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The present study examined the relationships among attention to emotion, emotional clarity, emotion regulation, and job satisfaction, and tested whether the plausible associations between emotional processes (e.g., attention to emotion, emotional clarity) and job satisfaction can be mediated by emotion regulation in a sample of Chinese medical staff. In total, 1,766 medical staff in Guangdong province completed questionnaires including the demographics, the Minnesota Satisfaction Questionnaire, Emotional Clarity, Attention to Emotion, and the Emotion Regulation Questionnaire. Results showed significant direct effect of emotional clarity, but not attention to emotion on job satisfaction. Cognitive reappraisal significantly mediated the associations between emotional processes (e.g., attention to emotion, emotional clarity) and job satisfaction whereas expressive suppression was not a statistically significant mediator. These results suggest that attention to emotion and emotional clarity contribute to job satisfaction by increasing certain emotion regulation strategies such as reappraisal. Intervention or medical education programs targeting enhancing emotional clarity and reappraisal may be beneficial for increasing job satisfaction of medical staff in China. [ABSTRACT FROM AUTHOR]

This study compared American and Chinese caregiving grandparents regarding variables reflecting challenges and resources in dealing with the demands of raising a grandchild. A total of 238 grandparent caregivers in the United States and 106 Chinese grandparent caregivers were sampled and completed research questionnaires for this study. Analyses indicated that after controlling for grandparents' gender, age, health, length of caregiving, and number of grandchildren, main effects for culture were significant for parental efficacy, authoritative parenting style, grandchild negative interpersonal dynamics, role satisfaction, well-being, and attachment to the grandchild. Correlational findings provided further understanding of cross-cultural similarities and differences in grandparent caregiving. Findings are discussed in the context of the globality of grandparent caregiving and the salience of family dynamic and values among Chinese grandparent caregivers. These findings also underscore the lack of supportive services for Chinese grandparents in light of their personal adaptive qualities and the demands of raising a grandchild. [ABSTRACT FROM AUTHOR]

Genome-wide association studies of brain imaging phenotypes are mainly performed in European populations, but other populations are severely under-represented. Here, we conducted Chinese-alone and cross-ancestry genome-wide association studies of 3,414 brain imaging phenotypes in 7,058 Chinese Han and 33,224 white British participants. We identified 38 new associations in Chinese-alone analyses and 486 additional new associations in cross-ancestry meta-analyses at P < 1.46 × 10 -11 for discovery and P < 0.05 for replication. We pooled significant autosomal associations identified by single- or cross-ancestry analyses into 6,443 independent associations, which showed uneven distribution in the genome and the phenotype subgroups. We further divided them into 44 associations with different effect sizes and 3,557 associations with similar effect sizes between ancestries. Loci of these associations were shared with 15 brain-related non-imaging traits including cognition and neuropsychiatric disorders. Our results provide a valuable catalog of genetic associations for brain imaging phenotypes in more diverse populations., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

The ongoing epidemic of SARS-CoV-2 is taking a substantial financial and health toll on people worldwide. Assessing the level and duration of SARS-CoV-2 neutralizing antibody (Nab) would provide key information for government to make sound healthcare policies. Assessed at 3-, 6-, 12-, and 18-month postdischarge, we described the temporal change of IgG levels in 450 individuals with moderate to critical COVID-19 infection. Moreover, a data imputation framework combined with a novel deep learning model was implemented to predict the long-term Nab and IgG levels in these patients. Demographic characteristics, inspection reports, and CT scans during hospitalization were used in this model. Interpretability of the model was further validated with Shapely Additive exPlanation (SHAP) and Gradient-weighted Class Activation Mapping (GradCAM). IgG levels peaked at 3 months and remained stable in 12 months postdischarge, followed by a significant decline in 18 months postdischarge. However, the Nab levels declined from 6 months postdischarge. By training on the cohort of 450 patients, our long-term antibody prediction (LTAP) model could predict long-term IgG levels with relatively high area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1-score, which far exceeds the performance achievable by commonly used models. Several prognostic factors including FDP levels, the percentages of T cells, B cells and natural killer cells, older age, sex, underlying diseases, and so forth, served as important indicators for IgG prediction. Based on these top 15 prognostic factors identified in IgG prediction, a simplified LTAP model for Nab level prediction was established and achieved an AUC of 0.828, which was 8.9% higher than MLP and 6.6% higher than LSTM. The close correlation between IgG and Nab levels making it possible to predict long-term Nab levels based on the factors selected by our LTAP model. Furthermore, our model identified that coagulation disorders and excessive immune response, which indicate disease severity, are closely related to the production of IgG and Nab. This universal model can be used as routine discharge tests to identify virus-infected individuals at risk for recurrent infection and determine the optimal timing of vaccination for general populations., (© 2023 The Authors. Journal of Medical Virology published by Wiley Periodicals LLC.)

Background: Follow-up study of coronavirus disease 2019 (COVID-19) survivors has rarely been reported. We aimed to investigate longitudinal changes in the characteristics of COVID-19 survivors after discharge., Methods: A total of 594 COVID-19 survivors discharged from Tongji Hospital in Wuhan from February 10 to April 30, 2020 were included and followed up until May 17, 2021. Laboratory and radiological findings, pulmonary function tests, electrocardiogram, symptoms and signs were analyzed., Results: 257 (51.2%) patients had at least one symptom at 3 months post-discharge, which decreased to 169 (40.0%) and 138 (28.4%) at 6-month and 12-month visit respectively. During follow-up period, insomnia, chest tightness, and fatigue were the most prevalent symptoms. Most laboratory parameters returned to normal, whereas increased incidence of abnormal liver and renal function and cardiovascular injury was evidenced after discharge. Fibrous stripes (213; 42.4%), pleural thickening and adhesions (188; 37.5%) and enlarged lymph nodes (120; 23.9%) were the most common radiographical findings at 3 months post-discharge. The abnormalities of pulmonary function included obstructive, restrictive, and mixed, which were 5.5%, 4.0%, 0.9% at 6 months post, and 1.9%, 4.7%, 0.2% at 12 months. Electrocardiogram abnormalities occurred in 256 (51.0%) patients at 3 months post-discharge, including arrhythmia, ST-T change and conduction block, which increased to 258 (61.1%) cases at 6-month visit and were maintained at high frequency (242;49.8%) at 12-month visit., Conclusions: Physiological, laboratory, radiological, or electrocardiogram abnormalities, particularly those related to renal, cardiovascular, and liver functions are common in patients who recovered from coronavirus disease 2019 (COVID-19) up to 12 months post-discharge., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America.)

Urbanicity is a growing environmental challenge for mental health. Here, we investigate correlations of urbanicity with brain structure and function, neuropsychology and mental illness symptoms in young people from China and Europe (total n = 3,867). We developed a remote-sensing satellite measure (UrbanSat) to quantify population density at any point on Earth. UrbanSat estimates of urbanicity were correlated with brain volume, cortical surface area and brain network connectivity in the medial prefrontal cortex and cerebellum. UrbanSat was also associated with perspective-taking and depression symptoms, and this was mediated by neural variables. Urbanicity effects were greatest when urban exposure occurred in childhood for the cerebellum, and from childhood to adolescence for the prefrontal cortex. As UrbanSat can be generalized to different geographies, it may enable assessments of correlations of urbanicity with mental illness and resilience globally., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

BACKGROUNDThe coronavirus disease 2019 (COVID-19) rapidly progressed to a global pandemic. Although some patients totally recover from COVID-19 pneumonia, the disease's long-term effects on the brain still need to be explored.METHODSWe recruited 51 patients with 2 subtypes of COVID-19 (19 mild and 32 severe) with no specific neurological manifestations at the acute stage and no obvious lesions on the conventional MRI 3 months after discharge. Changes in gray matter morphometry, cerebral blood flow (CBF), and white matter (WM) microstructure were investigated using MRI. The relationship between brain imaging measurements and inflammation markers was further analyzed.RESULTSCompared with healthy controls, the decrease in cortical thickness/CBF and the changes in WM microstructure were more severe in patients with severe disease than in those with mild disease, especially in the frontal and limbic systems. Furthermore, changes in brain microstructure, CBF, and tract parameters were significantly correlated (P < 0.05) with the inflammatory markers C-reactive protein, procalcitonin, and interleukin 6.CONCLUSIONIndirect injury related to inflammatory storm may damage the brain, altering cerebral volume, CBF, and WM tracts. COVID-19-related hypoxemia and dysfunction of vascular endothelium may also contribute to neurological changes. The abnormalities in these brain areas need to be monitored during recovery, which could help clinicians understand the potential neurological sequelae of COVID-19.FUNDINGNatural Science Foundation of China.

Although emerging data demonstrated mortality of young COVID-19 patients, no data have reported the risk factors of mortality for these young patients, and whether obesity is a risk for young COVID-19 patients remains unknown. We conducted a retrospective study including 13 young patients who died of COVID-19 and 40 matched survivors. Logistic regression was employed to characterize the risk factors of mortality in young obese COVID-19 patients. Most of the young deceased COVID-19 patients were mild cases at the time of admission, but the disease progressed rapidly featured by a higher severity of patchy shadows (100.00% vs 48.70%; P = .006), pleural thickening (61.50% vs 12.80%; P = .012), and mild pericardial effusion (76.90% vs 0.00%; P < .001). Most importantly, the deceased patients manifested higher body mass index (odds ratio [OR] = 1.354; 95% confidence interval [CI] = 1.075-1.704; P = .010), inflammation-related index C-reactive protein (OR = 1.014; 95% CI = 1.003-1.025; P = .014), cardiac injury biomarker hs-cTnI (OR = 1.420; 95% CI = 1.112-1.814; P = .005), and increased coagulation activity biomarker D-dimer (OR = 418.7; P = .047), as compared with that of survivors. Our data support that obesity could be a risk factor associated with high mortality in young COVID-19 patients, whereas aggravated inflammatory response, enhanced cardiac injury, and increased coagulation activity are likely to be the mechanisms contributing to the high mortality., (© 2020 Wiley Periodicals LLC.)

Objectives: In late December 2019, an outbreak of coronavirus disease (COVID-19) in Wuhan, China was caused by a novel coronavirus, newly named severe acute respiratory syndrome coronavirus 2. We aimed to quantify the severity of COVID-19 infection on high-resolution chest computed tomography (CT) and to determine its relationship with clinical parameters., Materials and Methods: From January 11, 2020, to February 5, 2020, the clinical, laboratory, and high-resolution CT features of 42 patients (26-75 years, 25 males) with COVID-19 were analyzed. The initial and follow-up CT, obtained a mean of 4.5 days and 11.6 days from the illness onset were retrospectively assessed for the severity and progression of pneumonia. Correlations among clinical parameters, initial CT features, and progression of opacifications were evaluated with Spearman correlation and linear regression analysis., Results: Thirty-five patients (83%) exhibited a progressive process according to CT features during the early stage from onset. Follow-up CT findings showed progressive opacifications, consolidation, interstitial thickening, fibrous strips, and air bronchograms, compared with initial CT (all P < 0.05). Before regular treatments, there was a moderate correlation between the days from onset and sum score of opacifications (R = 0.68, P < 0.01). The C-reactive protein, erythrocyte sedimentation rate, and lactate dehydrogenase showed significantly positive correlation with the severity of pneumonia assessed on initial CT (Rrange, 0.36-0.75; P < 0.05). The highest temperature and the severity of opacifications assessed on initial CT were significantly related to the progression of opacifications on follow-up CT (P = 0.001-0.04)., Conclusions: Patients with the COVID-19 infection usually presented with typical ground glass opacities and other CT features, which showed significant correlations with some clinical and laboratory measurements. Follow-up CT images often demonstrated progressions during the early stage from illness onset.

The Chinese Imaging Genetics (CHIMGEN) study establishes the largest Chinese neuroimaging genetics cohort and aims to identify genetic and environmental factors and their interactions that are associated with neuroimaging and behavioral phenotypes. This study prospectively collected genomic, neuroimaging, environmental, and behavioral data from more than 7000 healthy Chinese Han participants aged 18-30 years. As a pioneer of large-sample neuroimaging genetics cohorts of non-Caucasian populations, this cohort can provide new insights into ethnic differences in genetic-neuroimaging associations by being compared with Caucasian cohorts. In addition to micro-environmental measurements, this study also collects hundreds of quantitative macro-environmental measurements from remote sensing and national survey databases based on the locations of each participant from birth to present, which will facilitate discoveries of new environmental factors associated with neuroimaging phenotypes. With lifespan environmental measurements, this study can also provide insights on the macro-environmental exposures that affect the human brain as well as their timing and mechanisms of action.