Major depressive disorder (MDD) is a leading cause of disability worldwide. Investigating early-stage alterations in cerebral intrinsic activity among drug-naive patients may enhance our understanding of MDD’s neurobiological mechanisms and contribute to early diagnosis and intervention.

To examine alterations in the amplitude of low-frequency fluctuation (ALFF) in first-episode, drug-naive MDD individuals and explore associations between ALFF changes and clinical parameters, including depression severity and illness duration.

A total of 30 first-episode, drug-naive MDD individuals (mean illness duration 14 weeks) and 52 healthy controls were included in this study. Resting-state functional magnetic resonance imaging was used to obtain whole-brain ALFF measurements. Voxel-based ALFF maps were compared between MDD and healthy control groups using a two-sample t-test. Simple regression analysis was performed to assess associations between ALFF and clinical measures, including Hamilton Rating Scale for Depression (HAMD) scores and illness duration.

MDD individuals exhibited significantly increased ALFF in the dorsal anterior cingulate cortex and vermal subregion V3 of the cerebellum. Additionally, ALFF in the right dorsolateral prefrontal cortex was negatively correlated with HAMD scores (r = –0.591, P < 0.001). However, no significant association was found between ALFF and illness duration.

This study demonstrates early-stage ALFF alterations in drug-naive MDD patients, particularly in brain regions implicated in cognitive and emotional regulation. These findings suggest potential neuroimaging biomarkers for the early diagnosis and intervention of MDD.

The rural-oriented tuition-waived medical education program in China, started in 2010, provides free medical education to students committed to serving in rural areas to address medical staff shortages. Despite its success in training and deploying graduates, retaining them post-obligation remains challenging. This study explores the mechanisms behind the turnover intentions of rural-oriented medical students in Western China, offering insights for their retention.

Semi-structured interviews were conducted with 47 rural-oriented medical students and 30 health clinic directors in Nanning City. Interview data were analysed using grounded theory, and open, axial and selective coding was applied.

Through three levels of coding analysis, 34 tree nodes, 13 sub-categories and 3 main categories were identified from the interviews with rural-oriented medical students and health clinic directors. 3 main categories were Subjective Norms, Behavioural Attitudes, and Perceived Behavioural Control.

A model of turnover intention among rural-oriented medical students was developed. This model can serve as a valuable reference for future policy optimization concerning China’s rural order-directed medical students.

The emotion regulation network (ERN) in the brain provides a framework for understanding the neuropathology of affective disorders. Although previous neuroimaging studies have investigated the neurobiological correlates of the ERN in major depressive disorder (MDD), whether patients with MDD exhibit abnormal functional connectivity (FC) patterns in the ERN and whether the abnormal FC in the ERN can serve as a therapeutic response signature remain unclear.

A large functional magnetic resonance imaging dataset comprising 709 patients with MDD and 725 healthy controls (HCs) recruited across five sites was analyzed. Using a seed-based FC approach, we first investigated the group differences in whole-brain resting-state FC of the 14 ERN seeds between participants with and without MDD. Furthermore, an independent sample (45 MDD patients) was used to evaluate the relationship between the aforementioned abnormal FC in the ERN and symptom improvement after 8 weeks of antidepressant monotherapy.

Compared to the HCs, patients with MDD exhibited aberrant FC between 7 ERN seeds and several cortical and subcortical areas, including the bilateral middle temporal gyrus, bilateral occipital gyrus, right thalamus, calcarine cortex, middle frontal gyrus, and the bilateral superior temporal gyrus. In an independent sample, these aberrant FCs in the ERN were negatively correlated with the reduction rate of the HAMD17 score among MDD patients.

These results might extend our understanding of the neurobiological underpinnings underlying unadaptable or inflexible emotional processing in MDD patients and help to elucidate the mechanisms of therapeutic response.

In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion.

To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities. We hypothesize that individualized ALFF abnormalities can be portrayed as a unique linear combination of shared differential factors. Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization.

Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability.

This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.

Numerous studies of resting-state functional imaging and voxel-based morphometry (VBM) have revealed differences in specific brain regions of patients with bipolar disorder (BD), but the results have been inconsistent.

A whole-brain voxel-wise meta-analysis was conducted on resting-state functional imaging and VBM studies that compared differences between patients with BD and healthy controls using Seed-based d Mapping with Permutation of Subject Images software.

A systematic literature search identified 51 functional imaging studies (1842 BD and 2190 controls) and 83 VBM studies (2790 BD and 3690 controls). Overall, patients with BD displayed increased resting-state functional activity in the left middle frontal gyrus, right inferior frontal gyrus (IFG) extending to the right insula, right superior frontal gyrus and bilateral striatum, as well as decreased resting-state functional activity in the left middle temporal gyrus extending to the left superior temporal gyrus and post-central gyrus, left cerebellum, and bilateral precuneus. The meta-analysis of VBM showed that patients with BD displayed decreased VBM in the right IFG extending to the right insula, temporal pole and superior temporal gyrus, left superior temporal gyrus extending to the left insula, temporal pole, and IFG, anterior cingulate cortex, left superior frontal gyrus (medial prefrontal cortex), left thalamus, and right fusiform gyrus.

The multimodal meta-analyses suggested that BD showed similar patterns of aberrant brain activity and structure in the insula extending to the temporal cortex, fronto-striatal-thalamic, and default-mode network regions, which provide useful insights for understanding the underlying pathophysiology of BD.

Major depressive disorder (MDD) is a clinically and biologically heterogeneous syndrome. Identifying discrete subtypes of illness with distinguishing neurobiological substrates and clinical features is a promising strategy for guiding personalised therapeutics.

This study aimed to identify depression subtypes with correlated patterns of functional network connectivity and clinical symptoms by clustering patients according to a weighted linear combination of both features in a relatively large, medication-naïve depression sample.

We recruited 115 medication-naïve adults with MDD and 129 matched healthy controls, and evaluated all participants with magnetic resonance imaging. We used regularised canonical correlation analysis to identify component mapping relationships between functional network connectivity and symptom profiles, and K-means clustering was used to define distinct subtypes of patients.

Two subtypes of MDD were identified: insomnia-dominated subtype 1 and anhedonia-dominated subtype 2. Subtype 1 was characterised by abnormal hyperconnectivity within the ventral attention network and sleep maintenance insomnia. Subtype 2 was characterised by abnormal hypoconnectivity in the subcortical and dorsal attention networks, and prominent anhedonia symptoms.

Our study identified two distinct subtypes of patients with specific neurobiological and clinical symptom profiles. These findings advance understanding of the biological and clinical heterogeneity of MDD, offering a pathway for defining categorical subtypes of illness via consideration of both biological and clinical features.

Schizophrenia is considered a polygenic disorder. People with schizophrenia and those with genetic high risk of schizophrenia (GHR) have presented with similar neurodevelopmental deficits in hemispheric asymmetry. The potential associations between neurodevelopmental abnormalities and schizophrenia-related risk genes in both schizophrenia and those with GHR remains unclear.

To investigate the shared and specific alternations to the structural network in people with schizophrenia and those with GHR. And to identify an association between vulnerable structural network alternation and schizophrenia-related risk genes.

A total of 97 participants with schizophrenia, 79 participants with GHR and 192 healthy controls, underwent diffusion tensor imaging (DTI) scans at a single site. We used graph theory to characterise hemispheric and whole-brain structural network topological metrics. For 26 people in the schizophrenia group and 48 in the GHR group with DTI scans we also calculated their schizophrenia-related polygenic risk scores (SZ-PRSs). The correlations between alterations to the structural network and SZ-PRSs were calculated. Based on the identified genetic–neural association, bioinformatics enrichment was explored.

There were significant hemispheric asymmetric deficits of nodal efficiency, global and local efficiency in the schizophrenia and GHR groups. Hemispheric asymmetric deficit of local efficiency was significantly positively correlated with SZ-PRSs in the schizophrenia and GHR groups. Bioinformatics enrichment analysis showed that these risk genes may be linked to signal transduction, neural development and neuron structure. The schizophrenia group showed a significant decrease in the whole-brain structural network.

The shared asymmetric deficits in people with schizophrenia and those with GHR, and the association between anomalous asymmetry and SZ-PRSs suggested a vulnerability imaging marker regulated by schizophrenia-related risk genes. Our findings provide new insights into asymmetry regulated by risk genes and provides a better understanding of the genetic–neural pathological underpinnings of schizophrenia.

Inflammation might play a role in bipolar disorder (BD), but it remains unclear the relationship between inflammation and brain structural and functional abnormalities in patients with BD. In this study, we focused on the alterations of functional connectivity (FC), peripheral pro-inflammatory cytokines and their correlations to investigate the role of inflammation in FC in BD depression.

In this study, 42 unmedicated patients with BD II depression and 62 healthy controls (HCs) were enrolled. Resting-state-functional magnetic resonance imaging was performed in all participants and independent component analysis was used. Serum levels of Interleukin-6 (IL-6) and Interleukin-8 (IL-8) were measured in all participants. Correlation between FC values and IL-6 and IL-8 levels in BD was calculated.

Compared with the HCs, BD II patients showed decreased FC in the left orbitofrontal cortex (OFC) implicating the limbic network and the right precentral gyrus implicating the somatomotor network. BD II showed increased IL-6 (p = 0.039), IL-8 (p = 0.002) levels. Moreover, abnormal FC in the right precentral gyrus were inversely correlated with the IL-8 (r = −0.458, p = 0.004) levels in BD II. No significant correlation was found between FC in the left OFC and cytokines levels.

Our findings that serum IL-8 levels are associated with impaired FC in the right precentral gyrus in BD II patients suggest that inflammation might play a crucial role in brain functional abnormalities in BD.

To assess correlations between cruciferous vegetable intake and urinary isothiocyanate (ITC) level, in addition to glutathione S-transferase (GST) genotypes and other individual factors.

The study included cohort participants whose urinary ITC levels had been previously ascertained. Urinary ITC was assessed using HPLC. Usual dietary intake of cruciferous vegetables was assessed using a validated FFQ and total dietary ITC intake was calculated. Recent cruciferous vegetable intake was determined. GST genotypes were assessed using duplex real-time quantitative PCR assays. Spearman correlations were calculated between the covariates and urinary ITC levels and linear regression analyses were used to calculate the mean urinary ITC excretion according to GST genotype.

Urban city in China.

The study included 3589 women and 1015 men from the Shanghai Women’s and Men’s Health Studies.

Median urinary ITC level was 1·61 nmol/mg creatinine. Self-reported usual cruciferous vegetable intake was weakly correlated with urinary ITC level (rs=0·1149; P<0·0001), while self-reported recent intake was more strongly correlated with urinary ITC (rs=0·2591; P<0·0001). Overall, the GST genotypes were not associated with urinary ITC level, but significant differences according to genotype were observed among current smokers and participants who provided an afternoon urine sample. Other factors, including previous gastrectomy or gastritis, were also related to urinary ITC level.

The study suggests that urinary secretion of ITC may provide additional information on cruciferous vegetable intake and that GST genotypes are related to urinary ITC level only in some subgroups.