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In order to investigate the potential risk of organic pollutants in coal mining water, the persistence, bioaccumulation and toxicity of known organic pollutants in coal mining water were systematically simulated and assessed by using EPI Suite and toxicolgical data, and the analytic hierarchy process (AHP) was used to establish an evaluation system for priority organic pollutants in coal mining water based on two primary indexes and seven secondary indicators of toxic and environmental effects. The results showed that: ① there were 13 persistent persistent substances, 8 bioaccumulative substances and 1 toxic substances among 54 organic pollutants, halgenated hydrocarbons have the strongest persistence, polycyclic aromatic hydrocarbons have the strongest bioaccumulation, and the general trend of reaction rate with hydroxyl radicals (OH•) is as follows: ether>esters>halgenated hydrocarbons; aliphatic>aromatic. (Short-chain halgenated) aliphatic compounds have no bioaccumulative substances, and the bioaccumulation of polycyclic aromatic hydrocarbons is generally high, moreover, there were 4 or more benzene rings in the molecular structure of the bioaccumulative ones, and the increase in the number of benzene rings would lead to the enhancement of the bioaccumulation of polycyclic aromatic hydrocarbons. Triphenyl phosphate is a significant toxic substance, which needs to be focused on during coal mining water treatment. ② The 20 organic pollutants with the higher comprehensive score were screened out as priority pollutants in coal mining water, among which dichloromethane, 1,2-dichloroethane, toluene, dibutyl phthalate, di(2-ethylhexyl) phthalate, naphthalene, benzo [a] pyrene, dibenzo [a, h] anthracene, benzo [b] fluoranthracene, benzo [k] fluoranthracene and benzo [a] anthracene have the characteristics of emerging contaminants, however, the level of organic pollutants detected in coal mining water is insufficient to pose risks to human health and ecolgical environment presently, but with the implementation of national policies and the increase in demand for high-quality treatment and utilization of coal mining water. The control of organic pollutants in coal mining water will become an realistic demand for the protection and utilization of regional water resources, and the potential risk assessment system of priority organic pollutants constructed in this study can be used to screen out priority pollutants in coal mining water, and provide a theoretical basis for the future control of organic pollutants.

Abstract Background Sarcopenia is characterized by loss of skeletal muscle mass and function, and is a major risk factor for disability and independence in the elderly. Effective medication is not available. Dietary restriction (DR) has been found to attenuate aging and aging‐related diseases, including sarcopenia, but the mechanism of both DR and sarcopenia are incompletely understood. Methods In this study, mice body weight, fore and all limb grip strength, and motor learning and coordination performance were first analysed to evaluate the DR effects on muscle functioning. Liquid chromatography–mass spectrometry (LC–MS) was utilized for the metabolomics study of the DR effects on sarcopenia in progeroid DNA repair‐deficient Ercc1∆/− and Xpg−/− mice, to identify potential biomarkers for attenuation of sarcopenia. Results Muscle mass was significantly (P

Alzheimer's disease (AD) is the most common global dementia and is universally fatal. Most late-stage AD disease-modifying therapies are intravenous and target amyloid beta (Aβ), with only modest effects on disease progression: there remains a high unmet need for convenient, safe, and effective therapeutics. Senescent cells (SC) and the senescence-associated secretory phenotype (SASP) drive AD pathology and increase with AD severity. Preclinical senolytic studies have shown improvements in neuroinflammation, tau, Aβ, and CNS damage; most were conducted in transgenic rodent models with uncertain human translational relevance. In this study, aged cynomolgus monkeys had significant elevation of biomarkers of senescence, SASP, and neurological damage. Intermittent treatment with the senolytic navitoclax induced modest reversible thrombocytopenia; no serious drug-related toxicity was noted. Navitoclax reduced several senescence and SASP biomarkers, with CSF concentrations sufficient for senolysis. Finally, navitoclax reduced TSPO-PET frontal cortex binding and showed trends of improvement in CSF biomarkers of neuroinflammation, neuronal damage, and synaptic dysfunction. Overall, navitoclax administration was safe and well tolerated in aged monkeys, inducing trends of biomarker changes relevant to human neurodegenerative disease.

The extracellular matrix (ECM) provides structural support for tissues and regulatory signals for resident cells. ECM requires a careful balance between protein accumulation and degradation for homeostasis. Disruption of this balance can lead to pathological processes such as fibrosis in organs across the body. Post-translational crosslinking modifications to ECM proteins such as collagens alter ECM structure and function. Dysregulation of crosslinking enzymes as well as changes in crosslinking composition are prevalent in fibrosis. Because of the crucial roles these ECM crosslinking pathways play in disease, the enzymes that govern crosslinking events are being explored as therapeutic targets for fibrosis. Here, we review in depth the molecular mechanisms underlying ECM crosslinking, how ECM crosslinking contributes to fibrosis, and the therapeutic strategies being explored to target ECM crosslinking in fibrosis to restore normal tissue structure and function.

Objective: This study examined the longitudinal association of perceived stress, ikigai, and having someone one can count on in middle age with the advanced-level functional competency in older age, which is crucial for the maintenance of independent life among older adults. The issue is especially relevant in super-aged countries like contemporary Japan, where more and more older people live in a household consisting only of older people. Methods: Data were collected in 2019 from a total of 1692 retirees of the Aichi Workers’ Cohort Study participants in which baseline survey including psychological factors was conducted during their employment in 2002. Japan Science and Technology Agency Index of Competence (JST-IC) was used to measure the advanced-level functional competency. Multivariable-adjusted odds ratios (ORs) were obtained for having low JST-IC in later life by the degrees of psychological factors reported in the middle age adjusting for the presence of depressive mood in 2019. Results: Those who were not sure about ikigai (OR: 2.02, 95 % CI: 1.33 to 3.08) and who have no one to count on (OR: 2.19, 95 % CI: 1.52 to 3.16) in the middle age were significantly associated with low JST-IC after retirement. Having much stress was significantly inversely associated with a low JST-IC (OR: 0.69, 95 % CI: 0.50 to 0.97). Conclusion: Having ikigai and someone reliable, and stress during middle age might play a role in preventing impaired advanced-level functional competency. Improved ikigai and increased social interaction and support might improve functional competency. Further research might explore avenues for improving ikigai.

BackgroundIn Japan, challenges were reported in accurately estimating the prevalence of schizophrenia among the general population. Retrieving previous studies, we investigated that patients with schizophrenia were more likely to experience poor subjective well-being and various physical, psychiatric, and social comorbidities. These factors might have great potential for precisely classifying schizophrenia cases in order to estimate the prevalence. Machine learning has shown a positive impact on many fields, including epidemiology, due to its high-precision modeling capability. It has been applied in research on mental disorders. However, few studies have applied machine learning technology to the precise classification of schizophrenia cases by variables of demographic and health-related backgrounds, especially using large-scale web-based surveys. ObjectiveThe aim of the study is to construct an artificial neural network (ANN) model that can accurately classify schizophrenia cases from large-scale Japanese web-based survey data and to verify the generalizability of the model. MethodsData were obtained from a large Japanese internet research pooled panel (Rakuten Insight, Inc) in 2021. A total of 223 individuals, aged 20-75 years, having schizophrenia, and 1776 healthy controls were included. Answers to the questions in a web-based survey were formatted as 1 response variable (self-report diagnosed with schizophrenia) and multiple feature variables (demographic, health-related backgrounds, physical comorbidities, psychiatric comorbidities, and social comorbidities). An ANN was applied to construct a model for classifying schizophrenia cases. Logistic regression (LR) was used as a reference. The performances of the models and algorithms were then compared. ResultsThe model trained by the ANN performed better than LR in terms of area under the receiver operating characteristic curve (0.86 vs 0.78), accuracy (0.93 vs 0.91), and specificity (0.96 vs 0.94), while the model trained by LR showed better sensitivity (0.63 vs 0.56). Comparing the performances of the ANN and LR, the ANN was better in terms of area under the receiver operating characteristic curve (bootstrapping: 0.847 vs 0.773 and cross-validation: 0.81 vs 0.72), while LR performed better in terms of accuracy (0.894 vs 0.856). Sleep medication use, age, household income, and employment type were the top 4 variables in terms of importance. ConclusionsThis study constructed an ANN model to classify schizophrenia cases using web-based survey data. Our model showed a high internal validity. The findings are expected to provide evidence for estimating the prevalence of schizophrenia in the Japanese population and informing future epidemiological studies.

Abstract Aim Care for people with schizophrenia is shifting the locus from long‐stay mental hospitals to nonspecialized community‐based settings. Knowledge on the care is not a sole property of psychiatric specialists. Community healthcare workers who do not specialize in psychiatry are recommended to learn more about schizophrenia. This review aimed to summarize recent findings on subjective well‐being and physical, psychiatric, and social comorbidities in individuals with schizophrenia. Methods A literature review was conducted. We retrieved findings from existing systematic reviews and meta‐analyses as our preferred method. When data were not available, we referred to other types of studies. Results As per our review, individuals with schizophrenia demonstrated poor subjective well‐being, happiness, and life satisfaction despite individual differences. Pharmacotherapy caused weight gain and constipation, whereas race and hospitalization might affect weight reduction. Individuals with schizophrenia demonstrated poor oral health, a high prevalence of noncommunicable diseases, and unique eating behaviors. Depression, sleep disorders, smoking, and alcohol and drug consumption were frequently found in the individuals. Research findings regarding problematic internet and smartphone use and stress perception were limited. Low health literacy and neglect of preventable behaviors were frequently seen in individuals with schizophrenia. They tended to be less educated, poor, unemployed, unmarried/unattached, and had poor social cognition, resulting in little social support and a small social network. Conclusion Retrieving recent data, we confirmed that individuals with schizophrenia had poor subjective well‐being and suffer from various physical, psychiatric, and social comorbidities.

Magnesium–lithium alloys are arguably the lightest metal structural materials but have low strength. In order to increase strength, friction stir processing (FSP) is applied to a hot-rolled Mg-10Li-3Al-3Zn (LA103Z) sheet to study the effects on the microstructure and mechanical properties. In this study, the strengthening mechanisms of various FSP regions of an Mg-Li alloy were clarified by a combination of numerical simulation and experimental method. Based on ANSYS APDL, a finite element model with a moving heat source is established. Rotational speeds of 800, 1000, and 1200 rpm and traverse speeds of 100, 110, and 120 mm/min were used in this research. The simulation results confirm that the influence of the rotation speed on the alloy temperature field is greater than that of the travel speed. The temperature of the processing area increases with an increase in rotation speed and decreases with an increase in travel speed. Then, hot-rolled LA103Z alloy plates are processed by FSP. The correspondence between the numerical simulation and experiment was verified by infrared thermography. The results indicate that FSP decreases the grain size significantly for the dynamic recrystallization and dramatic mechanical crushing of the stirring pin. The α-Mg and AlLi are solid soluted in the β-Li matrix. The tensile strength of the processing zone is 260.67 MPa (1000 rpm, 110 mm/min) versus the 170.47 MPa of the base metal. The SZ has the highest microhardness of 77.8 HV (800 rpm, 120 mm/min) and decreases gradually to the BM. The severe deformation, recrystallization, and solid solution of the α-Mg are important factors contributing to the improved mechanical properties.

Background: The job environment has changed a lot during the period of the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to investigate the association between work-related stress and aggravation of pre-existing disease in workers during the first state of COVID-19 emergency in Japan. Methods: Data were obtained from a large internet survey conducted between August 25 and September 30, 2020 in Japan. Participants who reported that they had a job as well as current history of disease(s) (ie, pre-existing conditions) were included (n = 3,090). Aggravation of pre-existing disease during the state of emergency was self-reported. Work-related stress from April 2020 (since the state of COVID-19 emergency) was assessed according to a job demand–control model. Multivariable logistic regression models were used to analyze the association. Results: Aggravation of pre-existing diseases was reported by 334 participants (11%). The numbers of participants with high demand and low control were 112 (18%) and 100 (14%), respectively. Compared to medium demand, high demand was significantly associated with aggravation of pre-existing diseases (odds ratio 1.77; 95% confidence interval, 1.30–2.42). Low control compared to medium control was also significantly associated with aggravation of pre-existing diseases (odds ratio 1.39; 95% confidence interval, 1.02–1.92). Conclusion: Work-related stress during the first state of COVID-19 emergency was associated with aggravation of pre-existing disease during that period.

Objectives: To examine whether public trust was associated with the utilization of COVID-19 Contact Confirming Application (COCOA) in those who self-reported a history of COVID-19. Study design: Cross-sectional study. Methods: Data were obtained from the Japan Society and New Tobacco Internet Survey, a nationwide online survey conducted from February to March 2021, which also assessed items related to COVID-19 and public trust. We included 453 participants with a history of COVID-19. Participants' reports of their general trust in the national government and the related policies, attitudes toward COVID-19 vaccination, and the adherence to the preventive measures against SARS-CoV-2 spread were compared between COCOA users and non-users controlling for age, sex, and socioeconomic statuses by analysis of covariance. Mediation analysis was conducted to examine whether public trust mediates the associations of certain participants’ characteristics with COCOA utilization. Results: Seventy-six percent (344/453) reported the COCOA utilization. Compared to non-users, the users were younger, more likely to be men and had a tendency to have higher education. They were more willing to get COVID-19 vaccination, adherent to public health measures against the spread of the SARS-Cov-2, and more likely to express trust in government in general and policies related to COVID-19 independent of age, sex, and the socioeconomic status. Trust in government did not mediate the associations of age and education with COCOA utilization. Conclusions: The utilization of digital contact tracing technology for the health of public during pandemic was related to the degree of trust in the government in Japan.

The metabolic profiling of a wide range of chemical classes relevant to understanding sarcopenia under conditions in which sample availability is limited, e.g., from mouse models, small muscles, or muscle biopsies, is desired. Several existing metabolomics platforms that include diverse classes of signaling lipids, energy metabolites, and amino acids and amines would be informative for suspected biochemical pathways involved in sarcopenia. The sample limitation requires an optimized sample preparation method with minimal losses during isolation and handling and maximal accuracy and reproducibility. Here, two developed sample preparation methods, BuOH-MTBE-Water (BMW) and BuOH-MTBE-More-Water (BMMW), were evaluated and compared with previously reported methods, Bligh-Dyer (BD) and BuOH-MTBE-Citrate (BMC), for their suitability for these classes. The most optimal extraction was found to be the BMMW method, with the highest extraction recovery of 63% for the signaling lipids and 81% for polar metabolites, and an acceptable matrix effect (close to 1.0) for all metabolites of interest. The BMMW method was applied on muscle tissues as small as 5 mg (dry weight) from the well-characterized, prematurely aging, DNA repair-deficient Ercc1∆/− mouse mutant exhibiting multiple–morbidities, including sarcopenia. We successfully detected 109 lipids and 62 polar targeted metabolites. We further investigated whether fast muscle tissue isolation is necessary for mouse sarcopenia studies. A muscle isolation procedure involving 15 min at room temperature revealed a subset of metabolites to be unstable; hence, fast sample isolation is critical, especially for more oxidative muscles. Therefore, BMMW and fast muscle tissue isolation are recommended for future sarcopenia studies. This research provides a sensitive sample preparation method for the simultaneous extraction of non-polar and polar metabolites from limited amounts of muscle tissue, supplies a stable mouse muscle tissue collection method, and methodologically supports future metabolomic mechanistic studies of sarcopenia.

The aim of the present study was to derive dietary patterns to explain variation in a set of nutrient intakes or in the measurements of waist circumference (WC) and fasting blood glucose (FBG) using reduced rank regression (RRR) and to prospectively investigate these patterns in relation to the risk of developing metabolic syndrome (MetS) and its components during the follow-up. The study participants were comprised of 2944 government employees aged 30–59 years without MetS. RRR was applied with 38 food groups as predictors and with two sets of response variables. The first set included intake of putatively beneficial nutrients, and the first factor retained was named the Healthy Dietary Pattern (HDP). The second one included baseline WC and FBG, and the first factor was named the Unhealthy Dietary Pattern (UHDP). Multivariable Cox proportional hazard model was used to estimate hazard ratio and 95% confidence intervals with adjustments for age, sex, total energy consumption and other potential confounders. During the 5-year median follow-up, we ascertained 374 cases of MetS. The HDP score was inversely associated with the incidence of MetS (p-trend = 0.009) and hypertension (p-trend = 0.002) and marginally significantly associated with elevated triglyceride and decreased high-density lipoprotein cholesterol (p-trend = 0.08). The UHDP score was linearly positively associated with the incidence of MetS and all its components (all p-trend < 0.05). Both the HDP and UHDP predicted the development of MetS and its components.

In this paper, the pain point that cold chain transportation urgently needs for an efficient disinfection method is pointed out. Thus, this work aims at solving the problems and improving the disinfection efficiency in cold chain transportation. While Ultraviolet-C (UVC) irradiation is an effective method by which to kill viruses, it is difficult to apply the commonly used UVC-LED disinfection light source to ice-covered cold chain transportation due to its uneven light field distribution. Thus, the light field regulation of UVC-LED disinfection for cold chain transportation is studied. A UVC-LED chip with a wavelength of 275 nm was used as a light source, and parallel light was obtained by collimating lenses. Then, microlens array homogenization technology was used to shape the UVC light into a uniform light spot, with an energy space uniformity rate of 96.4%. Moreover, a simulation was conducted to compare the effects of the ice layer on the absorption of UVC light. Finally, an experiment was carried out to verify that the disinfection efficiency can be increased nearly by 30% with the proposed system by disinfecting E. coli (Escherichia coli), and the results indicate that the proposed system is an effective disinfection solution during cold chain transportation.