The association between executive dysfunction, brain dysconnectivity, and inflammation is a prominent feature across major psychiatric disorders (MPDs), schizophrenia, bipolar disorder, and major depressive disorder. A dimensional approach is warranted to delineate their mechanistic interplay across MPDs.

This single site study included a total of 1543 participants (1058 patients and 485 controls). In total, 1169 participants underwent diffusion tensor and resting-state functional magnetic resonance imaging (745 patients and 379 controls completed the Wisconsin Card Sorting Test). Fractional anisotropy (FA) and regional homogeneity (ReHo) assessed structural and functional connectivity, respectively. Pro-inflammatory cytokine levels [interleukin (IL)-1β, IL-6, and tumor necrosis factor-α] were obtained in 325 participants using blood samples collected with 24 h of scanning. Group differences were determined for main measures, and correlation and mediation analyses and machine learning prediction modeling were performed.

Executive deficits were associated with decreased FA, increased ReHo, and elevated IL-1β and IL-6 levels across MPDs, compared to controls. FA and ReHo alterations in fronto-limbic-striatal regions contributed to executive deficits. IL-1β mediated the association between FA and cognition, and IL-6 mediated the relationship between ReHo and cognition. Executive cognition was better predicted by both brain connectivity and cytokine measures than either one alone for FA-IL-1β and ReHo-IL-6.

Transdiagnostic associations among brain connectivity, inflammation, and executive cognition exist across MPDs, implicating common neurobiological substrates and mechanisms for executive deficits in MPDs. Further, inflammation-related brain dysconnectivity within fronto-limbic-striatal regions may represent a transdiagnostic dimension underlying executive dysfunction that could be leveraged to advance treatment.

To investigate the spiritual care needs and associated influencing factors among elderly inpatients with stroke, and to examine the correlations among spiritual care needs, spiritual well-being, self-perceived burden, self-transcendence, and social support.

A cross-sectional quantitative design was implemented, and the STROBE Checklist was used as the foundation of the study. A convenience sample of 458 elderly inpatients with stroke was selected from three hospitals in China. The sociodemographic characteristics questionnaire, the Nurse Spiritual Therapeutics Scale, the Functional Assessment of Chronic Illness Therapy—Spiritual Well-being, the Self-Perceived Burden Scale, the Chinese Self-Transcendence Scale, and the Perceived Social Support Scale were used. Descriptive statistics, correlation, Student's t-test, ANOVA, non-parametric, and multiple linear regression analyses were used to analyze the data.

The total score of spiritual care needs was 29.82 ± 7.65. Spiritual care needs were positively correlated with spiritual well-being (r = 0.709, p < 0.01), self-transcendence (r = 0.710, p < 0.01), and social support (r = 0.691, p < 0.01), whereas being negatively correlated with self-perceived burden (r = −0.587, p < 0.01). Religious beliefs, educational level, residence place, disease course, spiritual well-being, self-perceived burden, self-transcendence, and social support were found to be the main influencing factors.

The spiritual care needs were prevalent and moderate. It is suggested that nurses should enhance spiritual care knowledge and competence, take targeted spiritual care measures according to inpatients’ individual personality traits or characteristics and differences of patients, reduce their self-perceived burden and improve their spiritual well-being, self-transcendence and social support in multiple ways and levels, so as to meet their spiritual care needs to the greatest extent and enhance their spiritual comfort.

Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia.

To identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers.

We used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites.

We found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19–85.74%; sensitivity, 75.31–89.29% and area under the receiver operating characteristic curve, 0.797–0.909.

These results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.

The significance of spiritual care competence among nurses has been emphasized across countries and cultures in many studies. However, there were few studies on correlations among spiritual care competence, spiritual care perceptions, and spiritual health of nurses in China.

To investigate spiritual care competence, spiritual care perceptions, and spiritual health, and examine the correlations among spiritual care competence, spiritual care perceptions and spiritual health, and the mediating role of spiritual health between other two variables of Chinese nurses.

A cross-sectional and correlational design was implemented, and the STROBE Checklist was used to report the study. A convenience sample of 2,181 nurses were selected from 17 hospitals in 3 provinces, China. Participants provided data on sociodemographic by completing the Chinese Version of the Spiritual Care Competence Scale, the Chinese Version of the Spiritual Care-Giving Scale, and the Spiritual Health Scale Short Form. Descriptive statistics, univariate, multiple linear regression, and Pearson correlation analysis were used to analyze data.

The total scores of spiritual care competence, spiritual care perceptions, and spiritual health were 58.25 ± 16.21, 144.49 ± 16.87, and 84.88 ± 10.57, respectively, which both were moderate. Spiritual care competence was positively correlated with spiritual care perceptions (r = 0.653, p < 0.01) and spiritual health (r = 0.587, p < 0.01). And spiritual health played a mediating role between the other two variables (accounting for 35.6%).

The spiritual care competence, spiritual care perceptions, and spiritual health of Chinese nurses need to be improved. It is recommended that nursing managers should pay attention to spiritual care education of nurses, and improve spiritual care perceptions and spiritual health in multiple ways, so as to improve their spiritual care competence and to maximize the satisfy spiritual care needs of patients in China.

Based on hubs of neural circuits associated with addiction and their degree centrality (DC), this study aimed to construct the addiction-related brain networks for patients diagnosed with heroin dependence undertaking stable methadone maintenance treatment (MMT) and further prospectively identify the ones at high risk for relapse with cluster analysis.

Sixty-two male MMT patients and 30 matched healthy controls (HC) underwent brain resting-state functional MRI data acquisition. The patients received 26-month follow-up for the monthly illegal-drug-use information. Ten addiction-related hubs were chosen to construct a user-defined network for the patients. Then the networks were discriminated with K-means-clustering-algorithm into different groups and followed by comparative analysis to the groups and HC. Regression analysis was used to investigate the brain regions significantly contributed to relapse.

Sixty MMT patients were classified into two groups according to their brain-network patterns calculated by the best clustering-number-K. The two groups had no difference in the demographic, psychological indicators and clinical information except relapse rate and total heroin consumption. The group with high-relapse had a wider range of DC changes in the cortical−striatal−thalamic circuit relative to HC and a reduced DC in the mesocorticolimbic circuit relative to the low-relapse group. DC activity in NAc, vACC, hippocampus and amygdala were closely related with relapse.

MMT patients can be identified and classified into two subgroups with significantly different relapse rates by defining distinct brain-network patterns even if we are blind to their relapse outcomes in advance. This may provide a new strategy to optimize MMT.

Self-efficacy is a pivotal factor in the etiology and prognosis of major depression. However, longitudinal studies on the relationship between self-efficacy and major depressive disorder (MDD) are scarce. The objectives were to investigate: (1) the associations between self-efficacy and the 1-year and 2-year risks of first onset of MDD and (2) the associations between self-efficacy and the 1-year and 2-year risks of the persistence/recurrence of MDD, in a sample of first-year university students.

We followed 8079 first-year university students for 2 years from April 2018 to October 2020. MDD was ascertained by the Chinese version of the Composite International Diagnostic Interview (CIDI-3.0) based on self-report. Self-efficacy was measured by the 10-item General Self-efficacy (GSE) scale. Random effect logistic regression modeling was used to estimate the associations.

Among participants without a lifetime MDD, the data showed that participants with high baseline GSE scores were associated with a higher risk of first onset of MDD over 2 years [odds ratio (OR) 1.04, 95% confidence interval (CI) 1.01–1.08]. Among those with a lifetime MDD, participants with high baseline GSE scores were less likely to have had a MDD over 2 years (OR 0.93, 95% CI 0.88–0.99) compared to others.

A high level of GSE may be protective of the risk of persistent or recurrent MDD. More longitudinal studies in university students are needed to further investigate the impact of GSE on the first onset of MDD.

The significance of spiritual care needs among chronic diseases patients has been emphasized across countries and cultures in many studies. However, there were few studies on spiritual care needs among elderly patients with moderate-to-severe chronic heart failure (CHF) in China.

To investigate spiritual care needs and associated influencing factors among elderly patients with moderate-to-severe CHF, and to examine the relationships among spiritual care needs, self-perceived burden, symptom management self-efficacy, and perceived social support.

A cross-sectional design was implemented, and the STROBE Checklist was used to report the study. A convenience sample of 474 elderly patients with moderate-to-severe CHF were selected from seven hospitals in Tianjin, China. The sociodemographic characteristics questionnaire, the Spiritual Needs Questionnaire Scale, the Self-Perceived Burden Scale, the Self-efficacy for Symptom Management Scale, and the Perceived Social Support Scale were used. Descriptive statistics, univariate, multiple linear regression, and Pearson's correlation analysis were used to analyze data.

The total score of spiritual care needs among 474 elderly patients with moderate-to-severe CHF was 37.95 ± 14.71, which was moderate. Religious belief, educational background, self-perceived burden, symptom management self-efficacy, and perceived social support were the main factors affecting spiritual care needs, and spiritual care needs were negatively correlated with self-perceived burden (r = −0.637, p < 0.01) and positively correlated with symptom management self-efficacy (r = 0.802, p < 0.01) and social support (r = 0.717, p < 0.01).

The spiritual care needs of elderly patients with moderate-to-severe CHF were moderate, which were influenced by five factors. It is suggested that clinical nurses, families, and society should take targeted spiritual care measures to improve patients’ symptom management self-efficacy and perceived social support from many aspects, and reduce self-perceived burden to meet their spiritual care needs and improve the quality and satisfaction of spiritual care in nursing practice.

We aimed to evaluate the association between coffee and/or tea consumption and breast cancer (BC) risk among premenopausal and postmenopausal women and to conduct a network meta-analysis.

Systematic review and network meta-analysis.

We conducted a systematic review of electronic publications in the last 30 years to identify case–control studies or prospective cohort studies that evaluated the effects of coffee and tea intake.

Forty-five studies that included more than 3 323 288 participants were eligible for analysis. Network meta-analysis was performed to determine the effects of coffee and/or tea consumption on reducing BC risk in a dose-dependent manner and differences in coffee/tea type, menopause status, hormone receptor and the BMI in subgroup and meta-regression analyses. According to the first pairwise meta-analysis, low-dose coffee intake and high-dose tea intake may exhibit efficacy in preventing ER(estrogen receptor)− BC, particularly in postmenopausal women. Then, we performed another pairwise and network meta-analysis and determined that the recommended daily doses were 2–3 cups/d of coffee or ≥5 cups/d of tea, which contained a high concentration of caffeine, particularly in postmenopausal women.

Coffee and tea consumption is not associated with a reduction in the overall BC risk in postmenopausal women and is associated with a potentially lower risk of ER− BC. And the highest recommended dose is 2–3 cups of coffee/d or ≥5 cups of tea/d. They are potentially useful dietary protectants for preventing BC.