Biology subjects

Rao, N.

Publications and source records attributed to Rao, N..

At least 19 recordsLinked to original sources

bioRxiv2026

A multi-organ spatial metabolomic atlas of exercising mice reveals neuronal Complex I as a convergent and sufficient axis for tau pathology reduction in PS19

We constructed a spatially resolved metabolomic atlas of long-term exercise across six major organs in wild-type mice: brain, heart, lung, liver, kidney, and skeletal muscle, cataloguing 224 metabolic features and revealing coordinated inter-organ remodeling. Surprisingly, the brain showed particularly pronounced region-specific adaptation. Because pathological tau associates with synaptic mitochondria from early stages of tauopathy, we extended this multi-organ spatial metabolomic approach to PS19 mice and found that exercise reduced over 70% of observable tau pathology in PS19 hippocampus and restored the mitochondrial-related metabolome. Integrated proteomic and spatial metabolomic analyses identified NADH dehydrogenase Complex I as the convergent node. To test this finding biologically, we expressed the yeast NADH dehydrogenase, Ndi1, in PS19 neurons in the absence of exercise. This increased cerebral antioxidants, restored shuttle-linked metabolites, and reduced tau pathology. Increasing NADH dehydrogenase activity through NDI1 reproduces the core anti-tau and metabolic effects of exercise. These findings provide a molecular mechanism for how exercise may prevent or slow tau pathology accumulation, complementing the human-cohort literature linking exercise to delayed cognitive decline.

neuroscience↗

bioRxiv2026

Metabolic Coherence of the Mouse Brain

The brains metabolic demands are well established, but how metabolism is coordinated across anatomically distinct regions remains poorly understood. Here, using matrix-assisted laser desorption/ionization (MALDI) imaging integrated with the Allen Brain Atlas and optimal transport-based computational analysis, we map the spatial metabolome across twelve major mouse brain divisions. We define an optimal-transport-derived inter-regional metabolite similarity metric and refer to it as metabolic coherence. This structure is largely preserved in an amyloid mouse model of Alzheimers disease despite widespread changes in individual metabolite and lipid levels. Individual metabolites and lipids shift in a coordinated manner across regions, sustaining inter-regional relationships even as absolute levels change in patterns indicative of mitochondrial dysfunction. To test whether the coherence metric is responsive to local intervention, we targeted the left hippocampus of mice from this model via lentiviral shHIF1 knockdown or neuronal AAV-mediated AOX expression. Both interventions were associated with metabolite normalization at the injection site. More importantly, normalization extended across distal regions sharing high metabolic similarity with the hippocampus and was accompanied by improved social memory in a single behavioral assay. Gene modulation and amyloid plaque reduction localized to the injection site.

neuroscience↗

bioRxiv2025

GRNITE: Gene Regulatory Network Inference with Text Embeddings

Gene regulatory networks (GRNs) capture complex regulatory relationships that govern gene expression in cells. Inference of GRNs from single-cell RNA-seq (scRNA-seq) data has been an active topic of research in the past several years. However, despite the improvements in the data quality, the GRN inference problem remains a challenging task with many approaches showing variable performance dependent on the organism and cell type. To improve the quality of GRN inference and enable more comprehensive exploratory analyses of GRNs across various phenotypes of interest, we developed a two-stage meta-method called GRNITE. In the first step, GRNITE leverages LLM-based embeddings of plain text gene descriptions to create a prior gene interaction graph, which is then optimized with a graph neural network (GNN) to achieve a "universal" biological prior for GRN inference. In the second step, GRNITE uses a GNN to incorporate information from a GRN inferred from scRNA-seq data with any baseline inference method into our prior. The result of this two-step approach is a near-universal improvement in AUROC and recall of all evaluated methods, with minor trade-offs in precision. Furthermore, GRNITE is a lightweight meta-method, which adds a minimal amount of extra compute time on top of the original GRN inference performed. GRNITE and our pre-trained universal prior GRN are available on GitHub: https://github.com/aliaaz99/GRNITE.

bioinformatics↗

bioRxiv2025

A transgenic mouse allows to capture the HLA-C*06:02 immunopeptidome in a model of psoriasis

Psoriasis vulgaris is a T cell-mediated autoimmune skin condition affecting around one in fifty people worldwide. Whilst advanced immunomodulatory therapeutic options have become available in recent years, ongoing disease suppression is still required with no curative treatment available to date. The human leukocyte antigen class I allele HLA-C*06:02 is the main genetic risk determinant of psoriasis. Its function is to present peptide antigens to CD8+ T cells and natural killer cells which in turn elicit and perpetuate the immune response, yet little is known about ligands presented by HLA-C*06:02. To gain an understanding which HLA-C*06:02-restricted peptides are presented by epidermal cell populations and might be initiators of the autoimmune response in psoriasis, we have conducted an in depth immunopeptidomics analysis of HLA-C*06:02+ keratinocyte and melanocyte cell lines. Furthermore, we introduce a HLA-C*06:02 transgenic mouse which, in conjunction with the imiquimod model of psoriasis, allowed us to assess the ex vivo immunopeptidome of HLA-C*06:02 in psoriasiform skin. Overall, we detected 20,812 high confidence HLA-C*06:02 bound peptide ligands. Thus, we present a comprehensive coverage HLA-C in vitro immunopeptidomics dataset and the first HLA-C*06:02 ex vivo dataset of psoriasis-relevant peptide antigens that may inform the development of antigen-specific, novel curative therapeutic approaches in psoriasis.

immunology↗

bioRxiv2025

Intratumor Heterogeneity Through the Lens of Gene Regulatory Networks

Intratumor heterogeneity (ITH), the presence of heterogeneous genomic and transcriptomic populations in tumor and its implications for the cancer therapies has been one of the focal points of computational cancer biology in the past years. While ITH is well characterized at the genomic level, the regulatory wiring connecting clonal genotypes to transcriptional states remains largely unmapped. To understand whether the evidence for ITH at the gene regulatory level can be inferred from scRNA-seq data, we analyzed scRNA-seq datasets spanning triple-negative breast cancer, colorectal cancer, glioblastoma, and a longitudinal stage IV breast cancer cohort, inferring clone-specific gene regulatory networks (GRNs) and developing quantitative tools to compare them: a Wasserstein distance-based measure of regulatory divergence, a kth order neighborhood similarity framework distinguishing structural from functional rewiring, bootstrap-based edge confidence, and an integrated regulon classification pipeline. Our analyses demonstrate that tumor clones exhibit reproducibly distinct network architectures, and dominant clones show significantly greater regulatory divergence from normal cells than smaller clones, linking regulatory rewiring to clonal fitness. Treatment-induced remodeling exceeds clonal variation, with rewiring exhibiting structural divergence but functional convergence. Regulon analysis further resolved clone-variable, sample-specific, and broadly conserved programs, some of which containing transcription factors whose target genes independently were associated with patient survival.

bioinformatics↗

bioRxiv2024

Task relevance selectively modulates sensorimotor adaptation in the presence of multiple prediction errors.

Adaptation to consistently occurring sensorimotor errors is considered obligatory in nature. We probed the robustness of this finding by asking if humans can selectively attenuate adaptation based on the task-relevance of error signals. Subjects made planar reaches to three different targets: an arc (Experiment 1), a bar (Experiment 2), and a point (Experiment 3). During the reach, perturbations in extent (visuomotor gain), direction (visuomotor rotation) or both simultaneously were employed. In Experiment 1, subjects showed robust adaptation to the rotation when reaching to the arc even though the presence of this perturbation was irrelevant for achievement of the task goal. Interestingly however, rotation adaptation was strongly attenuated when it was presented simultaneously with a task-relevant gain perturbation. In Experiment 2, which involved reaches to the bar, again, subjects successfully adapted to the task-irrelevant gain perturbation when it occurred in isolation. However, adaptation was attenuated when the gain co-occurred with a task-relevant rotation. Experiment 3 revealed that the attenuation observed in the first two experiments was not due to an inability to adapt to co-occurring rotation and gain perturbations. Collectively, our results suggest that the sensorimotor system selectively tunes learning in the presence of multiple error signals, a finding that can potentially be explained by a biased competition mechanism. That is, given limited processing capacity, a salient attribute - the relevance of the error to the task goal in this case - is prioritized for processing and drives subsequent adaptive changes in motor output. NEW AND NOTEWORTHYThe motor system continuously uses error feedback to recalibrate movements in response to changes in body and environmental conditions. Such error-based adaptation is thought to be obligatory, occurring whenever error signals are present, and even if the learning interferes with achievement of the task goal. Contrary to this classical view, we demonstrate selective modulation of motor adaptation in the presence of multiple error signals based on their task-relevance.

neuroscience↗

bioRxiv2024

Loop Catalog: a comprehensive HiChIP database of human and mouse samples

HiChIP enables cost-effective and high-resolution profiling of chromatin loops. To leverage the increasing number of HiChIP datasets, we developed Loop Catalog (https://loopcatalog.lji.org), a web-based database featuring loop calls from 1000+ distinct human and mouse HiChIP samples from 152 studies plus 44 high-resolution Hi-C samples. We demonstrate its utility for interpreting GWAS and eQTL variants through SNP-to-gene linking, identifying enriched sequence motifs and motif pairs, and generating regulatory networks and 2D representations of chromatin structure. Our catalog spans over 4.19M unique loops, and with embedded analysis modules, constitutes an important resource for the field.

bioinformatics↗

bioRxiv2024

Mycobacterium dormancy and antibiotic tolerance within the retinal pigment epithelium of ocular tuberculosis

Tuberculosis (TB) is a leading cause of death among infectious diseases worldwide due to latent TB infection, which is the critical step for the successful pathogenic cycle. In this stage, Mycobacterium tuberculosis resides inside the host in a dormant and antibiotic-tolerant state. Latent TB infection can lead to a multisystemic diseases because M. tuberculosis invades virtually all organs, including ocular tissues. Ocular tuberculosis (OTB) occurs when the dormant bacilli within ocular tissues reactivate, originally seeded by hematogenous spread from pulmonary TB. Timely and accurate diagnosis as well as efficient chemotherapies are crucial in preventing poor visual outcomes of OTB patients. Histological evidence suggests that retinal pigment epithelium (RPE) cells play a central role in immune privilege and in the protection from the antibiotic effects, making them an anatomical niche for invading M. tuberculosis. RPE cells exhibit high tolerance to environmental redox stresses, allowing phagocytosed M. tuberculosis bacilli to maintain viability in a dormant state. However, the microbiological and metabolic mechanisms determining the interaction between the RPE intracellular environment and phagocytosed M. tuberculosis are largely unknown. Here, liquid chromatography mass spectrometry (LC-MS) metabolomics was used to illuminate the metabolic state within RPE cells reprogrammed to harbor dormant M. tuberculosis bacilli and enhance the antibiotic tolerance. The results have led to propose a novel therapeutic option to synthetically kill the dormant M. tuberculosis inside the RPE cells by modulating the phenotypic state of M. tuberculosis, thus laying the foundation for a new, innovative regimen for treating OTB. ImportanceUnderstanding the metabolic environment within the retinal pigment epithelium (RPE) cells altered by infection with M. tuberculosis and mycobacterial dormancy is crucial to identify new therapeutic methods to cure OTB. The present study showed that RPE cellular metabolism is altered to foster intracellular M. tuberculosis to enter into the dormant and drug tolerant state, thereby blunting the efficacy of anti-TB chemotherapy. RPE cells serve as an anatomical niche as the cells protect invading bacilli from antibiotic treatment. LC-MS metabolomics of RPE cells after co-treatment with H2O2 and M. tuberculosis infection showed that intracellular environment within RPE cells is enriched with greater level of oxidative stress. The antibiotic tolerance of intracellular M. tuberculosis within RPE cells can be restored by a metabolic manipulation strategy such as co-treatment of antibiotic with the most downstream glycolysis metabolite, phosphoenolpyruvate.

microbiology↗

bioRxiv2023

Elucidating the heterogeneity of immunotherapy response and immune-related toxicities by longitudinal ctDNA and immune cell compartment tracking in lung cancer

PurposeAlthough immunotherapy is the mainstay of therapy for advanced non-small cell lung cancer (NSCLC), robust biomarkers of clinical response are lacking. The heterogeneity of clinical responses together with the limited value of radiographic response assessments to timely and accurately predict therapeutic effect -especially in the setting of stable disease-call for the development of molecularly-informed real-time minimally invasive predictive biomarkers. In addition to capturing tumor regression, liquid biopsies may be informative in evaluating immune-related adverse events (irAEs). Experimental designWe investigated longitudinal changes in circulating tumor DNA (ctDNA) in patients with metastatic NSCLC who received immunotherapy-based regimens. Using ctDNA targeted error-correction sequencing together with matched sequencing of white blood cells and tumor tissue, we tracked serial changes in cell-free tumor load (cfTL) and determined molecular response for each patient. Peripheral T-cell repertoire dynamics were serially assessed and evaluated together with plasma protein expression profiles. ResultsMolecular response, defined as complete clearance of cfTL, was significantly associated with progression-free (log-rank p=0.0003) and overall survival (log-rank p=0.01) and was particularly informative in capturing differential survival outcomes among patients with radiographically stable disease. For patients who developed irAEs, peripheral blood T-cell repertoire reshaping, assessed by significant TCR clonotypic expansions and regressions were noted on-treatment. ConclusionsMolecular responses assist with interpretation of heterogeneous clinical responses especially for patients with stable disease. Our complementary assessment of the tumor and immune compartments by liquid biopsies provides an approach for monitoring of clinical benefit and immune-related toxicities for patients with NSCLC receiving immunotherapy. Statement of translational relevanceLongitudinal dynamic changes in cell-free tumor load and reshaping of the peripheral T-cell repertoire capture clinical outcomes and immune-related toxicities during immunotherapy for patients with non-small cell lung cancer.

genomics↗

bioRxiv2023

Lateralized Neural Entropy modulates with Grip Force during Precision Grasping

When holding a coffee mug filled to the brim, we strive to avoid spilling the coffee. This ability relies on the neural processes underlying the control of finger forces on a moment-to-moment basis. The brain activity lateralized to the contralateral hemisphere averaged over a trial and across the trials is known to be associated with the magnitude of grip force applied on an object. However, the mechanistic involvement of the variability in neural signals during grip force control remains unclear. In this study, we examined the dependence of neural variability over the frontal, central, and parietal regions assessed using noninvasive electroencephalography (EEG) on grip force magnitude during an isometric force control task. We hypothesized laterally specific modulation in EEG variability with higher magnitude of the grip force exerted during grip force control. We utilized an existing EEG dataset (64 channel) comprised of healthy young adults, who performed an isometric force control task while receiving visual feedback of the force applied. The force magnitude to be exerted on the instrumented object was cued to participants during the task, and varied pseudorandomly among 5, 10, and 15% of their maximum voluntary contraction (MVC) across the trials. We quantified neural variability via sample entropy (sequence-dependent measure) and standard deviation (sequence-independent measure) of the temporal EEG signal over the frontal, central, and parietal electrodes. The EEG sample entropy over the central electrodes showed lateralized, nonlinear, localized, modulation with force magnitude. Similar modulation was not observed over frontal or parietal EEG activity, nor for standard deviation in the EEG activity. Our findings highlight specificity in neural control of grip forces by demonstrating the modulation in sequence-dependent but not sequence-independent component of EEG variability. This modulation appeared to be lateralized, spatially constrained, and functionally dependent on the grip force magnitude. We discuss the relevance of these findings in scenarios where a finer precision is essential to enable grasp application, such as prosthesis and associated neural signal integration, and propose directions for future studies investigating the mechanistic role of neural entropy in grip force control.

neuroscience↗

bioRxiv2023

Charting spatial ligand-target activity using Renoir

The advancement of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics has enabled the inference of cellular interactions in a tissue microenvironment. Despite the development of cell-cell interaction inference methods, there is a lack of methods capable of mapping the influence of ligands on downstream target genes across a spatial topology with specific cell type composition, with the potential to shed light on niche-specific relationship between ligands and their downstream targets. Here we present Renoir for charting the ligand-target activities across a spatial topology and delineating spatial communication niches harboring specific ligand-target activities. Renoir also spatially maps pathway-level activity of ligand-target genesets and identifies domain-specific ligand-target activities. Across spatial datasets with varying resolution (spot to single-cell) ranging from development to disease, Renoir inferred cellular niches with distinct ligand-target interactions, spatially mapped pathway activities, and identified context-specific novel cell-cell interactions. Renoir uncovers biological insights and therapeutically-relevant cellular crosstalk from spatial transcriptomics data.

bioinformatics↗

bioRxiv2021

Plasticity of extrachromosomal and intrachromosomal BRAF amplifications in mediating targeted therapy dosage challenges

Cancer cells display two modes of focal amplifications (FAs), extrachromosomal DNA/double-minutes (ecDNA/DMs) and intrachromosomal homogenously staining regions (HSRs). Understanding the plasticity of these two modes is critical for preventing targeted therapy resistance. We developed a combined BRAF plus MEK inhibitor resistance melanoma model that bears high BRAF amplifications through both DM and HSR modes, and investigated FA dynamics in the context of drug resistance plasticity. Cells harboring FAs displayed mode switching between DMs and HSRs, from both de novo genetic changes and selection of preexisting subpopulations. We found that copy number plasticity is not exclusive to DMs. Single cell-derived clones with HSRs also exhibit BRAF copy number and corresponding HSR length plasticity that allows them to respond to dose reduction and recover from drug addiction. Upon kinase inhibitor escalation, we observed reproducible selection for cells with BRAF kinase domain duplications residing on DMs. In sum, the plasticity of FAs allows cancer cells to respond to drug dose changes through a myriad of mechanisms. These mechanisms include increases or decreases in DMs, shortening of HSRs, acquisition of secondary resistance mechanisms, and expression of alternative slicing oncogene variants. These results highlight the challenges in targeting the cellular vulnerabilities tied to focal amplifications. Statement of SignificanceUnderstanding the dynamics of oncogene amplifications is critical for appreciating tumorigenesis and preventing anticancer drug resistance. We found melanoma cells harboring BRAF amplifications in either DM or HSR formats to have high plasticity under different kinase inhibitor dosage challenges with evidence supporting de novo alterations, clonal selection, and coupling to additional resistance mechanisms. In in the absence of DMs, HSRs can offer comparable levels of plasticity as DMs.

cancer biology↗

bioRxiv2021

Generation of a molecular interactome of the glioblastoma perivascular niche reveals Integrin Binding Sialoprotein as a key mediator of tumor cell migration

Glioblastoma (GBM) is characterized by extensive microvascular hyperproliferation. In addition to supplying blood to the tumor, GBM vessels also provide trophic support to glioma cells and serve as conduits for migration into the surrounding brain promoting recurrence. Here, we enriched CD31-expressing glioma vascular cells (GVC) and A2B5-expressing glioma tumor cells (GTC) from primary GBM and utilized RNA sequencing to create a comprehensive interaction map of the secreted and extracellular factors elaborated by GVC that can interact with receptors and membrane molecules on GTC. To validate our findings, we utilized functional assays, including a novel hydrogel-based migration assay and in vivo mouse models to demonstrate that one identified factor, the little-studied integrin binding sialoprotein (IBSP) enhances tumor growth and promotes the migration of GTC along the vasculature. This perivascular niche interactome will serve a resource to the research community in defining the potential functions of the GBM vasculature.

cancer biology↗

bioRxiv2020

Modulation of Grasp Parameters using Arbitrary Cues about Object Property in Older Adults

Dexterous manipulation may be guided by explicit information about object property. Such a manipulation requires fine modulation of digit position and forces using explicit cues. Young adults can form arbitrary cue-object property associations for accurate modulation of digit position and forces. Aging, in contrast, might alter this conditional learning. Older adults are impaired in accurately modulating their digit forces using explicit cues about object property. However, it is not known whether older adults can use explicit cues about object property to modulate digit position. In this study, we instructed ten healthy older and ten young adults to learn a manipulation task using arbitrary color cues about object center of mass location. Subjects were required to exert clockwise, counterclockwise, or no torque on the object according to the color cue and lift the object while minimizing its tilt across sixty trials. Older adults produced larger torque error during the conditional learning trials than young adults. This resulted in a significantly slower rate of learning in older adults. Older, but not young adults, failed to modulate their digit position and forces using the color cues. Similar aging-related differences were not observed while learning the task using implicit knowledge about object property. Our findings suggest that aging impairs the ability to use explicit cues about object property to modulate both digit position and forces for dexterous manipulation. We discuss our findings in relation to age-related changes in the processes and the neural network for conditional learning.

neuroscience↗

bioRxiv2020

Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data

BackgroundExisting computational methods for studying miRNA regulation are mostly based on bulk miRNA and mRNA expression data. However, bulk data only allows the analysis of miRNA regulation regarding a group of cells, rather than the miRNA regulation unique to individual cells. Recent advance in single-cell miRNA-mRNA co-sequencing technology has opened a way for investigating miRNA regulation at single-cell level. However, as currently single-cell miRNA-mRNA co-sequencing data is just emerging and only available at small-scale, there is a strong need of novel methods to exploit existing single-cell data for the study of cell-specific miRNA regulation. ResultsIn this work, we propose a new method, CSmiR (Cell-Specific miRNA regulation) to use single-cell miRNA-mRNA co-sequencing data to identify miRNA regulatory networks at the resolution of individual cells. We apply CSmiR to the miRNA-mRNA co-sequencing data in 19 K562 single-cells to identify cell-specific miRNA-mRNA regulatory networks for understanding miRNA regulation in each K562 single-cell. By analyzing the obtained cell-specific miRNA-mRNA regulatory networks, we observe that the miRNA regulation in each K562 single-cell is unique. Moreover, we conduct detailed analysis on the cell-specific miRNA regulation associated with the miR-17/92 family as a case study. Finally, through exploring cell-cell similarity matrix characterized by cell-specific miRNA regulation, CSmiR provides a novel strategy for clustering single-cells to help understand cell-cell crosstalk. ConclusionsTo the best of our knowledge, CSmiR is the first method to explore miRNA regulation at a single-cell resolution level, and we believe that it can be a useful method to enhance the understanding of cell-specific miRNA regulation.

bioinformatics↗

bioRxiv2020

Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex

We used the 10x Genomics Visium platform to define the spatial topography of gene expression in the six-layered human dorsolateral prefrontal cortex (DLPFC). We identified extensive layer-enriched expression signatures, and refined associations to previous laminar markers. We overlaid our laminar expression signatures onto large-scale single nuclei RNA sequencing data, enhancing spatial annotation of expression-driven clusters. By integrating neuropsychiatric disorder gene sets, we showed differential layer-enriched expression of genes associated with schizophrenia and autism spectrum disorder, highlighting the clinical relevance of spatially-defined expression. We then developed a data-driven framework to define unsupervised clusters in spatial transcriptomics data, which can be applied to other tissues or brain regions where morphological architecture is not as well-defined as cortical laminae. We lastly created a web application for the scientific community to explore these raw and summarized data to augment ongoing neuroscience and spatial transcriptomics research (http://research.libd.org/spatialLIBD). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/969931v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@fcf6borg.highwire.dtl.DTLVardef@1fab44dorg.highwire.dtl.DTLVardef@53629dorg.highwire.dtl.DTLVardef@6f3de5_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2019

LMSM: a modular approach for identifying lncRNA related miRNA sponge modules in breast cancer

Until now, existing methods for identifying lncRNA related miRNA sponge modules mainly rely on lncRNA related miRNA sponge interaction networks, which may not provide a full picture of miRNA sponging activities in biological conditions. Hence there is a strong need of new computational methods to identify lncRNA related miRNA sponge modules. In this work, we propose a framework, LMSM, to identify LncRNA related MiRNA Sponge Modules from heterogeneous data. To understand the miRNA sponging activities in biological conditions, LMSM uses gene expression data to evaluate the influence of the shared miRNAs on the clustered sponge lncRNAs and mRNAs. We have applied LMSM to the human breast cancer (BRCA) dataset from The Cancer Genome Atlas (TCGA). As a result, we have found that the majority of LMSM modules are significantly implicated in BRCA and most of them are BRCA subtype-specific. Most of the mediating miRNAs act as crosslinks across different LMSM modules, and all of LMSM modules are statistically significant. Multi-label classification analysis shows that the performance of LMSM modules is significantly higher than baselines performance, indicating the biological meanings of LMSM modules in classifying BRCA subtypes. The consistent results suggest that LMSM is robust in identifying lncRNA related miRNA sponge modules. Moreover, LMSM can be used to predict miRNA targets. Finally, LMSM outperforms a graph clustering-based strategy in identifying BRCA-related modules. Altogether, our study shows that LMSM is a promising method to investigate modular regulatory mechanism of sponge lncRNAs from heterogeneous data. Author summaryPrevious studies have revealed that long non-coding RNAs (lncRNAs), as microRNA (miRNA) sponges or competing endogenous RNAs (ceRNAs), can regulate the expression levels of messenger RNAs (mRNAs) by decreasing the amount of miRNAs interacting with mRNAs. In this work, we hypothesize that the "tug-of-war" between RNA transcripts for attracting miRNAs is across groups or modules. Based on the hypothesis, we propose a framework called LMSM, to identify LncRNA related MiRNA Sponge Modules. Based on the two miRNA sponge modular competition principles, significant sharing of miRNAs and high canonical correlation between the sponge lncRNAs and mRNAs, LMSM is also capable of predicting miRNA targets. LMSM not only extends the ceRNA hypothesis, but also provides a novel way to investigate the biological functions and modular mechanism of lncRNAs in breast cancer.

bioinformatics↗

bioRxiv2019

Persistent Elevation of Electrical Pain Threshold following Continuous Theta Burst Stimulation over Primary Somatosensory Cortex in Humans

BackgroundPrimary somatosensory cortex (S1) is involved in pain processing and thus its suppression using neuromodulatory techniques such as continuous theta burst stimulation (cTBS) might be a potential pain management strategy in patients with neuropathic pain. S1 cTBS is known to elevate pain threshold in young adults. However, the persistence of this effect is unknown.\n\nObjective/HypothesisWe hypothesized persistent elevation of pain threshold following cTBS over S1 in healthy, young adults.\n\nMethodsWe recruited ten subjects in a sham-controlled crossover design and recorded their electrical pain threshold (EPT) for 40 min following cTBS over S1. We assessed corticospinal excitability (CSE) to rule out the involvement of primary motor cortex due to spread of current.\n\nResultscTBS over S1 elevated EPT without modulating CSE compared to sham stimulation. EPT was elevated for 40 min post-cTBS.\n\nConclusionsS1 can be focally targeted using cTBS for a longer lasting pain relief in patients.

neuroscience↗