Fecal microbiota transplantation from young mice rejuvenates aged hematopoietic stem cells by suppressing inflammation.

Hematopoietic stem cell (HSC) aging is accompanied by hematopoietic reconstitution dysfunction, including loss of regenerative and engraftment ability, myeloid differentiation bias, and elevated risks of hematopoietic malignancies. Gut microbiota, a key regulator of host health and immunity, has recently been reported to affect hematopoiesis. However, there is currently limited empirical evidence explaining the direct impact of gut microbiome on aging hematopoiesis. In this study, we performed fecal microbiota transplantation (FMT) from young mice to aged mice and observed a significant increment in lymphoid differentiation and decrease in myeloid differentiation in aged recipient mice. Furthermore, FMT from young mice rejuvenated aged HSCs with enhanced short-term and long-term hematopoietic repopulation capacity. Mechanistically, single-cell RNA sequencing deciphered that FMT from young mice mitigated inflammatory signals, upregulated the FoxO signaling pathway, and promoted lymphoid differentiation of HSCs during aging. Finally, integrated microbiome and metabolome analyses uncovered that FMT reshaped gut microbiota composition and metabolite landscape, and Lachnospiraceae and tryptophan-associated metabolites promoted the recovery of hematopoiesis and rejuvenated aged HSCs. Together, our study highlights the paramount importance of the gut microbiota in HSC aging and provides insights into therapeutic strategies for aging-related hematologic disorders.

Incidence of oncogenic HPV infection in women with and without mental illness: A population-based cohort study in Sweden.

BACKGROUND: Women with mental illness experience an increased risk of cervical cancer. The excess risk is partly due to low participation in cervical screening; however, it remains unknown whether it is also attributable to an increased risk of infection with human papillomavirus (HPV). We aimed to examine whether women with mental illness had an increased infection rate of HPV compared to women without mental illness. METHODS AND FINDINGS: Using a cohort design, we analyzed all 337,116 women aged 30 to 64 and living in Stockholm, who had a negative test result of 14 high-risk HPV subtypes in HPV-based screening, during August 2014 to December 2019. We defined women as exposed to mental illness if they had a specialist diagnosis of mental disorder or had a filled prescription of psychotropic medication. We identified incident infection of any high-risk HPV during follow-up and fitted multivariable Cox models to estimate hazard ratios (HR) with 95% confidence intervals (CI) for HPV infection. A total of 3,263 women were tested positive for high-risk HPV during follow-up (median: 2.21 years; range: 0 to 5.42 years). The absolute infection rate of HPV was higher among women with a specialist diagnosis of mental disorder (HR = 1.45; 95% CI [1.34, 1.57]; p < 0.001) or a filled prescription of psychotropic medication (HR = 1.67; 95% CI [1.55, 1.79]; p < 0.001), compared to women without such. The increment in absolute infection rate was noted for depression, anxiety, stress-related disorder, substance-related disorder, and ADHD, and for use of antidepressants, anxiolytics, sedatives, and hypnotics, and was consistent across age groups. The main limitations included selection of the female population in Stockholm as they must have at least 1 negative test result of HPV, and relatively short follow-up as HPV-based screening was only introduced in 2014 in Stockholm. CONCLUSIONS: Mental illness is associated with an increased infection rate of high-risk HPV in women. Our findings motivate refined approaches to facilitate the WHO elimination agenda of cervical cancer among these marginalized women worldwide.

Exposure to residential green and blue space and the natural environment is associated with a lower incidence of psychiatric disorders in middle-aged and older adults: findings from the UK Biobank.

BACKGROUND: There is increasing evidence for the role of environmental factors and exposure to the natural environment on a wide range of health outcomes. Whether exposure to green space, blue space, and the natural environment (GBN) is associated with risk of psychiatric disorders in middle-aged and older adults has not been prospectively examined. METHODS: Longitudinal data from the UK biobank was used. At the study baseline (2006-2010), 363,047 participants (women: 53.4%; mean age 56.7 ± 8.1 years) who had not been previously diagnosed with any psychiatric disorder were included. Follow-up was achieved by collecting records from hospitals and death registers. Measurements of green and blue space modeled from land use data and natural environment from Land Cover Map were assigned to the residential address for each participant. Cox proportional hazard models with adjustment for potential confounders were used to explore the longitudinal associations between GBN and any psychiatric disorder and then by specific psychiatric disorders (dementia, substance abuse, psychotic disorder, depression, and anxiety) in middle-aged and older adults. RESULTS: During an average follow-up of 11.5 ± 2.8 years, 49,865 individuals were diagnosed with psychiatric disorders. Compared with the first tertile (lowest) of exposure, blue space at 300 m buffer [hazard ratio (HR): 0.973, 95% confidence interval (CI): 0.952-0.994] and natural environment at 300 m buffer (HR: 0.970, 95% CI: 0.948-0.992) and at 1000 m buffer (HR: 0.975, 95% CI: 0.952-0.999) in the third tertile (highest) were significantly associated with lower risk of incident psychiatric disorders, respectively. The risk of incident dementia was statistically decreased when exposed to the third tertile (highest) of green space and natural environment at 1000 m buffer. The third tertile (highest) of green space at 300 m and 1000 m buffer and natural environment at 300 m and 1000 m buffer was associated with a reduction of 30.0%, 31.8%, 21.7%, and 30.3% in the risk of developing a psychotic disorder, respectively. Subgroup analysis suggested that the elderly, men, and those living with some comorbid conditions may derive greater benefits associated with exposure to GBN. CONCLUSIONS: This study suggests that GBN has significant benefits for lowering the risk of psychiatric disorders in middle-aged and older adults. Future studies are warranted to validate these findings and to understand the potential mechanistic pathways underpinning these novel findings.

Peripheral vertigo and subsequent risk of depression and anxiety disorders: a prospective cohort study using the UK Biobank.

BACKGROUND: Peripheral vertigo is often comorbid with psychiatric disorders. However, no longitudinal study has quantified the association between peripheral vertigo and risk of psychiatric disorders. Furthermore, it remains unknown how the white matter integrity of frontal-limbic network relates to the putative peripheral vertigo-psychiatric disorder link. METHODS: We conducted a cohort study including 452,053 participants of the UK Biobank with a follow-up from 2006 through 2021. We assessed the risks of depression and anxiety disorders in relation to a hospitalization episode involving peripheral vertigo using Cox proportional hazards models. We also examined the associations of peripheral vertigo, depression, and anxiety with MRI fractional anisotropy (FA) in a subsample with brain MRI data (N = 36,087), using multivariable linear regression. RESULTS: Individuals with an inpatient diagnosis of peripheral vertigo had elevated risks of incident depression (hazard ratio (HR) 2.18; 95% confidence interval (CI) 1.79-2.67) and anxiety (HR 2.11; 95% CI 1.71-2.61), compared to others, particularly within 2 years after hospitalization (HR for depression 2.91; 95% CI 2.04-4.15; HR for anxiety 4.92; 95% CI 3.62-6.69). Depression was associated with lower FA in most studied white matter regions, whereas anxiety and peripheral vertigo did not show statistically significant associations with FA. CONCLUSIONS: Individuals with an inpatient diagnosis of peripheral vertigo have increased subsequent risks of depression and anxiety disorders, especially within 2 years after hospitalization. Our findings further indicate a link between depression and lower microstructural connectivity as well as integrity beyond the frontal-limbic network.

Computational models advance deep brain stimulation for Parkinson's disease.

Deep brain stimulation(DBS) has become an effective intervention for advanced Parkinson's disease(PD), but the exact mechanism of DBS is still unclear. In this review, we discuss the history of DBS, the anatomy and internal architecture of the basal ganglia (BG), the abnormal pathological changes of the BG in PD, and how computational models can help understand and advance DBS. We also describe two types of models: mathematical theoretical models and clinical predictive models. Mathematical theoretical models simulate neurons or neural networks of BG to shed light on the mechanistic principle underlying DBS, while clinical predictive models focus more on patients' outcomes, helping to adapt treatment plans for each patient and advance novel electrode designs. Finally, we provide insights and an outlook on future technologies.

Bi-directional association between outdoor or social activities and cognitive function: do the PM2.5 exposure catalyze the detrimental inactivity-poor cognition cycle?

BACKGROUND: Previous research has shown that lack of leisure activities, either outdoor or social activities, impedes cognitive function. However, the interrelationship between poor cognition and deficient activities is understudied. In addition, whether exposure to air pollution, such as PM2.5, can accelerate the detrimental 'inactivity-poor cognition' cycle, is worthy of investigation. METHODS: We used data from the 2008, 2011, 2014, and 2018 waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). We assessed the frequency of outdoor or social activities at each wave. The cognitive function was examined using a China-Modified Mini-mental State Examination. We estimated the residential exposure to fine particular matter (PM2.5) via a satellite-based model. We applied cross-lagged panel (CLP) model to examine the bi-directional relationship between outdoor or social activities and cognitive function. We then examined the effect of PM2.5 exposure with sequent cognitive function and activities using generalized estimation equation (GEE) model. FINDINGS: Overall, we observed significant bi-directional associations between outdoor or social activities and cognitive function. Participants with better cognitive function in the last wave were more likely to engage in outdoor or social activities in the following wave (outdoor activities: ß = 0.37, 95% CI [0.27,0.48], P < 0.01; social activities: ß = 0.05, 95% CI [0.02,0.09] P < 0.01). Meanwhile, higher engagement in outdoor or social activities in the last wave was associated with more favorable cognitive function in the following wave (outdoor activities: ß = 0.06, 95% CI [0.03,0.09], P < 0.01; social activities: ß = 0.10, 95% CI [0.03,0.18], P < 0.01). Notably, an increase in PM2.5 exposure during the preceding year was significantly associated with a declining cognitive function (ß = -0.05, 95% CI [-0.08,-0.03], P < 0.01), outdoor activities (ß = -0.02, 95% CI [-0.04, -0.01], P < 0.01) and social activities (ß = -0.02, 95% CI [-0.02, -0.01], P < 0.01) in the current year; the lagged effects of the PM2.5 exposure in the past year of the last wave on activities and cognitive function of the following wave were also observed. INTERPRETATION: Our findings not only indicate the bi-directional links between the frequency of outdoor or social activities and cognitive function, but also report that PM2.5 exposure plays a role in catalyzing the detrimental inactivity-poor cognition cycle. Future research should investigate whether the policy-driven interventions, such as clean air policies, can break the unfavorable activity-cognition cycle, and thereby promoting health from the dual gains in leisure activities and cognition.

Associations between cooking fuel use, its transitions, and worsening sensory impairments among Chinese middle-aged and older adults: a cohort study.

BACKGROUND: This study aimed to explore the associations between household air pollution (HAP), measured by cooking fuel use, sensory impairments (SI), and their transitions in Chinese middle-aged and older adults. METHODS: Participants were recruited from the 2011 China Health and Retirement Longitudinal Study (CHARLS) and were subsequently followed up until 2018. Data on SI were collected by self-reported hearing and vision impairments, which were divided into three categories: non-SI, single SI (hearing or vision impairment), and dual SI (DSI). Cooking fuels, including solid and clean fuels, are proxies for HAP. The transitions of cooking fuels and SI refer to the switching of the fuel type or SI status from baseline to follow-up. Cox proportional hazard regression models were used to explore associations, and hazard ratios (HRs) and 95% confidence intervals (CI) were used to evaluate the strength of the association. RESULTS: The prevalence of non-SI, single SI, and DSI was 59.6%, 31.8%, and 8.6%, respectively, among the 15,643 participants at baseline in this study. Over a median follow-up of 7.0 years, 5,223 worsening SI transitions were observed. In the fully adjusted model, solid fuel use for cooking was associated with a higher risk of worsening SI transitions, including from non-SI to single SI (HR = 1.08, 95% CI = 1.01-1.16) and from non-SI to DSI (HR = 1.26, 95% CI = 1.09-1.47), but not from single SI to DSI. In addition, compared to those who always used solid fuels, participants who switched from solid to clean fuel for cooking appeared to have attenuated the risk of worsening SI transitions. The statistical significance of the associations remained in the set of sensitivity analyses. CONCLUSION: Solid fuel use was associated with higher risks of worsening SI transitions, while converting the type of cooking fuel from solid to clean fuels may reduce the risk of worsening SI transitions. Our study suggests that tailored clean fuel interventions, especially in developing countries, should be implemented to prevent sensory impairments and hence reduce the burden of sensory impairment-related disability.

The combined effect of air pollution and non-optimal temperature on mortality in Shandong Province, China: establishment of air health index.

PURPOSE: The air health index (AHI) captures the combined effects of air pollution and non-optimal temperatures and helps assess the atmospheric environment's overall health risk. Shandong Province is a crucial industrial base in China, and the health effects of air pollution and non-optimal temperature cannot be ignored. To construct an AHI for Shandong Province and assess the district-level mortality burden due to AHI in the study area. METHODS: Daily district-specific mortality, meteorological, and air pollution data over 2013-2018 were collected in Shandong Province, China. The AHI construction eventually incorporated PM2.5 and NO2, O3, and non-optimal temperatures. Attributable fraction (AF) and attributable number (AN) were used to estimate the district-specific mortality burden attributable to AHI. RESULTS: The average AHI value observed in Shandong Province was 6. Our research revealed a positive association between the total AHI and total mortality, with an overall trend of a slow increase followed by a rapid increase. The exposure-response curves, when stratified by gender, age, and cause of death, were approximately consistent with the overall trend. The provincial attributable fraction (AF) was 5.31% (95% CI 4.58%, 5.91%), and the attributable number (AN) was 188,246 (95% CI 162,396, 209,533). Overall, higher ANs mainly appeared in the southwestern area, while higher values of AF were observed in the central-eastern and central-northern areas. CONCLUSIONS: The air health index performs well in predicting death burden and can convey health risks related to exposure to the ambient environment to the public.

Association of solid fuel use with a risk score capturing dementia risk among middle-aged and older adults: A prospective cohort study.

OBJECTIVES: Whether household air pollution is associated with dementia risk remains unknown. This study examined the associations between solid fuel use for cooking and heating (the main source of household air pollution) and dementia risk. METHODS: This analysis included data on 11,352 participants (aged 45+ years) from the 2011 wave of China Health and Retirement Longitudinal Study, with follow-up to 2018. Dementia risk was assessed by a risk score using the Rotterdam Study Basic Dementia Risk Model (BDRM), which was subsequently standardized for analysis. Household fuel types of cooking and heating were categorized as solid (e.g., coal and crop residue) and clean (e.g., central heating and solar). Multivariable analyses were performed using generalized estimating equations. Moreover, we examined the joint associations of solid fuel use for cooking and heating with the BDRM score. RESULTS: After adjusting for potential confounders, we found an independent and significant association of solid (vs. clean) fuel use for cooking and heating with a higher BDRM score (e.g., ß = 0.17 for solid fuel for cooking; 95% confidence interval [CI]: 0.15-0.19). Participants who used solid (vs. clean) fuel for both cooking and heating had the highest BDRM score (ß = 0.32; 95% CI: 0.29-0.36). Subgroup analysis suggested stronger associations in participants living in rural areas. CONCLUSIONS: Solid fuel use for cooking and heating was independently associated with increased dementia risk in Chinese middle-aged and older adults, particularly among those living in rural areas. Our findings call for more efforts to facilitate universal access to clean energy for dementia prevention.

Mammography radiomics features at diagnosis and progression-free survival among patients with breast cancer.

BACKGROUND: The associations between mammographic radiomics and breast cancer clinical endpoints are unclear. We aimed to identify mammographic radiomics features associated with breast cancer prognosis. METHODS: Nested from a large breast cancer cohort in our institution, we conducted an extreme case-control study consisting of 207 cases with any invasive disease-free survival (iDFS) endpoint <5 years and 207 molecular subtype-matched controls with >5-year iDFS. A total of 632 radiomics features in craniocaudal (CC) and mediolateral oblique (MLO) views were extracted from pre-treatment mammography. Logistic regression was used to identify iDFS-associated features with multiple testing corrections (Benjamini-Hochberg method). In a subsample with RNA-seq data (n = 96), gene set enrichment analysis was employed to identify pathways associated with lead features. RESULTS: We identified 15 iDFS-associated features from CC-view yet none from MLO-view. S(1,-1)SumAverg and WavEnLL_s-6 were the lead ones and associated with favourable (OR 0.64, 95% CI 0.42-0.87, P = 0.01) and poor iDFS (OR 1.53, 95% CI 1.31-1.76, P = 0.01), respectively. Both features were associated with eight pathways (primarily involving cell cycle regulation) in tumour but not adjacent normal tissues. CONCLUSION: Our findings suggest mammographic radiomics features are associated with breast cancer iDFS, potentially through pathways involving cell cycle regulation.

Neuroendocrine pathways and breast cancer progression: a pooled analysis of somatic mutations and gene expression from two large breast cancer cohorts.

BACKGROUND: Experimental studies indicate that neuroendocrine pathways might play a role in progression of breast cancer. We aim to test the hypothesis that somatic mutations in the genes of neuroendocrine pathways influence breast cancer prognosis, through dysregulated gene expression in tumor tissue. METHODS: We conducted an extreme case-control study including 208 breast cancer patients with poor invasive disease-free survival (iDFS) and 208 patients with favorable iDFS who were individually matched on molecular subtype from the Breast Cancer Cohort at West China Hospital (WCH; N = 192) and The Cancer Genome Atlas (TCGA; N = 224). Whole exome sequencing and RNA sequencing of tumor and paired normal breast tissues were performed. Adrenergic, glucocorticoid, dopaminergic, serotonergic, and cholinergic pathways were assessed for differences in mutation burden and gene expression in relation to breast cancer iDFS using the logistic regression and global test, respectively. RESULTS: In the pooled analysis, presence of any somatic mutation (odds ratio = 1.66, 95% CI: 1.07-2.58) of the glucocorticoid pathway was associated with poor iDFS and a two-fold increase of tumor mutation burden was associated with 17% elevated odds (95% CI: 2-35%), after adjustment for cohort membership, age, menopausal status, molecular subtype, and tumor stage. Differential expression of genes in the glucocorticoid pathway in tumor tissue (P = 0.028), but not normal tissue (P = 0.701), was associated with poor iDFS. Somatic mutation of the adrenergic and cholinergic pathways was significantly associated with iDFS in WCH, but not in TCGA. CONCLUSION: Glucocorticoid pathway may play a role in breast cancer prognosis through differential mutations and expression. Further characterization of its functional role may open new avenues for the development of novel therapeutic targets for breast cancer.

Predicting the onset of freezing of gait in Parkinson's disease.

BACKGROUND: Freezing of gait is a debilitating symptom of Parkinson's disease associated with high risks of falls and poor quality of life. While productive therapy for FoG is still underway, early prediction of FoG could help high-risk PD patients to take preventive measures. In this study, we predicted the onset of FoG in de novo PD patients using a battery of risk factors from patients enrolled in PPMI cohort. METHODS: Baseline characteristics were compared between subjects who developed FoG (68 patients, 37.2%, pre-FoG group) during the five-year follow up and subjects who did not (115 patients, 62.8%, non-FoG group). A multivariate logistic regression model was built based on backward stepwise selection of factors that were associated with FoG onset in the univariate analysis. ROC curves were used to assess sensitivity and specificity of the predictive model. RESULTS: At baseline, age, PIGD score, cognitive functions, autonomic functions, sleep behavior, fatigue and striatal DAT uptake were significantly different in the pre-FoG group relative to the non-FoG group. However, there was no difference in genetic characteristics between the two patient sets. Univariate analysis showed several motor and non-motor factors that correlated with FoG, including PIGD score, MDS-UPDRS part II score, SDMT score, HVLT Immediate/Total Recall, MOCA, Epworth Sleepiness Scale, fatigue, SCOPA-AUT gastrointestinal score, SCOPA-AUT urinary score and CSF biomarker Abeta42. Multivariate logistic analysis stressed that high PIGD score, fatigue, worse SDMT performance and low levels of Abeta42 were independent risk factors for FoG onset in PD patients. CONCLUSIONS: Combining motor and non-motor features including PIGD score, poor cognitive functions and CSF Abeta can identify PD patients with high risk of FoG onset.

Reduction in daily ambient PM2.5 pollution and potential life gain by attaining WHO air quality guidelines in Tehran.

BACKGROUND: Fine particulate matter pollution (PM2.5) is widely considered to be a top-ranked risk factor for premature mortality and years of life lost (YLL). However, evidence regarding the effect of daily air quality improvement on life expectancy is scarce, especially in the Middle East such as Iran. This study aimed to investigate the potential benefits in life expectancy at concentrations meeting the daily PM2.5 standards during 2012-2016 in Tehran, Iran. METHODS: We collected daily non-accidental mortality and data on air pollutants and weather conditions from Tehran, Iran, 2012-2016. A quasi-Poisson or Gaussian time-series regression was employed to fit the associations between ambient PM2.5 and mortality or YLL. Potential gains in life expectancy (PGLE) and attributable fraction (AF) were estimated by assuming that daily PM2.5 concentrations attained the World Health Organization air quality guidelines (WHO AQG) 2005 (25 µg/m3) and 2021 (15 µg/m3). RESULTS: During the study period, a total of 221,231 non-accidental deaths were recorded in Tehran, resulting in 3.6 million YLL. The mean concentration of ambient PM2.5 was 34.7 µg/m3 (standard deviation: 15.3 µg/m3). For a 10-µg/m3 rise in 4-day moving average (lag 03-day) in PM2.5 concentration, non-accidental mortality and YLL increased by 1.12% (95% confidence interval: 0.60, 1.65) and 20.73 (7.08, 34.39) person years, respectively. A relatively higher effect was observed in males and young adults aged 18-64 years. We estimated that 39830 [AF = 1.1%] and 74284 [AF = 2.1%] YLL could potentially be avoided if daily PM2.5 concentrations attained the WHO AQG 2005 and 2021, respectively, which corresponded to potential gains in life expectancy of 0.18 (0.06, 0.30) and 0.34 (0.11, 0.56) years for each deceased person. PM2.5-associated PGLE estimates were largely robust when performing sensitivity analyses. CONCLUSIONS: Our findings indicated that short-term exposure to PM2.5 is associated with increased non-accidental YLL and mortality. Prolonged life expectancy could be achieved if the particulate matter air pollution level were kept under a stricter standard.

Nonlinear effect of air pollution on adult pneumonia hospital visits in the coastal city of Qingdao, China: A time-series analysis.

Many studies have illustrated adverse effects of short-term exposure to air pollution on human health, which usually assumes a linear exposure-response (E-R) function in the delineation of health effects due to air pollution. However, nonlinearity may exist in the association between air pollutant concentrations and health outcomes such as adult pneumonia hospital visits, and there is a research gap in understanding the nonlinearity. Here, we utilized both the distributed lag model (DLM) and nonlinear model (DLNM) to compare the linear and nonlinear impacts of air pollution on adult pneumonia hospital visits in the coastal city of Qingdao, China. While both models show adverse effects of air pollutants on adult pneumonia hospital visits, the DLNM shows an attenuation of E-R curves at high concentrations. Moreover, the DLNM may reveal delayed health effects that may be missed in the DLM, e.g., ozone exposure and pneumonia hospital visits. With the stratified analysis of air pollutants on adult pneumonia hospital visits, both models consistently reveal that the influence of air pollutants is higher during the cold season than during the warm season. Nevertheless, they may behave differently in terms of other subgroups, such as age, gender and visit types. For instance, while no significant impact due to PM2.5 in any of the subgroups abovementioned emerges based on DLM, the results from DLNM indicate statistically significant impacts for the subgroups of elderly, female and emergency department (ED) visits. With respect to adjustment by two-pollutants, PM10 effect estimates for pneumonia hospital visits were the most robust in both DLM and DLNM, followed by NO2 and SO2 based on the DLNM. Considering the estimated health effects of air pollution relying on the assumed E-R functions, our results demonstrate that the traditional linear association assumptions may overlook some potential health risks.

Association between outdoor artificial light at night and sleep duration among older adults in China: A cross-sectional study.

BACKGROUND: Light after dusk disrupts the circadian rhythms and shifts the timing of sleep later; but it is unknown whether outdoor artificial light at night (ALAN) affects sleep quality. This study aimed to explore the association between residential outdoor ALAN and sleep duration in a nationally representative sample of Chinese older adults. METHODS: We examined the cross-sectional associations of outdoor ALAN with self-reported sleep duration in 13,474 older adults participating in the 2017-2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Outdoor ALAN exposure was estimated at the residence level using satellite images. We applied generalized linear mixed models to investigate the association between ALAN exposure and sleep duration. We performed stratified analyses by age, sex, education, and household income levels. Moreover, we used multi-level logistic regression models to investigate the effects of ALAN on the short sleep duration (≤6 h) and the long sleep duration (>8 h), respectively, in reference to sleep for >6-8 h per day. RESULTS: We found a significant association between outdoor ALAN intensity and sleep duration. The highest quartile of ALAN was associated with 17.04 (95% CI: 9.42-24.78) fewer minutes of sleep as compared to the lowest quartile. The reductions in sleep duration per quartile change in ALAN were greater in the young old (≥65-85 years) and in those with higher levels of education, and those with higher household income, respectively. We did not detect a sex difference. In addition, those in the highest quartile of ALAN were more likely to report a 25% (95% CI: 10%-42%) increase in short sleep (<6 h), and a 21% (95% CI: 9%-31%) decrease in long sleep (>8 h). CONCLUSIONS: Increasing outdoor nighttime light intensity surrounding residences was associated with shorter sleep duration in older residents in China. This finding implies the importance of urban outdoor artificial light management as a potential means to lower the public health burden of sleep disorders.

Long-term exposure to PM2.5 constituents in relation to glucose levels and diabetes in middle-aged and older Chinese.

BACKGROUND: Previous studies have indicated the associations between fine particulate matter (PM2.5) exposure and diabetes or glucose levels. However, evidence linking PM2.5 constituents and diabetes or glucose levels was extensively scarce, particularly in developing countries. This study aimed to investigate the associations of exposure to PM2.5 and its five constituents (black carbon [BC], organic matter [OM], nitrate [NO3-], sulfate [SO42-], and ammonium [NH4+]) with diabetes and glucose levels among the middle-aged and elderly Chinese populations. METHODS: A national cross-sectional sample of participants aged 45+ years was enrolled from 28 provinces across China's mainland. Health examination and questionnaire survey for each respondent were performed during 2011-2012. Diabetes was determined by alternative definitions, and the main definition (MD) was self-report diabetes or antidiabetic medicine use or HbA1c ≥6.5 or fasting glucose ≥7 mmol/L or random glucose ≥11.1 mmol/L. Monthly exposure to PM2.5 mass and its five constituents (BC, OM, NO3-, SO42-, and NH4+) for each participant at residence were estimated using satellite-based spatiotemporal prediction models. Generalized linear models and linear mixed-effects models were used to assess the effects of exposure to PM2.5 and its constituents on diabetes or glucose levels, respectively. Stratification analyses were done by sex and age. RESULTS: We included a total of 17,326 adults over 45 years in this study. The 3-year mean (interquartile range [IQR]) concentrations of PM2.5, BC, OM, NO3-, SO42-, and NH4+ were 47.9 (27.4) µg/m3, 2.9 (2.2) µg/m3, 9.2 (6.6) µg/m3, 10.2 (9.4) µg/m3, 11.0 (5.2) µg/m3, and 7.1 (4.4) µg/m3, respectively. Per IQR rise in exposure to PM2.5 was significantly associated with an increase of 0.133 mmol/L (95% confidence interval, 0.048-0.219) in glucose concentrations. Similar positive associations were observed for BC (0.097 mmol/L [0.012-0.181]), OM (0.160 mmol/L [0.065-0.256]), NO3- (0.145 mmol/L [0.039-0.251]), SO42- (0.111 mmol/L [0.026-0.196]), and NH4+ (0.135 mmol/L [0.041-0.230]). Under different diabetes definitions, PM2.5 mass and selected constituents with the exception of SO42- were all associated with a higher risk of prevalent diabetes. In MD-based analysis, similar positive associations were observed for four constituents, with corresponding odds ratios of 1.180 (1.097-1.270) for PM2.5, 1.154 (1.079-1.235) for BC, 1.170 (1.079-1.270) for OM, 1.200 (1.098-1.312) for NO3-, and 1.123 (1.037-1.215) for NH4+. Stratified analyses showed a significantly higher risk of diabetes in males (1.225 [1.064-1.411]) than females (1.024 [0.923-1.136]) when exposed to PM2.5. Participants under 65 years were generally more vulnerable to diabetes hazards related to PM2.5 constituents exposure. CONCLUSIONS: Exposures to PM2.5 and its constituents (i.e., BC, OM, NO3-, and NH4+) were positively associated with increased risks of prevalent diabetes and elevated glucose levels in middle-aged and older adults.

Management algorithm of external fixation in lower leg arterial injury for limb salvages.

PURPOSE: The aim of this study is to investigate the outcome of these limb-threatening injuries through external fixation treatment and to discuss the case of patients' functional recovery after external fixation. METHODS: Demographics, surgical treatment and outcomes in 88 patients with lower leg arterial injuries treated by external fixation at two trauma centers from 2009 to 2018 were reviewed. The primary outcome was the rate of successful lower leg salvage, while secondary outcomes were complications and functional recovery. RESULTS: Eighty-eight patients were identified and 80 patients (90 legs) maintained a successful lower leg salvage. The mean age was 32.7 ± 10.8 years, and 81.8% were male. The primary outcomes included the following complications: pin-tract infection (8 legs), pins loosening (4 pins), wound superficial infection (7 legs), deep infection developed osteomyelitis (3 legs), bone nonunion or bone defect (17 legs) and amputation (8 legs). The average healing time of fracture was 5.6 ± 4.3 months. The maintain of external fixation average time was 5.8 ± 3.6 months. The improvement of scores of the pain, function and quality of life in our follow-up was statistically significant. CONCLUSION: For the lower extremity fracture patients with vascular injuries, using external fixation correctly can improve clinical outcomes and produce the improvement of pain, function and the quality of life. LEVEL OF EVIDENCE: Retrospective cohort, level IV.

Comprehensive assessment of water environmental carrying capacity for sustainable watershed development.

Due to insufficient understanding of human-water interaction, many water-related problems arise in watersheds, posing severe threats to the sustainability of watershed development. Although water environmental carrying capacity (WECC) is a powerful tool to support sustainable development of watersheds, few studies considered aquatic ecological factors and uncertainty in indicator values, leading to losses of sample information in the evaluation of WECC. This paper developed a systematic framework for comprehensive WECC assessment that included the indicator system and a novel variable fuzzy pattern recognition (VFPR) approach. The WECC index system incorporated aquatic ecological factors, and addressed uncertainties associated with the indicator values. The proposed VFPR-based assessment model could realize successive evaluation to retain more original information of the sample and distinguish similar result values by treating the sample as having a continuous degree of membership instead of the traditional point form. In addition, it could be more adaptable to various circumstances including extreme cases, and closely reflect the impacts of indicator changes on the results. The established evaluation framework has been applied to Dongjiang River Basin in Guangdong Province. The spatial differences and main influencing factors of WECC in the study area were analyzed. Results show that 50% and 16.7% of the sub-regions in the study area would be subject to a poor level of WECC under pessimistic and optimistic circumstances, respectively. WECCs in the upper and lower reaches are the best and worst, respectively, which is in line with the levels of economic development in the Dongjiang River Basin. The proposed method can also be applicable to many other problems involving numerous indicators.

Progress on CAR-T cell therapy for hematological malignancies.

Chimeric antigen receptor (CAR) T cell therapy is an effective treatment for hematological malignancies, which have experienced the development of CD19 CAR-T cells for B lymphoblastic leukemia and lymphoma, B cell maturation antigen (BCMA) CAR-T cells for multiple myeloid, and more recently, the development of CD7 CAR-T cells for T cell malignancies. There are more obstacles for myeloid malignancies compared to other hematological malignancies in this field, thus concerning researches are in more diverse ways. In order to obtain more effective clinical CAR-T cells with lower side effects, scientists have developed multi-target CAR-T cells, universal CAR-T cells, as well as CAR-T cells, CAR-NK cells, CAR-iMac cells derived from induced pluripotent stem cells (iPSC) by genetic engineering. Chinese scientists have made significant contribution to the invention and manufacture of origin CAR-T cells and the establishment of an intact clinical research system. This review introduces the latest progress involving CAR-T cell therapy for hematological malignancies including B lymphoblastic malignancies, T lymphoblastic malignancies and myeloid malignancies, and also discuss the future developments including multi-target, universal and iPSC-derived CAR-related cell therapy.

Public health insurance and cancer-specific mortality risk among patients with breast cancer: A prospective cohort study in China.

Little is known about how health insurance policies, particularly in developing countries, influence breast cancer prognosis. Here, we examined the association between individual health insurance and breast cancer-specific mortality in China. We included 7436 women diagnosed with invasive breast cancer between 2009 and 2016, at West China Hospital, Sichuan University. The health insurance plan of patient was classified as either urban or rural schemes and was also categorized as reimbursement rate (ie, the covered/total charge) below or above the median. Breast cancer-specific mortality was the primary outcome. Using Cox proportional hazards models, we calculated hazard ratios (HRs) for cancer-specific mortality, contrasting rates among patients with a rural insurance scheme or low reimbursement rate to that of those with an urban insurance scheme or high reimbursement rate, respectively. During a median follow-up of 3.1 years, we identified 326 deaths due to breast cancer. Compared to patients covered by urban insurance schemes, patients covered by rural insurance schemes had a 29% increased cancer-specific mortality (95% CI 0%-65%) after adjusting for demographics, tumor characteristics and treatment modes. Reimbursement rate below the median was associated with a 42% increased rate of cancer-specific mortality (95% CI 11%-82%). Every 10% increase in the reimbursement rate is associated with a 7% (95% CI 2%-12%) reduction in cancer-specific mortality risk, particularly in patients covered by rural insurance schemes (26%, 95% CI 9%-39%). Our findings suggest that underinsured patients face a higher risk of breast cancer-specific mortality in developing countries.