Biology subjects

Saini, R.

Publications and source records attributed to Saini, R..

11 recordsLinked to original sources

bioRxiv2026

Quantum machine learning for detection of sleep deprivation from EEG signals

Approximately 50% of the population in India is estimated to experience sleep-related disorders. Sleep deprivation is a prevalent condition that adversely impacts cognitive performance, neural functioning, and overall health. Electroencephalography (EEG) offers an objective means of capturing neural alterations associated with sleep loss, making it well-suited for automated detection frameworks. In this study, we explore the application of a Quantum Support Vector Machine and Hybrid Quantum Neural Networks to classify sleep-deprived and well-rested states using resting-state EEG signals. A comprehensive feature extraction pipeline is employed, incorporating spectral band power, band ratios, Hjorth parameters, and functional connectivity measures. These features are subsequently encoded into quantum states to construct a quantum kernel, which is then utilized for classification. Model performance is evaluated under both epoch-level and subject-level data partitioning schemes. The Hybrid Quantum Neural Network (HQNN) achieves the highest performance across both evaluation settings, attaining an accuracy of 96.88% at the epoch level and 81.25% at the subject level. The Quantum Support Vector Machine (QSVM) model achieves accuracies of 93.75% and 75.00% for epoch-level and subject-level evaluations, respectively. At subject-level and epoch-level evaluation, HQNN outperforms previously reported results (95.72% and 68.23%). Overall, these findings highlight the potential of quantum machine learning as a competitive approach for EEG-based sleep deprivation detection, with promising implications for real-world biomedical applications.

neuroscience↗

bioRxiv2026

mTOR regulates longevity through a bile-acid like hormonal mechanism and DHS- 26/DHRS1

The mTOR pathway is a central regulator of cellular metabolism and growth whose downregulation extends life span across taxa. In C. elegans, mTOR acts cell non-autonomously to influence organismal longevity, yet underlying mechanisms remain elusive. Here, we show that deletion of the TORC1 regulator, raga-1/RRAGA, enhances production of the bile acid-like hormone, dafachronic acid (DA), and extends life span dependent on DA-hormone biosynthetic genes and DA-cognate nuclear hormone receptor DAF-12, a homolog of mammalian farnesoid X receptor (FXR). Through functional genomic screens, we identify the evolutionarily conserved short chain dehydrogenase DHS-26/DHRS1 as a previously uncharacterized downstream regulatory target and effector of the mTOR-steroid axis essential for organismal longevity. Worm DHS-26 is expressed prominently in the canal associated neurons, cells which are essential to growth and development, suggesting a neuroendocrine mechanism. Murine DHRS1 also exhibits regulation by mTOR signaling and nuclear receptor FXR suggesting that the mTOR-DHS-26/DHRS1 axis is evolutionarily conserved. These findings suggest that mTOR signaling systemically impacts metazoan longevity through the regulation of bile acid-like hormone availability and nuclear receptor signal transduction.

genetics↗

bioRxiv2025

Dynamic Disorder in Chlorophyll Aggregation and Light-Harvesting Complex II in the Plant Thylakoid Membrane using Coarse-Grained Simulations

The dynamics of the aggregated light-harvesting complex (LHCII) associated with its antennae pigments can be crucial for a transition between light harvesting and dissipative states pivotal for non-photochemical quenching (NPQ). To this end, aggregation of chlorophyll-a (CLA) without the LHCII and pigment binding LHCII monomers in the plant thylakoid membranes have been investigated using coarse-grained molecular dynamics simulations at 293 K. Both CLA without the LHCII and pigment-binding LHCII monomers dynamically form and break dimers and higher-order aggregates in thylakoids within the simulation time. The contact lifetime and waiting time distributions of CLA dimers exhibit multiple time scales including most populated fast time scales and less populated slow time scales. The survival probability of CLA dimer in the absence of the LHCII follows a non-exponential decay with multiple residence time scales, leading to a time-dependent rate, unlike conventional rate theory. Such non-exponential decay of survival manifests the emergence of dynamic disorder in CLA without the LHCII resulting from the coupling between time scales of dimer formation and higher-order aggregates. The conformational fluctuations of the LHCII known for inter-CLA coupling variation occur on multiple time scales comparable to the LHCII dimer residence time scales leading to less probable but comparable and more probable slower inter-CLA fluctuations. This indicates the dynamic coupling in the LHCII conformations and their aggregates with the antennae pigments can result in dynamic disorder which will be highly relevant for the light-harvesting efficiency and regulation of NPQ. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/638782v1_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@5fd895org.highwire.dtl.DTLVardef@8456cforg.highwire.dtl.DTLVardef@5f5c69org.highwire.dtl.DTLVardef@abf6d0_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2023

Multigenerational inheritance of parasitic stress memory in Drosophila melanogaster

Organisms sense harmful environmental conditions and employ strategies to safeguard themselves. Moreover, they can communicate this experience to the next generation or beyond via non-DNA sequence-based mechanisms, referred to as intergenerational or transgenerational epigenetic inheritance, respectively. Using a specialist larval parasitoid, Leptopilina boulardi, and its host, Drosophila melanogaster, we show that the parental experience of parasitic stress results in an increased survivability of the immediate offspring of the host. Furthermore, we observe that the increased survivability in response to the parasitic stress is transmitted transgenerationally where the grandparents have been exposed to the parasitoid but not the parents. The increased survivability is primarily inherited through male parents, and at least one of the forms of the memory is better immune priming at larval stage. Our study suggests that the stress exposure during the pre-adult stage of the host has lifetime benefits for its progeny to deal with the future parasitic attack.

genetics↗

bioRxiv2023

SignEEG v1.0 : Multimodal Electroencephalography and Signature Database for Biometric Systems

Handwritten signatures in biometric authentication leverage unique individual characteristics for identification, offering high specificity through dynamic and static properties. However, this modality faces significant challenges from sophisticated forgery attempts, underscoring the need for enhanced security measures in common applications. To address forgery in signature-based biometric systems, integrating a forgery-resistant modality, namely, noninvasive electroencephalography (EEG), which captures unique brain activity patterns, can significantly enhance system robustness by leveraging multimodalitys strengths. By combining EEG, a physiological modality, with handwritten signatures, a behavioral modality, our approach capitalizes on the strengths of both, significantly fortifying the robustness of biometric systems through this multimodal integration. In addition, EEGs resistance to replication offers a high-security level, making it a robust addition to user identification and verification. This study presents a new multimodal SignEEG v1.0 dataset based on EEG and hand-drawn signatures from 70 subjects. EEG signals and hand-drawn signatures have been collected with Emotiv Insight and Wacom One sensors, respectively. The multimodal data consists of three paradigms based on mental, & motor imagery, and physical execution: i) thinking of the signatures image, (ii) drawing the signature mentally, and (iii) drawing a signature physically. Extensive experiments have been conducted to establish a baseline with machine learning classifiers. The results demonstrate that multimodality in biometric systems significantly enhances robustness, achieving high reliability even with limited sample sizes. We release the raw, pre-processed data and easy-to-follow implementation details.

neuroscience↗

bioRxiv2022

Bimodal pilot study on inner speech decoding reveals the potential of combining EEG and fMRI

The recognition of inner speech, which could give a voice to patients that have no ability to speak or move, is a challenge for brain-computer interfaces (BCIs). A shortcoming of the available datasets is that they do not combine modalities to increase the performance of inner speech recognition. Multimodal datasets of brain data enable the fusion of neuroimaging modalities with complimentary properties, such as the high spatial resolution of functional magnetic resonance imaging (fMRI) and the temporal resolution of electroencephalography (EEG), and therefore are promising for decoding inner speech. This paper presents the first publicly available bimodal dataset containing EEG and fMRI data acquired nonsimultaneously during inner-speech production. Data were obtained from four healthy, right-handed participants during an inner-speech task with words in either a social or numerical category. Each of the 8-word stimuli were assessed with 40 trials, resulting in 320 trials in each modality for each participant. The aim of this work is to provide a publicly available bimodal dataset on inner speech, contributing towards speech prostheses.

neuroscience↗

bioRxiv2022

Rethinking the Methods and Algorithms for Inner Speech Decoding - and Making them Reproducible

This study focuses on the automatic decoding of inner speech using noninvasive methods, such as electroencephalography (EEG)). While inner speech has been a research topic in philosophy and psychology for half a century, recent attempts have been made to decode nonvoiced spoken words by using various brain-computer interfaces. The main shortcomings of existing work are reproducibility and the availability of data and code. In this work, we investigate various methods (using Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU), Long Short-Term Memory Networks (LSTM)) for the detection task of 5 vowels and 6 words on a publicly available EEG dataset. The main contributions of this work are (1) subject dependent vs. subject-independent approaches, (2) the effect of different preprocessing steps (Independent Component Analysis (ICA), down-sampling and filtering), and (3) word classification (where we achieve state-of-the-art performance on a publicly available dataset). Overall we achieve a performance accuracy of 35.20% and 29.21% when classifying 5 vowels and 6 words respectively in a publicly available dataset, using our tuned iSpeech-CNN architecture. All of our code and processed data are publicly available to ensure reproducibility. As such, this work contributes to a deeper understanding and reproducibility of experiments in the area of inner speech detection.

neuroscience↗

bioRxiv2021

Integrative physiological, biochemical and transcriptomic analysis of hexaploid wheat roots and shoots provides new insights into the molecular regulatory network during Fe & Zn starvation

In plants, iron (Fe) & zinc (Zn) uptake and transportation from the rhizosphere to the grain is a critical process regulated by complex transcriptional regulatory networks. However, understanding the combined effect of Fe & Zn starvation on their uptake and transportation and the molecular regulatory networks that control them lack in wheat. Here, we performed a comprehensive physiological, biochemical and transcriptome analysis in two bread wheat genotypes, i.e. Narmada 195 and PBW 502, differing in inherent Fe & Zn content to understand the mechanism of Fe & Zn homeostasis. Compared to PBW 502, Narmada 195 exhibited increased tolerance to Fe & Zn withdrawal by an increased level of antioxidant enzymes and DPPH radical scavenging activity along with less malondialdehyde (MDA), H2O2 level, increased PS accumulation and lower reduction of root and shoot Fe & Zn content and length, leaf chlorosis, and leaf area. By integrating physiological and biochemical data along with co-expression & functional genome annotation and gene expression analysis, we identified 25 core genes associated with four key pathways, i.e. Met cycle (10), PS biosynthesis (4), antioxidant (3) and transport system (8) that were significantly modulated by Fe & Zn withdrawal in both the genotypes. Genes of these four pathways were more considerably up-regulated in Narmada 195, allowing better tolerance to Fe & Zn withdrawal and efficient uptake and transportation of Fe & Zn. Chromosomal distribution and sub-genome wise mapping of these genes showed a contribution from all the chromosomes except group 5 chromosomes with the highest number of genes mapped to chromosome 4 (24%) and sub-genome D (40%). Besides, we also identified 26 miRNAs targeting 14 core genes across the four pathways. Together, our work provides a crucial angle for an in-depth understanding of regulatory cross-talk among physiological, biochemical and transcriptional reprogramming underlying Fe & Zn withdrawal in wheat. Core genes identified can serve as valuable resources for further functional research for genetic improvement of Fe & Zn content in wheat grain. HighlightOur work provides a crucial angle for a comprehensive understanding of the regulatory mechanism underlying Fe & Zn withdrawal associated with physiological, biochemical and transcriptional reprogramming in wheat.

molecular biology↗

bioRxiv2020

Distinct Long-term Effects of Precision X-Radiation on Reflex Saliva Flow Rate and Tissue Integrity in a Preclinical Model of Chronic Hyposalivation

Chronic salivary hypofunction and xerostomia are common side effects of radiation therapy which is an essential component in the curative management in patients with head & neck cancers. Over the years, improvements in delivery techniques such as image-guided intensity modulated radiation therapy have led to improvement in cancer management but chronic hyposalivation continues to be a challenge that causes long-term health implications resulting in compromised quality of life. Recent advances in salivary stem cell research promise new frontier in the treatment of radiation-induced hyposalivation by initiating regeneration of radiation-damaged salivary parenchymal cells. Lack of a standard preclinical immunodeficient model to assess radiation-induced changes objectively and quantitatively in salivary flow rates will impede rapid progress towards the development of cellular therapies for chronic salivary dysfunction and attendant xerostomia. Herein, we report the first fully characterized novel cone-beam computed tomography (CBCT)-guided precision ionizing radiation (IR) induced chronic hyposalivation model in radiosensitive, immunodeficient transgenic NSG-SGM3 mice expressing three human cytokines including c-KIT ligand/stem cell factor. Additionally, we also report a novel and instantaneous method to objectively assess the kinetics of pilocarpine-stimulated salivary flowrate. Comprehensive structural and functional characterization of salivary glands revealed previously unknown and highly complex gender, age, IR dose and salivary gland subtype-specific effects of salivary-ablative precision IR.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pathology↗

bioRxiv2020

Sex-specific crossover rates did not change with parental age in Arabidopsis

Crossing over, the exchange of DNA between the chromosomes during meiosis, contributes significantly to genetic variation. The rate of crossovers (CO) varies depending upon the taxon, population, age, external conditions, and also, sometimes, between the sexes, a phenomenon called heterochiasmy. In the model plant Arabidopsis thaliana, the male rate of crossovers (mCO) is typically nearly double the female rate (fCO). With increasing parental age, it has been reported that the disparity decreases, because fCO rises while mCO remains stable. That finding, however, is based on chromosome-based averaging, and it is unclear whether all parts of the genome respond similarly. We addressed this point by examining how the level of heterochiasmy responded to parental age in eight genomic intervals distributed across the five chromosomes of Arabidopsis. Unlike the previous work, in each of the eight intervals, the level of heterochiasmy did not change with age, that is, the ratio mCO:fCO remained stable. As expected, though, amongst the intervals, the levels of heterochiasmy at any of the four ages examined, did vary. We propose that while the levels of heterochiasmy in Arabidopis might decrease with age on a chromosomal basis, as reported earlier, this is not true for all locations within each chromosome. This has practical implications for plant breeding research, a major aim of which is identifying ways to induce local increases in CO rates.

plant biology↗

bioRxiv2019

Multiple hormonal signalling pathways function cell-nonautonomously to control protein homeostasis in Caenorhabditis elegans

Protein homeostasis is crucial for viability of all organisms, and mutations that enhance protein aggregation cause different human pathologies, including polyglutamine (polyQ) diseases, such as some spinocerebellar ataxias or Huntington disease. Here, we report that neuronal Stomatin-like protein UNC-1 protects against aggregation of prone-to-aggregate proteins, like polyQs, -synuclein and {beta}-amyloid, in C. elegans. UNC-1, in IL2 neurons, antagonizes the function of the cytosolic sulfotransferase SSU-1 in neurohormonal signalling from ASJ neurons. The target of this hormone is the nuclear hormone receptor NHR-1, which acts cell-autonomously to protect from aggregation in muscles. A second nuclear hormone receptor, DAF-12, functions oppositely to NHR-1 to maintain protein homeostasis. Transcriptomics analyses reveal deep changes in the expression of genes involved in fat metabolism, in unc-1 mutants, which are regulated by NHR-1. This suggest that fat metabolism changes, controlled by neurohormonal signalling, contributes to modulate protein homeostasis.

genetics↗