Background The quality of occupational health technical services is directly linked to the protection of workers' health rights and the efficacy of occupational disease prevention and control. However, the industry still faces critical challenges: sporadic instances of institutional non-compliance and persistent irregularities in professional practice continue to undermine overall service performance. Objective To assess the current quality status of occupational health technical services in Zhejiang Province and propose countermeasures for quality improvement, providing a scientific basis for policy optimization and service delivery quality enhancement. Methods A total of 69 occupational health technical service institutions in Zhejiang Province that obtained formal accreditation as of April 30, 2024, were sampled, including 3 public institutions and 66 private institutions (comprising 3 formerly Class-A, 28 formerly Class-B, 11 formerly Class-C, and 24 newly certified institutions). Following the Technical Protocol for Quality Monitoring of Occupational Health Technical Service in Zhejiang Province and the Technical Protocol for Proficiency Testing of Occupational Health Detection in Zhejiang Province, a quality assessment task force comprising national and provincial experts was established. Evaluation was conducted across four dimensions: qualification maintenance and compliance, standardization of technical services, authenticity of technical services, and proficiency testing, utilizing a combination of document review, on-site inspections, and technical skill assessments. Results The occupational health technical service institutions in Zhejiang Province were predominantly private entities (82.5%), with significant disparities in overall service quality. The pass rates for qualification maintenance and compliance, technical service standardization, technical service authenticity, and the excellence rate for laboratory proficiency testing were 81.5%, 80.7%, 97.3%, and 90.4%, respectively. Regarding qualification maintenance, the pass rates for "environmental conditions" (49.8%, 56.7%) and "instrumentation and equipment" (58.2%、65.6%) were significantly lower for formerly Class-C and newly certified institutions compared to other categories. In terms of technical standardization, "standardized on-site inspections" recorded the lowest pass rate (67.4%), with newly certified institutions at only 48.0%. Regarding technical service authenticity, formerly Class-C institutions exhibited issues such as missing raw chromatograms for blank samples (85.7% pass rate). In laboratory proficiency testing, public and formerly Class-A institutions achieved 100% excellence rates, but the performance of formerly Class-C and newly certified institutions was comparatively weak; specifically, the failure rate for organic analysis in formerly Class-C institutions reached 20%; the failure rate for dust testing items in newly certified institutions was 10.3%. Conclusion The overall quality of occupational health technical services in Zhejiang Province still requires significant improvement, particularly in basic institutional conditions, the standardization of on-site inspections, and laboratory proficiency in organic and dust analysis. Formerly Class-C and newly certified institutions should be the primary focus of quality management efforts. Differentiated regulatory strategies are recommended, alongside strengthening interim and ex-post supervision to gradually enhance the quality of occupational health technical services across all institutions.

Distinct from the complementary inhibition mechanism through binding to the target with three-dimensional conformation of small molecule inhibitors, targeted protein degradation technology takes tremendous advantage of endogenous protein degradation pathway inside cells to degrade plenty of “undruggable” target proteins, which provides a novel route for the treatment of many serious diseases, mainly including proteolysis-targeting chimeras, lysosome-targeting chimeras, autophagy-targeting chimeras, antibody-based proteolysis-targeting chimeras, etc. Unlike proteolysis-targeting chimeras first found in 2001, which rely on ubiquitin-proteasome system to mainly degrade intracellular proteins of interest, lysosome-targeting chimeras identified in 2020, which was act as the fastly developing technology, utilize cellular lysosomal pathway through endocytosis mediated by lysosome-targeting receptor to degrade both extracellular and membrane proteins. As an emerging biomedical technology, nucleic acid-driven lysosome-targeting chimeras utilize nucleic acids as certain components of chimera molecule to replace with ligand to lysosome-targeting receptor or protein of interest, exhibiting broad application prospects and potential clinical value in disease treatment and drug development. This review mainly introduced present progress of nucleic acid-driven lysosome-targeting chimeras technology, including its basic composition, its advantages compared with antibody or glycopeptide-based lysosome-targeting chimeras, and focused on its chief application, in terms of the type of lysosome-targeting receptors. Most research about the development of nucleic acid-driven lysosome-targeting chimeras focused on those which utilized cation-independent mannose-6-phosphonate receptor as the lysosome-targeting receptor. Both mannose-6-phosphonate-modified glycopeptide and nucleic aptamer targeting cation-independent mannose-6-phosphonate receptor, even double-stranded DNA molecule moiety can be taken advantage as the ligand to lysosome-targeting receptor. The same as classical lysosome-targeting chimeras, asialoglycoprotein receptor can also be used for advance of nucleic acid-driven lysosome-targeting chimeras. Another new-found lysosome-targeting receptor, scavenger receptor, can bind dendritic DNA molecules to mediate cellular internalization of complex and lysosomal degradation of target protein, suggesting the successful application of scavenger receptor-mediated nucleic acid-driven lysosome-targeting chimeras. In addition, this review briefly overviewed the history of lysosome-targeting chimeras, including first-generation and second-generation lysosome-targeting chimeras through cation-independent mannose-6-phosphonate receptor-mediated and asialoglycoprotein receptor-mediated endocytosis respectively, so that a clear timeline can be presented for the advance of chimera technique. Meantime, current deficiency and challenge of lysosome-targeting chimeras was also mentioned to give some direction for deep progress of lysosome-targeting chimeras. Finally, according to faulty lysosomal degradation efficiency, more cellular mechanism where lysosome-targeting chimeras perform degradation of protein of interest need to be deeply explored. In view of current progress and direction of nucleic acid-driven lysosome-targeting chimeras, we discussed its current challenges and development direction in the future. Stability of natural nucleic acid molecule and optimized chimera construction have a great influence on the biological function of lysosome-targeting chimeras. Discovery of novel lysosome-targeting receptors and nucleic aptamer with higher affinity to the target will greatly facilitate profound advance of chimera technique. In summary, nucleic acid-driven lysosome-targeting chimeras have many superiorities, such as lower immunogenicity, expedient synthesis of chimera molecules and so on, in contrast to classical lysosome-targeting chimeras, making it more valuable. Also, the chimera technology provides new ideas and methods for biomedical research, drug development and clinical treatment, and can be used more widely through further research and optimization.

OBJECTIVE: This study reports the first imported case of Lassa fever (LF) in China. Laboratory detection and molecular epidemiological analysis of the Lassa virus (LASV) from this case offer valuable insights for the prevention and control of LF. METHODS: Samples of cerebrospinal fluid (CSF), blood, urine, saliva, and environmental materials were collected from the patient and their close contacts for LASV nucleotide detection. Whole-genome sequencing was performed on positive samples to analyze the genetic characteristics of the virus. RESULTS: LASV was detected in the patient's CSF, blood, and urine, while all samples from close contacts and the environment tested negative. The virus belongs to the lineage IV strain and shares the highest homology with strains from Sierra Leone. The variability in the glycoprotein complex (GPC) among different strains ranged from 3.9% to 15.1%, higher than previously reported for the seven known lineages. Amino acid mutation analysis revealed multiple mutations within the GPC immunogenic epitopes, increasing strain diversity and potentially impacting immune response. CONCLUSION The case was confirmed through nucleotide detection, with no evidence of secondary transmission or viral spread. The LASV strain identified belongs to lineage IV, with broader GPC variability than previously reported. Mutations in the immune-related sites of GPC may affect immune responses, necessitating heightened vigilance regarding the virus.
Humans ; China/epidemiology* ; Genome, Viral ; Lassa Fever/virology* ; Lassa virus/classification* ; Molecular Epidemiology ; Phylogeny

OBJECTIVE: To investigate chronic hepatitis C virus (HCV) infection's effect on gestational liver function, pregnancy and delivery complications, and neonatal development. METHODS: A total of 157 HCV antibody-positive (anti-HCV[+]) and HCV RNA(+) patients (Group C) and 121 anti-HCV(+) and HCV RNA(-) patients (Group B) were included as study participants, while 142 anti-HCV(-) and HCV RNA(-) patients (Group A) were the control group. Data on biochemical indices during pregnancy, pregnancy complications, delivery-related information, and neonatal complications were also collected. RESULTS: Elevated alanine aminotransferase (ALT) rates in Group C during early, middle, and late pregnancy were 59.87%, 43.95%, and 42.04%, respectively-significantly higher than Groups B (26.45%, 15.70%, 10.74%) and A (23.94%, 19.01%, 6.34%) ( P < 0.05). Median ALT levels in Group C were significantly higher than in Groups A and B at all pregnancy stages ( P < 0.05). No significant differences were found in neonatal malformation rates across groups ( P > 0.05). However, neonatal jaundice incidence was significantly greater in Group C (75.16%) compared to Groups A (42.25%) and B (57.02%) ( χ ² = 33.552, P < 0.001). HCV RNA positivity during pregnancy was an independent risk factor for neonatal jaundice ( OR = 2.111, 95% CI 1.242-3.588, P = 0.006). CONCLUSIONS Chronic HCV infection can affect the liver function of pregnant women, but does not increase the pregnancy or delivery complication risks. HCV RNA(+) is an independent risk factor for neonatal jaundice.
Humans ; Female ; Pregnancy ; Adult ; Pregnancy Complications, Infectious/epidemiology* ; Retrospective Studies ; Pregnancy Outcome ; Infant, Newborn ; Viremia/virology* ; Hepatitis C ; Hepacivirus/physiology* ; Hepatitis C, Chronic/virology* ; Young Adult ; Alanine Transaminase/blood*

Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.

Objective To investigate the electroencephalography(EEG)signal characteristics in patients with neuropathic pain(NP)associated with spinal cord injury(SCI).Methods A total of 90 patients with SCI from January,2018 to November,2023 were selected from the EEG database of the Department of Rehabilitation Medicine,Xijing Hospital,and divided into NP group(n=46)and non-NP group(n=44)according to their symptoms.The resting-state EEG power and reactivity to eye-opening were compared between two groups.Results Compared with non-NP group,EEG power increased in frontal lobe in α and β1 bands,central lobe in δ,θ,α1 and β1 bands,parietal lobe in α and β1 bands,temporal lobe in α and β1 bands,left occipital lobe in α2 band,and occipital lobe in α1 and β1 bands(|Z|>1.998,P<0.05)in NP group during eye-opening;during eye-closing,EEG power increased in prefrontal lobe in α1 and β1 bands,right frontal lobe in θ band,frontal lobe in α and β1 bands,left frontal lobe in β2 band,central lobe in δ,α1 and β1 bands,parietal lobe in α1 and β1 bands,left pari-etal lobe in α2 and β2 bands,right temporal lobe in θ band,temporal lobe in α and β bands,occipital lobe in α1 and β1 bands,and left occipital lobe in β2 band(|Z|>1.970,P<0.05);while the reactivity to eye-opening de-creased in right prefrontal lobe in β1 band,frontal lobe in θ,α and β bands,right central lobe in β1 band,parietal lobe in α1 and β1 bands,right parietal lobe in β2 band,right temporal lobe in δ and θ band,temporal lobe in α1 and β bands,left occipital lobe in α1 band,and occipital lobe in β1(|Z|>1.967,P<0.05).Conclusion Resting-state EEG power characteristically elevates in NP patients after SCI,and the reactivity to eye-open-ing reduces.

Objective To construct a quality control model for cervical liquid-based thin cell smears using two different artificial intelligence(AI)techniques and to compare the total use of the two methods to improve the level of quality control of cervical liquid-based thin cell smears through the assistance of hybrid AI.Methods In this study,105 cervical liquid-based thin cell smear samples were used.Convolutional neural network(CNN)algorithm and Transformer network algorithm were used as specific AI algorithms in the AI model.The labeled features included the number of cells in the slice,excessive red blood cells,excessive inflammatory cells,and air bubbles.The smear samples were pre-processed and digitized by smear,followed by image segmentation and feature extraction.Using the labeled feature data,machine learning models were trained and optimized.Statistical AI and physician QC results were analyzed by calculating KAPPA index,sensitivity,specificity,area under the curve(AUC),and other indexes for AI QC results.Results CNN algorithm QC results in normal smear,inflammatory background and bloody background were significantly different from the expert review QC results(P＜0.001).Transformer algorithm QC results were similar to the expert review results,with no statistical difference(P＞0.05).General practitioner QC results were statistically different from the expert review QC results in normal smear detection rate and bloody background(P＜0.001).CNN algorithm Kappa value was 0.567,which had medium consistency with expert review results.Transformer algorithm Kappa value was 0.890,with the best consistency with expert review results.General practitioner Kappa value was 0.675,which had better consistency with expert review results.Using the expert review results as a reference standard,the predictive efficacy of the Transformer algorithm and the general practitioners' QC results was evaluated,and the predictive efficacy of the Transformer algorithm was higher than that of the general practitioners in detecting hemorrhagic backgrounds and normal smears(inflammatory backgrounds:AUC=1.000;normal smears:AUC=0.768)(hemorrhagic backgrounds:AUC=0.849;normal smears:AUC=0.849;normal smear:AUC=0.500).Conclusion In this study,we found that the Transformer algorithm was effective in improving the quality control of cervical liquid-based thin-layer cell smears by assisting doctors to perform smear quality control scoring and improving the efficiency and accuracy of smear sample quality control.It can be used as a new quality control method for cervical cancer cytological screening and has potential clinical applications.