Disorders of consciousness (DOC) are pathological conditions characterized by severely suppressed brain function and the persistent interruption or loss of consciousness. Accurate diagnosis and evaluation of DOC are prerequisites for precise treatment. Traditional assessment methods are primarily based on behavioral scales, which are inherently subjective and rely on observable behaviors. Moreover, traditional methods have a high misdiagnosis rate, particularly in distinguishing minimally conscious state (MCS) from vegetative state/unresponsive wakefulness syndrome (VS/UWS). This diagnostic uncertainty has driven the exploration of objective, reliable, and efficient assessment tools. Among these tools, electroencephalography (EEG) has garnered significant attention for its non-invasive nature, portability, and ability to capture real-time neurodynamics. This paper systematically reviews the application of EEG biomarkers in DOC assessment. These biomarkers are categorized into 3 main types: resting-state EEG features, task-related EEG features, and features derived from transcranial magnetic stimulation-EEG (TMS-EEG). Resting-state EEG biomarkers include features based on spectrum, microstates, nonlinear dynamics, and brain network metrics. These biomarkers provide baseline representations of brain activity in DOC patients. Studies have shown their ability to distinguish different levels of consciousness and predict clinical outcomes. However, because they are not task-specific, they are challenging to directly associate with specific brain functions or cognitive processes. Strengthening the correlation between resting-state EEG features and consciousness-related networks could offer more direct evidence for the pathophysiological mechanisms of DOC. Task-related EEG features include event-related potentials, event-related spectral modulations, and phase-related features. These features reveal the brain’s responses to external stimuli and provide dynamic information about residual cognitive functions, reflecting neurophysiological changes associated with specific cognitive, sensory, or behavioral tasks. Although these biomarkers demonstrate substantial value, their effectiveness rely on patient cooperation and task design. Developing experimental paradigms that are more effective at eliciting specific EEG features or creating composite paradigms capable of simultaneously inducing multiple features may more effectively capture the brain activity characteristics of DOC patients, thereby supporting clinical applications. TMS-EEG is a technique for probing the neurodynamics within thalamocortical networks without involving sensory, motor, or cognitive functions. Parameters such as the perturbational complexity index (PCI) have been proposed as reliable indicators of consciousness, providing objective quantification of cortical dynamics. However, despite its high sensitivity and objectivity compared to traditional EEG methods, TMS-EEG is constrained by physiological artifacts, operational complexity, and variability in stimulation parameters and targets across individuals. Future research should aim to standardize experimental protocols, optimize stimulation parameters, and develop automated analysis techniques to improve the feasibility of TMS-EEG in clinical applications. Our analysis suggests that no single EEG biomarker currently achieves an ideal balance between accuracy, robustness, and generalizability. Progress is constrained by inconsistencies in analysis methods, parameter settings, and experimental conditions. Additionally, the heterogeneity of DOC etiologies and dynamic changes in brain function add to the complexity of assessment. Future research should focus on the standardization of EEG biomarker research, integrating features from resting-state, task-related, and TMS-EEG paradigms to construct multimodal diagnostic models that enhance evaluation efficiency and accuracy. Multimodal data integration (e.g., combining EEG with functional near-infrared spectroscopy) and advancements in source localization algorithms can further improve the spatial precision of biomarkers. Leveraging machine learning and artificial intelligence technologies to develop intelligent diagnostic tools will accelerate the clinical adoption of EEG biomarkers in DOC diagnosis and prognosis, allowing for more precise evaluations of consciousness states and personalized treatment strategies.

Objective To investigate the prevalence of work-related musculoskeletal disorders (WMSDs) in passenger drivers and its influencing factors. Methods A total of 951 passenger drivers in Guangdong Province were selected as the research subjects using the judgmental sampling method. A Musculoskeletal Injury Questionnaire was employed to assess the prevalence of WMSDs in the past year. Results The prevalence of WMSDs in passenger drivers was 41.11%. The result of multivariable logistic regression analysis showed that married drivers had a higher risk of WMSDs than single drivers (P<0.05). The lower the frequency of physical exercise, the longer the driving time per week, the longer the continuous driving time, the more restricted the driving working space, the poorer the foot comfort during driving, and the more affected the normal meal, the higher the risk of WMSDs (all P<0.05). The risk of WMSDs in drivers with sleep time ≤ 8.0 h/d was higher than that in drivers with sleep time > 8.0 h/d (P<0.01), and the risk of WMSDs in drivers with the same posture for a long time on the shoulder was higher than that in drivers without this poor working posture (P<0.01). Conclusion WMSDs were prevalent among passenger drivers, which was associated with demographic and adverse ergonomic factors. Intervention on lifestyle and adverse ergonomic factors could further reduce the risk of WMSDs of passenger drivers.

BackgroundNon-suicidal self-injury （NSSI） behaviors are common among adolescents with depressive disorders， and school bullying is recognized as a major risk factor. Previous research has shown that self-esteem and alexithymia are closely associated with both school bullying and NSSI. However， the mediating roles of self-esteem and alexithymia in the link between school bullying and NSSI are unclear. ObjectiveTo explore the mediating roles of alexithymia and self-esteem in the relationship between school bullying and NSSI behaviors in adolescents with depressive disorders， in order to inform intervention strategies targeting NSSI in this population. MethodsA total of 335 adolescents diagnosed with depressive disorders and treated at the First Psychiatric Hospital of Harbin from July 2023 to October 2024 were enrolled. Assessments included a self-developed demographic questionnaire， Adolescent Non-suicidal Self-injury Assessment Questionnaire-Behavior （ANSAQ-B）， Delaware Bullying Victimization Scale-Student （DBVS-S）， Rosenberg Self-Esteem Scale （RSES）， and 26-item Toronto Alexithymia Scale （TAS-26）. Pearson correlation analysis was used to examine the relationship among variables. Controlling for gender and age at onset of depressive symptoms， mediation analysis was performed using the “mediation” package in R 4.4.2. ResultsScores on DBVS-S and TAS-26 were positively correlated with ANSAQ-B score （r=0.408， 0.417， P<0.01）， while RSES scores were negatively correlated（r=-0.300， P<0.01）. Regression analysis showed that school bullying and alexithymia significantly positively predicted NSSI behaviors （B=0.212， 0.333， P<0.01）， while self-esteem negatively predicted NSSI behaviors （B=-0.368， P<0.01）. Alexithymia was found to mediate the relationship between school bullying and NSSI behaviors， with an indirect effect of 0.040 （95% CI： 0.018~0.069） ，account for 17.17% of the total effect. The indirect effect through self-esteem was not statistically significant （95% CI： -0.004~0.069）. ConclusionExposure to school bullying and high levels of alexithymia are important predictors of NSSI behavior in adolescents with depressive disorders， and school bullying may indirectly influence NSSI behavior through alexithymia. ［Funded by Scientific Research Project of Health Commition of Heilongjiang Province，（number， 20230303090154］

This case report presents a 16-year-old male patient with deficiency of adenosine deaminase 2(DADA2). The patient had a history of Raynaud′s phenomenon with digital ulcers since childhood. As the disease progressed, the patient developed retinal vasculitis, intracranial hemorrhage, skin necrosis, severe malnutrition, refractory hypertension, and gastrointestinal bleeding. Genetic testing revealed compound heterozygous mutations in the ADA2 gene (paternal c.1072G > A pathogenic mutation + maternal c.1065C > A variant of unknown clinical significance). ADA2 enzyme activity was significantly reduced (0.1 U/L). A multidisciplinary treatment team developed an individualized plan to address key issues, including nutritional support, blood pressure control, rehabilitation, pain management, and balancing anticoagulation/bleeding risks. After systematic intervention, the patient′s condition showed partial improvement. This case reveals clinical challenges such as anticoagulation decisions and nutritional support of DADA2. It also emphasizes the importance of early molecular diagnosis, tumor necrosis factor-α inhibitor targeted therapy, and multidisciplinary collaboration in management, underlining the core value of precision medicine in rare disease management.

Background::Acute pulmonary embolism (APE) is a fatal cardiovascular disease, yet missed diagnosis and misdiagnosis often occur due to non-specific symptoms and signs. A simple, objective technique will help clinicians make a quick and precise diagnosis. In population studies, machine learning (ML) plays a critical role in characterizing cardiovascular risks, predicting outcomes, and identifying biomarkers. This work sought to develop an ML model for helping APE diagnosis and compare it against current clinical probability assessment models.Methods::This is a single-center retrospective study. Patients with suspected APE were continuously enrolled and randomly divided into two groups including training and testing sets. A total of 8 ML models, including random forest (RF), Na?ve Bayes, decision tree, K-nearest neighbors, logistic regression, multi-layer perceptron, support vector machine, and gradient boosting decision tree were developed based on the training set to diagnose APE. Thereafter, the model with the best diagnostic performance was selected and evaluated against the current clinical assessment strategies, including the Wells score, revised Geneva score, and Years algorithm. Eventually, the ML model was internally validated to assess the diagnostic performance using receiver operating characteristic (ROC) analysis.Results::The ML models were constructed using eight clinical features, including D-dimer, cardiac troponin T (cTNT), arterial oxygen saturation, heart rate, chest pain, lower limb pain, hemoptysis, and chronic heart failure. Among eight ML models, the RF model achieved the best performance with the highest area under the curve (AUC) (AUC = 0.774). Compared to the current clinical assessment strategies, the RF model outperformed the Wells score ( P = 0.030) and was not inferior to any other clinical probability assessment strategy. The AUC of the RF model for diagnosing APE onset in internal validation set was 0.726. Conclusions::Based on RF algorithm, a novel prediction model was finally constructed for APE diagnosis. When compared to the current clinical assessment strategies, the RF model achieved better diagnostic efficacy and accuracy. Therefore, the ML algorithm can be a useful tool in assisting with the diagnosis of APE.

Objective To explore the expression level of serum long non-coding RNA(lncRNA)T342620 in patients with hepatocellular carcinoma(HCC)and the clinical value of single or combined detection with al-pha-fetoprotein(AFP)for HCC.Methods Case-control studies were conducted.A total of 69 patients with primary hepatocellular carcinoma(HCC group),32 patients with hepatitis B(hepatitis B group),20 patients with liver cirrhosis(liver cirrhosis group),30 patients after transcatheter hepatic arterial chemoembolization(TACE)for primary hepatocellular carcinoma(HCC postoperative group)and 50 healthy patients(health ex-amination group)treated in the General Hospital of Southern Theatre Command of PLA from April 2021 to May 2023 were selected as the study objects.The serum total RNA was extracted and the relative expression level of lncRNA T342620 in serum was detected by real-time quantitative PCR.Combined with the clinical di-agnosis and treatment data of patients,the correlation between its expression and pathological characteristics and serological indexes was analyzed,and the specificity and sensitivity of lncRNA T342620 alone and in com-bination with AFP in the diagnosis of HCC were analyzed by receiver operating characteristic(ROC)curve.The diagnostic efficacy was judged according to the area under the curve,and its application value in the diag-nosis of HCC was evaluated.The chi-square test was used for comparison between groups,and the Spearman method was used for correlation analysis.Results The serum expression levels of lncRNA T342620 in liver cancer group and postoperative liver cancer group were higher than those in healthy physical examination group,hepatitis B group and liver cirrhosis group,and the differences were statistically significant(P＜0.001).Clinical pathological and serological index analysis revealed that as the tumor size increased,the serum lncRNA-T342620 expression level also increased.In the HCC group,the serum lncRNA T342620 expression level was negatively correlated with albumin(ALB)and the A/G ratio(P＜0.05),while it was positively cor-related with α-L-fucosidase(AFU)and HBV-DNA(P＜0.05).In patients from the HCC postoperative group,the serum lncRNA T342620 expression level was positively correlated with total bile acid(TBA)(P＜0.05).ROC curve analysis demonstrated that when using serum lncRNA T342620 to distinguish,the sensitivi-ty and the specificity were 55.1％and 94.1％,respectively,indicating good diagnostic value.When combined with AFP detection,the sensitivity and the specificity improved to 91.3％and 91.2％,respectively,which were higher than those of individual indicators and had a superior diagnostic efficiency with area under the cuve(AUC)of 0.954 compared to AUC of AFP or lncRNA-T342620 alone(0.906,0.758),and the differ-ences were statistically significant(P＜0.05).Conclusion Serum lncRNA T342620 may be a new serological index for the auxiliary diagnosis of HCC.

Aim To investigate the effects of multi-gly-cosides of Tripterygium wilfordii(GTW)on mitochon-drial dynamics-related proteins and the mechanism of nephroprotective effects in IgA nephrophathy(IgAN)rats.Methods SPF grade male SD rats were random-ly divided into the Control group,modelling group,prednisone group(6.25 mg·kg·d-1)and GTW group(6.25 mg·kg·d-1).The IgAN rat model was established by the method of"bovine serum albumin(BSA)+carbon tetrachloride(CCl4)+lipopolysac-charide(LPS)".The total amount of urinary protein(24 h-UTP)and erythrocyte count in urine were meas-ured in 24 h urine.Blood biochemistry of serum albu-min(ALB),alanine aminotransferase(ALT),urea ni-trogen(BUN),and creatinine(Scr)were measured in abdominal aorta of the rats;immunofluorescence and HE staining were used to observe the histopathology of the kidneys;RT-PCR and Western blotting were used to detect the mRNA and protein expression levels of key proteins regulating mitochondrial division and fu-sion:dynamin-related protein 1(Drp1),mitochondrial fusion protein 1(Mfn1),and mitochondrial fusion pro-tein 2(Mfn2),and PTEN-induced putative kinase 1(Pink1),in the kidney tissue of rats.Results GTW significantly reduced urinary erythrocyte count and 24 h-UTP,decreased serum ALT,BUN and Scr levels,in-creased serum ALB levels,improved renal histopatho-logical status in IgAN rats,increased the protein and mRNA expression levels of Mfn1,Mfn2,and Pink1,and decreased the protein and mRNA expression levels of Drp1 in renal tissues.Conclusions GTW may regu-late mitochondrial structure and maintain the dynamic balance of mitochondrial dynamics by promoting the ex-pression of Mfn1,Mfn2,Pink1 and decreasing Drp1.This may result in a reduction in urinary erythrocyte counts and proteinuria,and an improvement in renal function.

Aim To explore the mechanism of action of Tripterygium glycosides tablets on kidney of rats with IgA nephropathy based on inflammation-related path-ways.Methods Forty-five male SD rats of SPF grade were randomly divided into control group and modeling group.In addition to the blank group,the modeling group used the combination of bovine serum albumin(BSA)+carbon tetrachloride(CC14)+lipopolysac-charide(LPS)to establish the IgA nephropathy rat model.Successfully modeled rats were randomly divid-ed into the model group,the prednisone group and Tripterygium glycosides tablets group,and the treat-ment group was given the drug by gavage from the 13 th week,and the 24 hours urine,blood and kidney tis-sues of the rats were collected and examined after 4 weeks of the administration of the drug.Urine erythro-cyte count,quantitative 24-h urine protein(24 h-UTP),urea nitrogen(BUN),and blood creatinine(Scr)were detected in each group;serum interleukin 1β(IL-1β)and tumor necrosis factor α(TNF-α)were detected by enzyme-linked immunosorbent assay(Elisa);the pathological changes in the renal tissues of the rats in each group were observed by horizontal hematoxylin-eosin(HE)staining;and the renal tis-sues in each group were observed by Western blotting.The expressions of LIGHT,HVEM,LTβR proteins and their mRNAs in rat kidney tissue were detected by Western blot and real-time fluorescence quantitative polymerase chain reaction(RT-PCR).Results Tripterygium glycosides tablets significantly reduced the levels of urinary erythrocyte count,24 h-UTP,BUN,and Scr in IgA nephropathy rats(P＜0.01),improved renal histopathology,lowered the levels of se-rum inflammatory factors IL-1β and TNF-α(P＜0.01),and lowered the levels of LIGHT,HVEM,LTβR proteins and their mRNA expression in renal tis-sues(P＜0.01).Conclusions Tripterygium glyco-sides tablets may inhibit the immune response and re-duce the release of inflammatory factors by down-regu-lating the LIGHT-HVEM/LT(3R pathway,thus reduc-ing the inflammatory response,lowering the urinary e-rythrocytes and urinary proteins,improving the renal nephron pathologic injury,and protecting the renal function.

Zinc oxide nanoparticles(ZnO NPs)have been gradually introduced into people's lives due to their excellent properties.In daily contact,ZnO NPs can enter the human body in a variety of ways and accumulate in tissues and organs.Inhalation is an important means by which ZnO NPs enter the human body and deposit in lungs.Studies have shown that exposure of lungs to ZnO NPs will cause a range of negative effects.The mechanism of pulmonary toxicity induced by ZnO NPs is related to Zn2+release,oxidative stress,DNA damage,autophagy,inflammation and pulmonary surfactant dysfunction.This paper reviews the pulmonary toxicity and mechanisms of ZnO NPs,and summarizes the prevention and treatment strategies,which provides scientific basis for safer use of nanomaterials,and potential intervention strategies for the prevention and treatment of nanotoxicity.

Objective To investigate the effect of Ilizarov technique combined with rotational center dome-shaped osteoto-my in the treatment of juvenile distal femoral valgus deformity.Methods A retrospective study was conducted to analyze the clinical data of 11 patients with valgus deformity of the distal femur who had been admitted and followed up completely from January 2016 to October 2020.There were 7 males and 4 females.The 6 patients were on the right side and 5 patients were on the left side.The age ranged from 10 to 14 years old.The center of roration of angulation(CORA)was identified at the distal femur deformity,and dome-shaped osteotomy was performed with the CORA as the midpoint.The annular external fixator was installed according to the needle threading principle of Ilizarov external fixation,and the distal femur was cut off.The valgus deformity under visual inspection of the distal femur was corrected immediately,and the external fixator was fixed and main-tained.The residual deformity and shortening were corrected according to the force line and length of the lower limbs suggested by the weight-bearing full-length anteroposterior and lateral X-rays of both lower limbs.Results All 11 patients were followed up for 13 to 25 months.The time of wearing external fixator was 12 to 17 weeks.In the last follow-up,both lower limbs were measured by the weight-bearing full-length anteroposterior and lateral X-rays,and the length of both lower limbs of 11 patients were equal,and the deformities were corrected.The score of hospital for special surgery(HSS)was used to evaluate the knee function,all of which were excellent.Conclusion The Ilizarov technique was applied in the treatment of distal femoral valgus deformity in adolescents using a rotating central dome-shaped osteotomy.Visual femoral valgus deformity was corrected imme-diately during the operation.After the operation,residual deformities and shortening were dynamically adjusted and corrected according to the force line and shortening degree of lower extremities indicated by the weight-bearing anteroposterior and lateral radiographs of both lower limbs,with minimal damage and fast recovery.