BACKGROUND:Astrocytes are the most abundant cells in the central nervous system,and various subsets of astrocytes are heterogeneous,performing a variety of special functions.Single-cell RNA sequencing(scRNA-seq)technology developed in recent years has extended our understanding of astrocyte heterogeneity from the perspective of transcriptome profiling. OBJECTIVE:To summarize the heterogeneity of scRNA-seq technology in different time and space,and pathological states and expand our knowledge of astrocyte heterogeneity on both molecular and functional levels. METHODS:The relevant articles on astrocyte heterogeneity and scRNA-seq were searched on PubMed,Elsevier,and CNKI databases.The search terms were"astrocytes,scRNA-seq,heterogeneity,Alzheimer disease,spinal cord injury,multiple sclerosis"in Chinese and English.Finally,74 articles were selected for viewing after screening according to inclusion criteria. RESULTS AND CONCLUSION:scRNA-seq studies related to the heterogeneity of astrocytes have shown that astrocyte is significantly heterogeneous across four aspects:species,developmental stage,central nervous system region,and pathological state.(1)Unique expression of certain genes occurs in astrocytes of different species,and the discovery of species-specific genes is beneficial for the translation of clinical studies.(2)During astrocyte development,differential gene expression emerged in the cellular subtypes identified at each stage,which further refined the cellular lineage of astrocytes and laid the foundation for the study of astrocyte developmental trajectories and mechanisms.(3)The discovery of differential gene expression allows regional localization of different astrocyte subpopulations and assists in the diagnosis and treatment of neurological diseases.(4)Astrocyte heterogeneity revealed by scRNA-seq can provide specific markers at the time of disease diagnosis and identify potential therapeutic targets.(5)The heterogeneity of astrocytes exists in many aspects,interacts with each other and is complex.The mechanisms of its generation,maintenance and transformation remain unclear.At present,molecular research on the single-cell level is still lacking.Linking transcriptionally defined astrocyte subpopulations to cellular activity,behavior and disease markers in real time remains one of the great challenges in the field.

Objective:To explore the predictive value of admission serum homocysteine levels and quantitative electroencephalogram (qEEG) indicators for adverse outcomes in patients with cerebral hemorrhage.Methods:A retrospective study was conducted on 89 patients, who were collected as the study objects with hemorrhagic stroke treated in the neurology intensive care unit at Kailuan General Hospital from January 2017 to December 2022. Patients were categorized into two groups based on modified Rankin Scale (mRS) scores at discharge: a good prognosis group (mRS≤2) and a poor prognosis group (mRS 3-6). Clinical data and qEEG monitoring of various brain regions were collected. The impact factors of hemorrhagic prognosis were analyzed using multifactorial logistic regression. ROC curve analysis was performed to assess the predictive value of qEEG and admission homocysteine levels for adverse outcomes in hemorrhagic stroke patients.Results:(1) The age of the poor prognosis group was higher than that of the good prognosis group((66.51+13.64) to (60.53+11.69), t=2.15, P=0.034) and admission serum homocysteine levels were significantly higher in the poor prognosis group than in the good prognosis group (17.28(15.52,24.72)mmol/L to 14.50(10.28,16.00)mmol/L, Z=4.14, P<0.001). (2) In the poor prognosis group, power values of δ brain waves in leads Fp1-2, F4, C4, P4, F8, and T4 were higher than those in the good prognosis group (87.99(41.57,196.69) to 50.67(26.64,54.75), Z=2.76, P=0.006); (79.17(40.71,200.00) to 45.06(20.22,61.00), Z=2.10, P=0.036); (72.64(34.97,219.78) to 34.42(19.81,63.4), Z=2.03, P=0.043); (65.06(33.36,177.45) to 28.12(15.88,63.36), Z=2.08, P=0.038); (52.92(25.64,187.91) to 23.61(11.67,43.26), Z=2.21, P=0.027); (66.67(32.56,180.76) to 36.31(17.2,53.78), Z=2.46, P=0.014); (57.30(25.24,127.04) to 29.57(11.91,41.89), Z=2.26, P=0.024). Power values of θ brain waves in leads Fp1-2, F3, F4, C3, C4, P3-4, O1, F7-8, and T3-4 were higher in the poor prognosis group(77.45(47.63,138.72)比35.88(20.92,44.81), Z=3.50, P<0.001); (77.05(35.16,120.22) to 38.74(19.86,58.09), Z=2.27, P=0.023); (85.24(52.53,147.90) to 35.42(14.7,52.59), Z=2.61, P=0.009); (75.81(37.90,124.97) to 36.85(17.92,55.43), Z=2.30, P=0.021); (72.00(43.92,123.54) to 28.37(14.02,51.9), Z=2.22, P=0.027); (67.08(32.01,104.05) to 31.32(17.98,45.28), Z=2.10, P=0.035); (55.33(32.29,94.30) to 25.64(11.87,34.01), Z=2.24, P=0.025); (48.84(20.64,96.28) to 19.85(9.83,28.58), Z=2.30, P=0.022);(48.46(25.06,81.78) to 23.95(8.80,29.16), Z=2.51, P=0.012); (64.46(39.38,112.44) to 26.85(15.74,39.58), Z=2.80, P=0.005); (65.68(31.78,102.00) to 31.09(15.98,46.96), Z=2.38, P=0.017); (45.26(28.34,73.14) to 21.45(10.57,36.59), Z=2.04, P=0.042); (43.50(22.58,78.67) to 25.45(11.91,32.26), Z=2.22, P=0.027). Power values of slow-wave index in leads Fp1-2, F3-4, C3-4, P4, F7-8, and T4, as well as the overall brain average, were higher in the poor prognosis group (6.64(2.98,10.42) to 3.65(2.31,4.30), Z=2.65, P=0.01); (6.53(3.96,11.65) to 3.53(2.56,4.51), Z=2.30, P=0.022); (7.38(4.62,13.12) to 3.83(1.70,4.71), Z=2.38, P=0.017); (5.88(4.02,12.15) to 3.18(2.21,4.46), Z=2.29, P=0.022); (6.13(3.83,11.22) to 2.97(1.53,4.58), Z=2.01, P=0.044); (6.07(3.53,9.39) to 2.74(2.00,3.81), Z=2.40, P=0.016);(4.11(2.51,9.23) to 2.18(1.37,2.82), Z=2.25, P=0.024); (5.71(3.81,10.44) to 3.22(1.86,4.04), Z=2.28, P=0.023); (6.00(3.65,10.37) to 3.04(2.00,4.00), Z=2.39, P=0.017); (4.08(2.56,8.33) to 2.08(1.60,3.14), Z=2.50, P=0.013), with significant statistical differences noted (5.45(3.31,10.08) to 3.17(2.02,4.88), Z=3.62, P=0.005). (3) Logistic regression results showed that admission homocysteine levels ( OR 1.311,95% CI 1.008-1.705, P=0.044), admission NIHSS scores ( OR 1.588,95% CI 1.074-2.349, P=0.020), and overall brain average slow-wave index were influencing factors for poor prognosis in cerebral hemorrhage ( OR 8.596,95% CI 1.088-67.889, P=0.041). (4) ROC curve analysis revealed that the AUC for predicting adverse outcomes in cerebral hemorrhage was 0.768 (95% CI (0.665, 0.872)) for admission homocysteine levels, 0.743 (95% CI (0.634, 0.852)) for the overall brain average slow-wave index, and 0.896 (95% CI (0.827, 0.965)) for admission NIHSS. The cutoff values were 15.67, 3.62, and 8.5, respectively. Sensitivity was 77.8%, 71.1%, and 68.9%, and specificity was 59.4%, 68.7%, and 100%, respectively. The Youden indices were 0.372, 0.398, and 0.689. Conclusion:In the acute phase of cerebral hemorrhage, electroencephalographic physiological changes manifest shows an increase in the δ, θ, and slow-wave index throughout the entire brain. Higher admission homocysteine levels suggest a worse prognosis in patients with cerebral hemorrhage. Admission homocysteine levels and overall brain average slow-wave index have certain predictive value for adverse outcomes in acute cerebral hemorrhage.

ObjectiveTo investigate the effects of acupuncture combined with Du-Moxibustion (ADM) on peripheral blood cell count and levels of immune factors in patients with occupational chronic benzene poisoning. Methods A total of 70 patients with occupational chronic benzene poisoning (leukopenia and neutropenia) were selected as the research subjects by judgement sampling method. They were randomly divided into a control group and an ADM group using a random number table method, with 35 cases in each group. Patients in the control group were treated with conventional Western medicine such as leukocyte boosting and symptomatic treatment. While patients in the ADM group were treated with ADM treatment in addition to treatments of the control group, once per week for five consecutive weeks. Peripheral blood samples of patients were collected before and after treatment from both groups, to detect cell counts and serum levels of immune factors. Results The white blood cell count, red blood cell count, absolute lymphocyte count, absolute neutrophil count, platelet count, and levels of hemoglobin, immunoglobulins (Ig) A, IgM, IgG, complement C3 and complement C4 of patients in both groups improved after treatment compared with those before treatment (all P<0.05). The white blood cell count, levels of IgA, IgM, IgG, complement C3 and complement C4 of patients in the ADM group were higher than those in the control group after treatment (all P<0.05). Conclusion ADM treatment can increase peripheral blood white blood cells and serum levels of immune factor in patients with occupational chronic benzene poisoning (leukopenia, neutropenia), which helps improve patient recovery and can be promoted clinically.

Background Arsenic, cobalt, barium, and other individual metal exposure have been confirmed to be associated with the incidence of kidney stones. However, there are few studies on the association between mixed metal exposure and kidney stones, especially in occupational groups. Objective To investigate the association between mixed metal exposure and kidney stones in an occupational population from a metal smelting plant. Methods A questionnaire survey was conducted to collect sociodemographic characteristics, medical history, and lifestyle information of 1158 mixed metal-exposed workers in a metal smelting plant in Guangdong Province from July 2021 to January 2022. Midstream morning urine samples were collected from the workers, the concentrations of 18 metals including lithium, vanadium, chromium, manganese, cobalt, nickel, copper, zinc, arsenic, selenium, strontium, molybdenum, cadmium, cesium, barium, tungsten, titanium, and lead were measured by inductively coupled plasma mass spectrometry, and the urinary mercury levels were measured by cold atomic absorption spectroscopy. Based on predetermined inclusion criteria, a total of 919 mixed metal-exposed workers were included in the study, including 117 workers in the kidney stone group and 802 workers in the non-kidney stone group. With a detection rate of urinary metals greater than 80% as entry criterion, 16 eligible metals were finally included for further analysis. Parametric or non-parametric methods were used to compare the differences between continuous or categorical variables of the non-kidney stone group and the kidney stone group. Logistic regression models were constructed to explore the association between individual metal exposures and kidney stones. Weighted quantile sum (WQS) regression models were used to evaluate the association between mixed metal exposure and kidney stones, as well as the weights of each metal on kidney stones. Then Bayesian kernel machine regression (BKMR) models were used to explore the overall effect of mixed metal exposure on renal calculi and the potential interactions between metals. Results We found that there were significant differences in sex, age, length of service, and body mass Index (BMI) between the non-kidney stone group and the kidney stone group (P<0.05). The urinary concentrations of molybdenum and barium in the kidney stone group were higher than those in the non-kidney stone group, and the differences were statistically significant (P<0.05). The logistic regression models demonstrated that urinary cobalt, arsenic, molybdenum, and barium were positively correlated with the risk of kidney stones (P_trend<0.05). The WQS regression models showed that the mixed exposure to vanadium, cobalt, arsenic, molybdenum, and barium was positively associated with the risk of kidney stones (P<0.05). Among them, molybdenum, arsenic, and barium accounted for 0.391, 0.337, and 0.154, respectively. The BKMR results revealed a positive association between metal mixture exposure and the risk of kidney stones (P<0.05). When other metals were fixed at the 25th, 50th, or 75th percentile, arsenic, molybdenum, cobalt, and barium exhibited significant positive effects on the risk of kidney stones (P<0.05), while vanadium showed a significant negative effect (P<0.05). The interaction analysis demonstrated interactions between barium and cobalt, as well as between vanadium and cobalt (P<0.05). Conclusion In the occupational population of this smelter, occupational mixed metal exposure could increase the risk of kidney stones, and the main metals are molybdenum, arsenic, barium, and cobalt.

Background Occupational exposure to lead, cadmium, or arsenic is a potential risk factor for blood pressure elevation. Current studies mainly focus on the relationship between a single metal and blood pressure. However, mixed metal exposure often exists in the actual working environment, and the interactive effects of polymetallic interactions on blood pressure and the dose-effect relationship remain unclear yet. Objective To explore the influence proportion of occupational exposure to lead, cadmium, or arsenic on blood pressure and their interactive effects. Methods From January to December 2021, workers from a smelter in southern China were selected. Demographic characteristics, height, weight, and blood pressure of workers were collected through questionnaire and physical examination. At the same time, their urine samples were collected and the levels of urinary lead, urinary cadmium, and urinary arsenic were detected by inductively coupled plasma mass spectrometry, and corrected by urinary creatinine (Cr). Linear regression and logistic regression were used to analyze the relationship between urinary lead, cadmium, and arsenic and blood pressure. Weighted quantile sum (WQS) regression was applied to evaluate the dose-effect relationship between urinary lead, cadmium, and arsenic exposures and blood pressure and the effect weight of each metal on blood pressure. Generalized linear regression and additive/multiplicative scaling were used to identify interactive effects of the three metals on blood pressure. Results A total of 1075 workers were included in this study, with a mean age of (44.68±5.11) years and mean working seniority of (24.66±5.23) years. There were 891 males (88.9%) and 184 were females (17.1%); 24.7% workers were drinkers and 45.7% workers were smokers; 302 workers (28.1%) reported hypertension and 37 of them were taking antihypertensive drugs. The P₅₀ (P₂₅, P₇₅) levels of urinary lead, urinary cadmium, and urinary arsenic were 6.11 (3.71, 11.08), 3.88 (2.68, 5.44), and 26.04 (19.99, 35.11) μg·g⁻¹, respectively. After adjusting for gender, age, working seniority, body mass index, smoking, drinking, and the usage of antihypertensive drugs, systolic and diastolic blood pressure increased by 0.772 and 0.418 mmHg respectively for 10% increase in lead, cadmium, and arsenic mixed exposure. Urinary cadmium, among the three single exposures, had the greatest effect on systolic and diastolic blood pressure, weight (w)=0.523 and 0.551 respectively. The interaction of urinary lead and urinary cadmium was positively correlated with the occurrence of hypertension, multiplicative interaction OR (OR_int)=1.88 (95%CI: 1.09, 3.63), attributable proportion due to interaction (AP)=1.19 (95%CI: 0.40, 8.18). Conclusion This study shows that mixed exposure to lead, cadmium, and arsenic has a positive relationship with blood pressure, in which cadmium plays a major role. Co-exposure to lead and cadmium has a positive interactive effect on hypertension development and systolic blood pressure elevation.

Objective: To investigate the effect of combined exposure to four heavy metals (lead, cadmium, arsenic, mercury) on early kidney injury in occupational population. Methods: A total of 384 workers exposed to combined heavy metals in a non-ferrous metal smelting plant in Guangdong Province were selected as the research subjects using judgment sampling method. The levels of blood lead, urinary cadmium and urinary arsenic were detacted by inductively coupled plasma mass spectrometry, while urinary mercury levels were measured using cold atomic absorption spectroscopy (acidic tin chloride reduction method). The levels of biomarkers such as urinary β₂-microglobulin (β₂-MG), kidney injury molecule-1 (Kim-1) and neutrophil gelatinase-associated lipocalin (NGAL) were detected by enzyme-linked immunosorbent assay. Spearman correlation analysis, linear regression, weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) models were used to analyze the association between the exposure to the four heavy metals and early kidney injury biomarkers. Results: The median of blood lead, urinary cadmium, urinary arsenic and urinary mercury were 0.47 μmol/L and 4.450, 27.790 and 0.520 μg/gCr, respectively. The median of urinary β₂-MG, Kim-1 and NGAL were 62.960, 1.130 and 18.150 μg/gCr, respectively. Spearman correlation analysis showed that urinary levels of β₂-MG, Kim-1, and NGAL were weakly correlated with blood lead and urinary mercury levels (all P<0.01), but not correlated with urinary cadmium and urinary arsenic (all P>0.05). The results of multiple linear regression analysis showed that urinary mercury was positively correlated with urinary β₂-MG, Kim-1 and NGAL (all P<0.01), urinary arsenic was positively correlated with urinary β₂-MG level (P<0.01), and blood lead was negatively correlated with urinary β₂-MG and Kim-1 (all P<0.05). The WQS regression analysis showed that the combined effect of the four heavy metals was positively correlated with urinary β₂-MG, Kim-1 and NGAL (all P<0.01), with mercury having the highest impact and lead the lowest. BKMR model analysis showed the increasing trend in urinary β₂-MG, Kim-1 and NGAL with the increasing levels of the combined exposure to the four heavy metals. Urinary β₂-MG, Kim-1 and NGAL decreased when urinary mercury level increased from the 25th percentile to the 75th percentile and the other metals were correspondingly fixed at a certain level. When the blood exposure levels of other metals remained at the corresponding median levels, urinary β₂-MG, Kim-1 and NGAL levels were positively correlated with urinary arsenic level, but no significant linear dose-response relationship was observed with the other three heavy metals. Conclusion: sLead, arsenic, and mercury are independently associated with early kidney injury biomarkers in occupational population from non-ferrous metal smelting. The four heavy metals had positive combined effects on urinary β₂-MG, Kim-1 and NGAL, with mercury having the greatest impact.

Enterotoxigenic Escherichia coli（ETEC）infection can induce watery diarrhea，leading to dehydration，electrolyte disturbance，and even death in severe cases. Recombinant B subunit/inactivated whole-cell cholera（rBS/WC）vaccine is effective in preventing ETEC infectious diarrhea. On the basis of the latest evidence on etiology and epidemiology of ETEC，as well as the effectiveness，safety，and health economics of rBS/WC vaccine，National Clinical Research Center for Child Health（The Children’s Hospital，Zhejiang University School of Medicine）and Zhejiang Provincial Center for Disease Control and Prevention invited experts to develop expert consensus on rBS/WC vaccine in prevention of ETEC infectious diarrhea. It aims to provide the clinicians and vaccination professionals with guidelines on using rBS/WC vaccine to reduce the incidence of ETEC infectious diarrhea.

Objective:To explore the effects of non-suicidal self-injury on suicidal ideation in adolescents with depressive disorder, and the mediating role of rumination and depression between them.Methods:A sample of 397 depressive disorder adolescents were recruited to complete the adolescent non-suicidal self-injury behaviour questionnaire, ruminative responses scale (RRS), self-rating depression scale (SDS), and Beck scale for suicide ideation-Chinese version(BSI-CV). All data processing and analysis were performed using SPSS 23.0.The mediating effect was tested by correlation analysis and Bootstrap analysis.Results:The non-suicidal self-injury score was (29.192±11.281), the rumination score was (65.036±12.284), the depression score was (75.770±11.278), and the suicidal ideation score was (40.681±11.626). Non-suicidal self-injury was significantly and positively correlated with suicidal ideation( r=0.403, P<0.01), rumination and depression( r=0.332, 0.470, both P<0.01). Rumination was significantly and positively correlated with depression and suicidal ideation( r=0.549, 0.181, both P<0.05). Depression was significantly and positively correlated with suicidal ideation( r=0.313, P<0.01). The direct effect value of non-suicidal self-injury on suicidal ideation was 0.341(95% CI=0.238-0.444), the indirect effect of non-suicidal self-injury on suicidal ideation through two pathways, the separate mediating effect value of depression was 0.057(95% CI=0.077-0.114), and the chain mediating effect value of rumination and depression was 0.026(95% CI=0.004-0.057). Conclusion:Non-suicidal self-injury can directly affect suicidal ideation of depressive disorder adolescents and indirectly through rumination and depression.

The importance of structural variants(SVs)for human phenotypes and diseases is now recognized.Although a variety of SV detection platforms and strategies that vary in sensitivity and specificity have been developed,few benchmarking procedures are available to confidently assess their performances in biological and clinical research.To facilitate the validation and application of these SV detection approaches,we established an Asian reference material by characterizing the genome of an Epstein-Barr virus(EBV)-immortalized B lymphocyte line along with identified benchmark regions and high-confidence SV calls.We established a high-confidence SV callset with 8938 SVs by integrating four alignment-based SV callers,including 109x Pacific Biosciences(PacBio)continuous long reads(CLRs),22 x PacBio circular consensus sequencing(CCS)reads,104x Oxford Nanopore Technologies(ONT)long reads,and 114×Bionano optical mapping plat-form,and one de novo assembly-based SV caller using CCS reads.A total of 544 randomly selected SVs were validated by PCR amplification and Sanger sequencing,demonstrating the robustness of our SV calls.Combining trio-binning-based haplotype assemblies,we established an SV benchmark for identifying false negatives and false positives by constructing the continuous high-confidence regions(CHCRs),which covered 1.46 gigabase pairs(Gb)and 6882 SVs supported by at least one diploid haplotype assembly.Establishing high-confidence SV calls for a benchmark sample that has been characterized by multiple technologies provides a valuable resource for investigating SVs in human biology,disease,and clinical research.

Implant dentures have become the main method for the treatment of dentition defects or complete edentulism. However, due to the lack of periodontal ligament and periodontal ligament proprioceptors, implant dentures have very limited cushioning and sensing capabilities and are prone to occlusal overload. As a risk factor for peri-implantitis, occlusal overload seriously threatens the stability and success rate of implant dentures. This paper reviews the occlusal overload of implant dentures, the causal relationship between occlusal overload and plaque biofilms in peri-implantitis, the mechanism by which occlusal overload promotes peri-implantitis, and the effect of reasonable clinical occlusal adjustment on healing. This review shows that occlusal overload is closely related to the occurrence of peri-implantitis. Occlusal overload can promote the process of peri-implantitis by increasing the release of inflammatory factors and mechanical transduction mechanisms. The intervention of the patients’ bad bite habits and occlusal adjustment can promote the healing of peri-implantitis. At present, there is no uniform standard ideal experimental model for occlusal overload. The phenomenon and mechanism of bone resorption around the implant caused by overload force still need further observation and research, which will help determine the intensity, direction and timing of occlusal loading to guide clinical occlusal adjustment.