Publications by authors named "John John"

Introduction: Diffusion-weighted magnetic resonance imaging (dMRI) is sensitive to the microstructural properties of brain tissues and shows great promise in detecting the effects of degenerative diseases. However, many approaches analyze single measures averaged over regions of interest without considering the underlying fiber geometry.

Methods: We propose a novel macrostructure-informed normative tractometry (MINT) framework to investigate how white matter (WM) microstructure and macrostructure are jointly altered in mild cognitive impairment (MCI) and dementia.

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Objectives: The neuromodulatory effects of transcranial alternating current stimulation (tACS) on electroencephalogram (EEG) dynamics are quite heterogenous. The primary objective of the study is to comprehensively characterize the effects of two tACS protocols on resting-state EEG.

Materials And Methods: A total of 36 healthy participants were recruited and were randomized into three groups.

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In this study, molecular beam epitaxial growth of strain-driven three-dimensional self-assembled Ge/GeSi islands on silicon-on-insulator (SOI) substrates, along with their optical and photodetection characteristics, have been demonstrated. The as-grown islands exhibit a bimodal size distribution, consisting of both Ge and GeSi alloy islands, and show significant photoluminescence (PL) emission at room temperature, specifically near optical communication wavelengths. Additionally, these samples were used to fabricate a Ge/GeSi islands/Si nanowire based phototransistor using a typical e-beam lithography process.

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Article Synopsis
  • Deep learning models using convolutional neural networks (CNNs) have been applied to classify Alzheimer's disease and assess dementia severity through 3D brain MRI scans, with a focus on improving interpretability using occlusion sensitivity analysis (OSA) and gradient-weighted class activation mapping (Grad-CAM).
  • The study investigates the effectiveness of these models, primarily trained on North American datasets, when applied to a different population in India (NIMHANS cohort), and assesses the advantages of utilizing a combined dataset for training.
  • Results demonstrate that feature localization aligns with established knowledge of Alzheimer's disease, indicating that OSA and Grad-CAM enhance interpretability by resolving diagnostic features at various scales.
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Background: Major psychiatric illnesses often cluster in families, and their impact on affected and unaffected members within families may reflect the consequence of both genetic and social liability.

Methods: Data was derived from 202 families with multiple affected individuals. Affected individuals (N = 259) had a diagnosis of schizophrenia, bipolar disorder, obsessive-compulsive disorder or substance use disorder.

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Purpose: In this review, we aim to determine the efficacy of Solution-Focused Interventions (SFI) among caregivers of persons living with different conditions.

Method: Articles published between 1 January 2000 and 31 December 2022 were used. Databases used included EBSCOhost, PubMed, ProQuest, ERIC, and Google Scholar.

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  • Researchers are exploring two-dimensional van der Waals (vdW) layered materials for creating heterostructures, leading to new electronic phenomena and potential applications in various tech fields.
  • Achieving low-disorder interfaces in these heterostructures has been a challenge, but thermal scanning probes have emerged as an effective solution to create pristine interfaces.
  • This technique significantly improves the electrical performance of monolayer WS transistors and enables the creation of quantum dots that can switch between macroscopic and single-electron current flow.
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Introduction: Diffusion MRI is sensitive to the microstructural properties of brain tissues, and shows great promise in detecting the effects of degenerative diseases. However, many approaches analyze single measures averaged over regions of interest, without considering the underlying fiber geometry.

Methods: Here, we propose a novel Macrostructure-Informed Normative Tractometry (MINT) framework, to investigate how white matter microstructure and macrostructure are jointly altered in mild cognitive impairment (MCI) and dementia.

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Introduction: The COVID-19 pandemic has brought about unparalleled suffering on a global scale, affecting both physical and mental well-being. In such challenging times, it becomes crucial to identify interventions that can alleviate negative mental health outcomes, such as stress, while promoting positive mental health outcomes, like well-being. We report the effectiveness of a mind-body practise, Isha Yoga, in promoting well-being.

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This study introduces the Deep Normative Tractometry (DNT) framework, that encodes the joint distribution of both macrostructural and microstructural profiles of the brain white matter tracts through a variational autoencoder (VAE). By training on data from healthy controls, DNT learns the normative distribution of tract data, and can delineate along-tract micro-and macro-structural abnormalities. Leveraging a large sample size via generative pre-training, we assess DNT's generalizability using transfer learning on data from an independent cohort acquired in India.

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Deep learning models based on convolutional neural networks (CNNs) have been used to classify Alzheimer's disease or infer dementia severity from T1-weighted brain MRI scans. Here, we examine the value of adding diffusion-weighted MRI (dMRI) as an input to these models. Much research in this area focuses on specific datasets such as the Alzheimer's Disease Neuroimaging Initiative (ADNI), which assesses people of North American, largely European ancestry, so we examine how models trained on ADNI, generalize to a new population dataset from India (the NIMHANS cohort).

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The family of 2-dimensional (2D) semiconductors is a subject of intensive scientific research due to their potential in next-generation electronics. While offering many unique properties like atomic thickness and chemically inert surfaces, the integration of 2D semiconductors with conventional dielectric materials is challenging. The charge traps at the semiconductor/dielectric interface are among many issues to be addressed before these materials can be of industrial relevance.

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Photobiomodulation, also called low-level light therapy, has been reported in animal studies to have an effect on brain activity and cognition. However, studies in humans regarding its effect on cognition and brain functional connectivity, and the required dose threshold for achieving the same have been very limited. We compared the effects of different doses of photobiomodulation (PBM) on cognition and resting state brain functional connectivity in 25 cognitively normal adults aged 55-70 years.

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We present , an unsupervised multi-step framework that can filter, denoise and subsample bundles derived from diffusion MRI-based whole-brain tractography. Our approach considers both the global bundle structure and local streamline-wise features. We apply to bundles generated from single-shell diffusion MRI data in an independent clinical sample of older adults from India using probabilistic tractography and the resulting 'cleaned' bundles can better align with the atlas bundles with reduced overreach.

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Objectives: The presentation and outcomes of acute decompensated heart failure (ADHF) during COVID times (June 2020 to Dec 2020) were compared with the historical control during the same period in 2019.

Methods: Data of 4806 consecutive patients of acute HF admitted in 22 centres in the country were collected during this period. The admission patterns, aetiology, outcomes, prescription of guideline-directed medical therapy (GDMT) and interventions were analysed in this retrospective study.

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Objective: Schizophrenia is associated with impairment in multiple cognitive domains. There is a paucity of research on the effect of prolonged illness duration (≥ 15 years) on cognitive performance along multiple domains. In this pilot study, we used the Global Neuropsychological Assessment (GNA), a brief cognitive battery, to explore the patterns of cognitive impairment in recent-onset (≤ 2 years) compared to chronic schizophrenia (≥ 15 years), and correlate cognitive performance with brain morphometry in patients and healthy adults.

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Article Synopsis
  • * It includes a dataset of 4,096 participants across 18 states, with blood samples collected for detailed analysis and neuroimaging data for 137 participants.
  • * The publicly available datasets aim to help researchers identify risk factors linked to cognitive impairment and dementia in older adults.
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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.

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Background: Family studies in obsessive-compulsive disorder (OCD) indicate higher rates of psychosis among their first-degree relatives (FDRs). However, the etiological and clinical relationships between the two disorders remain unclear. We compared the clinical characteristics and pharmacological treatment response in patients diagnosed with OCD with a family history of psychosis (OCD-FHP), with a family history of OCD (OCD-FHO) and those with sporadic OCD (OCD-S).

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Posterior Reversible Encephalopathy Syndrome (PRES) is a clinico-radiological diagnosis characterized by acute or subacute neurological symptoms. A 27-year-old woman at 35 weeks of pregnancy, who presented with generalized tonic-clonic seizures had persistently low Glasgow Coma Scale (GCS) score after delivery of the baby. Magnetic Resonance Imaging (MRI) of the brain showed T-2 Fluid Attenuated Inversion Recovery (FLAIR) hyperintensities in the brainstem, bilateral medial cerebellar hemispheres, bilateral medial temporal lobes, bilateral thalami, lentiform and caudate nuclei, and bilateral fronto-parieto-occipital lobes.

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Environmental factors such as adverse childhood experiences (ACEs) may affect neurocognition, an endophenotype for several mental illnesses. This study examines the effect of ACEs on neurocognitive performance in first-degree relatives (FDRs) of patients with severe mental illness to determine whether familial risk has a moderating effect on the relationship between ACEs and neurocognition. Unaffected FDRs from multiplex families with severe mental illnesses (schizophrenia, bipolar disorder, obsessive-compulsive disorder, or alcohol use disorder) (n = 324) and healthy controls (with no familial risk) (n = 188) underwent neurocognitive tests for processing speed, new learning, working memory and Theory of Mind.

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Article Synopsis
  • Researchers have created a heterostructure combining Molybdenum diselenide (MoSe) with Mg-doped Gallium Nitride (p-GaN) to improve light detection efficiency.
  • The device shows impressive performance, achieving high photocurrent ratios, a responsivity of 130 A/W, and low noise, making it suitable for a range of light wavelengths from ultraviolet to near-infrared (300-950 nm).
  • Additionally, it features rapid response times, indicating its potential for high-speed and low-noise photodetection applications.
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Introduction: Alkaptonuria is a rare autosomal recessive metabolic disorder characterized by accumulation of homogentisic acid (HGA) due to an inherited deficiency of the enzyme HGA oxidase. Unlike rheumatoid arthritis which affects the small joints of the hands and feet, ochronotic arthropathy predominantly involves the large weight-bearing joints such as hips, knees, and spine. The knee is the most common joint to be affected.

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