Background Previous studies have shown that bisphenol A exposure is associated with the risk of hypertension; however, most of them are cross-sectional and the conclusions are not consistent. Objective To evaluate the association between bisphenol A exposure and the incident risk of hypertension. Methods Based on a nested case-control design involving 1990 subjects derived from the Dongfeng-Tongji cohort, a total of 1080 subjects were included in this study after excluding 887 hypertensive cases at baseline and 23 subjects with missing blood pressure data in follow-up visits. Epidemiological information was collected through questionnaire survey, and serum bisphenol A concentration was detected by high performance liquid chromatography tandem mass spectrometry. Logistic regression model was used to analyze the potential association between serum bisphenol A level and the risk of hypertension incidence, and linear regression model was used to analyze the association between serum bisphenol A level and blood pressure changes between baseline and follow-up. Results The average age of the 1 080 participants was (62.03±7.45) years, of which 41.1% were male. During the follow-up period, a total of 477 (44.2%) developed hypertension. The median serum concentration of bisphenol A in the total population was 3.15 μg·L⁻¹, and the baseline bisphenol A concentration in the new case group (3.24 μg·L⁻¹) was higher than that in the control group (2.98 μg·L⁻¹) (P<0.05). After adjustment for selected covariates, the risk of hypertension increased by 12% (OR=1.12, 95%CI: 1.02, 1.22) for each unit increase in naturally log-transformed bisphenol A; the systolic blood pressure and diastolic blood pressure increased by 1.88 (95%CI: 1.08, 2.69) mmHg and 1.14 (95%CI: 0.68, 1.61) mmHg, respectively. Compared with the low bisphenol A tertile group, the risk of hypertension in the middle tertile and high tertile groups increased by 39% (OR=1.39, 95%CI: 1.01, 1.91) and 40% (OR=1.40, 95%CI: 1.02, 1.93) respectively; the systolic blood pressure increased by 5.91 (95%CI: 3.06, 8.76) mmHg and 5.71 (95%CI: 2.82, 8.59) mmHg, and the diastolic blood pressure increased by 3.09 (95%CI: 3.06, 8.59) mmHg and 2.89 (95%CI: 1.22, 4.57) mmHg, respectively (P_trend<0.001). A positive association between serum bisphenol A level and hypertension was found among those who were female, never/former smokers, never/former drinkers, without family history of hypertension, with physical exercise, and with prehypertension at baseline (P_trend<0.05). There was no interaction between selected stratified variables and bisphenol A levels on hypertension (P_interaction>0.05). Conclusion Bisphenol A exposure is positively associated with the risk of hypertension.

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.

Objective To address the quality problems caused by high porosity in the preparation of dental cobalt-chrome alloy prosthetics based on selective laser melting(SLM)technology,we investigated the influence mechanism of different forming process parameters on the microstructure and properties of the materials.Moreover,the range of form-ing process parameters that can effectively reduce defects was precisely defined.Methods The effects of laser power,scanning speed,and scanning distance on the pore properties,surface roughness,and hardness of dental cobalt-chrome al-loy were investigated by adjusting the printing parame-ters in the process of SLM.Through metallographic anal-ysis,image analysis,and molten pool simulation,the pore formation mechanism was revealed,and the relation-ship between the porosity and energy density of SLM dental cobalt-chrome alloy was elucidated.Results When the linear energy density was higher than 0.18 J/mm,the po-rosity defect easily appeared at the bottom of the molten pool.When the laser energy density was lower than 0.13 J/mm,defects occurred in the gap of the molten pool due to insufficient melting of powder.In particular,when the linear energy density exceeded the threshold of 0.30 J/mm or was below 0.12 J/mm,the porosity increased significantly to more than 1%.In addition,we observed a negative correlation between free surface roughness and energy density and an inverse re-lationship between macroscopic hardness and porosity.Conclusion On the basis of the conditions of raw materials and molding equipment used in this study,the key process parameters of SLM of molding parts with porosity lower than 1%were successfully determined.Specifically,these key parameters included the line energy density,which ranged from 0.13 J/mm to 0.30 J/mm,and the scan spacing should be strictly controlled below 90 μm.

miR-135 is a highly conserved miRNA in mammals and includes miR-135a and miR-135b.Recent studies have shown that miR-135b is a key regulatory factor in cardio-cerebrovascular diseases.It is involved in regulating the pathological process of myocardial infarction,myocardial ischemia/reperfusion injury,cardiac hypertrophy,atrial fibrillation,diabetic cardiomyopathy,atherosclerosis,pulmonary hyperten-sion,cerebral ischemia/reperfusion injury,Parkinson's disease,and Alzheimer's disease.Obviously,miR-135b is an emerging player in cardio-cerebrovascular diseases and is expected to be an important target for the treatment of cardio-cerebrovascular diseases.However,the crucial role of miR-135b in cardio-cerebrovascular diseases and its underlying mechanism of action has not been reviewed.Therefore,in this review,we aimed to comprehensively summarize the role of miR-135b and the signaling pathway mediated by miR-135b in cardio-cerebrovascular diseases.Drugs targeting miR-135b for the treatment of diseases and related patents,highlighting the importance of this target and its utility as a therapeutic target for cardio-cerebrovascular diseases,have been discussed.

In order to develop a positive quality control products for the detection of porcine repro-ductive and respiratory syndrome virus(PRRSV)nucleic acid by real-time fluorescent quantitative PCR(RT-qPCR),the positive quality control products of PRRSV-1 and PRRSV-2 M genes were prepared using armored RNA technology of MS2 phage.PRRSV-1 and PRRSV-2 M genes were amplified,purified and recovered,and ligated into pET28b vector containing MS2 mature enzyme protein gene and capsid protein.After transformed into BL21(DE3),the gene products were in-duced by IPTG and purified by PEG6000 precipitation method to prepare the armored RNA virus-like particles(AR-PRRSV)containing PRRSV M gene.Following the performance evaluation,as the positive quality control products of PRRSV-1 and PRRSV-2 M genes,AR-PRRSV1M and AR-PRRSV2M were calculated using YY/T 1652-2019 standard.Results showed that it had a good u-niformity,stable storage for the armored virus-like particles at-20,4,25 ℃ for 60 d,and 37 ℃ for 30 d.The prepared armored virus-like particles AR-PRRSV1M and AR-PRRSV2M were deter-mined by digital quantitative PCR(ddPCR)after preliminary quantification by RT-qPCR.The 104 copies/μL of AR-PRRSV1M and AR-PRRSV2M ddPCR fixation was(1.33+0.50)× 104 cop-ies/μL.The above results indicates that the AR-PRRSVM can be used as the quality control of the whole detection process(nucleic acid extraction,reverse transcription and RT-qPCR).

BACKGROUND: B-cell maturation antigen (BCMA)-directed chimeric antigen receptor T (CAR-T) therapy yield remarkable responses in patients with relapsed/refractory multiple myeloma (R/RMM). Circulating tumor DNA (ctDNA) reportedly exhibits distinct advantages in addressing the challenges posed by tumor heterogeneity in the distribution and genetic variations in R/RMM. METHODS: Herein, the ctDNA of 108 peripheral blood plasma samples from patients with R/RMM was thoroughly investigated before administration of anti-BCMA CAR-T therapy to establish its predictive potential. Flow cytometry is used primarily to detect subgroups of T cells or CAR-T cells. RESULTS: In this study, several tumor and T cell effector-mediated factors were considered to be related to treatment failure by an integrat analysis, including higher percentages of multiple myeloma (MM) cells in the bone marrow (P = 0.013), lower percentages of CAR-T cells in the peripheral blood at peak (P = 0.037), and higher percentages of CD8+ T cells (P = 0.034). Furthermore, there is a substantial correlation between high ctDNA level (>143 ng/mL) and shorter progression-free survival (PFS) (P = 0.007). Multivariate Cox regression analysis showed that high levels of ctDNA (>143 ng/mL), MM-driven high-risk mutations (including IGLL5 [P = 0.004], IRF4 [P = 0.024], and CREBBP [P = 0.041]), number of multisite mutations, and resistance-related mutation (ERBB4, P = 0.040) were independent risk factors for PFS. CONCLUSION: Finally, a ctDNA-based risk model was built based on the above independent risk factors, which serves as an adjunct non-invasive measure of substantial tumor burden and a prognostic genetic feature that can assist in predicting the response to anti-BCMA CAR-T therapy. REGISTERATION Chinese Clinical Trial Registry (ChiCTR2100046474) and National Clinical Trial (NCT04670055, NCT05430945).

Urate oxidase (Uox) plays a pivotal role in uric acid (UA) degradation, and it has been applied in controlling serum UA level in clinical treatment of hyperuricemia (HUA). However, because Uox is a heterogenous protein to the human body, the immune rejections typically occur after intravenous administration, which greatly hampers the application of Uox-based agents. In this study, we used Lactococcus lactis NZ9000, a food-grade bacterium, as a host to express exogenous Uox genes, to generate the Uox-expressing engineered strains to treat HUA. Aspergillus flavus-derived Uox (aUox) and the "resurrected" human-derived Uox (hUox) were cloned into vector and expressed in NZ9000, to generate engineered strains, respectively. The engineered NZ9000 strains were confirmed to express Uox and showed UA-lowering activity in a time-dependent manner in vitro. Next, in an HUA mice model established by oral gavage of yeast paste, the UA levels were increased by 85.4% and 106.2% at day 7 and day 14. By contrast, in mice fed with NZ9000-aUox, the UA levels were increased by 39.5% and 48.3% while in mice fed with NZ9000-hUox were increased by 57.0% and 82.9%, suggesting a UA-lowering activity of both engineered strains. Furthermore, compared with allopurinol, the first-line agent for HUA treatment, mice fed with NZ9000-aUox exhibited comparable liver safety but better kidney safety than allopurinol, indicating that the use of engineered NZ9000 strains not only alleviated kidney injury caused by HUA, but could also avoided the risk of kidney injury elicited by using allopurinol. Collectively, our study offers an effective and safe therapeutic approach for HUA long-term treatment and controlling.
Animals ; Lactococcus lactis/metabolism* ; Urate Oxidase/genetics* ; Mice ; Uric Acid/blood* ; Hyperuricemia ; Humans ; Administration, Oral ; Aspergillus flavus/genetics* ; Male

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.

OBJECTIVES: This study aimed to analyze the bacteria in dental caries and establish an optimized dental-ca-ries diagnosis model based on 16S ribosomal RNA (rRNA) data of oral flora. METHODS: We searched the public databa-ses of microbiomes including NCBI, MG-RAST, EMBL-EBI, and QIITA and collected data involved in the relevant research on human oral microbiomes worldwide. The samples in the caries dataset (1 703) were compared with healthy ones (20 540) by using the microbial search engine (MSE) to obtain the microbiome novelty score (MNS) and construct a caries diagnosis model based on this index. Nonparametric multivariate ANOVA was used to analyze and compare the impact of different host factors on the oral flora MNS, and the model was optimized by controlling related factors. Finally, the effect of the model was evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS: 1) The oral microbiota distribution obviously differed among people with various oral-health statuses, and the species richness and species diversity index decreased. 2) ROC curve was used to evaluate the caries data set, and the area under ROC curve was AUC=0.67. 3) Among the five hosts' factors including caries status, country, age, decayed missing filled tooth (DMFT) indices, and sampling site displayed the strongest effect on MNS of samples (P=0.001). 4) The AUC of the model was 0.87, 0.74, 0.74, and 0.75 in high caries, medium caries, low caries samples in Chinese children, and mixed dental plaque samples after controlling host factors, respectively. CONCLUSIONS The model based on the analysis of 16S rRNA data of oral flora had good diagnostic efficiency.
Humans ; Child ; Bacteria/genetics* ; Dental Caries/microbiology* ; Dental Caries Susceptibility ; Microbiota/genetics* ; RNA, Ribosomal, 16S