Outdoor Light at Night, Air Pollution, and Risk of Cerebrovascular Disease: A Cohort Study in China.

BACKGROUND: We sought to explore the associations of outdoor light at night (LAN) and air pollution with the risk of cerebrovascular disease (CeVD). METHODS: We included a total of 28 302 participants enrolled in Ningbo, China from 2015 to 2018. Outdoor LAN and air pollution were assessed by Satellite-derived images and land-use regression models. CeVD cases were confirmed by medical records and death certificates and further subdivided into ischemic and hemorrhagic stroke. Cox proportional hazard models were used to estimate hazard ratios and 95% CIs. RESULTS: A total of 1278 CeVD cases (including 777 ischemic and 133 hemorrhagic stroke cases) were identified during 127 877 person-years of follow-up. In the single-exposure models, the hazard ratios for CeVD were 1.17 (95% CI, 1.06-1.29) for outdoor LAN, 1.25 (1.12-1.39) for particulate matter with an aerodynamic diameter ≤2.5 µm, 1.14 (1.06-1.22) for particulate matter with aerodynamic diameter ≤10 µm, and 1.21 (1.06-1.38) for NO2 in every interquartile range increase. The results were similar for ischemic stroke, whereas no association was observed for hemorrhagic stroke. In the multiple-exposure models, the associations of outdoor LAN and PM with CeVD persisted but not for ischemic stroke. Furthermore, no interaction was observed between outdoor LAN and air pollution. CONCLUSIONS: Levels of exposure to outdoor LAN and air pollution were positively associated with the risk of CeVD. Furthermore, the detrimental effects of outdoor LAN and air pollution might be mutually independent.

Age at diagnosis modifies associations of type 2 diabetes with cancer incidence and mortality: a retrospective matched-cohort study.

AIMS/HYPOTHESIS: The age-specific associations between type 2 diabetes and cancer risk are not fully understood. The aim of this study was to assess how age at diagnosis modifies the associations between type 2 diabetes and cancer risk. METHODS: We used data from the Yinzhou Health Information System, and included 42,279 individuals who were newly diagnosed with type 2 diabetes between 2010 and 2014, as well as 166,010 age- and sex-matched control individuals without diabetes who were selected randomly from the electronic health records of the entire population. Patients were divided into four age groups according to age at diagnosis: <50, 50-59, 60-69 and ≥70 years. Stratified Cox proportional hazards regression models, with age as the time scale, were used to estimate the HRs and 95% CIs for the associations of type 2 diabetes with the risks of overall and site-specific cancers. Population-attributable fractions were also calculated for outcomes associated with type 2 diabetes. RESULTS: During median follow-up periods of 9.20 and 9.32 years, we identified 15,729 incident cancer cases and 5383 cancer deaths, respectively. Patients diagnosed with type 2 diabetes before 50 years of age had the highest relative risks of cancer incidence and mortality, with HRs (95% CI) of 1.35 (1.20, 1.52) for overall cancer incidence, 1.39 (1.11, 1.73) for gastrointestinal cancer incidence, 2.02 (1.50, 2.71) for overall cancer mortality, and 2.82 (1.91, 4.18) for gastrointestinal cancer mortality. Risk estimates decreased gradually with each decade increase in diagnostic age. The population-attributable fractions for overall cancer and gastrointestinal cancer mortality also decreased with increasing age. CONCLUSIONS/INTERPRETATION: The associations of type 2 diabetes with cancer incidence and mortality varied by age at diagnosis, with a higher relative risk among patients who were diagnosed at a younger age.

Somatic Mutations in UBA1 and Severe Adult-Onset Autoinflammatory Disease.

BACKGROUND: Adult-onset inflammatory syndromes often manifest with overlapping clinical features. Variants in ubiquitin-related genes, previously implicated in autoinflammatory disease, may define new disorders. METHODS: We analyzed peripheral-blood exome sequence data independent of clinical phenotype and inheritance pattern to identify deleterious mutations in ubiquitin-related genes. Sanger sequencing, immunoblotting, immunohistochemical testing, flow cytometry, and transcriptome and cytokine profiling were performed. CRISPR-Cas9-edited zebrafish were used as an in vivo model to assess gene function. RESULTS: We identified 25 men with somatic mutations affecting methionine-41 (p.Met41) in UBA1, the major E1 enzyme that initiates ubiquitylation. (The gene UBA1 lies on the X chromosome.) In such patients, an often fatal, treatment-refractory inflammatory syndrome develops in late adulthood, with fevers, cytopenias, characteristic vacuoles in myeloid and erythroid precursor cells, dysplastic bone marrow, neutrophilic cutaneous and pulmonary inflammation, chondritis, and vasculitis. Most of these 25 patients met clinical criteria for an inflammatory syndrome (relapsing polychondritis, Sweet's syndrome, polyarteritis nodosa, or giant-cell arteritis) or a hematologic condition (myelodysplastic syndrome or multiple myeloma) or both. Mutations were found in more than half the hematopoietic stem cells, including peripheral-blood myeloid cells but not lymphocytes or fibroblasts. Mutations affecting p.Met41 resulted in loss of the canonical cytoplasmic isoform of UBA1 and in expression of a novel, catalytically impaired isoform initiated at p.Met67. Mutant peripheral-blood cells showed decreased ubiquitylation and activated innate immune pathways. Knockout of the cytoplasmic UBA1 isoform homologue in zebrafish caused systemic inflammation. CONCLUSIONS: Using a genotype-driven approach, we identified a disorder that connects seemingly unrelated adult-onset inflammatory syndromes. We named this disorder the VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) syndrome. (Funded by the NIH Intramural Research Programs and the EU Horizon 2020 Research and Innovation Program.).

Rivaroxaban versus nadroparin for thromboprophylaxis following thoracic surgery for lung cancer: A randomized, noninferiority trial.

The benefit of rivaroxaban in thromboprophylaxis after oncologic lung surgery remains unknown. To evaluate the efficacy and safety of rivaroxaban, patients who underwent thoracic surgery for lung cancer were enrolled, and randomly assigned to rivaroxaban or nadroparin groups in a 1:1 ratio; anticoagulants were initiated 12-24 h after surgery and continued until discharge. Four hundred participants were required according to a noninferiority margin of 2%, assuming venous thromboembolism (VTE) occurrence rates of 6.0% and 12.6% for patients in the rivaroxaban and nadroparin groups, respectively. The primary efficacy outcome was any VTE during the treatment and 30-day follow-up periods. The safety outcome was any on-treatment bleeding event. Finally, 403 patients were randomized (intention-to-treat [ITT] population), with 381 included in per-protocol (PP) population. The primary efficacy outcomes occurred in 12.5% (25/200) of the rivaroxaban group and 17.7% (36/203) of the nadroparin group (absolute risk reduction, -5.2%; 95% confidence interval [CI], [-12.2-1.7]), indicating the noninferiority of rivaroxaban in ITT population. Sensitivity analysis was performed in the PP population and yielded similar results, confirming the noninferiority of rivaroxaban. In the safety analysis population, the incidence of any on-treatment bleeding events did not differ significantly between the groups (12.2% for rivaroxaban vs. 7.0% for nadroparin; relative risk [RR], 1.9; 95% CI, [0.9-3.7]; p = .08), including major bleeding (9.7% vs. 6.5%; RR, 1.6 [95% CI, 0.9-3.7]; p = .24), and nonmajor bleeding (2.6% vs. 0.5%; RR, 5.2 [95% CI, 0.6-45.2]; p = .13). Rivaroxaban for thromboprophylaxis after oncologic lung surgery was shown to be noninferior to nadroparin.

Prediction Model for Sensory Perception Abnormality in Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by heterogeneous clinical phenotypes. Patients often experience abnormal sensory perception, which may further affect the ASD core phenotype, significantly and adversely affecting their quality of life. However, biomarkers for the diagnosis of ASD sensory perception abnormality are currently elusive. We sought to identify potential biomarkers related to ASD sensory perception abnormality to construct a prediction model that could facilitate the early identification of and screening for ASD. Differentially expressed genes in ASD were obtained from the Gene Expression Omnibus database and were screened for genes related to sensory perception abnormality. After enrichment analysis, the random forest method was used to identify disease-characteristic genes. A prediction model was constructed with an artificial neural network. Finally, the results were validated using data from the dorsal root ganglion, cerebral cortex, and striatum of the BTBR T+ Itpr3tf/J (BTBR) ASD mouse model. A total of 1869 differentially expressed genes in ASD were screened, among which 16 genes related to sensory perception abnormality were identified. According to enrichment analysis, these 16 genes were mainly related to actin, cholesterol metabolism, and tight junctions. Using random forest, 15 disease-characteristic genes were screened for model construction. The area under the curve of the training set validation result was 0.999, and for the model function validation, the result was 0.711, indicating high accuracy. The validation of BTBR mice confirmed the reliability of using these disease-characteristic genes for prediction of ASD. In conclusion, we developed a highly accurate model for predicting ASD sensory perception abnormality from 15 disease-characteristic genes. This model provides a new method for the early identification and diagnosis of ASD sensory perception abnormality.

Proteomic-Based Approach Reveals the Involvement of Apolipoprotein A-I in Related Phenotypes of Autism Spectrum Disorder in the BTBR Mouse Model.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder. Abnormal lipid metabolism has been suggested to contribute to its pathogenesis. Further exploration of its underlying biochemical mechanisms is needed. In a search for reliable biomarkers for the pathophysiology of ASD, hippocampal tissues from the ASD model BTBR T+ Itpr3tf/J (BTBR) mice and C57BL/6J mice were analyzed, using four-dimensional (4D) label-free proteomic analysis and bioinformatics analysis. Differentially expressed proteins were significantly enriched in lipid metabolic pathways. Among them, apolipoprotein A-I (ApoA-I) is a hub protein and its expression was significantly higher in the BTBR mice. The investigation of protein levels (using Western blotting) also confirmed this observation. Furthermore, expressions of SphK2 and S1P in the ApoA-I pathway both increased. Using the SphK inhibitor (SKI-II), ASD core phenotype and phenotype-related protein levels of P-CREB, P-CaMKII, and GAD1 were improved, as shown via behavioral and molecular biology experiments. Moreover, by using SKI-II, we found proteins related to the development and function of neuron synapses, including ERK, caspase-3, Bax, Bcl-2, CDK5 and KCNQ2 in BTBR mice, whose levels were restored to protein levels comparable to those in the controls. Elucidating the possible mechanism of ApoA-I in ASD-associated phenotypes will provide new ideas for studies on the etiology of ASD.

Airborne Microplastic Concentrations in Five Megacities of Northern and Southeast China.

Airborne microplastics (MPs) are receiving increasing attention due to their ubiquitous nature and the potential human health consequences resulting from inhalation. The limited data for airborne MP concentrations vary widely among studies (∼4 orders of magnitude), but comparisons are tenuous due to the inconsistent collection and detection/enumeration methodologies among studies. Herein, we used uniform methodologies to obtain comparable airborne MP concentration data to assess MP exposure intensity in five Chinese megacities. Airborne MP concentrations in northern cities (358 ± 132 items/m3) were higher than those in southeast cities (230 ± 94 items/m3) but of a similar order of magnitude, unlike previous studies. The majority (94.7%) of MPs found in air samples were smaller than 100 µm, and the main shape of airborne MPs was fragments (88.2%). Polyethylene, polyester, and polystyrene were the dominant polymers comprising airborne MPs. No consistent relationships were detected between airborne MP concentration and typical socioeconomic indices, and the spatial and diurnal patterns for airborne MPs were different from various components of air quality indices (PM2.5, PM10, etc.). These findings reflect the contrasting source/generation dynamics between airborne MPs and other airborne pollutants. Maximum annual exposure of humans to airborne MPs was estimated in the range of 1-2 million/year in these megacities, highlighting the need for additional research examining the human health risks from the inhalation of airborne MPs.

Boundary Restored Network for Subpleural Pulmonary Lesion Segmentation on Ultrasound Images at Local and Global Scales.

To evaluate the application of machine learning for the detection of subpleural pulmonary lesions (SPLs) in ultrasound (US) scans, we propose a novel boundary-restored network (BRN) for automated SPL segmentation to avoid issues associated with manual SPL segmentation (subjectivity, manual segmentation errors, and high time consumption). In total, 1612 ultrasound slices from 255 patients in which SPLs were visually present were exported. The segmentation performance of the neural network based on the Dice similarity coefficient (DSC), Matthews correlation coefficient (MCC), Jaccard similarity metric (Jaccard), Average Symmetric Surface Distance (ASSD), and Maximum symmetric surface distance (MSSD) was assessed. Our dual-stage boundary-restored network (BRN) outperformed existing segmentation methods (U-Net and a fully convolutional network (FCN)) for the segmentation accuracy parameters including DSC (83.45 ± 16.60%), MCC (0.8330 ± 0.1626), Jaccard (0.7391 ± 0.1770), ASSD (5.68 ± 2.70 mm), and MSSD (15.61 ± 6.07 mm). It also outperformed the original BRN in terms of the DSC by almost 5%. Our results suggest that deep learning algorithms aid fully automated SPL segmentation in patients with SPLs. Further improvement of this technology might improve the specificity of lung cancer screening efforts and could lead to new applications of lung US imaging.

Decoupling Ionic and Electronic Pathways in Low-Dimensional Hybrid Conductors.

The construction of two-dimensional (2D) layered compounds for nanofluidic ion transport has recently attracted increasing interest due to the facile fabrication, tunable channel size, and high flux of these materials. Here we design a nacre-mimetic graphite-based nanofluidic structure in which the nanometer-thick graphite flakes are wrapped by negatively charged nanofibrillated cellulose (NFC) fibers to form multiple 2D confined spacings as nanochannels for rapid cation transport. At the same time, the graphite-NFC structure exhibits an ultralow electrical conductivity (σe ≤ 10-9 S/cm), even when the graphite concentration is up to 50 wt %, well above the percolation threshold (∼1 wt %). By tuning the hydration degree of graphite-NFC composites, the surface-charge-governed ion transport in the confined ∼1 nm spacings exhibits nearly 12 times higher ionic conductivity (1 × 10-3 S/cm) than that of a fully swollen structure (∼1.5 nm, 8.5 × 10-5 S/cm) at salt concentrations up to 0.1 M. The resulting charge selective conductor shows intriguing features of both high ionic conductivity and low electrical conductivity. Moreover, the inherent stability of the graphite and NFC components contributes to the strong functionality of the nanofluidic ion conductors in both acidic and basic environments. Our work demonstrates this 1D-2D material hybrid system as a suitable platform to study nanofluidic ion transport and provides a promising strategy to decouple ionic and electronic pathways, which is attractive for applications in new nanofluidic device designs.

High-throughput gene targeting and phenotyping in zebrafish using CRISPR/Cas9.

The use of CRISPR/Cas9 as a genome-editing tool in various model organisms has radically changed targeted mutagenesis. Here, we present a high-throughput targeted mutagenesis pipeline using CRISPR/Cas9 technology in zebrafish that will make possible both saturation mutagenesis of the genome and large-scale phenotyping efforts. We describe a cloning-free single-guide RNA (sgRNA) synthesis, coupled with streamlined mutant identification methods utilizing fluorescent PCR and multiplexed, high-throughput sequencing. We report germline transmission data from 162 loci targeting 83 genes in the zebrafish genome, in which we obtained a 99% success rate for generating mutations and an average germline transmission rate of 28%. We verified 678 unique alleles from 58 genes by high-throughput sequencing. We demonstrate that our method can be used for efficient multiplexed gene targeting. We also demonstrate that phenotyping can be done in the F1 generation by inbreeding two injected founder fish, significantly reducing animal husbandry and time. This study compares germline transmission data from CRISPR/Cas9 with those of TALENs and ZFNs and shows that efficiency of CRISPR/Cas9 is sixfold more efficient than other techniques. We show that the majority of published "rules" for efficient sgRNA design do not effectively predict germline transmission rates in zebrafish, with the exception of a GG or GA dinucleotide genomic match at the 5' end of the sgRNA. Finally, we show that predicted off-target mutagenesis is of low concern for in vivo genetic studies.

Dynamic correction of soft measurement model for evaporation process parameters based on ARMA.

To address the significant soft measurement errors in traditional static models for evaporation process parameters, which are characterized by continuity and cumulativity, this paper proposes a dynamic correction method for soft measurement models of evaporation process parameters based on the autoregressive moving-average model (ARMA). Initially, the Powell's directional evolution (Powell-DE) algorithm is utilized to identify the autoregressive order and moving average order of the ARMA model. Subsequently, the prediction error of a mechanism-reduced robust least squares support vector machine ensemble model is utilized as input. An error time series prediction model, which compensates for the errors in the autoregressive moving average model, is then applied for dynamic estimation of the prediction error. Finally, an integration strategy using the entropy method is employed to combine the static soft measurement model, based on the mechanism-reduced robust least squares support vector machine, with the dynamic correction soft measurement model, which is based on the error time series compensation of the ARMA model. The new model is analyzed and validated using production data from an alumina plant's evaporation process. Compared to traditional models, the new model demonstrates significantly improved prediction accuracy and is capable of dynamic prediction of evaporation process parameters.

Evolution of ferromagnetic cluster in perovskite La0.88Sr0.12MnO3 nanocrystalline detected by EPR spectrum.

Electron paramagnetic resonance (EPR) studies were performed on La0.88Sr0.12MnO3 (LSMO) nanocrystalline together with the measurement of its magnetization. Various spectrum parameters including line width, effective g-value and double-integrated intensities have been analyzed in detail. We found nonlinear behavior occurred in the inverse susceptibility far above the Curie temperature TC, indicating short-range ferromagnetic (FM) clusters and Griffiths-like phase behavior in the paramagnetic (PM) phase. Based on the variation of EPR spectra, except for a typical PM resonance peak, an extra resonance signal was observed in the lower field region and developed as temperature decreased from 320 K to 110 K, which gave a direct evidence of the existence of FM cluster in the PM region of LSMO nanocrystalline. We proposed that the appearance of the Griffiths phase was due to the short FM correlation in the PM regime enhanced by surface spin ordering.

Association between visit-to-visit lipid variability and risk of ischemic heart disease: a cohort study in China.

AIMS: To explore the associations between visit-to-visit lipid variability and risk of ischemic heart disease (IHD) in a population-based cohort in China. METHODS: We evaluated lipid variability in 30,217 individuals from the Yinzhou Health Information System who had ≥3 recorded lipid measurements during 2010-2014. We used various indicators including standard deviation (SD), coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV) to quantify the variability in triglycerides, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). We used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Overall, a total of 1305 participants with IHD were identified during the follow-up of 194,421 person-years. Subjects in Q4 had a 21% elevated risk of IHD (HR = 1.21, 95% CI: 1.03-1.41) for LDL-C variability (CV) compared with the reference (Q1). The HRs for Q4 vs Q1 were 1.21 (95% CI: 1.04-1.42) for HDL-C variability, and 1.28 (95% CI: 1.10-1.50) for TC variability. However, no association was observed between triglycerides variability and risk of IHD. CONCLUSIONS: Higher variability in LDL-C, HDL-C, and TC levels was associated with an elevated risk of IHD, suggesting that lipid variability could be considered as an independent risk factor of IHD.

Soft-sensing modeling of mother liquor concentration in the evaporation process based on reduced robust least-squares support-vector machine.

The evaporation process is vital in alumina production, with mother liquor concentration serving as a critical control parameter. To address the challenge of online detection, we propose the introduction of a soft measurement strategy. First, due to the significant fluctuations in the production process variables and inter-variable coupling, comprehensive grey correlation analysis and kernel principal component analysis are employed to reduce the input dimension and computational complexity of the data, enhancing the efficiency of the soft sensing model. The reduced robust least-squares support-vector machine (LSSVM), with its commendable predictive performance, is used for modeling and predicting the principal components. Concurrently, an improved Pattern Search-Differential Evolution (PS-DE) algorithm is proposed for optimizing the pivotal parameters of the LSSVM network. Lastly, on-site industrial data validation indicates that the new model offers superior tracking capabilities and heightened accuracy. It is deemed aptly suitable for the online detection of mother liquor concentration.

Fuzzy super twisting mode control of a rigid-flexible robotic arm based on approximate inertial manifold dimensionality reduction.

Introduction: The control of infinite-dimensional rigid-flexible robotic arms presents significant challenges, with direct truncation of first-order modal models resulting in poor control quality and second-order models leading to complex hardware implementations. Methods: To address these issues, we propose a fuzzy super twisting mode control method based on approximate inertial manifold dimensionality reduction for the robotic arm. This innovative approach features an adjustable exponential non-singular sliding surface and a stable continuous super twisting algorithm. A novel fuzzy strategy dynamically optimizes the sliding surface coefficient in real-time, simplifying the control mechanism. Results: Our findings, supported by various simulations and experiments, indicate that the proposed method outperforms directly truncated first-order and second-order modal models. It demonstrates effective tracking performance under bounded external disturbances and robustness to system variability. Discussion: The method's finite-time convergence, facilitated by the modification of the nonlinear homogeneous sliding surface, along with the system's stability, confirmed via Lyapunov theory, marks a significant improvement in control quality and simplification of hardware implementation for rigid-flexible robotic arms.

Synthesis of V2O5·nH2O nanobelts@polyaniline core-shell structures with highly efficient Zn2+ storage.

Aqueous zinc-ion batteries (AZIBs) are regarded as attractive candidates for next-generation energy storage devices. Among various cathode materials, V2O5·nH2O (VOH) possesses a high theoretical capacity but poor cycle stability due to the susceptibility of its open structure to damage by the quick shuttling of Zn2+. Herein, the structural stability of VOH is directly improved by wrapping polyaniline (PANI) on the VOH nanobelts (VOH@PANI). As a cathode material for AZIBs, the VOH nanobelts@PANI core-shell structures exhibit an outstanding cycle stability of 98% after 2000 cycles at 2 A g-1. The improved conductivity and additional energy storage contribution of the PANI endow VOH@PANI with a specific capacity as high as 440 mAh g-1 at 0.1 A g-1, substantially higher than pure VOH (291 mAh g-1). At the same time, high energy and power densities of 349 Wh kg-1 and 3347 W kg-1 are achieved. This work not only demonstrates that p-type doped PANI coatings on VOH can boost the Zn2+ storage of VOH, but also provides a novel method to enhance cathode materials for high electrochemical performance.

Estimation of cancer mortality attributable to excess body weight during 2006-2015 in China.

BACKGROUND: Cancer is one of the most common causes of death. Excess body weight (EBW), a risk factor for cancer, is highly prevalent in China. We aimed to estimate the number and proportion of cancer deaths attributed to EBW and their changes during 2006-2015 in China. METHODS: Population attributable fractions in 2006, 2010, and 2015 were calculated with 1) prevalence of overweight/obesity, exacted from the China Health and Nutrition Survey conducted in 8-9 provinces of China in 1997, 2000, and 2004; 2) relative risks for EBW and site-specific cancers, obtained from previous studies; 3) data on cancer deaths in 2006, 2010, and 2015, originated from the Chinese Cancer Registry Annual Report. RESULTS: In 2015, EBW contributed to 45,918 (3.1% of all) cancer deaths in China, with 24,978 (2.6%) in men and 20,940 (3.8%) in women. By region, the fraction of cancer deaths attributable to EBW ranged from 1.6% (West) to 4.1% (Northeast). Cancers of liver, stomach, and colorectum were the main EBW-attributable cancers. The fractions of cancer deaths attributable to EBW were 2.4% (95%CI: 0.8-4.2%) in 2006, 2.9% (95%CI: 1.0-5.2%) in 2010, and 3.1% (95%CI: 1.0-5.4%) in 2015, respectively, and increased for all gender, region, and cancer site during 2006-2015. CONCLUSIONS: The proportion of cancer deaths attributed to EBW was higher in women and Northeastern China, with an upward trend in the recent decade. A combination of comprehensive and individualized measures is necessary to reduce the prevalence of EBW and related cancer burden in China.

Exposure to Neighborhood Walkability and Residential Greenness and Incident Fracture.

Importance: Emerging studies have suggested that environmental factors are associated with fracture. However, little is known about the association of neighborhood walkability and residential greenness with fracture. Objective: To investigate the association of long-term exposure to walkability and greenness with incident fracture and explore the potential interaction effect. Design, Setting, and Participants: This cohort study recruited participants aged 40 years or older in Ningbo, China from June 2015 to January 2018. Participants were observed for outcomes through February 2023, with data analysis conducted in March 2023. Exposures: Neighborhood walkability was measured by a modified walkability calculation method according to a walk score tool. Residential greenness was assessed by satellite-derived normalized difference vegetation index (NDVI) within a 1000-m buffer. Main Outcomes and Measures: Incident fracture was ascertained according to International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes via the Yinzhou Health Information System. Cox proportional hazards models were fit, with age as time scale to estimate the associations of walkability and greenness with fracture. Potential effect modification was explored by covariates, as well as the interactive effect of walkability and greenness. Results: A total of 23 940 participants were included in this study with 13 735 being female (57.4%). The mean (SD) age at baseline was 63.4 (9.4) years. During a follow-up period of 134 638 person-years, 3322 incident fractures were documented. In the full adjusted model, every IQR increment in neighborhood walkability and residential greenness was associated with a hazard ratio (HR) of 0.88 (95% CI, 0.83-0.92) and 0.84 (95% CI, 0.80-0.89), respectively, for fracture. Furthermore, the association of greenness and fracture was greater with an increase in walkability. The HR (Q4 vs Q1) for greenness was 0.62 (95% CI, 0.46-0.82) in neighborhoods with the highest quartile of walkability. Conclusions and Relevance: This population cohort study suggested that long-term exposure to neighborhood walkability and residential greenness were both associated with lower risk of incident fracture. The benefits of greenness increased in more walkable areas.

Involvement of Kir4.1 in pain insensitivity of the BTBR mouse model of autism spectrum disorder.

Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder. Abnormal pain sensation is a common clinical symptom of ASD that seriously affects the quality of life of patients with ASD and their families. However, the underlying mechanism is unclear. It is believed to be related to the excitability of neurons and the expression of ion channels. Herein, we confirmed that baseline pain and Complete Freund's adjuvant (CFA)-induced chronic inflammatory pain were impaired in the BTBR T+ Itpr3tf/J (BTBR) mouse model of ASD. RNA sequencing (RNA-seq) analyses of the dorsal root ganglia (DRG), which are closely related to pain in ASD model mice, revealed that high expression of KCNJ10 (encoding Kir4.1) might be an important factor in ASD pain sensation abnormalities. The levels of Kir4.1 were further verified by western blotting, RT-qPCR, and immunofluorescence. By inhibiting Kir4.1, the pain insensitivity of BTBR mice improved, confirming that a high expression level of Kir4.1 was highly correlated with decreased pain sensitivity in ASD. Meanwhile, we found that the anxiety behaviours and the social novelty recognition were changed after CFA induced inflammatory pain. And after inhibiting Kir4.1, the stereotyped behaviours and social novelty recognition of BTBR mice were also improved. Further, we found that the expression levels of glutamate transporters, excitatory amino acid transporter 1 (EAAT1), and excitatory amino acid transporter 2 (EAAT2) were increased in the DRG of BTBR mice but decreased after inhibiting Kir4.1. This suggests that Kir4.1 may play a key role in the improvement of pain insensitivity in ASD by regulating glutamate transporters. In conclusion, our findings revealed the possible mechanism and role of Kir4.1 in the pain insensitivity in ASD, using bioinformatics analyses and animal experiments, and provided a theoretical basis for clinically targeted intervention in ASD.

Association of walkability and NO2 with metabolic syndrome: A cohort study in China.

BACKGROUND: Epidemiological studies have reported an association between traffic-related pollution with risk of metabolic syndrome (MetS). However, evidence from prospective studies on the association of walkability and nitrogen dioxide (NO2) with MetS is still scarce. We, therefore, aimed to evaluate the association of long-term exposure to NO2 and walkability with hazards of incident MetS. METHODS: A total of 17,965 participants without MetS diagnosed within one year at baseline were included in our study from a population-based prospective cohort in Yinzhou District, Ningbo, Zhejiang Province, China. Participants were followed up by the regional Health Information System (HIS) until December 15, 2021. MetS was defined based on the criteria of Chinese Diabetes Society (CDS2004). We used walkscore tools, calculating with amenity categories and decay functions, and spatial-temporal land-use regression (LUR) models to estimate walkability and NO2 concentrations. We used Cox proportional hazards regression models to examine the association of walkability and NO2 with hazards of MetS incidence reporting with hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Overall, we followed up 77,303 person-years and identified 4040 incident cases of MetS in the entire cohort. Higher walkability was inversely associated with incident MetS (HR = 0.94, 95 % CI: 0.91-0.99), whereas NO2 was positively associated with MetS incidence (HR = 1.07, 95 %CI: 1.00-1.15) per interquartile range increment in two-exposure models. Furthermore, we found a significant multiplicative interaction between walkability and NO2. Stronger associations were observed for NO2 and incident MetS among men, smokers, drinkers and participants who aged < 60 years and had higher levels of income. CONCLUSION: In summary, we found living in areas with lower walkability and higher concentrations of NO2 were associated with increased incidence of MetS. The beneficial effect of higher walkability may be attenuated by exposure to NO2.