Associations between multiple metals exposure and cognitive function in the middle-aged and older adults from China: A cross-sectional study.

The rapidly rising risk of cognitive decline is a serious challenge for the elderly. As the wide-distributed environmental chemicals, the effects of metals exposure on cognitive function have attracted much attention, but the results remain inclusive. This study aimed to investigate the roles of multiple metals co-exposure on cognition. We included a total of 6112 middle-aged and older participants, detected their plasma levels of 23 metals by using inductively coupled plasma mass spectrometry, and assessed their cognitive function by using the Mini-Mental State Examination (MMSE). The results showed that increased plasma levels of iron (Fe) and zinc (Zn) were positively associated with MMSE score, but the increased levels of nickel (Ni) and lead (Pb) were associated with decreased MMSE score (all FDR < 0.05). Subjects exposed to both high levels of Ni and Pb showed the lowest MMSE score [ß (95% CI) = -0.310 (-0.519, -0.100)], suggesting that Ni and Pb had a synergistic toxic effect on cognitive function. In addition, the hazardous roles of Ni and Pb were mainly found among subjects with low plasma level of Zn, but were not significant among those with high-Zn level [Ni: ß (95% CI) = -0.281 (-0.546, -0.015) vs. -0.146 (-0.351, 0.058); Pb: ß (95% CI) = -0.410 (-0.651, -0.169) vs. -0.060 (-0.275, 0.155)], which suggested that Zn could attenuate the adverse effects of Pb and Ni on cognitive function. The cognitive function was gradually decreased among subjects with increased number of adverse exposures to the above four metals (Ptrend < 0.001). In conclusion, our findings revealed the individual, interactive, and combined effects of Fe, Ni, Pb, and Zn on cognitive function, which may provide new perspectives on cognitive protection, but further prospective cohort studies and biological researches are needed to validate these findings.

Mediation of association between benzo[a]pyrene exposure and lung cancer risk by plasma microRNAs: A Chinese case-control study.

Epidemiologic studies have reported the positive relationship of benzo[a]pyrene (BaP) exposure with the risk of lung cancer. However, the mechanisms underlying the relationship is still unclear. Plasma microRNA (miRNA) is a typical epigenetic biomarker that was linked to environment exposure and lung cancer development. We aimed to reveal the mediation effect of plasma miRNAs on BaP-related lung cancer. We designed a lung cancer case-control study including 136 lung cancer patients and 136 controls, and measured the adducts of benzo[a]pyrene diol epoxide-albumin (BPDE-Alb) and sequenced miRNA profiles in plasma. The relationships between BPDE-Alb adducts, normalized miRNA levels and the risk of lung cancer were assessed by linear regression models. The mediation effects of miRNAs on BaP-related lung cancer were investigated. A total of 190 plasma miRNAs were significantly related to lung cancer status at Bonferroni adjusted P < 0.05, among which 57 miRNAs showed different levels with |fold change| > 2 between plasma samples before and after tumor resection surgery at Bonferroni adjusted P < 0.05. Especially, among the 57 lung cancer-associated miRNAs, BPDE-Alb adducts were significantly related to miR-17-3p, miR-20a-3p, miR-135a-5p, miR-374a-5p, miR-374b-5p, miR-423-5p and miR-664a-5p, which could in turn mediate a separate 42.2%, 33.0%, 57.5%, 36.4%, 48.8%, 32.5% and 38.2% of the relationship of BPDE-Alb adducts with the risk of lung cancer. Our results provide non-invasion biomarker candidates for lung cancer, and highlight miRNAs dysregulation as a potential intermediate mechanism by which BaP exposure lead to lung tumorigenesis.

Multiple metals exposure and blood mitochondrial DNA copy number: A cross-sectional study from the Dongfeng-Tongji cohort.

OBJECTIVE: Mitochondria are essential organelles that execute fundamental biological processes, while mitochondrial DNA is vulnerable to environmental insults. The aim of this study was to investigate the individual and mixture effect of plasma metals on blood mitochondria DNA copy number (mtDNAcn). METHODS: This study involved 1399 randomly selected subcohort participants from the Dongfeng-Tongji cohort. The blood mtDNAcn and plasma levels of 23 metals were determined by using quantitative real-time polymerase chain reaction (qPCR) and inductively coupled plasma mass spectrometer (ICP-MS), respectively. The multiple linear regression was used to explore the association between each metal and mtDNAcn, and the LASSO penalized regression was performed to select the most significant metals. We also used the quantile g-computation analysis to assess the mixture effect of multiple metals. RESULTS: Based on multiple linear regression models, each 1% increase in plasma concentration of copper (Cu), rubidium (Rb), and titanium (Ti) was associated with a separate 0.16% [ß(95% CI) = 0.158 (0.066, 0.249), P = 0.001], 0.20% [ß(95% CI) = 0.196 (0.073, 0.318), P = 0.002], and 0.25% [ß(95% CI) = 0.245 (0.081, 0.409), P = 0.003] increase in blood mtDNAcn. The LASSO regression also confirmed Cu, Rb, and Ti as significant predictors for mtDNAcn. There was a significant mixture effect of multiple metals on increasing mtDNAcn among the elder participants (aged ≥65), with an approximately 11% increase in mtDNAcn for each quartile increase in all metal concentrations [ß(95% CI) = 0.146 (0.048, 0.243), P = 0.004]. CONCLUSIONS: Our results show that plasma Cu, Rb and Ti were associated with increased blood mtDNA, and we further revealed a significant mixture effect of all metals on mtDNAcn among elder population. These findings may provide a novel perspective on the effect of metals on mitochondrial dysfunction.

Multiscale Feature Fusion and Semi-Supervised Temporal-Spatial Learning for Performance Monitoring in the Flotation Industrial Process.

This article studies the performance monitoring problem for the potassium chloride flotation process, which is a critical component of potassium fertilizer processing. To address its froth image segmentation problem, this article proposes a multiscale feature extraction and fusion network (MsFEFNet) to overcome the multiscale and weak edge characteristics of potassium chloride flotation froth images. MsFEFNet performs simultaneous feature extraction at multiple image scales and automatically learns spatial information of interest at each scale to achieve efficient multiscale information fusion. In addition, the potassium chloride flotation process is a multistage dynamic process with massive unlabeled data. To overcome its dynamic time-varying and working condition spatial similarity characteristics, a semi-supervised froth-grade prediction model based on a temporal-spatial neighborhood learning network combined with Mean Teacher (MT-TSNLNet) is proposed. MT-TSNLNet designs a new objective function for learning the temporal-spatial neighborhood structure of data. The introduction of Mean Teacher can further utilize unlabeled data to promote the proposed prediction model to better track the concentrate grade. To verify the effectiveness of the proposed MsFEFNet and MT-TSNLNet, froth image segmentation and grade prediction experiments are performed on a real-world potassium chloride flotation process dataset.

Associations of ambient air pollution exposure and lifestyle factors with incident dementia in the elderly: A prospective study in the UK Biobank.

OBJECTIVE: Dementia is an important disease burden among the elderly, and its occurrence may be profoundly affected by environmental factors. Evidence of the relationship between air pollution and dementia is emerging, but the extent to which this can be offset by lifestyle factors remains ambiguous. METHODS: This study comprised 155,828 elder adults aged 60 years and above in the UK Biobank who were dementia-free at baseline. Cox proportional hazard models were conducted to examine the associations of annual average levels of air pollutants in 2010, including nitrogen dioxide (NO2), nitrogen oxides (NOX), particulate matter (PM2.5, PM10, and PMcoarse) and lifestyle factors recorded at baseline [physical activity (PA), sleep patterns, or smoking status] with incident risk of dementia, and their interactions on both multiplicative and additive scales. RESULTS: During a 12-year period of follow-up, 4,389 incidents of all-cause dementia were identified. For each standarddeviationincrease in ambient NO2, NOX or PM2.5, all-cause dementia risk increases by 1.07-fold [hazard ratio (HR) and 95 % confidence interval (CI) = 1.07 (1.04, 1.10)], 1.05-fold (95 % CI: 1.02, 1.08) and 1.07-fold (95 % CI: 1.04, 1.10), whereas low levels of PA, poor sleep patterns, and smoking are associated with an elevated risk of dementia [HR (95 % CI) = 1.17 (1.09, 1.26), 1.13 (1.00, 1.27), and 1.14 (1.07, 1.21), respectively]. Furthermore, these air pollutants show joint effects with low PA, poor sleep patterns, and smoking on the onset of dementia. The moderate to high levels of PA could significantly or marginally significantly modify the associations between NO2, NOX or PM2.5 (P-int = 0.067, 0.036, and 0.067, respectively) and Alzheimer's disease (AD), but no significant modification effects are found for sleep patterns or smoking status. CONCLUSION: The increased exposures of NO2, NOX, or PM2.5 are associated with elevated risk of dementia among elderly UK Biobank population. These air pollutants take joint effects with low PA, poor sleep patterns, and smoking on the development of dementia. In addition, moderate to high levels of PA could attenuate the incident risk of AD caused by air pollution. Further prospective researches among other cohort populations are warranted to validate these findings.

DNA methylation aging signatures of multiple metals exposure and their mediation effects in metal-associated mortality: Evidence from the Dongfeng-Tongji cohort study.

Humans were exposed to multiple metals, but the impact of metals on DNA methylation-age (DNAm-age), a well-recognized aging measure, remains inconclusive. This study included 2942 participants from the Dongfeng-Tongji cohort. We detected their plasma concentrations of 23 metals and determined their genome-wide DNA methylation using the Illumina Human-MethylationEPIC BeadChip. Five DNAm-age acceleration indexes (DAIs), including HannumAge-Accel, HorvathAge-Accel, PhenoAge-Accel, GrimAge-Accel (residual from regressing corresponding DNAm-age on chronological age) and DNAm-mortality score (DNAm-MS), were separately calculated. We found that each 1-unit increase in ln-transformed copper (Cu) was associated with a separate 1.02-, 0.83- and 0.07-unit increase in PhenoAge-Accel, GrimAge-Accel, and DNAm-MS (all FDR<0.05). Each 1-unit increase in ln-transformed nickel (Ni) was associated with a 0.34-year increase in PhenoAge-Accel, while each 1-unit increase in ln-transformed strontium (Sr) was associated with a 0.05-unit increase in DNAm-MS. The Cu, Ni and Sr showed joint positive effects on above three DAIs. PhenoAge-Accel, GrimAge-Accel, and DNAm-MS mediated a separate 6.5%, 12.3%, 6.0% of the positive association between Cu and all-cause mortality; GrimAge-Accel mediated 14.3% of the inverse association of selenium with all-cause mortality. Our findings revealed the effects of Cu, Ni, Sr and their co-exposure on accelerated aging and highlighted mediation roles of DNAm-age on metal-associated mortality.

Semi-supervised deep embedded clustering with pairwise constraints and subset allocation.

Semi-supervised deep clustering methods attract much attention due to their excellent performance on the end-to-end clustering task. However, it is hard to obtain satisfying clustering results since many overlapping samples in industrial text datasets strongly and incorrectly influence the learning process. Existing methods incorporate prior knowledge in the form of pairwise constraints or class labels, which not only largely ignore the correlation between these two supervision information but also cause the problem of weak-supervised constraint or incorrect strong-supervised label guidance. In order to tackle these problems, we propose a semi-supervised method based on pairwise constraints and subset allocation (PCSA-DEC). We redefine the similarity-based constraint loss by forcing the similarity of samples in the same class much higher than other samples and design a novel subset allocation loss to precisely learn strong-supervised information contained in labels which consistent with unlabeled data. Experimental results on the two industrial text datasets show that our method can yield 8.2%-8.7% improvement in accuracy and 13.4%-19.8% on normalized mutual information over the state-of-the-art method.

Associations between multiple metals exposure and biological aging: Evidence from the Dongfeng-Tongji cohort.

Aging is related to a progressive decline in physiological functions and is affected by environmental factors. Metal exposures are linked with many health effects, but have poorly understood associations with aging. In this study, a total of 33,916 participants from the Dongfeng-Tongji cohort were included to establish biological age (BA) predictors by using recent advanced algorithms, Klemera and Doubal method (KDM) and Mahalanobis distance. Two biological aging indexes (BAIs), recorded as KDM-accel [the residual from regressing KDM-BA on chronological age] and physiological dysregulation (PD), were separately defined and tested on their associations with mortality by using Cox proportional hazard models. Among 3320 subjects with laboratory determinations of 23 metals in plasma, the individual and overall associations between these metals and BAIs were evaluated by using multiple-linear regression and weighted quantile sum (WQS) models. Both BAIs were prospectively associated with all-cause mortality among the whole participants [KDM-accel: HR(95%CI) = 1.23(1.18, 1.29); PD: HR(95%CI) = 1.37(1.31, 1.42)]. Each 1-unit increment in ln-transformed strontium and molybdenum were cross-sectionally associated with a separate 0.71- and 0.34-year increase in KDM-accel, and each 1 % increment in copper, rubidium, strontium, cobalt was cross-sectionally associated with a separate 0.10 %, 0.10 %, 0.09 %, 0.02 % increase in PD (all FDR < 0.05). The WQS models observed mixture effects of multi-metals on aging, with a 0.20-year increase in KDM-accel and a 0.04 % increase in PD for each quartile increase in ln-transformed concentrations of all metals [KDM-accel: ß(95%CI) = 0.20(0.08, 0.32); PD: ß(95%CI) = 0.04(0.02, 0.06)]. Our findings revealed that plasma strontium, molybdenum, copper, rubidium and cobalt were associated with accelerated aging. Multi-metals exposure showed mixture effects on the aging process, which highlights potential preventative interventions.

Amplification-driven BCL6-suppressed cytostasis is mediated by transrepression of FOXO3 and post-translational modifications of FOXO3 in urinary bladder urothelial carcinoma.

Muscle-invasive urinary bladder urothelial carcinoma (UBUC) is a lethal disease for which effective prognostic markers and potential therapy targets are still lacking. Previous array comparative genomic hybridization identified that 3q27 is frequently amplified in muscle-invasive UBUCs, one candidate proto-oncogene, B-cell CLL/lymphoma 6 (BCL6), mapped to this region. We therefore aimed to explore its downstream targets and physiological roles in UBUC progression. Methods: Specimens from UBUC patients, NOD/SCID mice and several UBUC-derived cell lines were used to perform quantitative RT-PCR, fluorescence in situ hybridization immunohistochemistry, xenograft, gene stable overexpression/knockdown and a series of in vitro experiments. Results: Amplification of the BCL6 gene lead to upregulation of BCL6 mRNA and protein levels in a substantial set of advanced UBUCs. High BCL6 protein level significantly predicted poor disease-specific and metastasis-free survivals. Knockdown of the BCL6 gene in J82 cells inhibited tumor growth and enhanced apoptosis in the NOD/SCID xenograft model. In vitro experiments demonstrated that BCL6 inhibited cytostasis, induced cell migration, invasion along with alteration of the expression levels of several related regulators. At molecular level, BCL6 inhibited forkhead box O3 (FOXO3) transcription, subsequent translation and upregulation of phosphorylated/inactive FOXO3 through phosphoinositide 3-kinase (PI3K)/AKT serine/threonine kinase (AKT) and/or epidermal growth factor receptor (EGFR)/mitogen-activated protein kinase 1/2 (MAP2K1/2) signaling pathway(s). Two BCL6 binding sites on the proximal promoter region of the FOXO3 gene were confirmed. Conclusion: Overexpression of BCL6 served a poor prognostic factor in UBUC patients. In vivo and in vitro studies suggested that BCL6 functions as an oncogene through direct transrepression of the FOXO3 gene, downregulation and phosphorylation of the FOXO3 protein.

Chlorobenzene degradation by electro-heterogeneous catalysis in aqueous solution: intermediates and reaction mechanism.

This study was performed to investigate the variables that influence chlorobenzene (CB) degradation in aqueous solution by electro-heterogeneous catalysis. The effects of current density, pH, and electrolyte concentration on CB degradation were determined. The degradation efficiency of CB was almost 100% with an initial CB concentration of 50 mg/L, current density 15 mA/cm2, initial pH 10, electrolyte concentration 0.1 mol/L, and temperature 25 degrees C after 90 min of reaction. Under the same conditions, the degradation efficiency of CB was only 51% by electrochemical (EC) process, which showed that electro-heterogeneous catalysis was more efficient than EC alone. The analysis results of Purge-and-Trap chromatography-mass spectrometry (P&T/GC/MS) and ion chromatography (IC) indicated that in the reaction process, the initial *OH attack could occur at the C-Cl bond of CB, yielding phenol and biphenyl with the release of Cl-. Further oxidation of phenol and biphenyl produced p-Vinylbenzoic acid and hydroquinol. Finally, the compounds were oxidized to butenedioic acid and other small-molecule acids.