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Nationwide longitudinal evidence linking cognitive decline with exposure to fine particulate matter (PM2.5) constituents remains scarce in China. By constructing a dynamic cohort based on the China Health and Retirement Longitudinal Study, we aimed to assess individual and joint associations of PM2.5 constituents with cognitive function among middle-aged and older adults in China. Linear mixed-effects models incorporated with quantile-based g-computation were applied to investigate individual and joint associations of long-term exposures to PM2.5 constituents with cognitive function. Among 13,507 respondents, we evaluated 38,950 follow-up records of cognitive function tests. Declines in global cognitive score associated with an interquartile range (IQR) increase in exposure were −1.477 (95% CI: −1.722, −1.232) for nitrate, followed by −1.331 (−1.529, −1.133) for ammonium, −1.033 (−1.184, −0.883) for sulfate, −0.988 (−1.144, −0.832) for organic matter and −0.822 (−0.946, −0.699) for black carbon. An IQR-equivalent increase in joint exposure to these PM2.5 constituents was associated with a decline of −1.353 (−1.659, −1.048) in global cognitive score. Female, younger, and well-educated individuals were at greater vulnerability to cognitive impairment related to individual and joint exposure to PM2.5 constituents. This study suggested that later-life exposures to PM2.5 constituents were associated with cognitive decline in middle-aged and older adults in China. [ABSTRACT FROM AUTHOR]

The impact of short-term exposure to air pollutants on the morbidity of schizophrenia, particularly in low- and middle-income countries, remains inadequately explored. The objective of this research was to investigate the relationship between short-term exposure to ambient air pollutants and the risk of schizophrenia hospitalization in Jingmen, China. We performed a time-stratified case-crossover study using daily records of hospital admissions due to schizophrenia in Jingmen Mental Health Center from 2015 to 2017. Environmental exposures to air pollutants and meteorological conditions on case and control days were estimated on the basis of measurements from ground monitoring stations. To investigate the relationship between short-term exposure to ambient air pollutants and the risk of hospitalization for schizophrenia, a conditional logistic regression model was employed. We performed subgroup analyses stratified according to sex, age groups, and season. In total, 4079 schizophrenia hospitalizations were recorded during the designated period. Increased risk of schizophrenia was merely associated with short-term exposure to SO2 and NO2. The estimated odds per interquartile range (IQR) increase in exposure was 1.112 (95% confidence interval (CI): 1.033, 1.196) for SO2 (IQR = 12 µg/m3) and 1.112 (95% CI: 1.033, 1.197) for NO2 (IQR = 18 µg/m3) on lag-0 day. Greater air pollution-schizophrenia associations were observed among middle-aged and older adults (over 45 years of age) and during the cold season. This study added case-crossover evidence indicating that short-term exposure to ambient air pollution, specifically SO2 and NO2, is linked to a higher risk of hospital admissions for schizophrenia. These findings contribute to a better understanding of the detrimental effects of air pollution on neuropsychiatric health conditions. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has drastically increased use of remote-delivered mental health services. This study identifies advantages and limitations of remote-delivered services on college campuses to inform mental health delivery post-pandemic. Methods: Clinicians (n = 30) were asked to evaluate COVID-19's impact on their work, environment, and wellness in an online survey. Qualitative data was coded using a thematic analysis approach, while quantitative data was analyzed using descriptive statistics. Results: Many clinicians reported benefits of remote services, including increased accessibility, greater convenience, no change in therapeutic alliance, and decreased stress for clinicians. Clinicians also experienced challenges such as social isolation, technological difficulties, and personal/family concerns. Clinicians envisioned a hybrid service combining online and in-person activities post-pandemic. Conclusions: Overall, remote-delivered mental health services on college campuses have potential in increasing treatment quality while highlighting a necessity for further research in hybrid mental health delivery. Supplemental data for this article can be accessed online at https://doi.org/10.1080/07448481.2022.2038178. [ABSTRACT FROM AUTHOR]

To study the classification efficiency of using texture feature machine learning method in distinguishing solid lung adenocarcinoma (SADC) and tuberculous granulomatous nodules (TGN) that appear as solid nodules (SN) in non-enhanced CT images. 200 patients with SADC and TGN who underwent thoracic non-enhanced CT examination from January 2012 to October 2019 were included in the study, 490 texture eigenvalues of 6 categories were extracted from the lesions in the non-enhanced CT images of these patients for machine learning, the classification prediction model is established by using relatively the best classifier selected according to the fitting degree of learning curve in the process of machine learning, and the effectiveness of the model was tested and verified. The logistic regression model of clinical data (including demographic data and CT parameters and CT signs of solitary nodules) was used for comparison. The prediction model of clinical data was established by logistic regression, and the classifier was established by machine learning of radiologic texture features. The area under the curve was 0.82 and 0.65 for the prediction model based on clinical CT and only CT parameters and CT signs, and 0.870 based on Radiomics characteristics. The machine learning prediction model developed by us can improve the differentiation efficiency of SADC and TGN with SN, and provide appropriate support for treatment decisions. [ABSTRACT FROM AUTHOR]

Objective: To investigate the prevalence of and risk factors associated with mental health symptoms in psychiatric outpatients and their family members in China during the COVID-19 pandemic. Methods: This cross-sectional, survey-based, region-stratified study collected demographic data and mental health measurements for depression, anxiety and acute stress from 269 psychiatric patients and 231 family members in the Second Xiangya Hospital in China from April 27, 2020 to May 8, 2020. Binary logistic regression analysis was performed to identify risk factors associated with mental health outcomes. Result: The results of this survey revealed that symptoms of depression, anxiety, and acute stress were highly prevalent symptoms in the psychiatric patient group. Respondents who were female, unmarried or highly educated were significantly more likely to have the above symptoms. In the family member group, more than half of them felt that the burden of nursing had increased during the epidemic. Subjects with a high degree of burden of care were significantly more likely to exhibit the above mental health symptoms, while females were significantly more likely to have acute stress. Conclusions: The results of this survey revealed a high prevalence of mental health disorder symptoms among psychiatric patients and an increased burden of nursing among their family members after the COVID-19 outbreak in China. Understanding the risk factors in those particular groups of people help improve the public health service system for mental health problems during public health events. For further study, exploration of the needs of mental health services and dynamic change tracking will be needed. [ABSTRACT FROM AUTHOR]

Objective: Studies on alterations in the regional neural activity in the brain of patients with bipolar disorder (BD) have provided conflicting results because of different medications used and study designs. A low bone mineral density (BMD) is also observed in patients with BD. This study aimed to further explore regional neural activities in unmedicated patients with BD and their association with BMD. Methods: In this study, 40 patients with BD and 42 healthy controls were scanned through resting-state functional magnetic resonance imaging (fMRI). Imaging data were analyzed with regional homogeneity (ReHo) and pattern classification. Pearson's correlation analyses were performed to explore the correlations between abnormal ReHo and BMD. Results: A significant increase in ReHo values in the left inferior frontal gyrus (IFG)/temporal pole, left cerebellum vermis I/vermis II/parahippocampal gyrus/brainstem, and right superior temporal gyrus (STG) and a decrease in ReHo in the occipital gyrus (OG; left middle OG/superior OG/bilateral cuneus) were found in the patients with BD (p < 0.05) compared with those in the healthy controls. No significant correlation was observed between the abnormal ReHo values in any of the brain regions of the patients with BMD.Support vector machine (SVM) analyses revealed that the ReHo values in the right STG for distinguishing patients from healthy controls showed an accuracy of 91.89%, a sensitivity of 75.68%, and a specificity of 83.78%. The ReHo values in the left cerebellum vermis I/vermis II/parahippocampal gyrus/brainstem indicated an accuracy of 78.38%, a sensitivity of 75.68%, and a specificity of 81.08%. Conclusion: This study further confirms the abnormal brain activities in extensive regions, and these brain regions are primarily located in the fronto–temporal–occipital circuit and the cerebellum vermis of patients with BD. The regional neural activity in the right STG and the left cerebellum vermis I/vermis II/parahippocampal gyrus/brainstem may serve as potential imaging markers to distinguish patients with BD from healthy controls. [ABSTRACT FROM AUTHOR]

Background: Medical comorbidities in people with mental disorders have recently gained more attention. People with bipolar disorder (BD) often have comorbid low bone mass, which is associated with increased fracture risk and related severe outcomes. However, few clinical studies on bone metabolism in BD patients are available. This study was designed to assess bone mineral density (BMD) and related influencing factors in a sample of newly diagnosed, drug-naïve individuals with BD and age- and sex-matched healthy controls. Methods: Sixty-one drug-naïve individuals with BD (DSM-V) and 95 healthy volunteers had their lumbar spine (L1–L4) and left hip (Neck/Troch/Ward's) BMD determined by dual-energy X-ray absorptiometry. Besides, sociodemographic and clinical assessment were collected. Between-group comparisons and within subgroup analysis were performed. Results: Drug-naïve patients with BD had significantly lower BMD in comparison to healthy controls in multiple sites (L1, L3, Neck, Troch, Ward's, and total hip). On subgroup analysis, overweight individuals with BD had higher bone mass, while females presented reduced BMD. Binary logistic regression showed that low BMD in multiple regions was associated with BD diagnosis, body mass index (BMI), gender, and age. Conclusion: Drug-naïve individuals with BD have lower BMD when compared to an age- and gender-matched healthy control sample. Low BMI and female gender are factors associated with this outcome. The underlying pathological mechanisms of BD comorbid with osteoporosis should be further explored. Clinical Trial Registration: www.chictr.org.cn , identifier ChiCTR190002137. [ABSTRACT FROM AUTHOR]

The microstructure of rapidly quenched A1-Mn alloys were studied by TEM and SEM. The icosahedral phase in AI-Mn alloys was observed to show various types of fractal morphologies, which may be classified into four kinds: 1) dendritic shape, 2) flower-like shape, 3) granular shape and 4) grain-oscillation shape. After being digitized by a computer, the fractal dimensions (D) of these morphologies were calculated. Based on the traditional diffusion limited aggregation (DLA) model computer simulations were made with two-seeded and many-seeded clusters, which reflect the growing mechanism of some fractal structures in A1-Mn alloys. It is suggested that these fractal structures are formed by many icosahedral particles about 20 nm in size aggregating during the rapid quenching process. [ABSTRACT FROM AUTHOR]