Objective To investigate the prognostic factors affecting survival in patients with natural killer T-cell lymphoma(NKTL),and then develop a prognostic model for predicting their overall survival(OS)based on random survival forest(RSF)algorithm.Methods Demographic and clinical pathological data of NKTL patients were collected from the SEER database during 2000 and 2020.The patients were divided into a training cohort(n=471)and a validation cohort(n=203)in a 7∶3 ratio.Cox regression analysis was performed to identify prognostic factors affecting OS,and a nomogram model was constructed based on the obtained factors.Meanwhile,RSF algorithm was used to determine prognostic factors affecting OS to build the RSF model.The models were evaluated using receiver operating characteristic(ROC)curve,calibration curve,decision curve,net reclassification improvement(NRI),and integrated discrimination improvement(IDI),and the predictive performances of the 2 models were compared.Risk scores for each patient were calculated using the 2 models.Then the patients were divided into high-and low-risk groups based on the median risk score,and survival curve was plotted for comparison.Results Ann Arbor stage,age,radiotherapy,combined treatment,and type of disease were identified as significant prognostic variables associated with OS.In the validation cohort,the area under the ROC curve(AUC)for the nomogram model at 1,3,and 5 years was 0.745,0.771,and 0.748,respectively,while the AUC for the RSF model was 0.764,0.792,and 0.761 at the same time points.ROC curve analysis indicated that both models demonstrated good accuracy and discrimination in predicting OS.Calibration curve analysis showed a strong consistency between the predicted and actual OS for both models.Both models effectively stratified the patients into poor and favorable prognosis groups,with the OS of patients in the poor prognosis group being significantly shorter than that of the favorable prognosis group(P＜0.000 1).Decision curve analysis revealed that the net benefit of the RSF model was superior to that of the nomogram model.Compared to the nomogram model,the NRI for the RSF model was 0.184(95％CI:0.098～0.267,P＜0.01),and the IDI was 0.300(95％CI:0.241～0.359,P＜0.01).Overall,the RSF model demonstrated superior predictive capability than the nomogram model.Conclusion Ann Arbor stage,age,radiotherapy,combined treatment,and type of disease are prognostic factors affecting the prognosis of NKTL patients.Our RSF model demonstrates strong predictive capability for the prognosis of NKTL patients and can effectively assess patient outcomes.

Objective To construct a prognosis prediction model of primary liver cancer after surgical treatment based on synthetic minority over-sampling technique(SMOTE)algorithm and machine learning model.Methods A retrospective cohort study was conducted on 4 297 patients with primary liver cancer from the surveillance,epidemiology,and end results(SEER)database.One-Hot Encoding and Multiple Imputation were used to preprocess the collect data,and SMOTE algorithm was employed to solve the imbalance of data categories.The obtained clinical variables were included in the machine learning model.Based on decision tree(DT),random forest(RF),gradient boosting decision tree(GBDT)and eXtreme Gradient Boosting(XGBoost),a prognostic prediction model(SMOTE+DT/RF/GBDT/XGBoost)was build,and then the best prediction model was determined by comparing the performance of various models.Finally,a prognostic analysis system for primary liver cancer was developed based on the optimal model,which was then visualized.Results The combination model SMOTE+RF showed the best predictive performance,with higher area under the curve(0.895),accuracy(0.811)and precision(0.806)than those of other models in receiver operating characteristic curve(ROC)analysis.Conclusion The SMOTE+RF prognostic prediction model can effectively predict the survival outcome of patients with primary liver cancer.

Objective To investigate the influencing factors for tendency towards depression in college students having music listening habits with music APP,and develop a prediction model and further optimize it.Methods A total of 1 157 college students were subjected with convenient sampling and surveyed with questionaires between April and May 2023.Univariate analysis and logistic regression analysis were employed to identify the influencing factors.Then a prediction model was constructed based on these factors.SMOTEENN over-sampling algorithm was utilized to enhance the dataset and construct the prediction model.Results Logistic regression analysis revealed that female(OR=1.730,95％CI:1.257～2.396),senior grade(OR=2.649,95％CI:1.198～7.506),postgraduate grade(OR=2.041,95％CI:1.231～3.885),major in Science(OR=1.573,95％CI:1.052～2.350),listening for a duration of 0.5～2 h(OR=1.661,95％CI:1.011～2.695),music style of melancholy(OR=2.668,95％CI:1.701～4.226)and of nostalgia(OR=1.751,95％CI:1.086～2.837),and frequency of comments on 0～5％of songs(OR=2.938,95％CI:1.018～8.417)were independent risk factors for depressive tendency.Time since listening to music for 1～3 years(OR=0.547,95％CI:0.347～0.872),listening to music from 14:00 to 18:00(OR=0.375,95％CI:0.167～0.845)and 18:00 to 21:00(OR=0.313,95％CI:0.148～0.671),and preference for Chinese style songs(OR=0.711,95％CI:0.541～0.941)were independent protective factors.The logistic early warning model based on SMOTEENN algorithm demonstrated optimal predictive performance with an AUC value of 0.923.Conclusion Our constructed logistic regression model has identified 9 independent influencing factors associated with depression tendency among college students.The early warning model based on SMOTEENN algorithm can predict the depression tendency more accurately for college students.

Kawasaki disease，a common acute febrile and eruptive disease in children，can lead to coronary artery disease，emerging as one of the most common causes of acquired heart diseases.However，the pathogenesis of Kawasaki disease with coronary artery lesions is unknown，and interaction between inflammatory cytokines and Kawasaki disease with its coronary artery lesions remains to be elucidated.This paper reviews the role of cytokines in Kawasaki disease complicated with coronary artery lesions，and explores the specific mechanisms of inflammatory and anti-inflammatory factors in detail.Cytokines play a key role in the pathogenesis of Kawasaki disease and the formation of coronary complications.This review highlights that monitoring the levels of cytokines is of great value in predicting the risk of Kawasaki disease and coronary complications.In addition，it is expected that interventions，for example，inhibition of pro-inflammatory factors and enhancement of the activity of anti-inflammatory factors，could improve the prognosis of some children with Kawasaki disease，which has potential importance in clinical applications.

Blood-brain barrier (BBB) damage after ischemia significantly influences stroke outcome. Compound LFHP-1c was previously discovered with neuroprotective role in stroke model, but its mechanism of action on protection of BBB disruption after stroke remains unknown. Here, we show that LFHP-1c, as a direct PGAM5 inhibitor, prevented BBB disruption after transient middle cerebral artery occlusion (tMCAO) in rats. Mechanistically, LFHP-1c binding with endothelial PGAM5 not only inhibited the PGAM5 phosphatase activity, but also reduced the interaction of PGAM5 with NRF2, which facilitated nuclear translocation of NRF2 to prevent BBB disruption from ischemia. Furthermore, LFHP-1c administration by targeting PGAM5 shows a trend toward reduced infarct volume, brain edema and neurological deficits in nonhuman primate

Objective:To explore the mechanism of circular permuted tumor necrosis factor-related apoptosis-inducing ligand (CPT) reversing the resistance to imatinib in chronic myeloid leukemia (CML) cells.Methods:Five patients with CML in the Affiliated Hospital of Inner Mongolia Medical University from 2016 to 2020 were selected, and heparinized bone marrow blood samples were collected at the first diagnosis and imatinib resistance phase, and mononuclear cells were isolated. The mononuclear cells collected at the first diagnosis were named A1-E1, and the mononuclear cells collected after imatinib resistance were named A2-E2. Human CML wild-type K562 cell line (K562-W) was given gradually increasing small doses of low-concentration imatinib to obtain imatinib-resistant K562 cells (K562-R). K562-R cells were cultured with 20 μg/L CPT and these cells were set as CPT-K562-R group. The CCK-8 method was used to detect the half inhibitory concentration ( IC50) of cells for imatinib. K562-W and K562-R cells were used to establish CML xenografts nude mice models, then the nude mice were divided into K562-W, K562-R and CPT-K562-R xenograft groups. Imatinib was perfused orally in all three groups, and CPT was injected subcutaneously in the CPT-K562-R group at the same time. The tumor volume of the three groups of nude mice before and 4 weeks after treatment with imatinib, and the survival time of the three groups of nude mice were compared. Western blot was used to detect the changes of tyrosine protein kinase receptor B4 (EphB4) and myeloid cell leukemia protein 1 (Mcl-1) protein levels in bone marrow mononuclear cells, K562 cell line and transplanted tumor tissues of CML patients. Results:The expressions of EphB4 protein in A2-E2 cells of 5 patients with CML were higher than those in A1-E1 cells (all P < 0.01). The IC50 of K562-W, K562-R and CPT-K562-R cells for imatinib were (0.160±0.015) mg/L, (5.450±0.460) mg/L, (0.300±0.035) mg/L, and the difference was statistically significant ( F = 390.65, P < 0.01). In cells of K562-W group, EphB4 and Mcl-1 proteins were expressed at low levels (0.54±0.02 and 0.70±0.08); in cells of K562-R group, the expressions of EphB4 and Mcl-1 proteins were enhanced (3.04±0.11 and 2.88±0.04); in cells of CPT-K562-R group, the expressions of EphB4 and Mcl-1 proteins decreased (0.57±0.03 and 0.38±0.04). Before imatinib treatment, there was no statistically significant difference in the tumor volumes of nude mice among the K562-W, K562-R and CPT-K562-R xenograft groups ( F = 0.39, P = 0.68), suggesting the transplanted tumors formed in nude mice were balanced; after imatinib treatment, the difference in the tumor volumes among the three groups were statistically significant ( F = 26.16, P < 0.01). The survival time of nude mice in the K562-W, K562-R and CPT-K562-R xenograft groups was (18.5±3.3) d, (10.0±2.4) d and (17.5±1.6) d, and the difference was statistically significant ( F = 20.45, P < 0.01). In K562-W xenograft group, both EphB4 and Mcl-1 proteins were expressed at low levels (0.55±0.06 and 0.67±0.06); in K562-R xenograft group, the expressions of EphB4 and Mcl-1 proteins were enhanced (1.95±0.08 and 6.21±0.53); the expressions of EphB4 and Mcl-1 in CPT-K562-R xenograft group decreased (0.59±0.04 and 0.37±0.04) and were close to their expressions in K562-W xenograft group. Conclusion:CPT may enhance the sensitivity of CML to imatinib by inhibiting the expressions of EphB4 and Mcl-1, and this may be a targeted pathway for imatinib therapy.

Objective:To investigate the distribution and drug resistance of pathogens causing blood stream infection in patients with pancreatic neoplasms.Methods:Clinical data of patients with pancreatic neoplasms complicated with bloodstream infection with confirmed pathological evidence admitted in the First Affiliated Hospital of Naval Medical University from January 2016 to June 2019 were collected. Bacteria were isolated from blood culture, and microbial sensitivity tests were analyzed by minimum inhibitory concentration and Kirby-Bauer methods. The distribution and drug resistance of pathogens causing blood stream infection in patients with pancreatic neoplasms were analyzed.Results:There were 116 cases (8.5%) with bloodstream infection in 1 372 patients with pancreatic neoplasms. A total of 156 bacterial strains were isolated from blood culture, of which 127 strains (81.4%) were gram negative aerobic bacteria, mainly including Escherichia coli (42 strains), Klebsiella pneumoniae (34 strains), Pseudomonas aeruginosa (12 strains), and 25 strains (16.0%) were gram positive aerobic bacteria, mainly including Enterococcus faecium (11 strains), Enterococcus faecalis (3 strains), Streptococcus angina (3 strains). 4 strains (2.6%) were anaerobic bacteria. The results of antibiotic susceptibility showed that the resistance rate of Escherichia coli to ampicillin was 90.5%, and to cefoperazone-sulbactam was 2.4%. The resistance rate of Klebsiella pneumoniae to piperacillin was 20.6%, and to cefoperazone-sulbactam was 5.9%. The resistance rate of Pseudomonas aeruginosa to imipenem was 41.7%, and no resistant strain was found to cefoperazone-sulbactam. The resistance rate of Enterococcus and Streptococcus pharyngitis to erythromycin were 85.7% and 33.3%, and no strains were resistant to vancomycin.Conclusions:The rate of blood stream infection in patients with pancreatic neoplasms was relatively high. In clinical practice, the distribution of pathogenic bacteria should be understood, the drug resistance should be monitored and antibiotics should be reasonably used, in order to maximally prevent and interfere with the occurrence of blood stream infection.

In addition to causing high disability and high fatality rates, ruptured intracranial aneurysms can also cause cognitive impairment. Although preventive surgical treatment can avoid intracranial aneurysm rupture and bleeding, patients may still have a certain degree of cognitive impairment, even in patients with good clinical recovery after surgery. There is no systematic review on the effect of different surgical methods on cognitive function, and the best surgical method is still inconclusive. This article reviews the cognitive impairment in patients with intracranial aneurysm, hoping to provide a basis for clinical treatment decisions.

Objective To explore the effect of quality control circles (QCCs) in improving the delivery health checkup report.Methods QCC was founded with the theme of"improving the quality of health checkup report delivery."First,we planned an activity schedule and identified topics.We then set target focuses for service personnel,distribution modes,and operating environments;planned countermeasures;and selected optimal policies.Circle members implemented the optimal policies jointly.Reports of physical examinations by the Guoyu health management center were selected and analyzed.The total number of reports before improvement (January to December 2015) was 59 189 of which 34 549 (58.4％) were male patients and 24 640 (41.6％) were female patients;their average age was (37.7± 11.4) years.The total number of reports after improvement (December 2016 to January 2017) was 6 568,of which 3 881 (59.1％) were male patients and 2 687(40.9％) were female patients;their average age was (39.9± 11.7) years.We compared the quality indicators and evaluated the comprehensive quality of the patients before and after improvement.A total of 65 531 physical examination reports of subjects examined at the center between February and December 2017 were selected for effect tracking,including 39 230 (59.9％) men and 26 301(40.1％) women,aged (38.1±11.5).Results The on-time delivery rate of the health examination reports from rose from 51.4％ to 94.0％.The ratio of system leakage to sign for reports decreased from 14.5％ to 0.8％.The average time between the examination and when each report was handed over to for distribution decreased from 29.8 hours to 4.2 hours,and the average time between each report being distributed to the providers checking in dropped from 509.8 hours to 72.8 hours,while the average time for the preparation of each report for delivery decreased from 13.5 seconds to 3.1 seconds.The average time between delivery of a report and its being signed decreased from 4.3 seconds to 0.1 seconds.Before the improvement,the expected goals were not met.After improvement,the delivery rate of the health examination reports was 100.0％,the delivery intact rate of the group reports was 100.0％,and the satisfaction rate of the group reports was 99.4％.The comprehensive quality for the members was obviously higher after the improvement than before.After 11 months of tracking,the delivery accuracy rate of health examination report still failed to reach the target value of 100.0％,but all other indicators reached the target value,with good results.Conclusions Application of QCC not only improved the delivery the health checkup reports,but also promoted service quality after medical examinations and ended medical dispute caused by the loss of physical examination reports.