Biology subjects

Akhter, A.

Publications and source records attributed to Akhter, A..

9 recordsLinked to original sources

bioRxiv2025

Frontal Vulnerability vs. Temporal Resilience: Neuro-compensatory mechanisms underline differential language aging trajectories

Age-related decline underlies cognitive functions such as sensorimotor control, executive functioning, memory, and language production (LP), whereas language comprehension (LC) tends to remain intact or improve across healthy adult lifespan. This preservation likely stems from structural and functional integrity within core language network (cLAN) regions. To investigate this hypothesis, we analyzed the relationships among brains resting-state functional connectivity (FC), structural connectivity (SC), and language behaviour (LC and LP) using a cross-sectional cohort of healthy adults (N = 652; M/F = 322/330; aged 18-88) from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) dataset. Six cognitive tasks assessing LC and LP were employed, with neuroimaging measures focused on region-specific connections within the cLAN. Using generalized additive mixed models (GAMMs), complex brain-behaviour interactions were identified. Behavioral analyses revealed established age-related dichotomy, LC abilities in vocabulary and proverb comprehension improved and in syntactic and semantic comprehension remained stable, whereas LP tasks, e.g., verbal fluency, picture priming, and tip of tongue exhibited significant decline across the lifespan. SC exhibited decline in both intra-and inter-hemispheric fronto-temporal and frontal lobe connections, contrasted by preserved or enhanced temporal lobe connectivity, supporting a pattern of frontal vulnerability concomitant with temporal resilience. Age-related FC patterns demonstrated overall preservation, reflecting compensatory mechanisms to sustain functional integrity despite structural degradation. GAMM analyses revealed complex relationships between brain connectivity and language performance across age. Thus, integrating knowledge of brain structure, function, and language abilities, we identified the brain network mechanisms associated with dichotomous language behavior along lifespan. SignificanceUnderstanding age-related changes in language abilities is vital for early detection of cognitive decline and intervention development. This study reveals heterogeneous language aging trajectories: language production often declines, while comprehension remains stable or improves. Notably, comprehension tasks with high executive and working memory demands also show resilience, suggesting compensatory mechanisms beyond crystallized knowledge. Using multimodal neuroimaging in a large adult lifespan cohort, we link behavioral patterns to distinct network dynamics within the core language system. We uncover relative vulnerability in frontal brain regions, with pronounced structural decline in fronto-temporal pathways, contrasted by resilience in temporal connectivity, which is preserved or strengthened. These findings highlight regionally specific vulnerabilities and compensatory functional adaptations, refining current models and providing a framework to guide research promoting healthy cognitive aging.

neuroscience↗

bioRxiv2024

Towards Reliable Diabetes Prediction: Innovations in Data Engineering and Machine Learning Applications

ObjectiveDiabetes is a metabolic disorder that causes the risk of stroke, heart disease, kidney failure, and other long-term complications because diabetes generates excess sugar in the blood. Machine learning (ML) models can aid in diagnosing diabetes at the primary stage. So, we need an efficient machine learning model to diagnose diabetes accurately. MethodsIn this paper, an effective data preprocessing pipeline has been implemented to process the data and random oversampling to balance the data, handling the imbalance distributions of the observational data more sophisticatedly. We used four different diabetes datasets to conduct our experiments. Several ML algorithms were used to determine the best models to predict diabetes faultlessly. ResultsThe performance analysis demonstrates that among all ML algorithms, RF surpasses the current works with an accuracy rate of 86% and 98.48% for dataset-1 and dataset-2; XGB and DT surpass with an accuracy rate of 99.27% and 100% for dataset-3 and dataset-4 respectively. Our proposal can increase accuracy by 12.15% compared to the model without preprocessing. ConclusionsThis excellent research finding indicates that the proposed models might be employed to produce more accurate diabetes predictions to supplement current preventative interventions to reduce the incidence of diabetes and its associated costs.

bioinformatics↗

bioRxiv2024

Amyloid beta glycation leads to neuronal mitochondrial dysfunction and Alzheimers pathogenesis through VDAC1-dependent mtDNA efflux

Glycation, the non-enzymatic attachment of reactive dicarbonyls to proteins, lipids, or nucleic acids, contributes to the formation of advanced glycation end-products (AGEs). In Alzheimers disease (AD), amyloid-beta (A{beta}) undergoes post-translational glycation to produce glycated A{beta} (gA{beta}), yet its pathological role remains poorly understood. Here, we demonstrate that gA{beta} promotes neuronal mitochondrial DNA (mtDNA) efflux via a VDAC1-dependent mechanism, activating the innate immune cGAS-STING pathway. Using aged AD mice and human AD brain samples, we observed cGAS-mtDNA binding and cGAS-STING activation in the neuronal cytoplasm. Knockdown of RAGE, cGAS, or STING, as well as pharmacological inhibition of VDAC1, protected APP mice from mitochondrial dysfunction and Alzheimers-like pathology. Neuron-specific cGAS knockdown confirmed its pivotal role in driving neuroinflammation and cognitive deficits. Treatment with ALT-711, an AGE cross-link breaker, alleviated gA{beta}-associated pathology. Furthermore, RAGE inhibition in APP knock-in mice suppressed innate immune activation and disease-associated gene expression, as revealed by spatially resolved transcriptomics. Collectively, our findings establish a mechanistic link between gA{beta} and innate immune activation, identifying VDAC1, the AGE-RAGE axis, and the cGAS-STING pathway as promising therapeutic targets in AD. Significance StatementThis study reveals how a modified form of amyloid-beta disrupts mitochondrial function in neurons, triggering innate immunity and disease progression. We show that this modified amyloid-beta damages mitochondria, activating a specific immune response in the brain. By identifying the key molecules involved, we provide potential targets for new Alzheimers treatments aimed at preventing mitochondrial damage and cognitive decline. This research offers fresh insights into Alzheimers development and highlights new therapeutic pathways.

neuroscience↗

bioRxiv2024

Explainable Deep Learning Framework: Decoding Brain Task and Prediction of Individual Performance in False-Belief Task at Early Childhood Stage

Decoding of brain tasks aims to identify individuals brain states and brain fingerprints to predict behavior. Deep learning provides an important platform for analyzing brain signals at different developmental stages to understand brain dynamics. Due to their internal architecture and feature extraction techniques, existing machine learning and deep-learning approaches for fMRI-based brain decoding must improve classification performance and explainability. The existing approaches also focus on something other than the behavioral traits that can tell about individuals variability in behavioral traits. In the current study, we hypothesized that even at the early childhood stage (as early as 3 years), connectivity between brain regions could decode brain tasks and predict behavioural performance in false-belief tasks. To this end, we proposed an explainable deep learning framework to decode brain states (Theory of Mind and Pain states) and predict individual performance on ToM-related false-belief tasks in a developmental dataset. We proposed an explainable spatiotemporal connectivity-based Graph Convolutional Neural Network (Ex-stGCNN) model for decoding brain tasks. Here, we consider a dataset (age range: 3-12 yrs and adults, samples: 155) in which participants were watching a short, soundless animated movie, "Partly Cloudy," that activated Theory-of-Mind (ToM) and pain networks. After scanning, the participants underwent a ToMrelated false-belief task, leading to categorization into the pass, fail, and inconsistent groups based on performance. We trained our proposed model using Static Functional Connectivity (SFC) and Inter-Subject Functional Correlations (ISFC) matrices separately. We observed that the stimulus-driven feature set (ISFC) could capture ToM and Pain brain states more accurately with an average accuracy of 94%, whereas it achieved 85% accuracy using SFC matrices. We also validated our results using five-fold cross-validation and achieved an average accuracy of 92%. Besides this study, we applied the SHAP approach to identify neurobiological brain fingerprints that contributed the most to predictions. We hypothesized that ToM network brain connectivity could predict individual performance on false-belief tasks. We proposed an Explainable Convolutional Variational Auto-Encoder model using functional connectivity (FC) to predict individual performance on false-belief tasks and achieved 90% accuracy.

neuroscience↗

bioRxiv2023

HIV Infection impairs the Host Response to Mycobacterium tuberculosis Infection by altering Surfactant Protein D function in the Human Lung Alveolar Mucosa

Tuberculosis is the leading cause of death for people living with HIV (PLWH). We hypothesized that altered functions of innate immune components in the human alveolar lining fluid of PLWH (HIV-ALF), drive susceptibility to Mycobacterium tuberculosis (M.tb) infection. Our results indicate a significant increase in oxidation of innate proteins and chemokine levels, and significantly lower levels and function of complement components and Th1/Th2/Th17 cytokines in HIV-ALF vs. control-ALF (non-HIV infected people). We further found a deficiency of surfactant protein-D (SP-D) and reduced binding of SP-D to M.tb that had been exposed to HIV-ALF. Primary human macrophages infected with M.tb exposed to HIV-ALF were significantly less capable of controlling the infection, which was reversed by SP-D replenishment in HIV-ALF. Thus, our data suggest that PLWH without antiretroviral therapy (ART) have declining host innate defense function in their lung mucosa, thereby favoring M.tb and potentially other pulmonary infections.

cell biology↗

bioRxiv2021

Ataxia-linked SLC1A3 mutations alter EAAT1 chloride channel activity and glial regulation of CNS function

Glutamate is the predominant excitatory neurotransmitter in the mammalian central nervous system (CNS). Excitatory Amino Acid Transporters (EAATs) regulate extracellular glutamate by transporting it into cells, mostly glia, to terminate neurotransmission and to avoid neurotoxicity. EAATs are also chloride (Cl-) channels, but the physiological role of Cl- conductance through EAATs is poorly understood. Mutations of human EAAT1 (hEAAT1) have been identified in patients with episodic ataxia type 6 (EA6). One mutation showed increased Cl- channel activity and decreased glutamate transport, but the relative contributions of each function of hEAAT1 to mechanisms underlying the pathology of EA6 remain unclear. Here we investigated the effects of five additional EA6-related mutations on hEAAT1 function in Xenopus laevis oocytes, and on CNS function in a Drosophila melanogaster model of locomotor behavior. Our results indicate that mutations with decreased hEAAT1 Cl- channel activity and functional glutamate transport can also contribute to the pathology of EA6, highlighting the importance of Cl- homeostasis in glial cells for proper CNS function. We also identified a novel mechanism involving an ectopic sodium (Na+) leak conductance in glial cells. Together, these results strongly support the idea that EA6 is primarily an ion channelopathy of CNS glia.

neuroscience↗

bioRxiv2021

Extracellular Delivery of Functional Mitochondria Reverses the Dysfunction of CD4+ T Cells in Aging

Mitochondrial dysfunction alters cellular metabolism, increases tissue oxidative stress, and may be principal to the dysregulated signaling and function of CD4+ T lymphocytes in the elderly. In this proof of principle study, we investigated whether the transfer of functional mitochondria into CD4+ T cells that were isolated from old mice (aged CD4+ T cells), could abrogate aging-associated mitochondrial dysfunction, and improve the aged CD4+ T cell functionality. Our results show that the delivery of exogenous mitochondria to aged non-activated CD4+ T cells led to significant mitochondrial proteome alterations highlighted by improved aerobic metabolism and decreased cellular mitoROS. Additionally, mito-transferred aged CD4+ T cells showed improvements in activation-induced TCR-signaling kinetics displaying markers of activation (CD25), increased IL-2 production, enhanced proliferation ex vivo. Importantly, immune deficient mouse models (RAG-KO) showed that adoptive transfer of mito-transferred naive aged CD4+ T cells, protected recipient mice from influenza A and Mycobacterium tuberculosis infections. These findings support mitochondria as targets of therapeutic intervention in aging.

immunology↗

bioRxiv2019

Normal levels of cellular sumoylation are largely dispensable for growth but facilitate heat tolerance in yeast

Numerous proteins are sumoylated in normally growing yeast and SUMO conjugation levels rise upon exposure to several stress conditions. We observe high levels of sumoylation also during early exponential growth and when nutrient-rich medium is used. However, we find that reduced sumoylation (~75% less than normal) is remarkably well-tolerated, with no apparent growth defects under non-stress conditions or under osmotic, oxidative, or ethanol stresses. In contrast, strains with reduced activity of Ubc9, the sole SUMO conjugase, are temperature-sensitive, implicating sumoylation in the heat stress response, specifically. Aligned with this, a mild heat shock triggers increased sumoylation which requires functional levels of Ubc9, but likely also depends on decreased desumoylation, since heat shock reduces protein levels of Ulp1, the major SUMO protease. Furthermore, we find that a ubc9 mutant strain with only ~5% of normal sumoylation levels shows a modest growth defect, has abnormal genomic distribution of RNA polymerase II (RNAPII), and displays a greatly expanded redistribution of RNAPII after heat shock. Together, our data implies that SUMO conjugations are largely dispensable under normal conditions, but a threshold level of Ubc9 activity is needed to maintain transcriptional control and to modulate the redistribution of RNAPII and promote survival when temperatures rise.

molecular biology↗

bioRxiv2019

Pathognomonic and epistatic genetic alterations in B-cell non-Hodgkin lymphoma

B-cell non-Hodgkins lymphoma (B-NHL) encompasses multiple clinically and phenotypically distinct subtypes of malignancy with unique molecular etiologies. Common subtypes of B-NHL such as diffuse large B-cell lymphoma (DLBCL) have been comprehensively interrogated at the genomic level. But rarer subtypes such as mantle cell lymphoma (MCL) remain sparsely characterized. Furthermore, multiple B-NHL subtypes have thus far not been comprehensively compared using the same methodology to identify conserved or subtype-specific patterns of genomic alterations. Here, we employed a large targeted hybrid-capture sequencing approach encompassing 380 genes to interrogate the genomic landscapes of 685 B-NHL tumors at high depth; including DLBCL, MCL, follicular lymphoma (FL), and Burkitt lymphoma (BL). We identified conserved hallmarks of B-NHL that were deregulated in the majority of tumor from each subtype, including the frequent genetic deregulation of the ubiquitin proteasome system (UPS). In addition, we identified subtype-specific patterns of genetic alterations, including clusters of co-occurring mutations and DNA copy number alterations. The cumulative burden of mutations within a single cluster were more discriminatory of B-NHL subtypes than individual mutations, implicating likely patterns of genetic cooperation that contribute to disease etiology. We therefore provide the first cross-sectional analysis of mutations and DNA copy number alterations across major B-NHL subtypes and a framework of co-occurring genetic alterations that deregulate genetic hallmarks and likely cooperate in lymphomagenesis.

genomics↗