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.

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.

BACKGROUND:Degenerative scoliosis is defined as a condition that occurs in adulthood with a coronal cobb angle of the spine>10° accompanied by sagittal deformity and rotational subluxation,which often produces symptoms of spinal cord and nerve compression,such as lumbar pain,lower limb pain,numbness,weakness,and neurogenic claudication.The finite element method is a mechanical analysis technique for computer modelling,which can be used for spinal mechanics research by building digital models that can realistically restore the human spine model and design modifications. OBJECTIVE:To review the application of finite element method in the etiology and treatment of degenerative scoliosis. METHODS:The literature databases CNKI,PubMed,and Web of Science were searched for articles on the application of finite element method in degenerative scoliosis published before October 2023.Search terms were"finite element analysis,biomechanics,stress analysis,degenerative scoliosis,adult spinal deformity"in Chinese and English.Fifty-four papers were finally included. RESULTS AND CONCLUSION:(1)The biomechanical findings from the degenerative scoliosis model constructed using the finite element method were identical to those from the in vivo experimental studies,which proves that the finite element method has a high practical value in degenerative scoliosis.(2)The study of the etiology and treatment of degenerative scoliosis by the finite element method is conducive to the prevention of the occurrence of the scoliosis,slowing down the progress of the scoliosis,the development of a more appropriate treatment plan,the reduction of complications,and the promotion of the patients'surgical operation.(3)The finite element method has gradually evolved from a single bony structure to the inclusion of soft tissues such as muscle ligaments,and the small sample content is increasingly unable to meet the research needs.(4)The finite element method has much room for exploration in degenerative scoliosis.

Background/Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation. Methods: The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation. Results: MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs. Conclusions In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.

Epilepsy,as the second most common neurological disease,has diverse causes,complex,difficult to treat,and disabling characteristics,which impose a heavy burden on patients' families and social life.Long term recurrent epileptic seizures and poor control lead to neuronal inactivation and cognitive impairment in patients.Therefore,it is becoming increasingly important to find new targeted treatment methods and explore the molecular regulatory mechanisms of epilepsy on neuronal damage.Iron induced cell death is a novel programmed cell death mediated by ferrous ions,characterized by the accumulation of ferrous ions,harmful lipid peroxides,and lethal reactive oxygen species,leading to damage to mitochondrial function and structure.With recent in-depth research on ferroptosis,it has been found that inhibiting ferroptosis related targets and pathways can alleviate seizures and progression of epilepsy and protect neurons.This article provides a brief overview of the molecular mechanisms and related regulation of ferroptosis,its role in epilepsy,and recent advances in related treatments.

Osteoarthritis(OA)is a common joint disease in clinical practice,and cartilage damage is a typical pathological change.The pathogenesis of OA is complex,and various adverse factors can lead to the occurrence of OA.Mitochondria are im-portant organelles within cells and play important roles in cellular physiological and pathological activ-ities.Mitochondrial quality control is an important regulatory mechanism in the body to maintain nor-mal mitochondrial structure and function,mainly including mitochondrial biogenesis,mitochondrial dynamics,mitochondrial autophagy,mitochondrial oxidative stress,and other forms.The imbalance of mitochondrial quality control in chondrocytes is closely related to the occurrence and development of osteoarthritis,and regulating the balance of mi-tochondrial quality control is a potential therapeu-tic point for osteoarthritis.The author reviewed rel-evant research literature in recent years to provide a review of the relationship between mitochondrial quality control and the occurrence and develop-ment of osteoarthritis,in order to provide new ideas and directions for the research and diagnosis and treatment strategies of osteoarthritis.

Objective:To investigate the methods and skills required for the safe and swift removal of primary or secondary sacral tumors located between the second (inclusive) and fourth sacral vertebrae.Methods:The clinical images, pathology reports, surgical procedures, operation durations, intraoperative bleeding volumes, and postoperative functional follow-up data of 26 patients undergoing sacral tumor resection at the First Affiliated Hospital of Zhengzhou University and Xinjiang Production and Construction Corps Hospital between May 2020 and February 2025 were retrospectively examined. Additionally, the safety measures for sacral tumor resection and techniques for expedited specimen removal were evaluated.Results:According to magnetic resonance imaging (MRI) findings, all 26 patients presented with sacral tumors located between the second (inclusive) and fourth sacral vertebrae. Specifically, 9 patients were diagnosed with primary sacral tumors, pathologically confirmed as chordomas, while 17 patients had secondary sacral tumors. Among the secondary tumor cases, 12 were attributed to recurrent rectal cancer invading the sacrum, and 5 were due to malignant teratomas invading the sacrum. The 26 patients underwent a treatment strategy that began with managing the relationship between the internal iliac artery, vein branches, and the tumor, followed by the resection of the sacrum. During surgery, the bilateral sciatic foramina were accurately positioned, and the presacral fascia was dissected subsequent to the fracture of the sacrum. Among the 26 patients, 9 underwent sacral tumor resection directly through the posterior sacral approach. The average operation time for these patients was (71.1±4.9) minutes, with average blood loss of (186.7±72.8) milliliters. On the other hand, 17 patients underwent sacral tumor resection by transitioning from the supine position to the prone knife position through a combined abdominal and sacral approach. The average operation time for this group was (213.5±19.3) minutes, with average blood loss of (480.0±93.0) milliliters, significantly longer than that of the posterior sacral approach. The follow-up period ranged from 1 to 48 months, with a median of 20 months, ending on March 31, 2025. During this time, 26 patients achieved autonomous defecation with the aid of medication. None of the patients reported any functional movement disorders or pain in their lower limbs. It was observed that two out of the 26 patients developed distant metastasis, while the remaining 24 patients survived without any tumors.Conclusion:By pretreated the relationship between the internal iliac vessels and sacral tumors prior to resecting sacral tumors, utilizing the approach of initially fracturing the sacrum followed by rupturing the presacral fascia, the tumor can be entirely eliminated, resulting in a brief surgical procedure, reduced intraoperative bleeding, and minimal postoperative complications.

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.