Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

The abuse of novel phenylcyclohexylpyridine drugs poses a significant threat to societal safety. The novel psychoactive substance 2-methyl-deschloroketamine (2-MDCK), belonging to the phenylcyclohexylpyridine class, has recently surfaced as a new compound. However, there is a lack of understanding regarding its metabolic pathways and the identification of suitable biomarkers. In this study, a human liver microsomal model was established, and ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) technology was applied to investigate the in vitro metabolism and products of 2-MDCK. The results indicate that 2-MDCK undergoes various metabolic reactions, including dehydrogenation, deamination, hydroxylation, and demethylation, leading to the formation of eight metabolites. By conducting actual testing on hair samples from 2-MDCK abusers, the existence of six metabolites was confirmed. Comparing the metabolic products in the liver microsomal in vitro model, M3.1 and M4.1 were identified as biomarkers for 2-MDCK consumption. Five samples of abusers of 2-methyl-dechloroketamine were provided by the Anti-Drug Brigade of the Hangzhou Public Security Bureau. Negative hair samples were provided by laboratory volunteers, and all samples were obtained with the informed consent of the volunteers. These findings provide a scientific basis for the detection and identification of 2-MDCK and its metabolites, as well as crucial support for the study of the metabolic mechanisms of similar novel psychoactive substances in the phenylcyclohexylpyridine class. This research holds significant importance in addressing the issue of abuse of new psychoactive substances.

Objective To observe the cage subsidence after oblique lateral interbody fusion(OLIF)for lumbar spondylo-sis,summarize the characteristics of the cage subsidence,analyze causes,and propose preventive measures.Methods The data of 144 patients of lumbar spine lesions admitted to our hospital from October 2015 to December 2018 were retrospectively ana-lyzed.There were 43 males and 101 females,and the age ranged from 20 to 81 years old,with an average of(60.90±10.06)years old.Disease types:17 patients of lumbar intervertebral disc degenerative disease,12 patients of giant lumbar disc hernia-tion,5 patients of discogenic low back pain,33 patients of lumbar spinal stenosis,26 patients of lumbar degenerative spondy-lolisthesis,28 patients of lumbar spondylolisthesis with spondylolisthesis,11 patients of adjacent vertebral disease after lumbar internal fixation,7 patients of primary spondylitis in the inflammatory outcome stage,and 5 patients of lumbar degenerative scoliosis.Preoperative dual-energy X-ray bone mineral density examination showed 57 patients of osteopenia or osteoporosis,and 87 patients of normal bone density.The number of fusion segments:124 patients of single-segment,11 patients of two-seg-ment,8 patients of three-segment,four-segment 1 patient.There were 40 patients treated by stand-alone OLIF,and 104 patients by OLIF combined with posterior pedicle screw.Observed the occurrence of fusion cage settlement after operation,conducted monofactor analysis on possible risk factors,and observed the influence of fusion cage settlement on clinical results.Results All operations were successfully completed,the median operation time was 99 min,and the median intraoperative blood loss was 106 ml.Intraoperative endplate injury occurred in 30 patients and vertebral fracture occurred in 5 patients.The mean follow-up was(14.57±7.14)months from 6 to 30 months.During the follow-up,except for the patients of primary lumbar interstitial in-flammation and some patients of lumbar spondylolisthesis with spondylolisthesis,the others all had different degrees of cage subsidence.Cage subsidence classification:119 patients were normal subsidence,and 25 patients were abnormal subsidence(23 patients were grade Ⅰ,and 2 patients were grade Ⅱ).There was no loosening or rupture of the pedicle screw system.The height of the intervertebral space recovered from the preoperative average(9.48±1.84)mm to the postoperative average(12.65±2.03)mm,and the average(10.51±1.81)mm at the last follow-up.There were statistical differences between postop-erative and preoperative,and between the last follow-up and postoperative.The interbody fusion rate was 94.4％.The low back pain VAS decreased from the preoperative average(6.55±2.2 9)to the last follow-up(1.40±0.82),and there was statistically significant different.The leg pain VAS decreased from the preoperative average(4.72±1.49)to the final follow-up(0.60± 0.03),and the difference was statistically significant(t=9.13,P＜0.000 1).The ODI index recovered from the preoperative av-erage(38.50±6.98)％to the latest follow-up(11.30±3.27)％,and there was statistically significant different.The complication rate was 31.3％(45/144),and the reoperation rate was 9.72％(14/144).Among them,8 patients were reoperated due to fusion cage subsidence or displacement,accounting for 57.14％(8/14)of reoperation.The fusion cage subsidence in this group had obvious characteristics.The monofactor analysis showed that the number of abnormal subsidence patients in the osteopenia or osteoporosis group,Stand-alone OLIF group,2 or more segments fusion group,and endplate injury group was higher than that in the normal bone mass group,OLIF combined with pedicle screw fixation group,single segment fusion group,and no endplate injury group,and the comparison had statistical differences.Conclusion Cage subsidence is a common phenomenon after 0-LIF surgery.Preoperative osteopenia or osteoporosis,Stand-alone OLIF,2 or more segments of fusion and intraoperative end-plate injury may be important factors for postoperative fusion cage subsidence.Although there is no significant correlation be-tween the degree of cage subsidence and clinical symptoms,there is a risk of cage migration,and prevention needs to be strengthened to reduce serious complications caused by fusion of cage subsidence,including reoperation.

BACKGROUND:Due to the young age of children,the occipital condyle and foramen magnum are not fully developed,and they are prone to various diseases and injuries in the occipitocervical junction,which requires surgical treatment in severe cases.However,anatomical parameters for the development of the occipital condyle and foramen magnum in children are lacking. OBJECTIVE:To measure the morphological structure of the occipital condyle and foramen magnum by three-dimensional reconstruction technique,and to provide important anatomical parameters for occipitocervical junction lesions,related surgical procedures and forensic identification. METHODS:Imaging data of 389 cases of primitive children and adolescents involved in skull base undergoing spiral CT scanning(247 males and 142 females)aged 1-18 years were collected and divided into 1-3-year-old group,4-6-year-old group,7-9-year-old group,10-12-year-old group,13-15-year-old group,and 16-18-year-old group according to their age.Mimics 16.0 software was used to reconstruct the skull base and measure the length and width of the foramen magnum.A formula was used to calculate the area and index of the foramen magnum.We measured the length,width and height of the occipital condyle,the angle between the long axis and the sagittal axis of the occipital condyle(O-S angle),the included angle between the midpoint of the front and back edges of the foramen magnum and the connection between the back edge of occipital condyle and the intersection point of the foramen magnum(F-O angle),and the included angle between the midpoint of the front and back edges of the foramen magnum and the midpoint of the back wall of the sublingual neural tube(F-H angle).Gender,side and age differences were analyzed among the indicators. RESULTS AND CONCLUSION:(1)In foramen magnum measurement,there was no significant difference between sexes in the index of the foramen magnum(P>0.05),but there were significant differences in length,width and area of the foramen magnum(P<0.05).(2)The O-S angle,F-O angle and F-H angle of the occipitral condyle were not significantly different between genders(P>0.05),but length,width and height of the occipital condyle were significantly different between genders(P<0.05).(3)There were no significant differences in the length of the occipital condyle among different groups(P>0.05),but there were significant differences in the width and height of the occipital condyle,O-S angle,F-O angle and F-H angle among different groups(P<0.05).(4)Length,width and area of the foramen magnum,length,width and height of the occipital condyle showed a wavy increasing trend with the increase of age,while O-S,F-O and F-H angles showed a wavy decreasing trend with the increase of age,while the index of the foramen magnum showed no significant change.(5)In conclusion,there are gender and lateral differences in the morphological indexes of the foramen magnum and the occipital condyle in children.These differences can provide an important reference for clinical surgical approach selection and forensic examination.

Objective To investigate the distribution and antimicrobial susceptibility of clinically isolated bacteria from intensive care units(ICUs)in hospitals of Hunan Province Antimicrobial Resistance Surveillance System from 2012 to 2021.Methods According to China Antimicrobial Resistance Surveillance System,data of clinically isolated bacterial strains and antimicrobial susceptibility testing results of bacteria from ICUs reported by all member units of Hunan Province Antimicrobial Resistance Surveillance System were analyzed with WHONET 2022 software.Results From 2012 to 2021,the total number of bacteria isolated from ICUs of member units of the Hunan Province Antimi-crobial Resistance Surveillance System was 5 777-22 369,with Gram-negative bacteria accounting for 76.1％-78.0％annually.Staphylococcus aureus ranked first among isolated Gram-positive bacteria each year.The top 5 bacteria among Gram-negative bacteria were Acinetobacter baumannii,Klebsiella pneumoniae,Escherichia coli,Pseudo-monas aeruginosa,and Stenotrophomonas maltophilia.Detection rate of methicillin-resistant Staphylococcus aureus showed a downward trend year by year.No Staphylococcus spp.were found to be resistant to vancomycin,teico-planin and linezolid.Detection rates of vancomycin-resistant Enterococcus faecalis and vancomycin-resistant Entero-coccus faecium were 0.6-1.1％and 0.6％-2.2％,respectively.Resistance rates of Escherichia coli and Kleb-siella pneumoniae to imipenem were 3.1％-5.7％and 7.7％-20.9％,respectively.Resistance rates of Pseudo-monasaeruginosa and Acinetobacter baumannii to imipenem were 24.6％-40.1％and 76.1％-80.9％,respective-ly.Detection rates of carbapenem-resistant Pseudomonas aeruginosa declined year by year.Acinetobacter baumannii maintained high susceptibility to polymyxin B,with resistance rate＜10％.Conclusion Antimicrobial resistance of bacteria from ICUs is serious.Carbapenem-resistant Enterobacteriales has an upward trend after 2019.It is nece-ssary to strengthen the surveillance of bacterial resistance and carry out multidisciplinary collaboration.

Objective:To evaluate the efficacy of acute T-cell lymphoblastic leukemia(T-ALL)in children and explore the prognostic risk factors.Methods:The clinical data of 127 newly diagnosed children with T-ALL admitted to five hospitals in Fujian province from April 2011 to December 2020 were retrospectively analyzed,and compared with children with newly diagnosed acute precursor B-cell lymphoblastic leukemia(B-ALL)in the same period.Kaplan-Meier analysis was used to evaluate the overall survival(OS)and event-free survival(EFS),and COX proportional hazard regression model was used to evaluate the prognostic factors.Among 116 children with T-ALL who received standard treatment,78 cases received the Chinese Childhood Leukemia Collaborative Group(CCLG)-ALL 2008 protocol(CCLG-ALL 2008 group),and 38 cases received the China Childhood Cancer Collaborative Group(CCCG)-ALL 2015 protocol(CCCG-ALL 2015 group).The efficacy and serious adverse event(SAE)incidence of the two groups were compared.Results:Proportion of male,age ≥ 10 years old,white blood cell count(WBC)≥ 50 × 109/L,central nervous system leukemia,minimal residual disease(MRD)≥ 1％during induction therapy,and MRD ≥ 0.01％at the end of induction in T-ALL children were significantly higher than those in B-ALL children(P＜0.05).The expected 10-year EFS and OS of T-ALL were 59.7％and 66.0％,respectively,which were significantly lower than those of B-ALL(P＜0.001).COX analysis showed that WBC ≥ 100 x 109/L at initial diagnosis and failure to achieve complete remission(CR)after induction were independent risk factors for poor prognosis.Compared with CCLG-ALL 2008 group,CCCG-ALL 2015 group had lower incidence of infection-related SAE(15.8％vs 34.6％,P=0.042),but higher EFS and OS(73.9％vs 57.2％,PEFS=0.090;86.5％vs 62.3％,PoS=0.023).Conclusions:The prognosis of children with T-ALL is worse than children with B-ALL.WBC ≥ 100 × 109/L at initial diagnosis and non-CR after induction(especially mediastinal mass has not disappeared)are the risk factors for poor prognosis.CCCG-ALL 2015 regimen may reduce infection-related SAE and improve efficacy.