Occupational pneumoconiosis remains the most common occupational disease in China, with occupational mineral dust exposure being its primary causative factor. Although national standards for online monitoring and early warning systems of coal mine dust concentrations have been established, national occupational health standards for rapid and online monitoring of dust concentration and particle size distribution in other industries are still limited. Among dust concentration sensor technologies, the light scattering method is the preferred choice for online dust monitoring owing to its wide measurement range and low cost. The beta-ray absorption method is mature but highly sensitive to humidity. The electrostatic induction method offers high sensitivity, simple structure, and low maintenance costs but exhibits high errors in low-concentration dust monitoring. The tapered element oscillating microbalance method is highly sensitive but costly. Multi-sensor data fusion technology can improve monitoring reliability, however, mature domestic products are not yet available. For monitoring dust particle size distribution, sieving and sedimentation methods are cumbersome. The aerodynamic method shows broad prospects in the online monitoring of respirable dust but has obvious measurement errors for larger dust particles. The use of optical measurement method is limited by dust morphology and is not suitable for monitoring coal dust particle size distribution. The electrical mobility method is primarily applicable to submicron dust. Future research should focus on promoting the application of monitoring technology for respirable dust particle size distribution in online monitoring of industrial dust. By integrating Internet of Things, data mining, and artificial intelligence technologies, along with multi-sensor data fusion and numerical simulation, dust concentration prediction models can be established to achieve accurate dust concentration monitoring and early warning of exceedances. The advancements of technologies will provide scientific support for the assessment of industrial dust hazards and the prevention and control of occupational pneumoconiosis.

Optimizing operation management mode is the core task to promote the high-quality development of public hospitals.Drawing on the typical experiences and practices of operation and management of representative in-ternational hospitals in the United States,the United Kingdom,Singapore and West China Hospital of Sichuan Univer-sity,Shanghai Jiao Tong University School of Medicine Affiliated Xinhua Hospital,Jilin University China-Japanese Union Hospital of Jilin University,and carrying out a full range of comparative analyses.Put forward the new situation of China's public hospital operations and management to establish a"big operations management"concept.By iden-tifying the operation management role,rationalizing the operation management organization structure and training operation management compound talents to discuss stablishing a committee system,integrating multi-departmental resources to form a scientific and sound problem identificaiton,feedback,consultation and improvement of working mechanism,and promote the high-quality development of publit hospitals.

Background The threshold limit values (TLVs) established and regularly updated by the American Conference of Governmental Industrial Hygienists (ACGIH) are widely adopted and referenced globally, serving as a crucial reference for China's occupational exposure limits (OELs). It is necessary to track it regularly and compare it with China's OELs. Objective To compare the OELs stipulated in Occupational exposure limits for hazardous agents in the workplace—Part 1: Chemical hazardous agents (GBZ 2.1—2019) and the ACGIH TLVs (2024) and to provide references for subsequent formulation and revision of OELs in China. Methods The OELs specified in GBZ 2.1—2019 and the TLVs issued by ACGIH were used to establish a database using Microsoft Excel 2019 software. Cross verification was conducted through matching Chemical Abstracts Service Registry Numbers (CAS Rn) and both Chinese and English names to ensure accuracy. Then, comparisons and analyses were carried out based on the type of limit values, which were matched as follows: permissible concentration-time weighted average (PC-TWA) with threshold limit value-time weighted average (TLV-TWA), permissible concentration-short term exposure limit (PC-STEL) with threshold limit value-short term exposure limit (TLV-STEL), and maximum allowable concentration (MAC) with threshold limit value-ceiling (TLV-C). Comparisons included types, quantities, and sizes of limits. Results The GBZ 2.1—2019 OELs and the ACGIH TLVs (2024) were generally consistent in terms of types and definitions, but there were differences in the number and size of the limits. In terms of the number of limits, GBZ 2.1—2019 specified 365 OELs for 358 chemical hazardous agents, while ACGIH TLVs (2024) included 316 corresponding limits. Among these, 148 (46.9%) limits were consistent, 38 (12.0%) were basically consistent, and 130 (41.1%) were inconsistent. In terms of the size of the limits, out of the 130 inconsistent limits, 51 OELs were lower than the corresponding TLVs, 67 OELs were higher than the corresponding TLVs, and 12 were under different limit types. For some chemical hazardous agents, their OELs were significantly lower or higher than their TLVs. Conclusion Some of the OELs for chemical hazardous agents specified in GBZ 2.1—2019 are significantly lower or higher than the TLVs. For these chemical hazardous factors, it is recommended to prioritize their inclusion in research projects and to complete the revisions as soon as possible based on the latest scientific evidence.

Objective:To explore the correlation of bone marrow polychonal plasma cell proportion (pPC% ) and clinical features in newly diagnosed multiple myeloma (NDMM) patients.Methods:A retrospective analysis of 317 patients with NDMM admitted to Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology from January 2018 to January 2023 was performed. The results of the pPC% in all patients were clear. The relationship between the pPC% and clinical characteristics was analyzed.Results:A total of 317 patients were included, comprising 180 males and 137 females. The median age at diagnosis was 61 (26-91) years, and 55.8% were 60 years or older. The pPC% in the bone marrow of patients with NDMM was different in the DS, International Staging System (ISS), and revised ISS (R-ISS) stages ( P=0.002, 0.010, and 0.049, respectively), whereas no statistical difference in pPC% was observed among patients with different FISH risk stratigrams ( P=0.971). The correlation coefficient between pPC% and hemoglobin (HGB) at the first diagnosis in patients was 0.211 ( P<0.01). The correlation coefficients with serum calcium, serum creatinine, M protein level, and β 2-microglobulin were -0.141, -0.120, -0.181, and -0.207, respectively, and the results of the significance test were P=0.012, 0.033, 0.004, and 0.002, respectively, indicating a negative correlation. Compared with the patients with a pPC% of ≥2.5%, the group of patients with a pPC% of <2.5% had significantly higher levels of light chain, serum calcium, serum creatinine, M protein, and β 2-microglobulin at the initial diagnosis ( P<0.05) ; lower HGB level ( P<0.001) ; and a higher proportion of patients in ISS stage Ⅲ ( P=0.034) . Conclusion:In this study, the pPC% in patients with NDMM was associated with clinical features of good prognosis, including higher HGB, lower serum calcium, serum creatinine, M protein quantity, β 2-microglobulin, light chain involvement, lower proportion of advanced disease (DS stage and ISS stage Ⅲ), and clinical features showing lower tumor burden.

Objective:To study the relationship between hemoglobin glycation index (HGI) and blood lipid indices such as low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), and plasma atherogenic index (AIP).Methods:This cross-sectional study included 16 049 participants from the Beijing Apple Garden community between December 2011 and August 2012. The subjects were divided into three groups based on the HGI quartile: low ( n=5 388), medium ( n=5 249), and high ( n=5 412). The differences in blood lipid indicators between different HGI groups were compared and multivariate logistic regression model was established to analyze the association between HGI and dyslipidemia. And multivariate logistic regression model was established to analyze the relationship between HGI and blood lipid indicators in different glucose metabolism populations. Results:There were 16 049 participants in all (mean age: 56 years), including 10 452 women (65.1%). They were classified into normal glucose tolerance (9 093 cases), prediabetes (4 524 cases), and diabetes (2 432 cases) based on glucose tolerance status. In the general population, with the increase of HGI, LDL-C, non-HDL-C, and AIP gradually increased (all P values for trends were <0.05), and the proportion of abnormalities increased significantly ( χ2=101.40, 42.91, 39.80; all P<0.001). A multivariate logistic regression model was established, which suggested a significant correlation between HGI and LDL-C, non-HDL-C, and AIP (all P<0.05), after adjusting for factors such as age, sex, fasting blood glucose, hypertension, body mass index, smoking, and alcohol consumption. In the overall population, normal glucose tolerance group, and diabetes group, HGI had the highest correlation with non-HDL-C ( OR values of 1.325, 1.678, and 1.274, respectively); in the prediabetes group, HGI had a higher correlation with LDL-C ( OR value: 1.510); and in different glucose metabolism groups, AIP and HGI were both correlated ( OR: 1.208-1.250), but not superior to non-HDL-C and LDL-C. Conclusion:HGI was closely related to LDL-C, non HDL-C, and AIP in the entire population and people with different glucose metabolism, suggesting that HGI may be a predictor of atherosclerotic cardiovascular disease.

Traditional microtubule inhibitors fail to significantly enhance the effect of colorectal cancer;hence,new and efficient strategies are necessary.In this study,a supramolecular nanoreactor(DOC@TA-Fe3+)based on tannic acid(TA),iron ion(Fe3+),and docetaxel(DOC)with microtubule inhibition,reactive oxygen species(ROS)generation,and glutathione peroxidase 4(GPX4)inhibition,is prepared for ferroptosis/apoptosis treatment.After internalization by CT26 cells,the DOC@TA-Fe3+nanoreactor escapes from the lysosomes to release payloads.The subsequent Fe3+/Fe2+conversion mediated by TA reducibility can trigger the Fenton reaction to enhance the ROS concentration.Additionally,Fe3+can consume gluta-thione to repress the activity of GPX4 to induce ferroptosis.Meanwhile,the released DOC controls microtubule dynamics to activate the apoptosis pathway.The superior in vivo antitumor efficacy of DOC@TA-Fe3+nanoreactor in terms of tumor growth inhibition and improved survival is verified in CT26 tumor-bearing mouse model.Therefore,the nanoreactor can act as an effective apoptosis and ferroptosis inducer for application in colorectal cancer therapy.

OBJECTIVE: This study explored whether thyroglobulin and thyroid disease prevalence rates were higher in pregnant Chinese women with a median urinary iodine concentration of 100-149 µg/L, compared with those with a median urinary iodine concentration of 150-249 μg/L maintained through sustainable universal salt iodization. METHODS: This was a cross-sectional study in which 812 healthy pregnant women were enrolled to collect samples of their household edible salt, urine, and blood during their routine antenatal care in the 18 counties in Fujian Province, China. The levels of salt iodine concentration, urinary iodine concentration (UIC), free triiodothyronine (FT3), free thyroid hormone (FT4), thyroid-stimulating hormone (TSH), thyroglobulin (Tg), thyroid peroxidase antibody and thyroglobulin antibody were assessed during the routine antenatal care visits. RESULTS: The median UIC (mUIC) in pregnant women was 130.8 μg/L (interquartile range = 91.5-198.1 μg/L) in the counties with an mUIC of 100-149 μg/L (Group I), and 172.0 μg/L (interquartile range = 123.5-244.4 μg/L) in the counties with an mUIC of 150-249 μg/L (Group II). Goiter prevalence and thyroid nodule detection rates showed no difference between Group I and Group II ( P > 0.05). Except for FT4 values, the TSH, FT4, FT3, Tg and Tg values > 40 (μg/L) and the thyroid diseases prevalence rate (TDR) showed no significant differences between Group I and Group II ( P > 0.05), whether or not iodine supplementation measures were taken. CONCLUSION Compared with an mUIC of 150-249 μg/L, not only there was no difference in thyroid morphology, but also the Tg value, rate of Tg values > 40 µg/L, and TDR were not higher in pregnant women in the counties with an mUIC of 100-149 μg/L achieved through sustainable universal salt iodization in Fujian Province, China.
Female ; Humans ; Pregnancy ; Cross-Sectional Studies ; Iodine/urine* ; Pregnant Women ; Sodium Chloride, Dietary ; Thyroglobulin ; Thyroid Gland ; Thyrotropin ; East Asian People

Background Phenolic compounds may adversely affect human health, but the current relevant studies are mostly limited to the impact of single phenolic compound exposure on human health, and there is still a lack of studies on the population-based association between combined exposure to multiple common phenolic compounds and dyslipidemia. Objective To explore the association of phenolic compound combined exposure and dyslipidemia based on principal component analysis-random forest (PCA-RF) strategy. Methods The data were from the National Health and Nutrition Examination Survey (2013–2016). A total of 1301 adult residents aged ≥ 20 years with complete information on demographics and lifestyle, urine phenol concentrations (bisphenol A, bisphenol F, bisphenol S, triclocarban, benzophenone, and triclosan), and serum concentrations of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were included in this study. The concentrations of six urinary phenolic compounds were determined by solid phase extraction coupled with high performance liquid chromatography and tandem mass spectrometry, and the lipid indicators were determined by enzymatic methods. Principal component analysis combined with random forest model was used for model construction. First, principal component analysis was performed on 18 original variables including 6 phenolic compounds and 12 basic characteristic indicators, and then random forest model was established with dyslipidemia and its four evaluation indicators as dependent variables and the extracted principal components as independent variables, respectively. Results The PCA-RF analysis showed that bisphenol A, bisphenol F, and benzophenone may be important factors for dyslipidemia in the study subjects; bisphenol A, bisphenol F, and triclosan may be important factors for TC level in the study subjects; bisphenol A, bisphenol F, triclocarban, and benzophenone may be important factors for TG level in the study subjects; bisphenol A may be an important factor for LDL-C level in the study subjects; bisphenol F and benzophenone may be important factors for HDL-C level in the study subjects. Conclusion Phenolic compound exposure may be an important risk factor for the development of dyslipidemia. PCA-RF strategy can be effectively used to explore the association between phenolic compound exposure and dyslipidemia in the population.

Objective To investigate the feasibility of establishment of ultrasound radiomics-based models for classification of hepatic echinococcosis, so as to provide insights into precision ultrasound diagnosis of hepatic echinococcosis. Methods The ultrasonographic images were retrospectively collected from 200 patients with hepatic echinococcosis in Shiqu County, Ganzi Tibetan Autonomous Prefecture, Sichuan Province in October 2014, and the regions of interest were plotted in ultrasonographic images of hepatic echinococcosis lesions. The ultrasound radiomics features of hepatic echinococcosis were extracted with 25 methods, and screened using pre-selection and the least absolute shrinkage and selection operator. Then, all ultrasonographic images were randomly assigned into the training and independent test sets according to the type of lesions at a ratio of 7:3. Machine learning models for classification of hepatic echinococcosis were created based on two classifiers, including kernel logistic regression (KLR) and medium Gaussian support vector machine (MGSVM). The receiver operating characteristic (ROC) curves were plotted, and the sensitivity, specificity and areas under the curves (AUC) of the created machine learning models for classification of hepatic echinococcosis were calculated. Results A total of 5 005 ultrasound radiomics features were extracted from 200 patients with hepatic echinococcosis using 25 methods, and 36 optimal radiomics features were screened through feature selection, based on which two machine learning models were created, including KLR and MGSVM. ROC curve analysis showed that MGS-VM presented a higher efficacy for hepatic echinococcosis classification than KLR in the training set, with a sensitivity of 0.82, a specificity of 0.78 and AUC of 0.88, while KLR presented a higher efficacy for hepatic echinococcosis classification than MGSVM in the independent test set, with a sensitivity of 0.82, a specificity of 0.72 and AUC of 0.86, respectively. Conclusions Ultrasound radiomics-based machine learning models are feasible for hepatic echinococcosis classification.

Objective: To observe the effects of herb-partitioned moxibustion and ginger-partitioned moxibustion on the growth of colon tumors in rats with colitis-associated colon cancer (CACC), and explore the mechanism of moxibustion intervening CACC through the purinergic receptor P2X ligand-gated ion channel 7 (P2X7R)/signal transducer and activator of transcription 3 (STAT3)/vascular endothelial growth factor (VEGF) pathway. Methods: A total of 26 male Sprague-Dawley rats were selected. According to the random number table method, 6 rats were selected as the normal group. The remaining 20 rats were injected intraperitoneally with azoxymethane (AOM) combined with oral dextran sodium sulfate (DSS) to prepare the CACC model. After the model was successfully established, 2 rats were randomly selected for model identification. The remaining 18 rats which were successfully modeled were randomly divided into a model group, a herb-partitioned moxibustion group and a ginger-partitioned moxibustion group, with 6 rats in each group. Moxibustion intervention was performed in the herb-partitioned moxibustion group and the ginger-partitioned moxibustion group at Qihai (CV 6) and bilateral Tianshu (ST 25). Moxibustion was performed twice at each point each time, once a day, at a 1-day interval after 6 consecutive interventions, for a total of 30 interventions. After intervention, the colon tumor load, pathological change and histopathological score were observed. Immunohistochemistry was used to detect the expressions of VEGF, P2X7R, phospho-STAT3 (p-STAT3), and nuclear factor-kappa B p65 (NF-κB p65) proteins in rat colon tissue. Western blot was used to detect the levels of p-STAT3 and NF-κB p65 proteins in rat colon tissue. Results: Compared with the normal group, the colon tumor load and histopathological score in the model group were significantly increased (both P<0.001), and different grades of dysplasia were observed in colon tissue from the model group, reaching the degree of adenocarcinoma; the expression level of P2X7R protein in colon tissue was significantly decreased (P<0.001), and the expression levels of p-STAT3, NF-κB p65 and VEGF proteins were significantly increased (all P<0.001) in the model group. Compared with the model group, the colon tumor load, colon histopathological score and the levels of p-STAT3, NF-κB p65 and VEGF proteins in colon tissue were significantly decreased (all P<0.05) in the herb-partitioned moxibustion group and the ginger-partitioned moxibustion group while the expression levels of P2X7R protein in colon tissue were significantly increased (both P<0.05). Conclusion: Both herb-partitioned moxibustion and ginger-partitioned moxibustion can reduce the colon tumor load in CACC rats and delay the progression of colon adenomas. The mechanism may be mediated by the P2X7R/STAT3 pathway to inhibit STAT3 phosphorylation, thereby reducing VEGF protein expression.