Neuroimaging- and machine-learning-based brain-age prediction of schizophrenia is well established. However, the diagnostic significance and the effect of early medication on first-episode schizophrenia remains unclear.

To explore whether predicted brain age can be used as a biomarker for schizophrenia diagnosis, and the relationship between clinical characteristics and brain-predicted age difference (PAD), and the effects of early medication on predicted brain age.

The predicted model was built on 523 diffusion tensor imaging magnetic resonance imaging scans from healthy controls. First, the brain-PAD of 60 patients with first-episode schizophrenia, 60 healthy controls and 21 follow-up patients from the principal data-set and 40 pairs of individuals in the replication data-set were calculated. Next, the brain-PAD between groups were compared and the correlations between brain-PAD and clinical measurements were analysed.

The patients showed a significant increase in brain-PAD compared with healthy controls. After early medication, the brain-PAD of patients decreased significantly compared with baseline (P < 0.001). The fractional anisotropy value of 31/33 white matter tract features, which related to the brain-PAD scores, had significantly statistical differences before and after measurements (P < 0.05, false discovery rate corrected). Correlation analysis showed that the age gap was negatively associated with the positive score on the Positive and Negative Syndrome Scale in the principal data-set (r = −0.326, P = 0.014).

The brain age of patients with first-episode schizophrenia may be older than their chronological age. Early medication holds promise for improving the patient's brain ageing. Neuroimaging-based brain-age prediction can provide novel insights into the understanding of schizophrenia.

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.

Cognitive impairment is common in late-life depression, which may increase Alzheimer disease (AD) risk. Therefore, we aimed to investigate whether late-life major depressive disorder (MDD) has worse cognition and increases the characteristic AD neuropathology. Furthermore, we carried out a comparison between treatment-resistant depression (TRD) and non-TRD. We hypothesized that patients with late-life depression and TRD may have increased β-amyloid (Aβ) deposits in brain regions responsible for global cognition.

We recruited 81 subjects, including 54 MDD patients (27 TRD and 27 non-TRD) and 27 matched healthy controls (HCs). Neurocognitive tasks were examined, including Mini-Mental State Examination and Montreal Cognitive Assessment to detect global cognitive functions. PET with Pittsburgh compound-B and fluorodeoxyglucose were used to capture brain Aβ pathology and glucose use, respectively, in some patients.

MDD patients performed worse in Montreal Cognitive Assessment (p = 0.003) and had more Aβ deposits than HCs across the brain (family-wise error-corrected p < 0.001), with the most significant finding in the left middle frontal gyrus. Significant negative correlations between global cognition and prefrontal Aβ deposits existed in MDD patients, whereas positive correlations were noted in HCs. TRD patients had significantly more deposits in the left-sided brain regions (corrected p < 0.001). The findings were not explained by APOE genotypes. No between-group fluorodeoxyglucose difference was detected.

Late-life depression, particularly TRD, had increased brain Aβ deposits and showed vulnerability to Aβ deposits. A detrimental role of Aβ deposits in global cognition in patients with late-onset or non-late-onset MDD supported the theory that late-life MDD could be a risk factor for AD.

Few studies have explored the complex relationship of pro- and anti-inflammatory cytokines with cognitive function in adolescents with first-episode schizophrenia, bipolar disorder, or major depressive disorder.

In total, 26, 35, and 29 adolescents with first-episode schizophrenia, bipolar disorder, and major depressive disorder, respectively, and 22 age- and sex-matched controls were included in the current study. Cytokines, namely interleukin (IL)-2, IL-6, tumor necrosis factor (TNF)-α, and C-reactive protein (CRP), were assessed. The Wisconsin Card Sorting Test (WCST) and the working memory task were administered to assess cognitive function.

Using generalized linear models with adjustment for demographic data and clinical symptoms, patients with bipolar disorder were found to exhibit the highest levels of CRP (P = .023), IL-6 (P = .022), and TNF-α (P = .011), and had the lowest IL-2 levels (P = .034) among the four groups. According to the results of the WCST and working memory task, adolescents with schizophrenia exhibited the lowest performance in cognitive function. In addition, among the assessed cytokines, only CRP levels (P = .027) were negatively associated with WCST scores.

Dysregulated pro- and anti-inflammatory cytokines and impaired cognitive functioning were observed in first-episode adolescent-onset schizophrenia, bipolar disorder, and major depressive disorder. The altered cytokine profiles may play important roles in the pathophysiology of schizophrenia, bipolar disorder, and major depressive disorder.

Dysregulated proinflammatory cytokines have been shown to be associated with suicidal behavior. Cognitive deficits in working memory and inhibitory control have been demonstrated in depressed patients and people with suicidal ideation (SI). However, the association between proinflammatory cytokines, SI, and cognitive deficits in patients with major depressive disorder (MDD) remains unclear.

A total of 77 patients with MDD and age-/sex-matched 60 healthy individuals were recruited. MDD patients were divided into two groups: with SI (n = 36) and no SI (n = 41). SI was defined by a score of ≥2 in item 3 of the 17-item Hamilton Rating Scale for Depression. Levels of proinflammatory cytokines, including soluble interleukin-6 receptor, soluble tumor necrosis factor-α receptor type 1, and C-reactive protein (CRP), were measured, and cognitive function was assessed using 2-back task and Go/No-Go task.

Patients with SI had higher levels of CRP than those without SI and controls (P = .007). CRP was positively associated with SI (β = 0.21, P = .037), independent of cognitive function and depressive symptoms. Furthermore, SI was associated with cognitive deficits in working memory and inhibitory control after adjusting for confounding factors (P < .05).

Our findings suggest that higher levels of serum CRP and deficits in working memory and inhibitory control may be associated with higher SI among patients with MDD.

Normative data are essential for neuropsychological evaluations, but they are scarce for Mandarin-speaking populations, despite Mandarin being the language with the most native speakers. Several normative data studies have been reported in recent years for Mandarin speakers, who reside in different countries/regions (e.g., mainland China, Taiwan, and Singapore, etc.). This review aims to serve as a reference guide to appropriate norms when working with a Mandarin-speaking patient and to guide future endeavors in test validation and development in areas where studies to date fall short.

We conducted a systematic review utilizing the PsycInfo, PubMed, and China Knowledge Resource Integrated databases as well as additional literature search through citations. We performed evaluations of the existing norms based on their test selection, cognitive domains covered, sample size, language, regions of participant recruitment, stratification by age/gender/education levels, and reporting of other psychometric properties. We focused on articles that included performance-based tests for adults but excluded those with purely clinical norms or from commercial publishers.

We reviewed 1155 articles found through literature search and identified 43 articles reporting normative data for this population that met our inclusion criteria. Sixty-five distinctive tests and 127 versions were covered. The results are presented within two detailed tables organized by articles and tests, respectively.

We discussed the strengths and limitations of these normative reports. Practitioners are recommended to utilize normative data that most closely approximate a test-taker’s cultural and demographic backgrounds. Limitations of the current review are also discussed.

Recent cannabis exposure has been associated with lower rates of neurocognitive impairment in people with HIV (PWH). Cannabis’s anti-inflammatory properties may underlie this relationship by reducing chronic neuroinflammation in PWH. This study examined relations between cannabis use and inflammatory biomarkers in cerebrospinal fluid (CSF) and plasma, and cognitive correlates of these biomarkers within a community-based sample of PWH.

263 individuals were categorized into four groups: HIV− non-cannabis users (n = 65), HIV+ non-cannabis users (n = 105), HIV+ moderate cannabis users (n = 62), and HIV+ daily cannabis users (n = 31). Differences in pro-inflammatory biomarkers (IL-6, MCP-1/CCL2, IP-10/CXCL10, sCD14, sTNFR-II, TNF-α) by study group were determined by Kruskal–Wallis tests. Multivariable linear regressions examined relationships between biomarkers and seven cognitive domains, adjusting for age, sex/gender, race, education, and current CD4 count.

HIV+ daily cannabis users showed lower MCP-1 and IP-10 levels in CSF compared to HIV+ non-cannabis users (p = .015; p = .039) and were similar to HIV− non-cannabis users. Plasma biomarkers showed no differences by cannabis use. Among PWH, lower CSF MCP-1 and lower CSF IP-10 were associated with better learning performance (all ps < .05).

Current daily cannabis use was associated with lower levels of pro-inflammatory chemokines implicated in HIV pathogenesis and these chemokines were linked to the cognitive domain of learning which is commonly impaired in PWH. Cannabinoid-related reductions of MCP-1 and IP-10, if confirmed, suggest a role for medicinal cannabis in the mitigation of persistent inflammation and cognitive impacts of HIV.

To examine the association between sleep duration in different stages of life and amnestic mild cognitive impairment (aMCI).

A total of 2472 healthy elderly and 505 patients with aMCI in China were included in this study. The study analyzed the association between aMCI and sleep duration in different stages of life.

We compared sleep duration in different stages of life and analyzed the association between Montreal Cognitive Assessment scores and sleep duration by curve estimation. Logistic regression was used to evaluate the association between aMCI and sleep duration.

In the analysis, there were no results proving that sleep duration in youth (P = 0.719, sleep duration < 10 hours; P = 0.999, sleep duration ≥ 10 hours) or midlife (P = 0.898, sleep duration < 9 hours; P = 0.504, sleep duration ≥ 9 hours) had a significant association with aMCI. In the group sleeping less than 7 hours in late life, each hour more of sleep duration was associated with approximately 0.80 of the original risk of aMCI (P = 0.011, odds ratio = 0.80, 95% confidence interval = 0.68–0.95).

Among the elderly sleeping less than 7 hours, there is a decreased risk of aMCI for every additional hour of sleep.

To establish optimal gestational weight gain (GWG) in Chinese pregnant women by Chinese-specific BMI categories and compare the new recommendations with the Institute of Medicine (IOM) 2009 guidelines.

Multicentre, prospective cohort study. Unconditional logistic regression analysis was used to evaluate the OR, 95 % CI and the predicted probabilities of adverse pregnancy outcomes. The optimal GWG range was defined as the range that did not exceed a 1 % increase from the lowest predicted probability in each pre-pregnancy BMI group.

From nine cities in mainland China.

A total of 3731 women with singleton pregnancy were recruited from April 2013 to December 2014.

The optimal GWG (ranges) by Chinese-specific BMI was 15·0 (12·8–17·1), 14·2 (12·1–16·4) and 12·6 (10·4–14·9) kg for underweight, normal weight and overweight pregnant women, respectively. Inappropriate GWG was associated with several adverse pregnancy outcomes. Compared with women gaining weight within our proposed recommendations, women with excessive GWG had higher risk for macrosomia, large for gestational age and caesarean section, whereas those with inadequate GWG had higher risk for low birth weight, small for gestational age and preterm delivery. The comparison between our proposed recommendations and IOM 2009 guidelines showed that our recommendations were comparable with the IOM 2009 guidelines and could well predict the risk of several adverse pregnancy outcomes.

Inappropriate GWG was associated with higher risk of several adverse pregnancy outcomes. Optimal GWG recommendations proposed in the present study could be applied to Chinese pregnant women.

To explore the relationship between parameters of Na and K excretion using 24-h urine sample and mild cognitive impairment (MCI) in general population.

This is a cross-sectional study.

Community-based general population in Emin China.

Totally, 1147 subjects aged ≥18 years were selected to complete the study, with a multistage proportional random sampling method. Cognitive status was assessed with Mini Mental State Examination (MMSE) questionnaire and timed 24-h urine specimens were collected. Finally, 561 participants aged ≥35 years with complete urine sample and MMSE data were included for the current analysis and divided into groups by tertiles of 24-h urinary sodium to potassium ratio (24-h UNa/K) as lowest (T1), middle (T2) and highest (T3) groups.

The MMSE score was significantly lower in T3, compared with the T1 group (26·0 v. 25·0, P = 0·002), and the prevalent MCI was significantly higher in T3 than in T1 group (11·7 % v. 25·8 %, P < 0·001). In multiple linear regression, 24-UNa/K (β: −0·184, 95 % CI −0·319, −0·050, P = 0·007) was negatively associated with MMSE score. In multivariable logistic regression, compared with T1 group, 24-h UNa/K in the T2 and T3 groups showed 2·01 (95 % CI 1·03, 3·93, P = 0·041) and 3·38 (95 % CI 1·77, 6·44, P < 0·001) fold odds for presence of MCI, even after adjustment for confounders. More augmented results were demonstrated in sensitivity analysis by excluding individuals taking anti-hypertensive agents.

Higher 24-h UNa/K is in an independent association with prevalent MCI.

It is important to maintain the psychological well-being of front-line healthcare staff during the coronavirus disease 2019 (COVID-19) pandemic.

To examine COVID-19-related stress and its immediate psychological impact on healthcare staff.

All healthcare staff working in the fever clinic, from 20 January 2020 to 26 March 2020, of a tertiary general hospital were enrolled. Stress management procedures were in place to alleviate concerns about the respondents’ own health and the health of their families, to help them adjust their work and to provide psychological support via a hotline. Qualitative interviews were undertaken and the Sources of Distress and the Impact of Event Scale-Revised (IES-R) were administered.

Among the 102 participants (25 males; median age 30 years, interquartile range (IQR) = 27–36), the median IES-R total score was 3 (IQR = 0–8), and 6 participants (6.0%) scored above the cut-off on the IES-R (≥20). Safety and security were acceptable or better for 92 (90.2%) participants. The top four sources of distress were worry about the health of one's family/others at 0.88 (IQR = 0.25–1.25), worry about the virus spread at 0.50 (IQR = 0.00–1.00), worry about changes in work at 0.50 (IQR = 0.00–1.00) and worry about one's own health at 0.25 (IQR = 0.25–0.75). There was a moderate correlation between the IES-R score and the Sources of Distress score (rho = 0.501, P = 0.001).

The stress levels of healthcare staff in the fever clinic during the COVID-19 epidemic were not elevated. Physio-psychosocial interventions, including fulfilment of basic needs, activation of self-efficacy and psychological support, are helpful and worth recommending in fighting COVID-19.

Although poverty associated with severe mental illness (SMI) has been documented in many studies, little long-term evidence of social drift exists. This study aimed to unravel the poverty transitions among persons with SMI in a fast change community in China.

Two mental health surveys, using the International Classification of Disease (ICD-10), were conducted in the same six townships of Xinjin county, Chengdu, China in 1994 and 2015. A total of 308 persons with SMI identified in 1994 were followed up in 2015. The profiles of poverty transitions were identified and regression modelling methods were applied to determine the predictive factors of poverty transitions.

The poverty rate of persons with SMI increased from 39.9% to 49.4% in 1994 and 2015. A larger proportion of them had fallen into poverty (27.3%) rather than moved out of it (17.8%). Those persons with SMI who had lost work ability, had physical illness and more severe mental disabilities in 1994, as well as those who had experienced negative changes on these factors were more likely to live in persistent poverty or fall into poverty. Higher education level and medical treatment were major protective factors of falling into poverty.

This study shows long-term evidence on the social drift of persons with SMI during the period of rapid social development in China. Further targeted poverty alleviation interventions should be crucial for improving treatment and mental recovery and alleviating poverty related to SMI.