Biology subjects

AGGARWAL, A.

Publications and source records attributed to AGGARWAL, A..

4 recordsLinked to original sources

bioRxiv2025

Brain connectivity using EEG data

The goal of this work was to use EEG data from epilepsy patients and analyze it for connectivity between brain regions using cross-power spectral density (CPSD). We took data from 76 EEG sessions by removing those with epileptic seizures. Then, we calculated CPSD for the 210 electrode pairs for each patient. Initially, we calculated CPSD in the entire sample and then stratified it based on frequency bands related to different brain states. We observed the brain hubs, the default mode network (DMN) and the anti-correlated network attached to the DMN. The connectivity of the brain changed with change in frequency and hence, brain states. EEG analysis with CPSD is a relatively inexpensive, longer duration and more convenient method over fMRI but provides similar information. Similar study can be used to identify brain connectivity patterns while brain is performing a specific task by collecting EEG data for the task.

neuroscience↗

bioRxiv2025

Long term improvement in Alzheimers Disease with Transcranial Direct Current Stimulation

Alzheimers disease (AD) is a protracted illness with no known cure. Transcranial direct current stimulation (tDCS) is an upcoming treatment for the disease. However, clinical studies conducted to study its impact on patients are very limited in duration and sample size. This limits the use of tDCS to AD patients over the long-term. To address the issue, this work uses an Alzheimers disease progression model (ADPM) to extrapolate the results from shorter clinical studies (10days to 6months) to a longer duration (10years). ADPM is a machine learning model of AD created using ADNI (Alzheimers Disease Neuroimaging Initiative) data from over a decade. It has been demonstrated to be better at predicting progression of AD compared to other models. Since AD is a progressive disease, it is useful to know about the impact of tDCS over a longer duration and predict the optimal duration and site of treatment. To achieve this goal, present work integrates limited data from tDCS treatment of AD patients and extrapolates it to a decade using the AD prediction model (ADPM). Based on this, it provides guidelines for site, dose and duration of treatment for patients with AD.

neuroscience↗

bioRxiv2023

Melanocytes Exhibit Distinct Cell States Governed by A Gene Regulatory Network Under Stochastic Influence

Melanocytes serve as a protector of the skin against external stressors such as ultraviolet radiations. While melanocytes remain functional for nearly the entire lifespan of an individual, how they respond efficiently and survive such insults remain elusive. Here, we show the co-existence of multiple distinct states of normal human epidermal melanocytes (NHEMs). Using a progressive pigmentation model, we show that stochasticity in gene expression can lead to the co-existence of multiple melanocyte states. Using active enhancers and gene expression footprint, we identified state-specific transcription factors and constructed a gene regulatory network (GRN). The GRN couples pigmentation and cell cycle regulators and explains the co-existence and transitions of the melanocyte states. Finally, we show that NHEMs respond to external cues by altering the cell state dynamics. These results demonstrate that stochasticity in gene expression followed by epigenetic modification leads to the co-existence of multiple melanocyte states enabling an efficient response to environmental cues.

cell biology↗

bioRxiv2021

Temporal resolution of melanogenesis determine fatty acid metabolism as key skin pigment regulator

Therapeutic methods to modulate skin pigmentation has important implications for skin cancer prevention and for treating meta-inflammatory-triggered cutaneous conditions. Modulators of cAMP signalling of melanocyte have met with minimal clinical efficacy. Towards defining new potential targets, we followed temporal dynamics orchestrating melanocyte differentiation by using a cell-autonomous pigmentation model. Our study elucidates three dominant phases of synchronized metabolic and transcriptional reprogramming. The induction phase is concomitant with a paradoxical decrease in MITF levels, reduced proliferation, and increased anabolic metabolism mediated by AKT phosphorylation. The melanogenic phase shows rapid uptake of glucose and fatty acid, transiently forming lipid droplets through SREBF1-mediated regulation of fatty acid metabolism. This heightened bioenergetic activity impairs mitochondria and the recovery phase is marked by a shift to aerobic glycolysis and activation of the NRF2 detoxication pathway. Finally, we show that inhibitors of lipid metabolism indeed resolve hyper-pigmentary conditions in a guinea pig UV-tanning model. Our studies reveal metabolic control mechanisms of melanocytes that could govern the balance between differentiation and proliferation in a variety of cutaneous diseases.

cell biology↗