Objective: To understand the current situation and related factors of screening myopia among students in special education schools, so as to provide evidence for promoting the health level of this population. Methods: From November 2021 to December 2023, a total of 281 students from 6 special education schools in 5 districts of Tianjin were selected by cluster random sampling method for computer optometry visual acuity examination for non ciliary paralysis and questionnaire survey. Multiple Logistic regression was performed to analyze the influencing factors of screening myopia among special education students. Results: The screening myopia detection rate among these special education students in Tianjin was 27.0%, and the screening myopia detection rates of students with autism, developmental delays, and intellectual disabilities were 22.4%, 12.5%, and 33.0%, respectively. The degree of myopia increased with age ( χ 2 trend =22.65, P <0.01). Multivariate Logistic regression analysis showed that age(10-13 years old: OR =5.40, 14-17 years old: OR =8.40, 18-23 years old: OR =6.02), accommodation(non resident: OR =0.29), daily mobile phone usage ≥2 hours ( OR =2.37), and daily computer/tablet usage ≥2 hours ( OR =2.70) were the risk factors for screening myopia among special education students ( P <0.05). Conclusions The detection rate and degree of screening myopia increase with age in special education students. Prolonged screen time exposure is a primary risk factor for screening myopia in special education students. Effective myopia prevention and control strategies should be designed according to the characteristics of special education students.

ObjectiveTo investigate the role of 4-week high-intensity interval training (HIIT) in modulating the metabolic homeostasis of the pyruvate-lactate axis in the hippocampus of rats with chronic unpredictable mild stress (CUMS) to improve their depressive-like behavior. MethodsForty-eight SPF-grade 8-week-old male SD rats were randomly divided into 4 groups: the normal quiet group (C), the CUMS quiet group (M), the normal exercise group (HC), and the CUMS exercise group (HM). The M and HM groups received 8 weeks of CUMS modeling, while the HC and HM groups were exposed to 4 weeks of HIIT starting from the 5th week (3 min (85%-90%) S_max+1 min (50%-55%) S_max, 3-5 cycles, S_max is the maximum movement speed). A lactate analyzer was used to detect the blood lactate concentration in the quiet state of rats in the HC and HM groups at week 4 and in the 0, 2, 4, 8, 12, and 24 h after exercise, as well as in the quiet state of rats in each group at week 8. Behavioral indexes such as sucrose preference rate, number of times of uprightness and number of traversing frames in the absenteeism experiment, and other behavioral indexes were used to assess the depressive-like behavior of the rats at week 4 and week 8. The rats were anesthetized on the next day after the behavioral test in week 8, and hippocampal tissues were taken for assay. LC-MS non-targeted metabolomics, target quantification, ELISA and Western blot were used to detect the changes in metabolite content, lactate and pyruvate concentration, the content of key metabolic enzymes in the pyruvate-lactate axis, and the protein expression levels of monocarboxylate transporters (MCTs). Results4-week HIIT intervention significantly increased the sucrose preference rate, the number of uprights and the number of traversed frames in the absent field experiment in CUMS rats; non-targeted metabolomics assay found that 21 metabolites were significantly changed in group M compared to group C, and 14 and 11 differential metabolites were significantly dialed back in the HC and HM groups, respectively, after the 4-week HIIT intervention; the quantitative results of the targeting showed that, compared to group C, lactate concentration in the hippocampal tissues of M group, compared with group C, lactate concentration in hippocampal tissue was significantly reduced and pyruvate concentration was significantly increased, and 4-week HIIT intervention significantly increased the concentration of lactate and pyruvate in hippocampal tissue of HM group; the trend of changes in blood lactate concentration was consistent with the change in lactate concentration in hippocampal tissue; compared with group C, the LDHB content of group M was significantly increased, the content of PKM2 and PDH, as well as the protein expression level of MCT2 and MCT4 were significantly reduced. The 4-week HIIT intervention upregulated the PKM2 and PDH content as well as the protein expression levels of MCT2 and MCT4 in the HM group. ConclusionThe 4-week HIIT intervention upregulated blood lactate concentration and PKM2 and PDH metabolizing enzymes in hippocampal tissues of CUMS rats, and upregulated the expression of MCT2 and MCT4 transport carrier proteins to promote central lactate uptake and utilization, which regulated metabolic homeostasis of the pyruvate-lactate axis and improved depressive-like behaviors.

ObjectiveThis study aimed to investigate the effects of 4-week high-intensity interval training (HIIT) on synaptic plasticity in the prefrontal cortex (PFC) of rats exposed to chronic unpredictable mild stress (CUMS), and to explore its potential mechanisms. MethodsA total of 48 male Sprague-Dawley rats were randomly divided into 4 groups: control (C), model (M), control plus HIIT (HC), and model plus HIIT (HM). Rats in groups M and HM underwent 8 weeks of CUMS to establish depression-like behaviors, while groups HC and HM received HIIT intervention beginning from the 5th week for 4 consecutive weeks. The HIIT protocol consisted of repeated intervals of 3 min at high speed (85%-90% maximal training speed, S_max) alternated with one minute at low speed (50%-55% S_max), with 3 to 5 sets per session, conducted 5 d per week. Behavioral assessments and tail-vein blood lactate levels were measured at the end of the 4th and 8th weeks. After the intervention, rat PFC tissues were collected for Golgi staining to analyze synaptic morphology. Enzyme-linked immunosorbent assays (ELISA) were employed to detect brain-derived neurotrophic factor (BDNF), monocarboxylate transporter 1 (MCT1), lactate, and glutamate levels in the PFC, as well as serotonin (5-HT) levels in serum. Additionally, Western blot analysis was conducted to quantify the expression of synaptic plasticity-related proteins, including c-Fos, activity-regulated cytoskeleton-associated protein (Arc), and N-methyl-D-aspartate receptor 1 (NMDAR1). ResultsCompared to the control group (C), the CUMS-exposed rats (group M) exhibited significant reductions in sucrose preference rates, number of grid crossings, frequency of upright postures, and entries into and duration spent in open arms of the elevated plus maze, indicating marked depressive-like behaviors. Additionally, the group M showed significantly reduced dendritic spine density in the PFC, along with elevated levels of c-Fos, Arc, NMDAR1 protein expression, and increased concentrations of lactate and glutamate. Conversely, BDNF and MCT1 contents in the PFC and 5-HT levels in serum were significantly decreased. Following HIIT intervention, rats in the group HM displayed considerable improvement in behavioral indicators compared with the group M, accompanied by significant elevations in PFC MCT1 and lactate concentrations. Furthermore, HIIT notably normalized the expression levels of c-Fos, Arc, NMDAR1, as well as glutamate and BDNF contents in the PFC. Synaptic spine density also exhibited significant recovery. ConclusionFour weeks of HIIT intervention may alleviate depressive-like behaviors in CUMS rats by increasing lactate levels and reducing glutamate concentration in the PFC, thereby downregulating the overexpression of NMDAR, attenuating excitotoxicity, and enhancing synaptic plasticity.

Background::Acute respiratory distress syndrome (ARDS) is a common cause of respiratory failure in many critically ill patients. Although inflammasome activation plays an important role in the induction of acute lung injury (ALI) and ARDS, the regulatory mechanism of this process is still unclear. When cells are stimulated by inflammation, the integrity and physiological function of mitochondria play a crucial part in pyroptosis. However, the underlying mechanisms and function of mitochondrial proteins in the process of pyroptosis are largely not yet known. Here, we identified the 18-kDa translocator protein (TSPO), a mitochondrial outer membrane protein, as an important mediator regulating nucleotide-binding domain, leucine-rich repeat, and pyrin domain-containing protein 3 (NLRP3) inflammasome activation in macrophages during ALI.Methods::TSPO gene knockout (KO) and lipopolysaccharide (LPS)-induced ALI/ARDS mouse models were employed to investigate the biological role of TSPO in the pathogenesis of ARDS. Murine macrophages were used to further characterize the effect of TSPO on the NLRP3 inflammasome pathway. Activation of NLRP3 inflammasome was preformed through LPS + adenosine triphosphate (ATP) co-stimulation, followed by detection of mitochondrial membrane potential, reactive oxygen species (ROS) production, and cell death to evaluate the potential biological function of TSPO. Comparisons between two groups were performed with a two-sided unpaired t-test. Results::TSPO-KO mice exhibited more severe pulmonary inflammation in response to LPS-induced ALI. TSPO deficiency resulted in enhanced activation of the NLRP3 inflammasome pathway, promoting more proinflammatory cytokine production of macrophages in LPS-injured lung tissue, including interleukin (IL)-1β, IL-18, and macrophage inflammatory protein (MIP)-2. Mitochondria in TSPO-KO macrophages tended to depolarize in response to cellular stress. The increased production of mitochondrial damage-associated molecular pattern led to enhanced mitochondrial membrane depolarization and pyroptosis in TSPO-KO cells. Conclusion::TSPO may be the key regulator of cellular pyroptosis, and it plays a vital protective role in ARDS occurrence and development.

Objective To investigate the application effect of the self-made nerve bundle with 3 mm of spatial distance between the two ends in repair of median nerve rupture of the wrist.Methods A total of 24 patients with median nerve rupture of the wrist from July 2014 to August 2020 were included.The self-made nerve bundle with 3 mm of spatial distance between the two ends was applied,and then the epineurium was anastomosed continuously,and no nerve bundle was exposed.After 4 weeks of plaster external fixation,functional exercise was gradually strengthened.The median nerve recovery was evaluated according to Burchiel efficacy evaluation criteria.Results At the last follow-up,the sensory recovery of the middle finger reached S4 level,the functions of thumb to palm and finger to finger recovered,and the thenar eminence was full without atrophy.At the last follow-up,the median nerve recovery was excellent in 18 cases,good in 6 cases,and the excellent and good rate was 100% .Conclusion The epineural anastomosis of self-made nerve bundle with 3 mm of spatial distance between the two ends can achieve accurate counterpoint,prevent scar compression,avoid neuroma,and effectively restore the function of the median nerve.

The biological characteristics and pathogenicity of Klebsiella oxytoca isolated from sick carrier pigeons in Gansu province were explored by morphological observations,biochemical testing,16S rRNA PCR analysis,and RNA sequencing.The drug resistance and pathogenicity of the isolated strains were studied by histopathological observation,drug susceptibility testing,and pathogenicity analysis.The livers,lungs,hearts,and other organs of the sick pigeons were bleeding.In addition,the livers were yellow and brittle,and the lungs were purulent.A Gram-negative,short,rod-shaped bacterium was successfully isolated from the sick pigeon.Pink,smooth,moist,and round colonies grew on MacConkey's agar.The result of the indigo matrix test was positive.The homology between the amplified 16S rRNA sequence and MN330093.1 was 100.00％,indicating that the sick pigeon was infected with K.oxytoca.The strain was named GS-BY-GG.K.Oxytoca GS-BY-GG was resistant to 10 drugs,including penicillin,ampicillin,and furazolidone,and sensitive to 5 others,which included florfenicol,meropenem,and gentamicin.Histopathological observation showed bleeding in multiple organs.The liver cells were irregu-larly arranged with brown-yellow pigmentation.Extensive cell necrosis and exfoliation were observed in the trachea and mucosal epithelium,with inflammatory cell infiltration in the mucosal layer.The isolates were highly pathogenic in specific pathogen-free chickens.These findings provide support for the clinical diagnosis and control of K.oxytoca GS-BY-GG.

Objective To explore the dynamic changes in monoamine oxidase A(MAOA)and forkhead box A1(FOXA1)levels during neuroendocrine differentiation(NED)in prostate cancer,providing new strategies for the treatment of neuroendocrine prostate cancer.Methods Cell models and mouse transplantation models of NED were established through long-term sustained induction with enzalutamide(ENZ).Dynamic expression of MAOA and FOXA1 in NED was detected by Western Blot and Real-time PCR.GEO database data were selected to analyze the dynamic trends in MAOA and FOXA1 levels in multiple NED models.We constructed a mouse transplantation model of human prostate cancer cell lines and analyzed the dynamic expression of MAOA and FOXA1 in the in vivo NED model by immunohistochemistry.MAOA expression was disrupted with lentiviral transfection,and the impact on FOXA1 was detected.Results Both MAOA and FOXA1 concentrations showed dynamic characteristics,increasing and then decreasing during the NED process.Knockdown of MAOA in prostate cancer cells led to decreased expression of FOXA1.This MAOA may play different roles at different stages of NED by acting through FOXA1.Conclusions Both MAOA and FOXA1 levels showed increasing,then decreasing,trends during NED.The expression of MAOA affected the level of FOXA1,and MAOA/FOXA1 may play a dynamic regulatory role in the NED process.

Objective:To investigate the effect of progression of disease within 24 months(POD24)on overall survival(OS)in patients with mantle cell lymphoma(MCL),and compare the clinical characteristics between POD24 and non-POD24 patients.Methods:A retrospective analysis was performed on 50 MCL patients with treatment indications and regular treatment who were admitted to the Affiliated Hospital of Xuzhou Medical University from January 2010 to August 2020.According to the occurrence of POD24,the patients were grouped for prognostic evaluation and clinical characteristics comparison.Results:Univariate Cox regression analysis showed that POD24,PLT,albumin,MIPI score,ECOG PS score,LDH were the factors influencing OS in newly diagnosed MCL patients(all P＜0.05).The results of multivariate Cox regression analysis showed that POD24[HR=16.797(95％CI:3.671-76.861),P＜0.001],albumin＜40 g/L[HR=3.238(95％CI:1.095-9.572),P=0.034]and ECOG PS score≥2[HR=4.005(95％CI:1.033-15.521),P=0.045]were independent risk factors influencing OS in MCL patients.The incidence of PLT＜100 × 109/L(33.3％vs 5.9％,P=0.033)and ECOG PS score≥2(45.5％vs 5.9％,P=0.040)were significantly higher in POD24 patients than those in non-POD24 patients.Conclusion:POD24 is an independent poor prognostic factor affecting the OS of MCL patients,and the patients with PLT＜100 × 109/L and ECOG PS score ≥2 at diagnosis have a higher probability of POD24.

Objective:To investigate the effect of endothelial activation and stress index(EASIX)on the prognosis of patients with angioimmunoblastic T-cell lymphoma(AITL)and peripheral T-cell lymphoma,not otherwise specified(PTCL-NOS),and to compare the clinical characteristics of patients in the low EASIX and high EASIX groups.Methods:The clinical data of 59 newly diagnosed AITL and PTCL-NOS patients admitted to the Affiliated Hospital of Xuzhou Medical University from January 2010 to September 2021 were retrospectively analyzed.The optimal cut-off value of EASIX was determined by receiver operating characteristic(ROC)curve;The chi-square test was used to analyze the correlation between EASIX and clinical features of patients with AITL and PTCL-NOS;The Kaplan-Meier survival curve was used to analyze the overall survival(OS)and progression-free survival(PFS)of the patients;Univariate and multivariate analyses were performed by using Cox proportional hazards model.Results:The optimal cut-off value of EASIX was 0.95,based on which the patients were divided into a low EASIX(＜0.95)group and a high EASIX(≥ 0.95)group.Compared with the low EASIX group,the high EASIX group had a higher proportion of patients with advanced Ann Arbor stage,higher risk according to IPI,elevated LDH,hypoproteinemia,anemia,B symptoms,extranodal involvement,and bone marrow involvement.Survival analysis showed that the OS and PFS of patients in the high EASIX group were significantly shorter than those in the lower EASIX group(P＜0.001).The multivariate analysis showed that EASIX was an independent risk factor for OS[HR=7.217(95％CI:1.959-26.587),P=0.003]and PFS[HR=2.718(95％CI:1.032-7.161),P=0.043]of PTCL patients.Conclusion:High EASIX in newly diagnosed patients with AITL and PTCL-NOS suggests a poor prognosis,and high EASIX is a risk factor affecting prognosis of the patients.

Objective:To construct and validate the best predictive model for 28-day death risk in patients with septic shock based on different supervised machine learning algorithms.Methods:The patients with septic shock meeting the Sepsis-3 criteria were selected from Medical Information Mart for Intensive Care-Ⅳ v2.0 (MIMIC-Ⅳ v2.0). According to the principle of random allocation, 70% of these patients were used as the training set, and 30% as the validation set. Relevant predictive variables were extracted from three aspects: demographic characteristics and basic vital signs, serum indicators within 24 hours of intensive care unit (ICU) admission and complications possibly affecting indicators, functional scoring and advanced life support. The predictive efficacy of models constructed using five mainstream machine learning algorithms including decision tree classification and regression tree (CART), random forest (RF), support vector machine (SVM), linear regression (LR), and super learner [SL; combined CART, RF and extreme gradient boosting (XGBoost)] for 28-day death in patients with septic shock was compared, and the best algorithm model was selected. The optimal predictive variables were determined by intersecting the results from LASSO regression, RF, and XGBoost algorithms, and a predictive model was constructed. The predictive efficacy of the model was validated by drawing receiver operator characteristic curve (ROC curve), the accuracy of the model was assessed using calibration curves, and the practicality of the model was verified through decision curve analysis (DCA).Results:A total of 3?295 patients with septic shock were included, with 2?164 surviving and 1?131 dying within 28 days, resulting in a mortality of 34.32%. Of these, 2?307 were in the training set (with 792 deaths within 28 days, a mortality of 34.33%), and 988 in the validation set (with 339 deaths within 28 days, a mortality of 34.31%). Five machine learning models were established based on the training set data. After including variables at three aspects, the area under the ROC curve (AUC) of RF, SVM, and LR machine learning algorithm models for predicting 28-day death in septic shock patients in the validation set was 0.823 [95% confidence interval (95% CI) was 0.795-0.849], 0.823 (95% CI was 0.796-0.849), and 0.810 (95% CI was 0.782-0.838), respectively, which were higher than that of the CART algorithm model (AUC = 0.750, 95% CI was 0.717-0.782) and SL algorithm model (AUC = 0.756, 95% CI was 0.724-0.789). Thus above three algorithm models were determined to be the best algorithm models. After integrating variables from three aspects, 16 optimal predictive variables were identified through intersection by LASSO regression, RF, and XGBoost algorithms, including the highest pH value, the highest albumin (Alb), the highest body temperature, the lowest lactic acid (Lac), the highest Lac, the highest serum creatinine (SCr), the highest Ca 2+, the lowest hemoglobin (Hb), the lowest white blood cell count (WBC), age, simplified acute physiology score Ⅲ (SAPSⅢ), the highest WBC, acute physiology score Ⅲ (APSⅢ), the lowest Na +, body mass index (BMI), and the shortest activated partial thromboplastin time (APTT) within 24 hours of ICU admission. ROC curve analysis showed that the Logistic regression model constructed with above 16 optimal predictive variables was the best predictive model, with an AUC of 0.806 (95% CI was 0.778-0.835) in the validation set. The calibration curve and DCA curve showed that this model had high accuracy and the highest net benefit could reach 0.3, which was significantly outperforming traditional models based on single functional score [APSⅢ score, SAPSⅢ score, and sequential organ failure assessment (SOFA) score] with AUC (95% CI) of 0.746 (0.715-0.778), 0.765 (0.734-0.796), and 0.625 (0.589-0.661), respectively. Conclusions:The Logistic regression model, constructed using 16 optimal predictive variables including pH value, Alb, body temperature, Lac, SCr, Ca 2+, Hb, WBC, SAPSⅢ score, APSⅢ score, Na +, BMI, and APTT, is identified as the best predictive model for the 28-day death risk in patients with septic shock. Its performance is stable, with high discriminative ability and accuracy.