Data aggregation across multiple research centers is gaining importance in the context of MRI research, driving diverse high-dimensional datasets to form large-scale heterogeneous sample, increasing statistical power and relevance of machine learning and deep learning algorithm. Site-related effects have been demonstrated to introduce bias in MRI features and confound subsequent analyses. Although Combating Batch (ComBat) technique has been recently reported to successfully harmonize multi-scale neuroimaging features, its performance assessments are still limited and largely based on qualitative visualizations and statistical analyses.
View Article and Find Full Text PDFGrowing evidence suggests the neurobiological mechanism upholding post-COVID-19 depression mainly relates to immune response and subsequent unresolved low-grade inflammation. Herein we exploit a broad panel of cytokines serum levels measured in COVID-19 survivors at one- and three-month since infection to predict post-COVID-19 depression. 87 COVID survivors were screened for depressive symptomatology at one- and three-month after discharge through the Beck Depression Inventory (BDI-13) and the Zung Self-Rating Depression Scale (ZSDS) at San Raffaele Hospital.
View Article and Find Full Text PDFAim: One-third of patients with major depressive disorder (MDD) do not achieve full remission and have high relapse rates even after treatment, leading to increased medical costs and reduced quality of life and health status. The possible specificity of treatment-resistant depression (TRD) neurobiology is still under investigation, with risk factors such as higher inflammatory markers being identified. Given recent findings on the role of choroid plexus (ChP) in neuroinflammation and hippocampus in treatment response, the aim of the present study was to evaluate inflammatory- and trophic-related differences in these regions along with ventricular volumes among patients with treatment-sensitive depression (TSD), TRD, and healthy controls (HCs).
View Article and Find Full Text PDF