Biology subjects

Parekh, P.

Publications and source records attributed to Parekh, P..

3 recordsLinked to original sources

bioRxiv2022

Sample size requirement for achieving multisite harmonization using structural brain MRI features

When data is pooled across multiple sites, the extracted features are confounded by site effects. Harmonization methods attempt to correct these site effects while preserving the biological variability within the features. However, little is known about the sample size requirement for effectively learning the harmonization parameters and their relationship with the increasing number of sites. In this study, we performed experiments to find the minimum sample size required to achieve multisite harmonization (using neuroHarmonize) using volumetric and surface features by leveraging the concept of learning curves. Our first two experiments show that site-effects are effectively removed in a univariate and multivariate manner; however, it is essential to regress the effect of covariates from the harmonized data additionally. Our following two experiments with actual and simulated data showed that the minimum sample size required for achieving harmonization grows with the increasing average Mahalanobis distances between the sites and their reference distribution. We conclude by positing a general framework to understand the site effects using the Mahalanobis distance. Further, we provide insights on the various factors in a cross-validation design to achieve optimal inter-site harmonization.

neuroscience↗

bioRxiv2021

Lymphotoxin-alpha expression in the meninges causes lymphoid tissue formation and neurodegeneration

Lymphotoxin alpha (LT) plays an important role in lymphoid organ development and cellular cytotoxicity in the immune system. LT expression is increased in the cerebrospinal fluid of naive and progressive multiple sclerosis (MS) patients and post-mortem meningeal tissue. Here we show that persistently increased levels of LT in the cerebral meninges can give rise to lymphoid-like structures and underlying MS-like cortical pathology. Stereotaxic injections of recombinant LT into the rat meninges leads to acute meningeal inflammation and subpial demyelination that resolves after 28 days. Injection of an LT lentiviral vector induces lymphoid-like immune cell aggregates, maintained over 3 months, including T-cell rich zones containing podoplanin+ fibroblastic reticular stromal cells and B-cell rich zones with a network of follicular dendritic cells, together with expression of lymphoid chemokines and their receptors. Extensive microglial activation, subpial demyelination and marked neuronal loss occurs in the underlying cortical parenchyma. These results show that chronic LT overexpression is sufficient to induce formation of meningeal lymphoid-like structures and subsequent neurodegeneration. SummaryIncreased release of lymphotoxin-alpha contributes to the pro-inflammatory milieu of the cerebrospinal fluid of MS patients. A persistent elevated expression of this cytokine in the meninges of rats gives rise to chronic inflammation with lymphoid tissue induction and accompanying neurodegenerative and demyelinating pathology in the underlying brain tissue.

neuroscience↗

bioRxiv2020

Protocol for Magnetic Resonance Imaging Acquisition, Quality Assurance, and Quality Check for the Accelerator Program for Discovery in Brain Disorders using Stem Cells

ObjectiveThe Accelerator Program for Discovery in Brain Disorders using Stem Cells (ADBS) is a longitudinal study focused on collecting and analysing clinical, neuropsychological, neurophysiological, and multimodal neuroimaging data from five cohorts of patients with major psychiatric disorders from genetically high-risk families, their unaffected first-degree relatives, and healthy subjects. Here, we present a complete description of the acquisition of multimodal MRI data along with the quality assurance (QA) and quality check (QC) procedures that we are following in this study. MethodsThe QA procedure consists of monitoring of different quantitative measurements using an agar gel and a geometrical phantom. For the already acquired data from human subjects, we describe QC steps for each imaging modality. To quantify reliability of outcome measurements, we perform test-retest reliability on human volunteers. ResultsWe have presented results from analysis of phantom data and test-retest reliability on a human volunteer. Results show consistency in data acquisition and reliable quantification of different outcome measurements. ConclusionThe acquisition protocol and QA-QC procedures described here can yield consistent and reliable outcome measures. We hope to acquire and eventually release high quality longitudinal neuroimaging dataset that will serve the scientific community and pave the way for interesting discoveries.

neuroscience↗