Biology subjects

Kar, S.

Publications and source records attributed to Kar, S..

At least 55 records · Page 3Linked to original sources

bioRxiv2021

Engineered SARS-CoV-2 receptor binding domain improves immunogenicity in mice and elicits protective immunity in hamsters

Global containment of COVID-19 still requires accessible and affordable vaccines for low- and middle-income countries (LMICs).1 Recently approved vaccines provide needed interventions, albeit at prices that may limit their global access.2 Subunit vaccines based on recombinant proteins are suited for large-volume microbial manufacturing to yield billions of doses annually, minimizing their manufacturing costs.3 These types of vaccines are well-established, proven interventions with multiple safe and efficacious commercial examples.4-6 Many vaccine candidates of this type for SARS-CoV-2 rely on sequences containing the receptor-binding domain (RBD), which mediates viral entry to cells via ACE2.7,8 Here we report an engineered sequence variant of RBD that exhibits high-yield manufacturability, high-affinity binding to ACE2, and enhanced immunogenicity after a single dose in mice compared to the Wuhan-Hu-1 variant used in current vaccines. Antibodies raised against the engineered protein exhibited heterotypic binding to the RBD from two recently reported SARS-CoV-2 variants of concern (501Y.V1/V2). Presentation of the engineered RBD on a designed virus-like particle (VLP) also reduced weight loss in hamsters upon viral challenge.

molecular biology↗

bioRxiv2021

Neural epidermal growth factor-like 1 protein variant increases survival and modulates the inflammatory and immune responses in human ACE-2 transgenic mice infected with SARS-CoV-2

Coronavirus disease 2019 (COVID-19) is a viral illness caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is a worsening global pandemic. COVID-19 has caused at least 1.7 million deaths worldwide and over 300,000 in the United States. Recently, two promising vaccines are being administered in several countries. However, there remains an urgent need for a therapeutic treatment for COVID-19 patients with severe respiratory damage that can lead to intensive care, prolonged hospitalization, or mortality. Moreover, an increasing population of patients manifest lingering disabling symptoms (called Long Haulers). Here, we tested the efficacy of a recombinant neural epidermal growth factor like 1 protein variant (NELL1-NV1) in a COVID-19 mouse model, transgenic mice expressing the human angiotensin I-converting enzyme 2 (ACE2) receptor (tg-mice hACE2) infected with SARS-CoV-2. The administration of NELL1-NV1 to SARS-CoV-2-infected tg-mice hACE2 significantly improved clinical health score and increased survival. Analyses of bronchoalveolar (BAL) fluid demonstrated decreased levels of several cytokines and chemokines (IFN-{gamma}, IL-10, IL-12 p70, CXCL-10/IP-10, MIG and Rantes), in NV1-treated treated mice compared to controls. Cytokines including IL-1, IL-9, IL-6, LIX/CXCL5, KC/CXCL1, MIP-2/CXCL2, MIP-1/CCL3, and G-CSF, critical to immune responses such as neutrophil recruitment, viral clearance and vascularization, were increased compared to controls. Our data suggest the potential of NELL1-NV1-based therapy to mitigate the cytokine storm, modulate the abnormal immune response and repair respiratory tissue damage in COVID-19 patients.

immunology↗

bioRxiv2021

Unraveling the origin of Glucose mediated disparate proliferation dynamics of Cancer stem cells

Cancer stem cells (CSCs) often switch on their self-renewal programming aggressively to cause a relapse of cancer. Intriguingly, glucose differentially triggers the proliferation propensities in CSCs in an origin-dependent manner by controlling the expression of the key transcription factor like Nanog. However, the factors that critically govern this glucose-stimulated proliferation dynamics of CSCs remains elusive. Herein, by proposing a mathematical model of glucose-mediated Nanog regulation in CSCs, we showed that the differential proliferation behavior of CSCs can be explained by considering the experimentally observed varied expression levels of key positive (STAT3) and negative (p53) regulators of Nanog. Our model reconciles various experimental observations and predicts ways to fine-tune the proliferation dynamics of specific CSCs in a context-dependent manner. In future, these modeling insights will be useful in developing improved therapeutic strategies to get rid of harmful CSCs.

systems biology↗

bioRxiv2020

Suppression of miR-155 attenuates lung cytokine storm induced by SARS-CoV-2 infection in human ACE2-transgenic mice

Coronavirus disease 2019 (COVID-19) is a recent global pandemic. It is a deadly human viral disease, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with a high rate of infection, morbidity and mortality. Therefore, there is a great urgency to develop new therapies to control, treat and prevent this disease. Endogenous microRNAs (miRNAs, miRs) of the viral host are key molecules in preventing viral entry and replication, and building an antiviral cellular defense. Here, we have analyzed the role of miR-155, one of the most powerful drivers of host antiviral responses including immune and inflammatory responses, in the pathogenicity of SARS-CoV-2 infection. Subsequently, we have analyzed the potency of anti-miR-155 therapy in a COVID-19 mouse model (mice transgenic for human angiotensin I-converting enzyme 2 receptor (tg-mice hACE2)). We report for the first time that miR-155 expression is elevated in COVID-19 patients. Further, our data indicate that the viral load as well as miR-155 levels are higher in male relative to female patients. Moreover, we find that the delivery of anti-miR-155 to SARS-CoV-2-infected tg-mice hACE2 effectively suppresses miR-155 expression, and leads to improved survival and clinical scores. Importantly, anti-miR-155-treated tg-mice hACE2 infected with SARS-CoV-2 not only exhibit reduced levels of pro-inflammatory cytokines, but also have increased anti-viral and anti-inflammatory cytokine responses in the lungs. Thus, our study suggests anti-miR-155 as a novel therapy for mitigating the lung cytokine storm induced by SARS-CoV-2 infection.

immunology↗

bioRxiv2020

Fine-tuning Nanog expression heterogeneity by altering MicroRNA regulation

Nanog exhibits a robust heterogeneous expression pattern within a population of embryonic stem cells (ESCs) under varied culture conditions. However, an efficient way to fine-tune the Nanog expression heterogeneity remains elusive. Herein, by employing a stochastic modeling approach, we demonstrate that Nanog expression heterogeneity can be controlled by modulating the regulatory features of a Nanog transcript specific microRNA. We demonstrate how and why the extent of origin dependent fluctuations in Nanog expression level can be altered by varying either the binding efficiency of the microRNA-mRNA complex or the expression level of the respective microRNA. Moreover, our model makes experimentally feasible and insightful predictions to maneuver the Nanog expression heterogeneity explicitly to achieve cell-type specific differentiation of ESCs.

systems biology↗

bioRxiv2020

A Human-Immune-System mouse model for COVID-19 research(DRAGA mouse: HLA-A2.HLA-DR4.Rag1KO.IL-2Rγc KO.NOD)

We report the first Human Immune System (HIS)-humanized mouse model ("DRAGA": HLA-A2.HLA-DR4.Rag1KO.IL-2R{gamma}cKO.NOD) for COVID-19 research. This mouse is reconstituted with human cord blood-derived, HLA-matched hematopoietic stem cells. It engrafts human epi/endothelial cells expressing the human ACE2 receptor for SARS-CoV-2 and TMPRSS2 serine protease co-localized on lung epithelia. HIS-DRAGA mice sustained SARS-CoV-2 infection, showing deteriorated clinical condition, replicating virus in the lungs, and human-like lung immunopathology including T-cell infiltrates, microthrombi and pulmonary sequelae. Among T-cell infiltrates, lung-resident (CD103+) CD8+ T cells were sequestered in epithelial (CD326+) lung niches and secreted granzyme B and perforin, indicating cytotoxic potential. Infected mice also developed antibodies against the SARS-CoV-2 viral proteins. Hence, HIS-DRAGA mice showed unique advantages as a surrogate in vivo human model for studying SARS-CoV-2 immunopathology and for testing the safety and efficacy of candidate vaccines and therapeutics.

immunology↗

bioRxiv2020

Molecular modelling predicts SARS-CoV-2 ORF8 protein and human complement Factor 1 catalytic domain sharing common binding site on complement C3b

Pathogens are often known to use host factor mimicry to take evolutionary advantage. As the function of the non-structural ORF8 protein of SARS-CoV-2 in the context of host-pathogen relationship is still obscure, we investigated its role in host factor mimicry using computational protein modelling techniques. Modest sequence similarity of ORF8 of SARS-CoV-2 with the substrate binding site within the C-terminus serine-protease catalytic domain of human complement factor 1 (F1; PDB ID: 2XRC), prompted us to verify their resemblance at the structural level. The modelled ORF8 protein was found to superimpose on the F1 fragment. Further, protein-protein interaction simulation confirmed ORF8 binding to C3b, an endogenous substrate of F1, via F1-interacting region on C3b. Docking results suggest ORF8 to occupy the binding groove adjacent to the conserved "arginine-serine" (RS) F1-mediated cleavage sites on C3b. Comparative H-bond interaction dynamics indicated ORF8/C3b binding to be of higher affinity than the F1/C3b interaction. Hence, ORF8 is predicted to inhibit C3b proteolysis by competing with F1 for C3b binding using molecular mimicry with a possibility of triggering unregulated complement activation. This could offer a mechanistic premise for the unrestrained complement activation observed in large number of SARS-CoV-2 infected patients.

bioinformatics↗

bioRxiv2020

Transcriptomic expression patterns of two contrasting lowland rice varieties reveal high iron stress tolerance

Iron (Fe) toxicity is a major challenge for plant cultivation in acidic water-logged soil environments, where lowland rice is a major staple food crop. Only few studies addressed the molecular characterization of excess Fe tolerance in rice, and these highlight different mechanisms for Fe tolerance in the studied varieties. Here, we screened 16 lowland rice varieties for excess Fe stress growth responses to identify contrasting lines, Fe-tolerant Lachit and -susceptible Hacha. Hacha and Lachit differed in their physiological and morphological responses to excess Fe, including leaf growth, leaf rolling, reactive oxygen species generation, Fe and metal contents. These responses were mirrored by differential gene expression patterns, obtained through RNA-sequencing, and corresponding GO term enrichment in tolerant versus susceptible lines. From the comparative transcriptomic profiles between Lachit and Hacha in response to excess Fe stress, individual genes of the category metal homeostasis, mainly root-expressed, may contribute to the tolerance of Lachit. 22 out of these 35 metal homeostasis genes are present in selection sweep genomic regions, in breeding signatures and/or differentiated during rice domestication. These findings will serve to design targeted Fe tolerance breeding of rice crops. Summary statementLowland rice varieties Hacha and Lachit were selected for contrasting abilities to cope with iron excess stress. Morphological and physiological phenotypes were mirrored by molecular transcriptome changes, indicating altered metal homeostasis in the root as an adaptive tolerance mechanism in Lachit.

plant biology↗

bioRxiv2020

Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies new candidate susceptibility genes for breast and ovarian cancer

Familial, genome-wide association (GWAS), and sequencing studies and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWAS) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through novel application of a pleiotropy-guided conditional/conjunction false discovery rate approach for the first time in the setting of a TWAS. This identified 14 new candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 new candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR < 0.05 that were > 1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. Overlaying candidate causal risk variants identified by GWAS fine mapping onto expression prediction models for genes at known loci suggested that the association for 55% of these genes was driven by the underlying GWAS signal. SignificanceThe 22 new genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk.

genetics↗

bioRxiv2020

Body size and composition and site-specific cancers in UK Biobank: a Mendelian randomisation study

ObjectivesTo investigate the casual role of body mass index, body fat composition and height in cancer. DesignTwo stage mendelian randomisation study SettingPrevious genome wide association studies and the UK Biobank ParticipantsGenetic instrumental variables for body mass index (BMI), fat mass index (FMI), fat free mass index (FFMI) and height from previous genome wide association studies and UK Biobank. Cancer outcomes from 367 586 participants of European descent from the UK Biobank. Main outcome measuresOverall cancer risk and 22 site-specific cancers risk for genetic instrumental variables for BMI, FMI, FFMI and height. ResultsGenetically predicted BMI (per 1 kg/m2) was not associated with overall cancer risk (OR 0.99; 95% confidence interval (CI) 0-98-1.00, p=0.105). Elevated BMI was associated with increased risk of stomach cancer (OR 1.15, 95% (CI) 1.05-1.26; p=0.003) and melanoma (OR 0.96, 95% CI 0.92-1.00; p=0.044). For sex-specific cancers, BMI was positively associated with uterine cancer (OR 1.08, 95% CI 1.01-1.14; p=0.015) but inversely associated with breast (OR 0.95, 95% CI 0.92-0.98; p=0.001), prostate (OR 0.95, 95% CI 0.92-0.99; p=0.007) and testicular cancer (OR 0.89, 95% CI 0.81-0.98; p=0.017). Elevated FMI (per 1 kg/m2) was associated with gastrointestinal cancer (stomach cancer OR 4.23, 95% CI 1.18-15.13, p=0.027; colorectal cancer OR 1.94, 95% CI 1.23-3.07; p=0.004). Increased height (per 1 standard deviation, approximately 6.5cm) was associated with increased risk of overall cancer (OR 1.06; 95% 1.04-1.09; p = 2.97x10-8) and most site-specific cancers with the strongest estimates for kidney, non-Hodgkin lymphoma, colorectal, lung, melanoma and breast cancer. ConclusionsThere is little evidence for BMI as a casual risk factor for cancer. BMI may have a causal role for sex-specific cancers, although with inconsistent directions of effect, and FMI for gastrointestinal malignancies. Elevated height is a risk factor for overall cancer and multiple site cancers.

genetics↗

bioRxiv2020

Unraveling the aggregation dynamics of amyloidogenesis: A data-driven mathematical modeling approach

Proteins often get misfolded into highly ordered amyloid aggregates that are found to be associated with various neurodegenerative diseases. However, the dynamical events that lead to such self organization of different types of proteins are still poorly understood due to the experimentally untractable complex molecular mechanism, which governs the process of amyloidogenesis. Herein, we propose a generic and data-driven mathematical modeling approach that enables us to decipher a most probable molecular mechanism responsible for amyloidogensis in a context dependent manner. The preferred model efficiently elucidates various aspects of amyloid forming kinetics as a function of initial protein concentration, and qualitatively predicts the dynamics of amyloidogenesis for point mutated proteins. Importantly, the model analysis reveals that intermediate aggregates formed just after the primary necleation steps plays a vital role in dictating the nature of amyloid forming kinetics. Moreover, our model makes experimentally feasible insightful predictions to formulate better therapeutic measures in future to counter unwanted amyloidogenesis by just fine-tuning the molecular interactions related to amyloidogenesis. Author SummaryIn cells, proteins mostly function by being in a native folded conformation. However, under certain circumstances, some of these proteins undergo high degree of aggregation and eventually misfold to form highly stable amyloid aggregates that are often involved in different neurodegenerative disease progression and pathogenesis. To develop appropriate therapeutic strategies to resist such oligomerazation of protein, it is imperative to unravel the molecular interactions that essentially organize the dynamical events of amyloidogenesis. We have proposed a generic computational modeling framework to elucidate the important molecular events that govern the dynamics of amyloid formation. Our model reconciles diverse set of experimental observations including different mutant phenotyes from a dynamical perspective, and predicts possible ways to control the kinetics of amyloid formation experimentally. In future, these insights will be helpful to design drugs to treat patients with neurodegenerative disorders. Importantly, our model, in general, will be quite useful to figure out the important molecular events that are orchestrating the amyloidogenesis of different amyloid forming proteins.

systems biology↗

bioRxiv2019

Germline and somatic genetic variants in the p53 pathway interact to affect cancer risk, progression and drug response

Insights into oncogenesis derived from cancer susceptibility loci could facilitate better cancer management and treatment through precision oncology. However, therapeutic applications have thus far been limited by our current lack of understanding regarding both their interactions with somatic cancer driver mutations and their influence on tumorigenesis. Here, by integrating germline datasets relating to cancer susceptibility with tumour data capturing somatically-acquired genetic variation, we provide evidence that single nucleotide polymorphism (SNPs) and somatic mutations in the p53 tumor suppressor pathway can interact to influence cancer development, progression and treatment response. We go on to provide human genetic evidence of a tumor-promoting role for the pro-survival activities of p53, which supports the development of more effective therapy combinations through their inhibition in cancers retaining wild-type p53. SignificanceWe describe significant interactions between heritable and somatic genetic variants in the p53 pathway that affect cancer susceptibility, progression and treatment response. Our results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and identify novel therapeutic targets.

cancer biology↗

bioRxiv2019

Dynamical reorganization of transcriptional events governs robust Nanog heterogeneity

Nanog maintains pluripotency of embryonic stem cells (ESC's), while demonstrating high expression heterogeneity within an ESC population. Intriguingly, in ESC's, the overall heterogeneity at the Nanog mRNA level under various culture conditions gets precisely partitioned into intrinsic (~45%) and extrinsic (~55%) fluctuations. However, the dynamical origin of such a robust transcriptional noise regulation, still remains illusive. Herein, we conceived a new stochastic simulation strategy centered around Gillespie's stochastic simulation algorithm to efficiently capture fluctuations of different origins that are operative within a simple Nanog transcriptional regulatory network. Our model simulations reconcile the strict apportioning of Nanog transcriptional fluctuation, while predicting possible experimental scenarios to avoid such an exact noise segregation. Importantly, model analyses reveal that different culture conditions essentially preserve the Nanog expression heterogeneity by altering the dynamics of transcriptional events. These insights will be essential to systematically maneuver cell-fate decision making events of ESC's for therapeutic applications.

bioinformatics↗

bioRxiv2019

High-throughput allelic expression imbalance analyses identify candidate breast cancer risk genes

Fine-mapping of breast cancer GWAS regions has identified 195 high confidence signals containing more than 5,000 credible causal variants (CCVs). The CCVs are predominantly noncoding and enriched in regulatory elements and thus may confer the risk by altering gene expression in cis. We analyzed allelic expression imbalance (AEI) of genes surrounding known breast cancer signals, using normal breast and breast tumor transcriptome data and imputed genotypes. Fourteen genes, including NTN4, were identified whose expression was associated with CCV genotype. We showed that CCVs at this signal were located within an enhancer that physically interacts with the NTN4 promoter. Furthermore, knockdown of NTN4 in breast cells increased cell proliferation in vitro and tumor growth in vivo. Here, we present the most comprehensive AEI analysis of breast cancer CCVs resulting in identification of new candidate risk genes.

genetics↗

bioRxiv2019

Fine-mapping of 150 breast cancer risk regions identifies 178 high confidence target genes

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants (CCVs) in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium, and enriched genomic features to determine variants with high posterior probabilities (HPPs) of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of potentially causal variants, using gene expression (eQTL), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways, were over-represented among the 178 highest confidence target genes.

genetics↗

bioRxiv2019

Genetic predisposition to mosaic Y chromosome loss in blood is associated with genomic instability in other tissues and susceptibility to non-haematological cancers

Mosaic loss of chromosome Y (LOY) in circulating white blood cells is the most common form of clonal mosaicism, yet our knowledge of the causes and consequences of this is limited. Using a newly developed approach, we estimate that 20% of the UK Biobank male population (N=205,011) has detectable LOY. We identify 156 autosomal genetic determinants of LOY, which we replicate in 757,114 men of European and Japanese ancestry. These loci highlight genes involved in cell-cycle regulation, cancer susceptibility, somatic drivers of tumour growth and cancer therapy targets. Genetic susceptibility to LOY is associated with non-haematological health outcomes in both men and women, supporting the hypothesis that clonal haematopoiesis is a biomarker of genome instability in other tissues. Single-cell RNA sequencing identifies dysregulated autosomal gene expression in leukocytes with LOY, providing insights into how LOY may confer cellular growth advantage. Collectively, these data highlight the utility of studying clonal mosaicism to uncover fundamental mechanisms underlying cancer and other ageing-related diseases.

genetics↗

bioRxiv2018

Anemia Diagnosis on a Simple Paper-based Assay

In developing countries, the maternal and neonatal mortality rate is often affected by prenatal period anemia, a preventable and ubiquitous impairment attributed due to low hemoglobin (Hgb) concentration. We report the development of a simple, frugal (~ 0.02 $ per test), rapid and high fidelity paper-based colorimetric microfluidic device for point-of-care (POC) detection of anemia. We validate our findings with 32 blood samples collected from different patients covering a wide spectrum of anemia and subsequently, compare with standard pathological results measured using a hematology analyzer. POC based Hgb estimates are correlated with the pathological gold standard estimates of Hgb levels (r = 0.909), and the POC test method yielded similar sensitivity and specificity for detecting mild anemia (n = 8) (<11 g/dl) (sensitivity: 87.5%, specificity: 100 %) and for severe anemia (n = 3) (<7 g/dl) (sensitivity: 100 %, specificity: 100 %). The estimated Hgb levels are, within 1.5 g/dl from the pathological estimate, for 91 % of the blood samples. Results demonstrate the elevated efficacy and viability of this POC colorimetric diagnostic test, in comparison to the state-of-the-art complex and expensive diagnostic tests for anemia detection.

bioengineering↗

bioRxiv2018

Rapid Eye Movement sleep deprivation of rat generates ROS in the hepatocytes and make them more susceptible to oxidative stress

BackgroundRapid Eye Movement sleep deprivation (REMSD) of rats causes inflammation of the liver and apoptotic cell death of neurons and hepatocytes. Studies also suggest that REMSD are involved with muscle injury, cardiac injury and neurodegerative diseases.\n\nObjective and methodsThe aim of this research was to determine whether REMSD of rats would generate reactive oxygen species (ROS) and create oxidative stress in the hepatocytes. We selectively deprived the rats from REM sleep using the standard flower pot method.\n\nResultsWe observed that when rats were subjected to REMSD, the levels of ROS in the hepatocytes increased with the increase in the number of days of REMSD by [~]265%, but it returned towards normal levels after recovery sleep for 5 days ([~]36%) compared to controls. Nitric oxide synthase (iNOS) gene and protein was found elevated in hepatocytes in response to REM sleep loss as confirmed by real time PCR and western blot analysis compared to controls. The level of nitric oxide (NO) also increased by [~] 675% in the hepatocytes of REMSD rats as compared to that of control group of animals.\n\nDiscussionWe have analyzed the oxidative stress generated and potentiation of hepatocytes against oxidative stress in response to REMSD. Since, REM sleep is known to play an important role for survival of most animals and has important role in maintenance of body physiology. Hence, our findings that loss of REM sleep in hepatocytes of rats can affect the ROS levels and induce iNOS & NO circulation, while making them more susceptible to oxidative stress assumes significance.\n\nHighlights of the studyO_LIWe observed elevated levels of ROS in the hepatocytes of REM sleep deprived rats.\nC_LIO_LIThe hepatocytes of REMSD group of rats were found more susceptible to oxidative stress than that of control groups.\nC_LIO_LIWe found increased expression of iNOS gene and nitric oxide synthase protein in the hepatocytes of REMSD rats.\nC_LIO_LIWe observed that nitric oxide levels in the hepatocytes of REM sleep deprived rats increased positively with days of REMSD, but returned to its normal levels after 5 days of recovery sleep.\nC_LI

molecular biology↗