Objective:To study the relationship between urinary arsenic methylation metabolism patterns and skin keratinization and pigmentation abnormalities in population exposed to arsenic through drinking water.Methods:Using a cross-sectional study method, a survey on endemic arsenic poisoning was conducted among permanent residents of drinking water endemic arsenic poisoning areas in Bayannur City, Inner Mongolia Autonomous Region in 2004 (before water improvement). In 2017 (after water improvement), 71 arsenic exposed individuals were followed up as survey subjects. According to the "Diagnosis of Endemic Arsenism" (WS/T 211-2015), the clinical grading of skin injuries (skin keratinization, pigmentation abnormalities) in the survey subjects was evaluated. Urine samples were collected for detection of arsenic methylation metabolite levels by high-performance liquid chromatography inductively coupled plasma mass spectrometry and calibrated with urinary creatinine. The changes and amplitudes of urinary arsenic methylation indicators before and after water improvement were calculated and analyzed according to the outcome of skin keratinization and pigmentation abnormalities which were divided into reduced, unchanged, and added groups.Results:(1) The changes in urinary total arsenic (TAs), inorganic arsenic (iAs), monomethyl arsenic (MMA), and dimethyl arsenic (DMA) levels in different outcome groups of skin keratinization were compared, and the differences were statistically significant ( H = 9.08, 8.77, 9.28, 8.57, P < 0.05). The changes in urinary TAs, iAs, MMA, DMA levels, iAs percentage (iAs%), DMA percentage (DMA%), and primary methylation index (PMI) in different outcome groups of skin pigmentation abnormalities were compared, and the differences were statistically significant ( H = 8.04, 10.67, 8.29, 9.14, 6.30, 9.10, 7.20, P < 0.05). (2) The comparison of amplitudes in urinary TAs, iAs, MMA, and DMA levels in different outcome groups of skin keratinization showed statistically significant differences ( H = 6.92, 7.34, 6.66, 6.16, P < 0.05). The amplitudes in urinary iAs level, iAs%, DMA%, and PMI in different outcome groups of skin pigmentation abnormalities were compared, and the differences were statistically significant ( H = 7.94, 7.61, 9.95, 7.22, P < 0.05). Conclusion:The changes pattern of urinary TAs, iAs, MMA, DMA, iAs%, DMA%, and PMI in population exposed to arsenic through drinking water is related to the transformation of skin keratinization and pigmentation abnormalities.

Objective:To study the relationship between the levels of multiple elements in urine and the risk of arsenic poisoning in populations exposed to drinking water arsenic in Inner Mongolia Autonomous Region (Inner Mongolia).Methods:From April 2023 to January 2024, a case-control study method was used to select 128 individuals with a residence time of ≥10 years in drinking water arsenic exposed areas in Inner Mongolia as study subjects. Eighty-one individuals diagnosed with arsenic poisoning were selected as the case group, and 47 healthy individuals were selected as the control group for urine sample collection and questionnaire survey. Inductively coupled plasma mass spectrometry was employed to determine the levels of 10 elements (chromium, manganese, cobalt, nickel, copper, zinc, arsenic, molybdenum, cadmium and lead) in urine. The levels of each element in urine were divided into four groups ( Q1, Q2, Q3, and Q4 groups) based on quartiles. The associations between the levels of various elements in urine and the risk of arsenic poisoning were studied using binary logistic regression model and restricted cubic spline (RCS). Results:The age of the control group and the case group [ M ( Q1, Q3)] were 61 (53, 69) and 61 (56, 67) years old, respectively. There were 19 and 43 males, and 28 and 38 females, respectively. There was no statistically significant differences in age and and gender composition between the two groups ( Z = - 0.39, P = 0.700; χ 2 = 1.91, P = 0.167). The levels of urinary copper and cadmium of the case group were higher than those of the control group, and the differences were statistically significant ( Z = - 2.66, - 2.16, P < 0.05). The results of univariate logistic regression analysis showed that urinary copper was an influencing factor for arsenic poisoning ( P = 0.017). The results of multivariate logistic regression analysis revealed that after adjusting for covariates, urinary copper and arsenic were independent influencing factors of arsenic poisoning ( P < 0.05). Taking Q1 group as a reference, urinary copper in Q3 group [ OR (95% CI) = 8.23 (1.81, 37.39), P = 0.006] increased the risk of arsenic poisoning, while urinary arsenic in Q2, Q3, and Q4 groups [ OR (95% CI) = 0.24 (0.06, 0.92), 0.12 (0.03, 0.53), 0.15 (0.04, 0.63), P < 0.05] decreased the risk of arsenic poisoning. After adjusting for covariates, RCS did not show a dose-response relationship between urinary copper, urinary arsenic, and arsenic poisoning ( P > 0.05). Conclusion:Urinary arsenic and copper are associated with the risk of arsenic poisoning in the drinking water arsenic exposed areas of Inner Mongolia, copper exposure may contribute significantly to arsenic poisoning.

Objective:To study the relationship between urinary arsenic methylation metabolism patterns and skin keratinization and pigmentation abnormalities in population exposed to arsenic through drinking water.Methods:Using a cross-sectional study method, a survey on endemic arsenic poisoning was conducted among permanent residents of drinking water endemic arsenic poisoning areas in Bayannur City, Inner Mongolia Autonomous Region in 2004 (before water improvement). In 2017 (after water improvement), 71 arsenic exposed individuals were followed up as survey subjects. According to the "Diagnosis of Endemic Arsenism" (WS/T 211-2015), the clinical grading of skin injuries (skin keratinization, pigmentation abnormalities) in the survey subjects was evaluated. Urine samples were collected for detection of arsenic methylation metabolite levels by high-performance liquid chromatography inductively coupled plasma mass spectrometry and calibrated with urinary creatinine. The changes and amplitudes of urinary arsenic methylation indicators before and after water improvement were calculated and analyzed according to the outcome of skin keratinization and pigmentation abnormalities which were divided into reduced, unchanged, and added groups.Results:(1) The changes in urinary total arsenic (TAs), inorganic arsenic (iAs), monomethyl arsenic (MMA), and dimethyl arsenic (DMA) levels in different outcome groups of skin keratinization were compared, and the differences were statistically significant ( H = 9.08, 8.77, 9.28, 8.57, P < 0.05). The changes in urinary TAs, iAs, MMA, DMA levels, iAs percentage (iAs%), DMA percentage (DMA%), and primary methylation index (PMI) in different outcome groups of skin pigmentation abnormalities were compared, and the differences were statistically significant ( H = 8.04, 10.67, 8.29, 9.14, 6.30, 9.10, 7.20, P < 0.05). (2) The comparison of amplitudes in urinary TAs, iAs, MMA, and DMA levels in different outcome groups of skin keratinization showed statistically significant differences ( H = 6.92, 7.34, 6.66, 6.16, P < 0.05). The amplitudes in urinary iAs level, iAs%, DMA%, and PMI in different outcome groups of skin pigmentation abnormalities were compared, and the differences were statistically significant ( H = 7.94, 7.61, 9.95, 7.22, P < 0.05). Conclusion:The changes pattern of urinary TAs, iAs, MMA, DMA, iAs%, DMA%, and PMI in population exposed to arsenic through drinking water is related to the transformation of skin keratinization and pigmentation abnormalities.

Objective:To study the relationship between the levels of multiple elements in urine and the risk of arsenic poisoning in populations exposed to drinking water arsenic in Inner Mongolia Autonomous Region (Inner Mongolia).Methods:From April 2023 to January 2024, a case-control study method was used to select 128 individuals with a residence time of ≥10 years in drinking water arsenic exposed areas in Inner Mongolia as study subjects. Eighty-one individuals diagnosed with arsenic poisoning were selected as the case group, and 47 healthy individuals were selected as the control group for urine sample collection and questionnaire survey. Inductively coupled plasma mass spectrometry was employed to determine the levels of 10 elements (chromium, manganese, cobalt, nickel, copper, zinc, arsenic, molybdenum, cadmium and lead) in urine. The levels of each element in urine were divided into four groups ( Q1, Q2, Q3, and Q4 groups) based on quartiles. The associations between the levels of various elements in urine and the risk of arsenic poisoning were studied using binary logistic regression model and restricted cubic spline (RCS). Results:The age of the control group and the case group [ M ( Q1, Q3)] were 61 (53, 69) and 61 (56, 67) years old, respectively. There were 19 and 43 males, and 28 and 38 females, respectively. There was no statistically significant differences in age and and gender composition between the two groups ( Z = - 0.39, P = 0.700; χ 2 = 1.91, P = 0.167). The levels of urinary copper and cadmium of the case group were higher than those of the control group, and the differences were statistically significant ( Z = - 2.66, - 2.16, P < 0.05). The results of univariate logistic regression analysis showed that urinary copper was an influencing factor for arsenic poisoning ( P = 0.017). The results of multivariate logistic regression analysis revealed that after adjusting for covariates, urinary copper and arsenic were independent influencing factors of arsenic poisoning ( P < 0.05). Taking Q1 group as a reference, urinary copper in Q3 group [ OR (95% CI) = 8.23 (1.81, 37.39), P = 0.006] increased the risk of arsenic poisoning, while urinary arsenic in Q2, Q3, and Q4 groups [ OR (95% CI) = 0.24 (0.06, 0.92), 0.12 (0.03, 0.53), 0.15 (0.04, 0.63), P < 0.05] decreased the risk of arsenic poisoning. After adjusting for covariates, RCS did not show a dose-response relationship between urinary copper, urinary arsenic, and arsenic poisoning ( P > 0.05). Conclusion:Urinary arsenic and copper are associated with the risk of arsenic poisoning in the drinking water arsenic exposed areas of Inner Mongolia, copper exposure may contribute significantly to arsenic poisoning.

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 construct an assessment tool for laparoscopic left lateral sectionectomy skills.Methods:From November 2023 to January 2024, 22 clinical experts in hepatopancreatobiliary surgery from different regions of China were selected for this study. A preliminary indicator system was established through literature review, and the indicators and their weights at each level were determined using the Delphi method and analytic hierarchy process (AHP).Results:In the two rounds of consultation, the expert positive coefficients were 100.00% and 90.91%, authority coefficients were 0.984 and 0.985, Kendall coefficients were 0.231 and 0.193 ( P<0.001), and Cronbach's α coefficients were 0.905 and 0.865, respectively. A skill assessment tool for laparoscopic left lateral sectionectomy skills was constructed consisting of 5 primary indicators and 23 secondary indicators. AHP analysis showed that the concordance rate of each matrix of the secondary indicators was <0.1, meeting the consistency test requirements. Conclusions:The assessment tool for laparoscopic left lateral sectionectomy skills developed in this study is objective and reliable for evaluating the surgical skills of novice surgeons.

Objective:To analyze the effect of panax notoginseng saponins(PNS)on mTORC1-HIF1α signaling pathway,and to explore its effect and mechanisms on the differentiation balance of Th17/Treg cells in CD4+T cells.Methods:Isolate the spleens of C57BL/6 mice,then select CD4+T cells by magnetic beads and cultured in vitro.The optimal concentration of PNS was screened by the CCK-8,and then these cells were divided into control group and PNS treatment group(5,10 and 20 μg/ml),each gives correspond-ing drug treatment after 48 h.Afterwards,flow cytometry was used to detect differentiation of Th17/Treg cells.Real-time quantitative fluorescent PCR was used to detect the expressions of RORγt,Foxp3,mTOR,Raptor,HIF1α mRNA.ELISA was used to detect the levels of IL-17A and IL-10 in the supernatant of cell culture.Western blot was used to detect the expressions and phosphorylation levels of 4EBP1,S6K and HIF1α proteins.Results:5,10,20 μg/ml PNS could significantly inhibit Th17 cells differentiation and promote Treg cells differentiation;5,10,20 μg/ml PNS could significantly reduce the expression of RORγt mRNA,and then reduce the level of IL-17A;20 μg/ml PNS could significantly promote the expression of Foxp3 mRNA and increase the level of IL-10;10,20 μg/ml PNS could significantly decrease the phosphorylation of 4EBP1 and S6K;5,10,20 μg/ml PNS could significantly reduce the expression of HIF1α mRNA and inhibit the expression of HIF1α protein.Conclusion:Certain concentrations of PNS can inhibit the differentiation of Th17 cells in CD4+T cells,and promote the differentiation of Treg cells,which is related with modulating mTORC1-HIF1α signaling pathway.

Objective:To assess the prognostic impact of frailty on elderly inpatients with heart failure.Methods:This prospective cohort study enrolled 121 in elderly patients with heart failure from Beijing Hospital, the General Hospital of the People's Liberation Army, and Beijing Tsinghua Changgung Hospital between September 2018 and April 2019.Patients were assessed for frailty using the Fried frailty phenotype and categorized into frail and non-frail groups.Follow-ups were conducted at 3-, 6-, and 12-months post-enrollment through clinic visits or phone calls to record adverse events.Composite endpoints include all-cause mortality and rehospitalization duo to deterioration of heart failure.Results:The study included 121 patients with an average age of 78.0±7.4 years, of whom 71(58.7%)were male and 57(47.1%)were classified as frail.Compared to the non-frail group, the frail group had lower estimated glomerular filtration rates[49.5±20.7 ml/(min·1.73m 2) vs.(64.0±27.1)ml/(min·1.73m 2)], lower scores in Basic Activities of Daily Living[5.0(4.0, 6.0) vs.6.0(5.0, 6.0)], Instrumental Activities of Daily Living[2.0(1.3, 7.8) vs.7.0(5.0, 8.0)], and Mini-Mental State Examination[26.0(16.0, 28.0) vs.27.0(22.3, 29.0)], all P<0.05.They also experienced longer hospital stays[10.5(6.0, 18.8)days vs.8.0(6.0, 11.8)days, P=0.008].During the follow-up period, the incidence of composite endpoint events was significantly higher in the frail group(43.9% vs.25.0%, P=0.029).Kaplan-Meier survival analysis demonstrated that the one-year incidence of composite endpoint events was significantly higher in the frail group( P=0.013).Multivariable Cox regression analysisindicated that frailty was an independent risk factor for composite endpoint events( HR=2.201, 95% CI: 1.089-4.447, P=0.028). Conclusions:Frailty is an independent risk factor for poor outcomes in elderly hospitalized patients with heart failure and should be considered a crucial factor in clinical assessment and treatment strategies.

Objective:We evaluated frailty in elderly hospitalized patients with atrial fibrillation and analyzed the relevance, consistency, and diagnostic power of different frailty tools.Methods:From September 2018 to April 2019, a total of 197 elderly patients with atrial fibrillation aged ≥ 65 years in Beijing Hospital, Chinese PLA General Hospital, and Beijing Tsinghua Changgung Hospital were prospectively enrolled.Five frailty tools, including the clinical frailty scale(CFS), FRAIL scale(FRAIL), Fried frailty phenotype(Fried), Edmonton frail scale(EFS), and comprehensive geriatric assessment-frailty index(CGA-FI), were used for frailty assessment.Results:A total of 197 hospitalized elderly patients with atrial fibrillation were enrolled, with an average age of(77.5±7.1)years old(57.4% male). The prevalence of frailty, according to the five frailty tools, were 25.4%(FRAIL), 27.9%(EFS), 34.5%(Fried), 40.6%(CFS), and 42.6%(CGA-FI), respectively.CFS had a good correlation(correlation coefficient 0.80)and and consistency(Kappa value 0.71, 95% CI 0.61~0.81)with CGA-FI.The combined frailty index was used as the gold standard for frailty diagnosis.The results showed that CFS and CGA-FI had high diagnostic sensitivity(95.9 % and 98.0 %, respectively)and specificity(77.7 % and 75.7 %, respectively). Conclusions:Frailty is common in elderly hospitalized patients with atrial fibrillation, showing multidimensional features, and physical weakness is not prominet.CFS and CGA-FI are recommended for the assessment of frailty in patients with atrial fibrillation, which had good correlation and consistency.

Objective:To evaluate the association of different biomarkers with frailty in elderly hospitalized patients.Methods:In this cross-sectional study, a total of 319 elderly patients aged 65 years or older hospitalized in Beijing Hospital between September 2018 and February 2019 were enrolled.Patients had a mean age of(75.0±6.6)years and 151(47.3%)were women.Based on the Fried phenotype, patients were divided into a non-frail group(244 cases, 76.5%)and a frail group(75 cases, 23.5%). The clinical characteristics and biomarker levels of the two groups were compared.The association of different biomarkers with frailty was evaluated by using the receiver operating characteristic(ROC)curve.The Youden index was used for the optimal cutoff values and the area under the curve(AUC)were calculated.AUCs of different biomarkers were compared to assess their correlations with frailty.Results:Hemoglobin, lipid levels(triglycerides, total cholesterol and low-density lipoprotein cholesterol), and prealbumin were significantly lower in the frail group than in the non-frail group( P<0.05), while N-terminal pro-B type natriuretic peptide(NT-proBNP)and high-sensitivity C reactive protein(hsCRP)levels were significantly higher than in the non-frail group( P<0.05). Thyrotropin(TSH)and free triiodothyronine(FT3)levels were significantly lower( P<0.05)and trans-triiodothyronine(rT3)was significantly higher( P<0.05)in the frail group.The combination of six biomarkers[hemoglobin, prealbumin, hsCRP, 25-dihydroxy vitamin D3[25(OH)D3], rT3 and NT-pro BNP]had the most powerful correlation with frailty(AUC=0.705, 95% CI: 0.652-0.755), but the correlation was not significantly different from that of the combination of 3 markers(hemoglobin, rT3 and hsCRP)(ROC=0.010, 95% CI: -0.0106-0.0306, P>0.05). Either of the two combinations was significantly better than the combination of 2 markers(hemoglobin and rT3)(ROC=0.143, 95% CI: 0.0406-0.245; ROC=0.153, 95% CI: 0.0498-0.256; all P<0.01). Conclusions:Hemoglobin, lipids, prealbumin, TSH and FT3 levels decrease while NT-proBNP and hsCRP levels increase in elderly hospitalized frail patients.The 6-biomarker combination[hemoglobin, prealbumin, hsCRP, 25(OH)D3, rT3 and NT-pro BNP]and 3-biomarker combination(hemoglobin, rT3 and hsCRP)have better correlation with frailty than the 2-biomarker combination(hemoglobin and rT3).