Convergence and divergence in neurostructural signatures of unipolar and bipolar depressions: Insights from surface-based morphometry and prospective follow-up.

BACKGROUND: Bipolar disorder (BD) is often misidentified as unipolar depression (UD) during its early stages, typically until the onset of the first manic episode. This study aimed to explore both shared and unique neurostructural changes in patients who transitioned from UD to BD during follow-up, as compared to those with UD. METHODS: This study utilized high-resolution structural magnetic resonance imaging (MRI) to collect brain data from individuals initially diagnosed with UD. During the average 3-year follow-up, 24 of the UD patients converted to BD (cBD). For comparison, the study included 48 demographically matched UD patients who did not convert and 48 healthy controls. The MRI data underwent preprocessing using FreeSurfer, followed by surface-based morphometry (SBM) analysis to identify cortical thickness (CT), surface area (SA), and cortical volume (CV) among groups. RESULTS: The SBM analysis identified shared neurostructural characteristics between the cBD and UD groups, specifically thinner CT in the right precentral cortex compared to controls. Unique to the cBD group, there was a greater SA in the right inferior parietal cortex compared to the UD group. Furthermore, no significant correlations were observed between cortical morphological measures and cognitive performance and clinical features in the cBD and UD groups. LIMITATIONS: The sample size is relatively small. CONCLUSIONS: Our findings suggest that while cBD and UD exhibit some common alterations in cortical macrostructure, numerous distinct differences are also present. These differences offer valuable insights into the neuropathological underpinnings that distinguish these two conditions.

Altered individual gray matter structural covariance networks in early abstinence patients with alcohol dependence.

While alterations in cortical thickness have been widely observed in individuals with alcohol dependence, knowledge about cortical thickness-based structural covariance networks is limited. This study aimed to explore the topological disorganization of structural covariance networks based on cortical thickness at the single-subject level among patients with alcohol dependence. Structural imaging data were obtained from 61 patients with alcohol dependence during early abstinence and 59 healthy controls. The single-subject structural covariance networks were constructed based on cortical thickness data from 68 brain regions and were analyzed using graph theory. The relationships between network architecture and clinical characteristics were further investigated using partial correlation analysis. In the structural covariance networks, both patients with alcohol dependence and healthy controls displayed small-world topology. However, compared to controls, alcohol-dependent individuals exhibited significantly altered global network properties characterized by greater normalized shortest path length, greater shortest path length, and lower global efficiency. Patients exhibited lower degree centrality and nodal efficiency, primarily in the right precuneus. Additionally, scores on the Alcohol Use Disorder Identification Test were negatively correlated with the degree centrality and nodal efficiency of the left middle temporal gyrus. The results of this correlation analysis did not survive after multiple comparisons in the exploratory analysis. Our findings may reveal alterations in the topological organization of gray matter networks in alcoholism patients, which may contribute to understanding the mechanisms of alcohol addiction from a network perspective.

The volume of gray matter mediates the relationship between glucolipid metabolism and neurocognition in first-episode, drug-naïve patients with schizophrenia.

We aimed to examine the hypotheses that glucolipid metabolism is linked to neurocognition and gray matter volume (GMV) and that GMV mediates the association of glucolipid metabolism with neurocognition in first-episode, drug-naïve (FEDN) patients with schizophrenia. Parameters of glucolipid metabolism, neurocognition, and magnetic resonance imaging were assessed in 63 patients and 31 controls. Compared to controls, patients exhibited higher levels of fasting glucose, triglyceride, and insulin resistance index, lower levels of cholesterol and high-density lipoprotein cholesterol, poorer neurocognitive functions, and decreased GMV in the bilateral insula, left middle occipital gyrus, and left postcentral gyrus. In the patient group, triglyceride levels and the insulin resistance index exhibited a negative correlation with Rapid Visual Information Processing (RVP) mean latency, a measure of attention within the Cambridge Neurocognitive Test Automated Battery (CANTAB), while showing a positive association with GMV in the right insula. The mediation model revealed that triglyceride and insulin resistance index had a significant positive indirect (mediated) influence on RVP mean latency through GMV in the right insula. Glucolipid metabolism was linked to both neurocognitive functions and GMV in FEDN patients with schizophrenia, with the effect pattern differing from that observed in chronic schizophrenia or schizophrenia comorbid with metabolic syndrome. Moreover, glucolipid metabolism might indirectly contribute to neurocognitive deficits through the mediating role of GMV in these patients.

Interactions between overweight/obesity and alcohol dependence impact human brain white matter microstructure: evidence from DTI.

There is inconsistent evidence for an association of obesity with white matter microstructural alterations. Such inconsistent findings may be related to the cumulative effects of obesity and alcohol dependence. This study aimed to investigate the possible interactions between alcohol dependence and overweight/obesity on white matter microstructure in the human brain. A total of 60 inpatients with alcohol dependence during early abstinence (44 normal weight and 16 overweight/obese) and 65 controls (42 normal weight and 23 overweight/obese) were included. The diffusion tensor imaging (DTI) measures [fractional anisotropy (FA) and radial diffusivity (RD)] of the white matter microstructure were compared between groups. We observed significant interactive effects between alcohol dependence and overweight/obesity on DTI measures in several tracts. The DTI measures were not significantly different between the overweight/obese and normal-weight groups (although widespread trends of increased FA and decreased RD were observed) among controls. However, among the alcohol-dependent patients, the overweight/obese group had widespread reductions in FA and widespread increases in RD, most of which significantly differed from the normal-weight group; among those with overweight/obesity, the alcohol-dependent group had widespread reductions in FA and widespread increases in RD, most of which were significantly different from the control group. This study found significant interactive effects between overweight/obesity and alcohol dependence on white matter microstructure, indicating that these two controllable factors may synergistically impact white matter microstructure and disrupt structural connectivity in the human brain.

Disrupted white matter structural networks in individuals with alcohol dependence.

Previous diffusion tensor imaging (DTI) studies have demonstrated widespread white matter microstructure damage in individuals with alcoholism. However, very little is known about the alterations in the topological architecture of white matter structural networks in alcohol dependence (AD). This study included 67 AD patients and 69 controls. The graph theoretical analysis method was applied to examine the topological organization of the white matter structural networks, and network-based statistics (NBS) were employed to detect structural connectivity alterations. Compared to controls, AD patients exhibited abnormal global network properties characterized by increased small-worldness, normalized clustering coefficient, clustering coefficient, and shortest path length; and decreased global efficiency and local efficiency. Further analyses revealed decreased nodal efficiency and degree centrality in AD patients mainly located in the default mode network (DMN), including the precuneus, anterior cingulate and paracingulate gyrus, median cingulate and paracingulate gyrus, posterior cingulate gyrus, and medial part of the superior frontal gyrus. Furthermore, based on NBS approaches, patients displayed weaker subnetwork connectivity mainly located in the region of the DMN. Additionally, altered network metrics were correlated with intelligence quotient (IQ) scores and global assessment function (GAF) scores. Our results may reveal the disruption of whole-brain white matter structural networks in AD individuals, which may contribute to our comprehension of the underlying pathophysiological mechanisms of alcohol addiction at the level of white matter structural networks.

Efficacy, toxicity and prognostic factors of pyrotinib­involved neoadjuvant therapy in HER2­positive breast cancer: A retrospective study.

Pyrotinib is a novel irreversible tyrosine kinase inhibitor targeting the human epidermal growth factor receptor (HER), whose efficacy in treating metastatic HER2-positive (HER2+) breast cancer has been confirmed. The present study aimed to explore the efficacy, safety and prognostic factors of pyrogenic-involved neoadjuvant therapy in patients with HER2+ breast cancer. A total of 49 patients with HER2+ breast cancer who received pyrotinib-neoadjuvant therapy were recruited. All patients received pyrotinib plus chemotherapy with or without trastuzumab neoadjuvant treatment for six cycles (21 days/cycle). Concerning the clinical response, 4 (8.2%), 36 (73.4%) and 9 (18.4%) patients achieved complete response, partial response and stable disease after 6-cycle pyrotinib-neoadjuvant treatment, respectively; the objective response rate and disease control rate reached 81.6 and 100.0%, respectively. Concerning the pathological response, 23 (46.9%), 12 (24.5%), 12 (24.5%) and 2 (4.1%) patients were evaluated as Miller-Payne grade 5, 4, 3 and 2, respectively. In addition, 23 (46.9%) patients achieved pathological complete response (pCR) in the breast tissue, 40 (81.6%) patients achieved pCR in lymph nodes, while 22 (44.9%) patients obtained total pCR (tpCR). Further multivariate logistic regression analysis demonstrated that pyrotinib plus trastuzumab and chemotherapy (vs. pyrotinib plus chemotherapy) was independently correlated with increased tpCR (P=0.048). The most frequent adverse events included diarrhea (81.6%), anemia (69.4%), nausea and vomiting (63.3%), and fatigue (51.0%). The majority of the adverse events were mild and controllable. In conclusion, pyrotinib-neoadjuvant therapy presented optimal efficacy and mild toxicity in patients with HER2+ breast cancer, whose efficacy was affected by the combination treatment with trastuzumab.

Automated Digital Interventions and Smoking Cessation: Systematic Review and Meta-analysis Relating Efficiency to a Psychological Theory of Intervention Perspective.

BACKGROUND: Smoking remains a highly significant preventable global public health problem. In this context, digital interventions offer great advantages in terms of a lack of biological side effects, possibility of automatic delivery, and consequent human resource savings relative to traditional interventions. Such interventions have been studied in randomized controlled trials (RCTs) but have not been systematically reviewed with the inclusion of text-based and multiplatform-based interventions. In addition, this area has not been evaluated from the perspective of the psychological theoretical basis of intervention. OBJECTIVE: The aim of this paper is to assess the efficiency of digital interventions in RCT studies of smoking cessation and to evaluate the effectiveness of the strategies used for digital interventions. METHODS: An electronic search of RCTs was conducted using PubMed, Embase, and the Cochrane Library by June 30, 2021. Eligible studies had to compare automated digital intervention (ADI) to the use of a self-help guideline or no intervention. Participants were current smokers (aged 16 years or older). As the main outcome, abstinence after endpoint was extracted from the studies. Systematic review and meta-analysis were conducted to assess the efficiency of ADIs. Metaregressions were conducted to assess the relationship between intervention theory and effectiveness. RESULTS: A total of 19 trials (15,472 participants) were included in the analysis. The overall abstinence rate (95% CI) at the endpoint was 17.8% (17.0-18.7). The overall risk ratio of the intervention group compared to the controls at the endpoint was 17.8% (17.0-18.7). Cochrane risk-of-bias tool for randomized trials (ROB 2) suggested that most of the studies had a low risk of bias (56.3%). Psychological theory-related constructs or predictors, which refer to other theory-based concepts (rather than only behavioral theory) such as craving or anxiety, are associated with effectiveness. CONCLUSIONS: This study found that ADI had a clear positive effect compared to self-help guidelines or to no intervention, and effectiveness was associated with theory-related constructs or predictors. ADIs should be promoted by policy makers and clinical practitioners to address the huge gap between the need for smoking cessation and availability of traditional treatment resources. Possible increases in ADI efficiency may be achieved by optimally integrating psychotherapeutic theories and techniques. TRIAL REGISTRATION: PROSPERO CRD42021256593; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=256593.

The metabolic effects of antipsychotics in the early stage of treatment in first-episode patients with schizophrenia: A real-world study in a naturalistic setting.

OBJECTIVE: This study aims to better characterize the metabolic effects of antipsychotics in the early stage of treatment in first-episode patients with schizophrenia. METHODS: We performed a retrospective real-world study in a naturalistic setting that included inpatients with first-episode drug-naïve schizophrenia; metabolic profiles were measured at baseline and 2 weeks and 4 weeks after antipsychotic treatment. The metabolic profiles of medicated patients with first-episode schizophrenia were also included. RESULTS: Insulin resistance, based on the ratio of triglycerides to high-density lipoprotein cholesterol (TG/HDL-C), increased significantly after 2 weeks of antipsychotic treatment, whereas fasting glucose (FG) decreased significantly. Regarding lipid metabolism, triglycerides (TG), cholesterol (CHOL) and low-density lipoprotein cholesterol (LDL-C) increased significantly after 2 weeks of antipsychotic treatment; however, high-density lipoprotein cholesterol (HDL-C) decreased significantly after 4 weeks of antipsychotic treatment. There were no statistically significant differences between the antipsychotic groups in any of the metabolic parameters evaluated. CONCLUSION: Our study revealed that insulin resistance and lipid metabolic abnormalities occurred as early as two weeks after the initiation of antipsychotic treatment. Our findings suggest that metabolic profiles should been monitored in the early stage of antipsychotics treatment in clinical practice. Further research is needed to explore the underlying mechanisms of the short-term effects of antipsychotics on metabolic parameters.