This review delves into brain imaging genomics, an interdisciplinary field merging brain imaging, genomics, and additional biomarkers with clinical data. The primary aim is to uncover new insights into the brain’s phenotypic, genetic, and molecular characteristics. We emphasize recent advances in genome-wide association studies and transcriptome-wide association studies, especially their integration with MRI-derived phenotypes in humans. These studies are crucial for understanding how various factors influence brain structure and function in normal and pathological states. Furthermore, this review highlights imaging transcriptomics progress in non-human primates, essential for elucidating brain organization and improving animal models evolutionarily to bridge gaps in understanding human disorders. We conclude that brain imaging genomics is set to transform research in neurological and psychiatric disorders, owing to its holistic approach that merges advanced genetic analysis with detailed imaging, will deepen our understanding of the brain, and usher in a new epoch in brain imaging research.
RATIONALE AND OBJECTIVES:Accurate preoperative evaluation of human epidermal growth factor receptor 2 (HER2) status is crucial for guiding personalized treatment in gastric cancer (GC). This study aimed to evaluate the clinical value of CT-based multi-subregion habitat radiomics for noninvasive preoperative prediction of HER2 expression. MATERIALS AND METHODS:This retrospective study enrolled 857 pathologically confirmed GC patients from two medical centers. Patients were stratified into HER2-positive and HER2-negative groups according to postoperative pathology. At Center 1, 657 patients were randomly divided into training (n = 460) and testing (n = 197) cohorts (7:3 ratio), while 200 patients from Center 2 served as an external validation (ex-vad) cohort. Radiomics features were extracted from contrast-enhanced venous-phase CT images, and a radiomics score (Radscore) was subsequently generated. Tumor regions of interest underwent unsupervised clustering to define habitat subregions, forming models based on two, three, and four subregions. The optimal habitat model was selected based on predictive accuracy. A combined model integrating the optimal habitat model and key clinical features was subsequently constructed. RESULTS:Six models were developed: clinical, Radscore, Habitat2, Habitat3, Habitat4, and combined (Habitat3 plus clinical variables). In the training cohort, area under the receiver operating characteristic (ROC) curve values were 0.68 (95% confidence intervals (CI), 0.62-0.75), 0.78 (0.73-0.83), 0.75 (0.69-0.81), 0.90 (0.87-0.94), 0.78 (0.73-0.84), and 0.94 (0.91-0.97), respectively. The combined model achieved superior predictive performance in both training, test and ex-vad cohorts, followed by Habitat3. CONCLUSION:The Habitat3 model robustly predicts HER2 expression in GC. The combined model further improves predictive accuracy. SUMMARY STATEMENT:This study developed CT-based radiomics habitat models for predicting HER2 expression in gastric cancer. Habitat3 achieved optimal performance, and its combination with clinical variables yielded superior efficacy and clinical applicability, providing a robust non-invasive tool for preoperative HER2 assessment in gastric cancer.
BACKGROUND:Intervention based on the information-motivation-behavioral skills (IMB) model have been applied in the self-management of patients with chronic diseases and achieved ideal results, but there were few reports on the application of this model in PD patients. OBJECTIVE:To evaluate the effectiveness of the IMB model-based intervention in improving medication adherence, self-health management abilities, and quality of life (QoL) in PD patients. METHODS:A total of 70 patients were randomly divided into the control group and the intervention group. The intervention group received IMB model-based health education, while the control group received routine health education only. The effectiveness of the intervention was evaluated by measuring medication adherence, self-management ability and QoL at 3 months and 6 months after the intervention. RESULTS:For medication adherence, at 3 months, medication adherence improved in both groups but showed no significant inter-group difference (P > 0.05). At 6 months, medication adherence in the intervention group was significantly higher than in the control group (P < 0.05). Self-health management scores significantly increased over time in both groups, and the intervention group demonstrated significantly greater improvement at both 3 months and 6 months (P < 0.05). While PDQ-39 scores showed no significant difference at 3 months (P > 0.05), the intervention group exhibited significantly greater improvement in QoL at 6 months (P < 0.05). CONCLUSION:IMB model-based health education takes into account patients' knowledge, motivation and behavioral skills, providing a structured and individualized intervention. It is a valuable approach for improving long-term medication adherence, enhancing self-management abilities, and ultimately boosting the QoL in PD patients.
Objective:This study aims to evaluate the efficacy of reduced-intensity or no heparin anticoagulation strategy in comparison to standard anticoagulation strategy during extracorporeal membrane oxygenation (ECMO) support. Materials and methods:Systematic literature review and meta-analysis, complying with the PRISMA guidelines (PROSPERO-CRD42025633878). Results:Eleven studies comprising 958 patients were included in the analysis. Four studies included only patients treated with veno-venous extracorporeal membrane oxygenation (V-V ECMO) for acute respiratory distress syndrome or respiratory failure, two studies focused exclusively on patients treated with veno-arterial extracorporeal membrane oxygenation (V-A ECMO), and five studies included a mixture of patients with both modalities. Most studies (n = 8) were of high quality, as indicated by a Newcastle-Ottawa Scale score of ≥ 6. The overall incidence of bleeding complications was 34% (95% confidence interval (CI): 0.35-0.67), without heterogeneity observed among the studies (I 2 = 43%). The overall incidence of thrombotic events was 14.6% (95% CI: 0.65-1.54; I 2 = 49%). The overall in-hospital mortality was 49% (95% CI: 0.67-1.21; I 2 = 41%), while the red blood cell transfusion rate was 41.2% (95% CI: 0.08-1.02; I 2 = 76%). Conclusion:Reduced-intensity or no heparin anticoagulation appears to be a feasible and safe strategy, demonstrating the potential to reduce bleeding complications without a significant increase in thrombotic events, and may be associated with improved patient outcomes. Systematic review registration:https://www.crd.york.ac.uk/PROSPERO/view/CRD42025633878, identifier CRD42025633878.
Background and Purpose:Observational studies suggest an association between insulin resistance (IR) and chronic obstructive pulmonary disease (COPD), but this link is susceptible to confounding and reverse causality. This study integrated cross-sectional analysis with Mendelian Randomization (MR) to systematically evaluate their potential causal relationship. Methods:Using NHANES data, we employed complex sampling weighting and multivariable logistic regression to assess the observational association between IR (measured by HOMA-IR) and COPD. For genetic analysis, genetic variants strongly associated with IR were selected as instrumental variables from GWAS summary data. Two-sample MR analyses were conducted using inverse-variance weighted (IVW), weighted median, and MR-Egger regression, with rigorous testing for pleiotropy and heterogeneity. Results:Observational analysis showed no significant association before confounder adjustment (P=0.166). After adjustment, moderate IR levels (third quintile) were associated with increased COPD risk (OR=2.24, 95% CI: 1.15-4.37, P=0.018). MR analysis revealed inconsistent estimates: IVW suggested a weak risk effect (OR=1.009, P<0.001), while MR-Egger indicated a protective effect (OR=0.998, P=1.54e-05). The MR-Egger intercept test detected significant horizontal pleiotropy (P<2e-16), indicating that genetic instruments influence COPD through pathways independent of IR, violating a key MR assumption. The genetic effect sizes were extremely small and not clinically meaningful. Conclusion:This integrated analysis does not support an independent causal role of IR in COPD. The observational association is confounded and non-linear, while genetic evidence is undermined by substantial pleiotropy. Therefore, IR should be regarded as a comorbid risk marker reflecting a systemic metabolic-inflammatory state rather than a direct causal target. For COPD patients with comorbid IR, clinical management should shift from targeting a single metabolic parameter toward a comprehensive strategy grounded in smoking cessation and pulmonary rehabilitation, alongside active management of obesity and dyslipidemia. Future research should prioritize elucidating the common upstream mechanisms linking metabolic dysregulation and lung function decline.
