OBJECTIVE To explore and evaluate the machine learning model for prediction of bacterial bloodstream infections established based on routine test data.METHODS By means of retrospective survey,a total of 5 421 pa-tients who were hospitalized in 3 medical institutions from Jan.2015 to Dec.2022 were recruited as the research subjects,1 914 of whom were assigned as the bloodstream infection group,and 3 507 were assigned as the non-bloodstream infection group.The baseline data including gender and age and the results of routine laboratory tests were collected from the enrolled patients.The 3 types of machine learning algorithms,logistic regression,support vector machine and random forest,were respectively used for the screening of the optimal prediction model;the contribution of feature variables to the predictive capability of the model was interpreted through SHAP.The fea-ture variables of the model were optimized by using recursive feature elimination method,and the predictive effi-ciency of the model was evaluated by the area under the curve(AUC)of receiver operating characteristic(ROC)curves.RESULTS Totally 26 variables involving age,gender and blood routine test indexes were included.The random forest was chosen as the optimal machine learning algorithm for the establishment of prediction model for bloodstream infections,and the accuracy of the model was 0.709,with the AUC 0.706.The result of SHAP ex-planation indicated that the age,hematokrit and erythrocyte volume distribution width-CV had remarkable effect on the model's making right decisions.17 variables of the prediction model showed more remarkable effect than 26 variable on distinguishing from the gram-positive bacteria bloodstream infections from the gram-negative bacteria bloodstream infections,with the AUC 0.715,the sensitivity 0.701,the specificity 0.632.CONCLUSIONS The prediction model that is established based on the blood routine test indexes by machine learning algorithm can pre-dict the bacterial bloodstream infection.Meanwhile,the feature selection strategy can further improve the predic-tive efficiency of the model on basis of lowering the dimensionality.

OBJECTIVE To explore and evaluate the machine learning model for prediction of bacterial bloodstream infections established based on routine test data.METHODS By means of retrospective survey,a total of 5 421 pa-tients who were hospitalized in 3 medical institutions from Jan.2015 to Dec.2022 were recruited as the research subjects,1 914 of whom were assigned as the bloodstream infection group,and 3 507 were assigned as the non-bloodstream infection group.The baseline data including gender and age and the results of routine laboratory tests were collected from the enrolled patients.The 3 types of machine learning algorithms,logistic regression,support vector machine and random forest,were respectively used for the screening of the optimal prediction model;the contribution of feature variables to the predictive capability of the model was interpreted through SHAP.The fea-ture variables of the model were optimized by using recursive feature elimination method,and the predictive effi-ciency of the model was evaluated by the area under the curve(AUC)of receiver operating characteristic(ROC)curves.RESULTS Totally 26 variables involving age,gender and blood routine test indexes were included.The random forest was chosen as the optimal machine learning algorithm for the establishment of prediction model for bloodstream infections,and the accuracy of the model was 0.709,with the AUC 0.706.The result of SHAP ex-planation indicated that the age,hematokrit and erythrocyte volume distribution width-CV had remarkable effect on the model's making right decisions.17 variables of the prediction model showed more remarkable effect than 26 variable on distinguishing from the gram-positive bacteria bloodstream infections from the gram-negative bacteria bloodstream infections,with the AUC 0.715,the sensitivity 0.701,the specificity 0.632.CONCLUSIONS The prediction model that is established based on the blood routine test indexes by machine learning algorithm can pre-dict the bacterial bloodstream infection.Meanwhile,the feature selection strategy can further improve the predic-tive efficiency of the model on basis of lowering the dimensionality.

With the extensive application of uranium in military, industrial and civil fields, the possibility of human exposure to uranium has become increasingly likely. When uranium is accidentally released into the environment, it can enter the human body by various pathways and accumulate in the kidneys, leading to proximal tubule epithelial cell damage or even death, and in severe cases, nephrotoxicity. Uranium exerts both chemical and radiological toxicity, with its kidney-damaging effects primarily attributed to chemical toxicity. Low-level uranium exposure causes mild kidney damage, while prolonged or high-level exposure alters kidney structure and biomarker level of uranium-induced nephrotoxicity (such as creatinine, urea nitrogen and kidney injury molecule-1, etc.). Uranium exposure also induces DNA damage and mutations, kidney inflammation, and renal cell autophagy. Current research on uranium nephrotoxicity primarily focuses on uranium-induced mitochondrial dysfunction, which leads to oxidative stress and apoptosis (mainly by mitochondrial and endoplasmic reticulum pathway), ultimately causing renal tissue damage. However, the molecular mechanisms underlying uranium-induced kidney toxicity remain incomplete. Future research on mechanism of uranium-induced cell damage, especially metabolism, intracellular distribution, and additional mechanisms, remains a long-term and challenging endeavor.

Syringa oblata is a traditional Mongolian medicine mainly distributed in the Helan Mountains (the boundaries of Inner Mongolia and Ningxia, China) and the north of Yan Mountains (Aohan Qi, Inner Mongolia, China). It is clinically used to treat diseases caused by Heyi, such as heartache and heat pathogen in the heart. Phytochemical studies on S. oblata revealed the presence of iridoids, lignans, triterpenes, phenylpropanoids, phenylethanoids, and volatile components. Pharmacological investigations revealed a broad spectrum of bioactivities, such as antimicrobial, antioxidant, antiproliferative, and hepatoprotective effects. This article summarized the chemical components and pharmacological activities of S. oblata, providing a scientific rationale for its bioactive constituents, quality control, and utilization as an important medicine.

Objective To investigate the effect of the Notch signaling pathway on the proliferation and invasion of human SW982 synovial sarcoma cells. Methods SW982 cells and normal human synovial cells were routinely cultured, and the expression of proteins related to the Notch pathway was compared. The Notch signaling pathway was manipulated by NICD1 overexpression, CFB1 shRNA lentivirus, and the γ-secretase inhibitor, DAPT. CCK-8 and wound healing assays were carried out to investigate the role of the Notch signaling pathway in SW982 cells. Results The Notch signaling pathway clearly showed higher activity in human SW982 synovial sarcoma cells than in normal human synovial cells (P ＜ 0.05). The proliferation and invasion of SW982 cells were significantly upregulated by overexpressing NICD1; however, were suppressed by downregulating the Notch signaling pathway using CFB1 shRNA or DAPT (P ＜ 0.05). Conclusion Our findings demonstrate that the proliferation and invasion of human SW982 synovial sarcoma cells are dependent on Notch signaling pathway activity.

Objective To investigate the role of Notch signaling pathway to maintain the stem cell-like characteristics of osteosarcoma and its underlying mechanism.Methods Lentiviral NICD1 or Numb-shRNA was transduced into MG63 osteosarcoma cells to activate Notch activity in vitro.The impact of Notch on osteosarcoma stem cells were assessed by the tumor sphere formation assay and flow cytometry analysis of cell surface markers STRO-1/CD117.The expression of stem cell related genes (Sox2,Oct4) were evaluated by Western blot and qPCR.The nude mice were randomly divided into 3 groups:the NICD1 overexpression (NICD-OE) group,the DAPT group and the control (CON) group.The tumor growth was monitored for 8 weeks and the tumor volume and weight were recorded weekly.To investigate whether Notch regulates Eph pathway,Eph pathway related protein EphB,pEphB was measured by Western blot.The impact of ephrinB 1 on NICD overexpression cell were assessed by tumor sphere formation assay.The expression of Sox2 and Oct4 was evaluated by Western blot.Results NICD1 overexpression or Numb-shRNA increased the activity of Notch pathway.The Notch-activated osteosarcoma showed enhanced in vitro tumor spheroid formation capacity,increased Stro-1/CD117double positive ratio,and upregulated expression of Sox2 and Oct4 in vitro.In animal experiments,it was found that activation of Notch pathway promoted tumor formation in vivo and Notch inhibition decreased it.The primary osteosarcoma cells were obtained from mice xenograft treated with DAPT and its tumor sphere formation capacity was significantly reduced.Finally,The Notch pathway inhibits the phosphorylation of EphB,as well as the downstream signal pathway of EphB,but there is no significant change in total EphB.The activation of Eph pathway inhibited Notch induced up-regulation of tumor sphere formation and Sox2 and Oct4 expression.Conclusion Notch signaling pathway maintains the stem cell-like characteristics of osteosarcoma probably by inhibiting the Eph pathway.

Objective: To investigate the efficacy and safety of anlotinib hydrochloride capsules for the treatment of advanced soft tissue sarcoma based on the data from Department of Bone and Soft Tissue Tumor, Peking University Cancer Hospital&Institute. Methods: Patients were randomized allocated at 2:1 ratio for the anlotinib treatment and placebo group. The treatment group received 12 mg/day of anlotinib for 14 consecutive days in a 21-day cycle. The primary end-point was progression-free survival (PFS), and the secondary end-points were disease control rate (DCR), overall survival (OS), and adverse event rate. Results: A total of 46 patients were enrolled in this study; 7 of them were excluded from per protocol set (PPS). Among the remaining 39 patients, 28 were included in the anlotinib group and 11 in the placebo group. In the anlotinib group, 4 patients had partial remission and 13 had stable disease (SD), whereas in the placebo group, 3 patients had SD. The difference in DCR between the 2 groups was statistically significant (60.7% vs . 27.3%, P=0.082). The DCR of the advanced soft tissue sarcoma in the anlotinib group was 78.6% (11/14). The median PFS in the anlotinib group was 12.4 (95% confidence interval [CI]: 7.6 to 17.2) months, which was significantly longer than 4 months in the placebo group (95% CI: 1.7 to 6.3 months, P=0.043); however, the difference in OS between the 2 groups was not significant (19.4 vs . 17.6 months, P=0.961). Regarding the safety, 2 patients had severe adverse events (7.14%) possibly related with treatment in the anlotinib group; one of them had pneumothorax. The other adverse events were grade 1 to 2. Conclusions: Soft tissue sarcoma is highly responsive to anlotinib, with prolonged PFS. Anlotinib is well tolerated and can be used as a treatment option for advanced soft tissue sarcoma.

Objective:To explore the outcome of soft tissue sarcoma (STS) on patients with soft tissue metastasis. Methods:We ana-lyzed 25 STS patients with soft tissue metastasis primarily localized on extremity and trunk. The study was conducted from June 2010 to June 2016 by retrospective analysis of the clinical and pathological characteristics of the patients. The assessed endpoints were overall survival. Results:Six patients (24%) had synchronous soft tissue metastasis, and 19 patients (76%) had metachronous metasta-sis. The average time for primary tumor recession of metastatic lesions was 45.3 months. Metastases were most common in parts of the trunk in 18 patients (72%), followed by the head and neck in 5 patients (20%). Eleven patients (44%) with lung metastasis had poor prognosis. Conclusion:STS occurred more rarely in soft tissue metastasis than in pulmonary metastasis. Neoadjuvant chemotherapy and surgical treatment were the major therapies employed. Targeted therapy as a new treatment rendered good results.

Objective To investigate the effect of galangin on proliferation and apoptosis of glioma cells in vitro.Methods (1) The glioma cells U87 and U25 1were divided into blank control group,DMSO group,100,200,300 and 400 μmol/L galangin treatment groups.MTT was used to study the effects of drugs on the proliferation of U251 and U87 cells.(2) Hoechest staining was used to observe cell apoptosis in the presence of different concentrations of galangin (0,100 and 200 μmol/L).(3) Flow cytometry was employed to detect the apoptosis of U251 and U87 cells in the presence of different concentrations of galangin (1 00 and 200 μmol/L).(4) Western blotting was employed to detect the expressions of apoptosis-related protein 3-Catenin,B-cell lymphoma-2 (Bcl-2),Bcl-2 related protein gene (Bax),cleaved-caspase-3,cleaved-caspase-9 and poly (ADP-ribose) polymerase (PARP) in the presence of different concentrations of galangin.Results (1) The proliferation of U251 and U87 cells was obviously inhibited atter 100,200,300 and 400 μmol/L galangin treatments,and dose-effect relation was noted.The concentrations of galangin at half rate of inhibition (IC50) were 281,321,276 and 229 μmol/L in U251 cells,and 289.4,261.1,247.4 and 225.3 μ mol/L in the U87 cells after 100,200,300 and 400μmol/L galangin treatments for 24 h.(2) Under the action of galangin,corresponding increase in apoptosis rates of U251 and U87 cells was noted following the increase of galangin concentrations (0,100 and 200 μmol/L),with significant differences (P＜0.05).(3) The detection of cell apoptosis by flow cytometry found similar changes.(4) Western blotting results indicated that galangin at the concentration of 0,100 and 200 μmol/L could significantly decrease the expressions of apoptosis-related protein 3-Catenin and Bcl-2,and increase the Bax,cleaved-caspase-3 and cleaved-caspase-9,and cleaved-PARP expressions;significant differences were noted between each two concentrations (P＜0.05).Conclusion Galangin can inhibit proliferation of glioma cells U251 and U87,and induce mitochondrial pathway of apoptosis via Wnt/β-Catenin signaling.

OBJECTIVETo characterize the clinical features of desmoid tumor, assess the efficacy of conservative chemotherapy for inoperable desmoid tumor and analyze the prognostic factors.

METHODSFrom August 2009 to December 2013, 52 patients with inoperable desmoid tumor were treated in our department and received chemotherapy with vinorelbine combined with low-dose methotrexate. The clinical data of the patients were analyzed retrospectively.

RESULTSThe patients studied included 22 male and 30 female patients with the age of disease onset ranging from 2 to 46 years (mean 18.7 years). The lesions occurred most frequently in the lower limbs (36.5%, 19/52) and the tumor size ranged from 2.7 to 37 cm (mean 9.5 cm). The patients were followed up for a median of 29 months (7 to 64 months). The chemotherapy lasted for 4 to 30 months (median 12 months). After completion of the chemotherapy, 1 patient had a complete response (CR), 18 showed partial responses (PR), 27 cases had stable disease (SD), and 6 had progressive disease (PD), with an overall response rate (ORR) of 88.5%. The progression-free survival (PFS) time of the patients ranged from 4 to 63 months (median 26.5 months) with a 2-year PFS rate of 76.7% and 5-year PFS rate of 41.9%. A longer chemotherapy duration (over 12 months) was associated with a more favorable prognosis. No significant differences in PFS were found between the patients stratified by gender, age of disease onset, age when receiving chemotherapy, tumor site, or tumor size.

CONCLUSIONFor recurrent, inoperable and progressive desmoid tumor, long enough cycles of vinorelbine combined with low-dose methotrexate can be an effective and safe option for tumor control.

Adolescent ; Adult ; Antineoplastic Combined Chemotherapy Protocols ; Child ; Child, Preschool ; Disease-Free Survival ; Female ; Fibromatosis, Aggressive ; drug therapy ; Humans ; Male ; Methotrexate ; administration & dosage ; therapeutic use ; Middle Aged ; Prognosis ; Retrospective Studies ; Vinblastine ; administration & dosage ; analogs & derivatives ; therapeutic use ; Young Adult