe C (0.96%). Conclusions GeneXpert detection can quickly and effectively diagnose rifampicin-resistant tuberculosis, which is helpful for early clinical diagnosis and treatment. In this region, the rpoB gene mutation probes of rifampicin-resistant tuberculosis mainly occurr in Probe E and Probe A, with the least mutations in Probe C.

Objective:To evaluate the value and effectiveness of the enhanced recovery after surgery (ERAS) theory in orthopedic surgery, and to provide a theoretical basis for optimizing rehabilitation plans during the perioperative period of orthopedic surgery.Methods:Relevant literature on the application of accelerated rehabilitation in orthopedic perioperative period officially published in Pubmed and the Chinese Medical Journal Database From January 2000 to October 2022 was searched and included in randomized controlled and clinical case studies. The patients were divided into the experimental group (ERAS group) and the control group (conventional treatment group). The patients in the experimental group were treated with ERAS mode after surgery, while the patients in the control group were treated with conventional rehabilitation mode after surgery. The hospital stay, postoperative complications, postoperative nausea and vomiting, and postoperative incidence rate of deep vein thrombosis in the two groups were statistically analyzed.Results:Finally, a total of 1 301 patients were included in 9 articles, divided into an experimental group (ERAS group, n=643) and a control group (conventional treatment group, n=652). There was a statistically significant difference in hospital stay between the experimental group and the control group ( MD=-4.11, 95% CI: -6.73 to -1.49, P=0.002); The overall effect tendency of the incidence of complications between the experimental group and the control group was statistically significant ( P=0.005); Compared with the control group, the incidence rate of postoperative nausea and vomiting in the experimental group was lower ( P=0.04); The incidence rate of postoperative deep vein thrombosis in the experimental group was lower than that in the control group ( P=0.02). Conclusions:The application of accelerated rehabilitation concept in orthopedic surgery patients can reduce the length of hospital stay, and reduce the incidence rate of postoperative complications, nausea and vomiting, and deep vein thrombosis.

Objective:To investigate the value of radiomics features derived from cardiac MR (CMR) cine images for predicting late gadolinium enhancement (LGE) in patients with hypertrophic cardiomyopathy (HCM).Methods:Firstly, a total of 300 HCM patients with definite diagnosis who underwent CMR examination in Beijing Anzhen Hospital from May 2017 to August 2021 were retrospectively included, and were divided into a training set and a test set with a proportion of 7∶3 using random stratified sampling method. Then, a total of 89 HCM patients with definite diagnosis who underwent CMR examination in Beijing Anzhen Hospital from January 2022 to May 2023 were included for external validation. The CVI42 software was used to obtain the cardiac function parameters. Intraclass correlation coefficient (ICC), Pearson correlation coefficient and least absolute shrinkage and selection operator (LASSO) were used to select radiomics features. Finally, LASSO regression and three machine learning algorithms (including support vector machine, linear discriminant analysis and naive Bayes) were used to build prediction models. The area under the receiver operating characteristic curve (AUC) was used to evaluate the prediction value of the model.Results:Totally 1 409 features were extracted from each patient, and 19 features were retained to build radiomics signature after dimension reduction. Although no significant differences among the four methods, the prediction performance and stability of LASSO regression were relatively good. The AUC was 0.795 (95%CI 0.735-0.855) in the training set, 0.765 (95%CI 0.668-0.862) in the test set and 0.721(95%CI 0.598-0.845) in the external validation set.Conclusions:The features extracted from CMR cine images can be used to predict LGE in HCM patients. LASSO regression is recommended for model construction.

Objective:To evaluate the pancreatic subclinical dysfunction after intensity-modulated radiation therapy (IMRT) for gastric cancer by analyzing biochemical indexes and pancreatic volume changes, and to reduce the dose of pancreas by dosimetric prediction and dose limitation.Methods:30 patients with gastric cancer who received 45 Gy postoperative adjuvant radiotherapy were retrospectively selected. The pancreas was delineated and its dose and anatomical relationship with planning target volume (PTV) were evaluated. Fasting blood glucose, serum lipase and amylase, and pancreatic volume changes before and after radiotherapy were analyzed. The correlation between the changes of biochemical indexes and volume and pancreatic dose was evaluated by Pearson analysis. The threshold of the dosimetric prediction was obtained by receiver operating characteristic (ROC) curve. Finally, the feasibility of dosimetric limitation in IMRT was assessed.Results:The pancreatic volume of 30 patients was 37.6 cm 3, and 89.0% of them were involved in PTV. D mean of the pancreas was 45.92 Gy, and 46.45 Gy, 46.46 Gy and 45.80 Gy for the pancreatic head, body and tail, respectively. The fasting blood glucose level did not significantly change. The serum lipase levels were significantly decreased by 66% and 77%(both P<0.001), and the serum amylase levels were significantly declined by 24% and 38%(both P<0.001) at 6 and 12 months after radiotherapy. Pancreatic volumes of 22 patients was decreased by 47% within 18 months after radiotherapy. ROC curve analysis showed that pancreatic V 45Gy had the optimal predictive value for the decrease by 1/3 of serum lipase and amylase levels at 6 months and serum amylase level at 12 months after radiotherapy, and the cut-off value was V 45Gy<85%. Pancreatic D mean yielded the optimal predictive value for the decrease by 2/3 of serum lipase level at 12 months after radiotherapy, and the cut-off value was D mean<45.01 Gy. After" whole pancreas" and" outside PTV pancreas" dose limit, V 45Gy of the pancreas was decreased by 11% and 7%, D mean of the pancreas was declined by 2% and 2%, and D mean of the pancreatic tail was decreased by 3%, respectively. Conclusions:Serum lipase and amylase levels significantly decline at 6 and 12 months after adjuvant radiotherapy for gastric cancer, and pancreatic volume is decreased significantly within 18 months after radiotherapy. Pancreatic V 45Gy<85% and D mean<45.01 Gy are the dose prediction values for the decrease of serum lipase and amylase levels. The dose can be reduced to certain extent by dosimetric restriction.

Rejection after lung transplantation, including acute rejection (AR) and chronic rejection manifested with chronic lung allograft dysfunction (CLAD), is the main factor affecting the long-term survival of allografts. Exosome, a type of extracellular nanovesicle for intercellular communication among eukaryotic cells, could carry complex biological information and participate in various physiological and pathological processes. Exosome has become a critical immune medium in rejection, regulates the incidence and development of rejection through multiple pathways, and also plays a key role in the monitoring and management of rejection. In this article, the type of rejection after lung transplantation, the mechanism underlying the role of exosome in regulating rejection, exosome acting as biomarkers and the application in rejection treatment were reviewed, aiming to provide a novel direction for comprehensive diagnosis and treatment of rejection following lung transplantation.

The management of drainage tube is an important part of nursing work. Patient restraint and tube fixation cannot effectively prevent unplanned extubation (UEX) when the tube is accidentally pulled by violence. The nursing innovation team of Henan Provincial People's Hospital designed a medical drainage tube anti-pull device in order to change the existing technology of preventing drainage tube disconnecting by means of restraint and fixation, and to interfere with the basic cause of drainage tube disconnection, and obtained the national utility model patent (patent number: ZL 2020 2 2843025.1). The design of sleeve and clasp is that when the drainage tube is pulled by accidental violence, the friction fastener clamps the drainage tube mechanically to achieve the purpose of braking the drainage tube and prevent the drainage tube from coming out. Card sleeve ring fracture design can be applied to drainage tubes of different diameters, and the buzzer device at the instant of the snap ring into the card set warning medical staff to the occurrence of risk events, so that the nurse can come in the first place for effective treatment, which is a fuse for surgical drainage tubes and is to timely and effectively prevent UEX.

Tryptophan 2,3-dioxygnease 2 (TDO2) is specific for metabolizing tryptophan to kynurenine (KYN), which plays a critical role in mediating immune escape of cancer. Although accumulating evidence demonstrates that TDO2 overexpression is implicated in the development and progression of multiple cancers, its tumor-promoting role in esophageal squamous cell carcinoma (ESCC) remains unclear. Here, we observed that TDO2 was overexpressed in ESCC tissues and correlated significantly with lymph node metastasis, advanced clinical stage, and unfavorable prognosis. Functional experiments showed that TDO2 promoted tumor cell proliferation, migration, and colony formation, which could be prevented by inhibition of TDO2 and aryl hydrocarbon receptor (AHR). Further experimentation demonstrated that TDO2 could promote the tumor growth of KYSE150 tumor-bearing model, tumor burden of C57BL/6 mice with ESCC induced by 4-NQO, enhance the expression of phosphorylated AKT, with subsequent phosphorylation of GSK3