OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

Objective: To analyze the school tuberculosis (TB) outbreaks and preventive treatment in Hefei from 2022 to 2024, so as to provide reference for TB prevention and control in schools. Methods: Data were collected on all school based TB outbreaks occurring during 2022-2024 in Hefei, defined as ≥2 epidemiologically linked TB cases within the same school during a single semester. Statistical analyses were performed using the Chi square test. Results: Close contacts exhibited significantly higher TB incidence (2.88%) and latent mycobacterium tuberculosis infection (LTBI) rates (13.80%) in the school TB outbreaks, compared to non close contacts (0.12% and 2.63%, respectively). Among close contacts, secondary school students showed lower TB incidence (0.48%) and LTBI prevalence (3.42%) than both primary school or younger children (0.68%, 6.95%) and college students ( 0.78% , 6.50%), with statistically significant differences ( χ 2=360.91, 6.37; 791.71, 102.03, all P <0.05). The proportion of LTBI individuals recommended for preventive therapy was higher in primary school or younger groups (98.59%) than in secondary (95.25%) or college students (86.34%) ( χ 2=25.86, P <0.01). However, among those recommended, close contacts had higher uptake (85.82%) and completion rates (87.25%) of preventive therapy than non close contacts (69.63% and 70.57%); similarly, secondary school students demonstrated higher uptake (91.21%) and completion rates (86.45%) compared to primary school or younger (88.57%, 83.87%) and college students (57.28%, 64.08%) ( χ 2=30.52, 26.72; 125.17, 38.84, all P <0.01). Subsequent TB incidence among LTBI close contacts (13.30%) and among those who did not complete preventive therapy (22.73%) were significantly higher than among non close contacts (2.80%, 2.41%), respectively ( χ 2=32.19, 13.87, both P <0.05). Conclusions In school TB outbreaks, close contacts face higher LTBI prevalence and subsequent TB risk than non close contacts. College students show notably low adherence to preventive therapy. It is necessary to take targeted measures to improve the compliance of preventive measures among students.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

A throat swab sample from a pediatric case in Tongzhou District, Beijing was identified as enterovirus; the patient was a 1-year-and-8-month-old male sporadic case. Whole-genome sequencing revealed a viral genome length of 7 436 bp. BLAST alignment confirmed the serotype as EV-D68. Phylogenetic analysis of the whole genome indicated that this strain belongs to the B3 clade, showing closer genetic proximity to the 2018 Shanghai strain MW697453 with 99.53% whole-genome nucleotide homology. Genetic and amino acid variation analysis demonstrated that the B3 subclade to which this strain belongs exhibits a nucleotide deletion at positions 718–726, differing from deletion sites observed in other B3 clade strains. A key neuropathogenic amino acid site, T650A, was found to have undergone mutation. Recombination analysis confirmed no cross-clade recombination events in this strain. This study conducted genetic characterization of the strain's evolutionary relationship with EV-D68 strains from different regions and years in China, providing data support for formulating prevention and control measures against EV-D68 infection.

Objective To understand the current situation and influencing factors of salary satisfaction of staff in tertiary public hospitals,and provide suggestions for improving the reform of salary system.Methods A questionnaire survey was conducted on 816 employees from 7 tertiary public hospitals in Hunan Province,and the basic situation,salary level,salary promotion,salary system and salary distribution were studied.Descriptive analysis and binary logistic regression model were used to analyze the status quo and influencing factors of employee salary satisfaction.Results The overall satisfaction score of the 816 survey respondents'salary was 71.56 points,at a relatively high level.There was a large difference in satisfaction levels among different regions.Salary level and salary increase satisfaction were 69.19 and 70.90 points respectively,and satisfaction was low.Region,affiliation with a university,cadre status,and title were the main factors affecting salary satisfaction.Conclusion The salary satisfaction of staff in tertiary public hospitals was generally higher in Hunan Province,and the reform had shown positive results.The satisfaction with salary increases and salary levels was relatively low,and it was suggested that the government reasonably determine the salary level of public hospitals and establish a scientific and reasonable salary increase mechanism.It will improve supporting reforms and promote equal pay for equal work.

Objective:To elucidate the genomic characteristics of the immunoglobulin (IG) heavy-chain variable region and light-chain variable region, the expression of subclones, and the prognostic significance in patients with CLL.Methods:Blood and/or bone marrow specimens were gathered from a cohort of 36 patients with CLL diagnosed at Jiangsu Province Hospital from December 2018 to May 2023, including 12 cases of B cell receptor (BCR) stereotyped patients. IG heavy-chain (IGH) and light-chain (IG Kappa [IGK] and IG lambda [IGL]) gene rearrangements were performed using next-generation sequencing (NGS) technology to analyze the characteristics and prognostic value in CLL.Results:NGS detection of IG variable region (IGHV) demonstrated a significant correlation and superior consistency with Sanger sequencing ( r=0.957, P < 0.001). Among the 36 patients, the IGH variant (IGHV) was observed in 9 (25.0%) but not in 27 (75.0%) participants. The incidence of the MYD88 mutation was higher among patients with mutated IGHV [1/27 (3.7%) vs 4/9 (44.4%), P=0.00]. A high incidence of trisomy 12 was observed in the IGHV #8/#8B subset [4/11 (36.4%) vs 1/25 (4.0%), P=0.023], which were more likely to develop Richter transformation [8/11 (72.7%) vs 4/25 (16.0%), P=0.002]. In the patient cohort, 36 individuals (36/36, 100.0%) used the IGK variable, whereas 15 individuals (15/36, 41.7%) employed the IGL variable (IGLV). IGLV3 - 21 reported the highest utilization rate in IGLV (5/15, 33.3%). Remarkably, patients with CLL with IGLV3-21 fragments were exclusively observed in the Binet C stage and Rai Phase Ⅲ-Ⅳ, with an incidence of del (13) (q14) at 60.0% (3/5). The median time to first treatment (TTFT) of patients with or without IGLV3 - 21 fragments was 5.2 (1.1 - 41.5) and 9.9 (0.1 - 94.4) months, respectively. Using the total reads threshold of 2.5%, 4 (4/36, 11.1%) samples were detected to have two IGHV productive clones. The median TTFT and overall survival (OS) time were 2.8 (0.9-72.7) and 12.8 months in patients with one mutated clone and 57.5 (32.0-120.7) and 51.8 months in those with two mutated clones, respectively. The median TTFT and OS time were 10.9 (0.3-94.4) and 6.3 (0.1 - 12.5) months in patients with one unmutated clone and 49.9 (22.2 - 211.1) and 30.0 (9.6 - 50.3) months in those with multiple unmutated clones, respectively ( P>0.05) . Conclusions:Detection of IG gene rearrangements using NGS technology not only facilitates the analysis of the IGHV mutation status, dominant clones, and prognostic value but also contributes to the exploration of IGK/IGL gene rearrangement fragments and the utilization of subclones. Further, it provides information about the poor prognosis of IGLV3 - 21 CLL. The shortened survival of the two unmutated clone groups in the IGHV unmutated group may indicate a poor prognosis.

Objective:To investigate whether a distant-image screen display has an inhibitory effect on children's nearwork-induced transient myopia (NITM).Methods:A prospective self-controlled study was conducted.From March 2022 to March 2023, 120 pediatric volunteers, aged 4 to 12 years, with a mean age of (5.0±2.2) years, were recruited at Tianjin Eye Hospital.Subjects with refractive errors underwent tests wearing corrective lenses.Subjects were categorized based on accommodative response into three groups: accommodative lead (16 subjects, 32 eyes), accommodative equivalent (48 subjects, 96 eyes), and accommodative lag (56 subjects, 112 eyes). Subjects were also divided by myopia status into myopic (20 subjects, 40 eyes) and non-myopic (100 subjects, 200 eyes) groups.Using a random number table, the subjects were assigned to first view video images for 30 minutes on either an iPad or a distant light screen display.After a two-hour rest between the two sessions, the viewing modality was switched.Visual acuity, refractive power, lens thickness, NITM degree, and NITM recovery time were recorded before and after viewing videos via both modalities.Visual acuity, lens thickness, NITM degree, and recovery time following video viewing via the two modalities across different accommodation types and refractive types were compared.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Tianjin Eye Hospital (No.2022099), and all guardians of the subjects provided informed consent for this study.Results:The NITM degree and recovery time after watching videos on a distant-image screen display were (0.00±0.36)D and (25.33±15.48) seconds, respectively.The NITM degree and recovery time after watching videos on an iPad were (-0.20±0.40)D and (33.33±17.68) seconds, respectively.Compared with watching videos on an iPad, watching videos on a distant-image screen display resulted in better immediate distance vision, lower myopic refractive power, thinner lens thickness, lower NITM degree, and shorter recovery time, with statistically significant differences ( t=-7.688, 7.842, -4.210, 2.331, -2.887; all P<0.05). After viewing the distant-image screen display and iPad, there was no significant difference in the overall comparison of visual acuity change, lens thickness change, NITM degree and NITM recovery time among the accommodative lead, accommodative equivalent and accommodative lag groups ( H=0.584, 4.923, 1.514, 2.634; all P>0.05. H=3.265, 1.884, 1.606, 1.922; all P>0.05), and there was also no significant difference between the myopic and non-myopic groups ( Z=-1.555, -1.700, -0.254, -2.336; all P>0.05. Z=-1.125, -0.446, -1.033, -0.759; all P>0.05). Conclusions:The use of a distant-image screen display can reduce the NITM caused by near viewing and shorten the NITM recovery time, which is effective for children with different refractive states and accommodative types.

Surgical intervention for malignant bone tumors frequently results in bone defects located at the metaphysis of the long bones in the lower extremities.The morphological heterogeneity of the metaphysis poses significant challenges for conventional treatment methods to adequately conform to the defect area.The utilization of three-dimensional(3D)-printed titanium bone repair scaffolds has emerged as an effective reconstructive approach for metaphyseal bone defects,as these scaffolds offer precise shape conformity and provide adequate mechanical support.However,the current commonly used scaffolds do not adequately replicate the biomechanical environment of bone defects,resulting in suboptimal bone ingrowth within the scaffolds and subsequent prosthesis loosening and failure post-operation.Bone is a highly force-responsive organ,and its fate is regulated by biomechanical signals.Consequently,designing scaffolds with consideration of biomechanical principles to ensure mechanical compatibility between the scaffolds and the bone defect sites is a critical factor influencing the success of bone defects reconstruction.This review primarily introduces the biomechanical factors influencing bone defect repair and the advancements in designing 3D-printed titanium bone repair scaffolds biomechanically matched with bones,offering theoretical guidance for scaffold design and preparation.

Osteoporosis is a prevalent skeletal condition characterized by reduced bone mass and strength, leading to increased fragility. Buqi-Tongluo (BQTL) decoction, a traditional Chinese medicine (TCM) prescription, has yet to be fully evaluated for its potential in treating bone diseases such as osteoporosis. To investigate the mechanism by which BQTL decoction inhibits osteoclast differentiation in vitro and validate these findings through in vivo experiments. We employed MTS assays to assess the potential proliferative or toxic effects of BQTL on bone marrow macrophages (BMMs) at various concentrations. TRAcP experiments were conducted to examine BQTL's impact on osteoclast differentiation. RT-PCR and Western blot analyses were utilized to evaluate the relative expression levels of osteoclast-specific genes and proteins under BQTL stimulation. Finally, in vivo experiments were performed using an osteoporosis model to further validate the in vitro findings. This study revealed that BQTL suppressed receptor activator of NF-κB ligand (RANKL)-induced osteoclastogenesis and osteoclast resorption activity in vitro in a dose-dependent manner without observable cytotoxicity. The inhibitory effects of BQTL on osteoclast formation and function were attributed to the downregulation of NFATc1 and c-fos activity, primarily through attenuation of the MAPK, NF-κB, and Calcineurin signaling pathways. BQTL's inhibitory capacity was further examined in vivo using an ovariectomized (OVX) rat model, demonstrating a strong protective effect against bone loss. BQTL may serve as an effective therapeutic TCM for the treatment of postmenopausal osteoporosis and the alleviation of bone loss induced by estrogen deficiency and related conditions.
Animals ; NFATC Transcription Factors/genetics* ; Drugs, Chinese Herbal/pharmacology* ; Ovariectomy ; Osteoclasts/metabolism* ; Female ; Osteogenesis/drug effects* ; Rats, Sprague-Dawley ; Rats ; NF-kappa B/genetics* ; Osteoporosis/genetics* ; Signal Transduction/drug effects* ; Bone Resorption/genetics* ; Cell Differentiation/drug effects* ; Humans ; RANK Ligand/metabolism* ; Mitogen-Activated Protein Kinases/genetics* ; Transcription Factors