Biology subjects

Grover, P.

Publications and source records attributed to Grover, P..

18 recordsLinked to original sources

bioRxiv2026

Chronic Electrophysiology Captures Progressive Variability in DNA-Damaged Cardiac Networks

Electrophysiological recordings provide a key functional readout of cardiac health. Most in vitro studies rely on acute measurements rather than recording evolving functional changes. Here, we implement a microelectrode array (MEA) based system for chronic electrophysiological monitoring of human induced pluripotent stem cell-derived cardiomyocyte (iPSC-CM) monolayers. Electrophysiology recordings were maintained for up to 40 days, enabling longitudinal assessment of field potential amplitude, field potential duration, beat frequency, conduction velocity, and waveform morphology. Untreated iPSC-CM monolayers exhibited stable electrophysiological behavior throughout chronic culture. Following exposure to the cardiotoxic chemotherapeutic doxorubicin, chronic recordings captured progressive deterioration in electrical activity, including reduced field potential amplitude, altered repolarization dynamics, increased beat-to-beat variability, and reduced conduction that persisted after drug removal. Electrode-resolved analyses further revealed pronounced progressive spatial variability, highlighting localized responses that would be obscured by population-averaged measurements. Endpoint assays indicated reduced calcium transient amplitude and altered calcium reuptake, decreased mitochondrial membrane potential, and loss of connexin 43, findings consistent with the impaired electrical activity observed in chronic recordings. Together, these results establish chronic electrophysiological monitoring as a powerful approach for resolving the spatiotemporal progression of cardiotoxicity and other dynamic cardiac processes in vitro.

bioengineering↗

bioRxiv2026

Pharmacologic DPP-4 inhibition promotes CD8⁺ T cell metabolic fitness to enhance anti-tumor activity

Metabolic dysfunction is a hallmark of CD8+ T cell exhaustion in the tumor microenvironment. Thus, there is growing interest in developing strategies that enhance anti-tumor functions of CD8+ T cells via metabolic reprogramming. Here, we identify dipeptidyl peptidase 4 (DPP-4) as a previously unknown regulator of CD8+ T cell function and metabolism. We discovered that DPP-4 is upregulated in exhausted CD8+ T cells. Pharmacological inhibition of DPP-4 with the FDA-approved anti-diabetic drug sitagliptin transcriptionally and metabolically reprogrammed CD8+ T cells, increasing spare mitochondrial respiratory capacity, proliferation, cytotoxic mediator production, and antigen-specific cancer cell killing capability. The functional effects of sitagliptin were dependent on upregulation of glutamate decarboxylase 1 (GAD1), an enzyme that feeds glutamate into the tricarboxylic acid (TCA) cycle, highlighting a new role for GAD1 in CD8+ T cell respiration and proliferation. We found that systemic inhibition of DPP-4 in preclinical mouse glioblastoma (GBM) models prolongs survival in a CD8+ T cell-dependent manner, and retrospective clinical cohort analysis revealed better outcomes in GBM patients using DPP-4 inhibitors. Importantly, preconditioning of Chimeric Antigen Receptor (CAR) T-cells with DPP-4 inhibition enhanced their cytotoxicity, persistence, and therapeutic efficacy in pediatric GBM. Together, our findings provide mechanistic and biological rationale for repurposing readily accessible DPP-4 inhibitors to enhance anti-tumor CD8+ T cell responses.

immunology↗

bioRxiv2026

A minimally invasive floating-wire interface for transcranial deep brain stimulation

BackgroundNon-invasive neuromodulation technologies have advanced considerably. Yet, precise and focal activation of deep brain regions remains challenging due to the rapid attenuation of electric fields across the scalp, skull and brain surface. ObjectiveWe present FLOATES (FLOAting Transcranial Electrical Stimulation), a novel approach that employs an untethered wire implanted in the brain which passively relays currents injected transcranially from the brain surface to deep brain regions, achieving focused stimulation deep within the brain. MethodsWe validated FLOATES through a combination of simulations, benchtop testing, and in vivo rodent studies. The benchtop experiments confirmed the ability to relay the field across the floating wire. Rodent studies demonstrated capability to stimulate deep brain regions in vivo. ResultsOur simulation and benchtop testing results indicate that FLOATES can deliver significantly higher electric fields to subcortical regions compared to conventional transcranial stimulation approaches. Further in-vivo results demonstrated deep subthalamic nuclei stimulation to evoke limb motor responses and demonstrated a significantly lower motor threshold compared to transcranial stimulation. Finite element simulations reveal that the efficiency of FLOATES depends on several key parameters including input field strength, wire length and diameter, exposed electrode area, impedance, and tip geometry. Simulations using a human-sized head model suggest that electric fields sufficient for brain stimulation can be obtained with reasonable currents injected to the scalp. ConclusionTogether, these results establish a theoretical and experimental foundation for FLOATES as a minimally invasive and spatially precise brain stimulation platform in modulating deep neural circuits implicated in neuropsychiatric and movement disorders.

bioengineering↗

bioRxiv2025

Identifying Neural Biomarkers of Risk-Taking from Intracranial EEG Recordings

Risk-taking behavior is associated with neuropsychiatric disorders such as addiction. In this study, we present a data-driven approach to identify neural biomarkers of risk-taking from intracranial stereo-electroencephalography (sEEG) recordings. Using time and frequency domain features, we train a classifier to distinguish between risk-taking and risk-avoidance behaviors. Based on data from a single patient, the model achieves an accuracy of 68.5%, which is significantly above chance. These results highlight the potential of identifying risk-taking states from invasive recordings. Clinical SignificanceThis work demonstrates the feasibility of identifying risk-related biomarkers from intracranial recordings, highlighting a promising direction for closed-loop neuromodulation for neuropsychiatric conditions.

neuroscience↗

bioRxiv2024

DeepFocus: A Transnasal Approach for Optimized Deep Brain Stimulation of Reward Circuit Nodes

ObjectiveTranscranial electrical stimulation (TES) is an effective technique to modulate brain activity and treat diseases. However, TES is primarily used to stimulate superficial brain regions and is unable to reach deeper targets. The spread of injected currents in the head is affected by volume conduction and the additional spreading of currents as they move through head layers with different conductivities, as is discussed in [1]. In this paper, we introduce DeepFocus, a technique aimed at stimulating deep brain structures in the brains "reward circuit" (e.g. the orbitofrontal cortex, Brodmann area 25, amygdala, etc.). ApproachTo accomplish this, DeepFocus utilizes transnasal electrode placement (under the cribriform plate and within the sphenoid sinus) in addition to electrodes placed on the scalp, and optimizes current injection patterns across these electrodes. To quantify the benefit of DeepFocus, we develop the DeepROAST simulation and optimization platform. DeepROAST simulates the effect of complex skull-base bones geometries on the electric fields generated by DeepFocus configurations using realistic head models. It also uses optimization methods to search for focal and efficient current injection patterns, which we use in our simulation and cadaver studies. Main ResultsIn simulations, optimized DeepFocus patterns created larger and more focal fields in several regions of interest than scalp-only electrodes. In cadaver studies, DeepFocus patterns created large fields at the medial orbitofrontal cortex (OFC) with magnitudes comparable to stimulation studies, and, in conjunction with established cortical stimulation thresholds, suggest that the field intensity is sufficient to create neural response, e.g. at the OFC. SignificanceThis minimally invasive stimulation technique can enable more efficient and less risky targeting of deep brain structures to treat multiple neural conditions.

neuroscience↗

bioRxiv2024

Topological confinement by a membrane anchor suppresses phase separation into protein aggregates: implications for prion diseases

Protein misfolding and aggregation are a hallmark of various neurodegenerative disorders. However, the underlying mechanisms driving protein misfolding in the cellular context are incompletely understood. Here we show that the restriction of conformational degrees of freedom by a membrane anchor stabilizes the native protein conformation and suppresses liquid-liquid phase separation and protein aggregation. Inherited prion diseases in humans and neurodegeneration in transgenic mice are linked to the expression of anchorless prion protein (PrP), suggesting that the C-terminal glycosylphosphatidylinositol (GPI) anchor of native PrP impedes spontaneous formation of neurotoxic and infectious PrP species. Combining novel in vitro and in vivo approaches, we show that anchoring to membranes prevents spontaneous aggregation of PrP. Upon release from the membrane, PrP undergoes a rapid conformational transition to detergent-insoluble aggregates. Our study supports an essential role of the GPI anchor in preventing spontaneous misfolding of PrPC.

molecular biology↗

bioRxiv2023

NEMO reshapes the protein aggregate interface and promotes aggrephagy by co-condensation with p62

NEMO is a ubiquitin-binding protein which regulates canonical NF-{kappa}B pathway activation in innate immune signaling, cell death regulation and host-pathogen interactions. Here we identified an NF-{kappa}B-independent function of NEMO in proteostasis regulation by promoting autophagosomal clearance of protein aggregates. NEMO-deficient cells accumulate misfolded proteins upon proteotoxic stress and are vulnerable to proteostasis challenges. Moreover, a patient with a mutation in the NEMO gene resulting in defective binding of NEMO to linear ubiquitin chains, developed a widespread mixed brain proteinopathy, including -synuclein, tau and TDP-43 pathology. NEMO amplifies linear ubiquitylation at -synuclein aggregates and promotes the local concentration of p62 into foci. In vitro, NEMO lowers the threshold concentrations required for ubiquitin-dependent phase transition of p62. In summary, NEMO reshapes the aggregate surface for efficient autophagosomal clearance by providing a mobile phase at the aggregate interphase favoring co-condensation with p62.

cell biology↗

bioRxiv2023

A novel ground truth dataset enables robust 3D nuclear instance segmentation in early mouse embryos

For investigations into fate specification and cell rearrangements in time-lapse images of preimplantation embryos, automated 3D instance segmentation of nuclei and subsequent nuclear tracking are invaluable. Often, the images low signal-to-noise ratio and high voxel anisotropy and the nucleis dense packing and variable shapes limit the performance of many segmentation methods, while subsequent tracking of nuclear instances is complicated by low frame rates and sample movements. Supervised machine learning approaches can radically improve segmentation accuracy and enable easier tracking, but they often require large amounts of difficult-to-obtain annotated 3D data. Here we report a novel mouse line expressing near-infrared nuclear reporter H2B-miRFP720. H2B-miRFP720 is the longest wavelength nuclear reporter in mice and can be imaged simultaneously with other reporters with minimal overlap. We then generate a dataset, which we call BlastoSPIM, of 3D microscopy images of H2B-miRFP720-expressing embryos with ground truth for nuclear instance segmentation. Using BlastoSPIM, we benchmark the performance of seven convolutional neural networks and identify Stardist-3D as the most accurate instance segmentation method across preimplantation development. We then construct a complete pipeline for nuclear instance segmentation with our BlastoSPIM-trained Stardist-3D models and lineage tracking from the 8-cell stage to the end of preimplantation development (> 100 nuclei). Finally, we demonstrate BlastoSPIMs usefulness as pre-train data for related problems, both for a different imaging modality and for different model systems. BlastoSPIM, its corresponding Stardist-3D models, and documentation of the full associated analysis pipeline are available at: blastospim.flatironinstitute.org.

developmental biology↗

bioRxiv2022

Noninvasive, automated and reliable detection of spreading depolarizations in severe traumatic brain injury using scalp EEG

BackgroundNoninvasive detection of spreading depolarizations (SD), as a potentially treatable mechanism of worsening brain injuries after traumatic brain injuries (TBI), has remained elusive. Current methods to detect SDs are based on intracranial recording, an invasive method with limited spatial coverage. Less invasive methods to diagnose SD are needed to improve generalizability and application of this emerging science and to guide worsening brain injury treatments. Here, we demonstrate, for the first time, a signal processing paradigm that can enable automated detection of SDs using noninvasive electroencephalography (EEG). MethodsBuilding on our previously developed WAVEFRONT algorithm, we have designed a novel automated SD detection method. This algorithm, with learnable parameters and improved velocity estimation, extracts and tracks propagating power depressions, as well as near-DC shifts using low-density EEG. This modified WAVEFRONT is robust to the amplitude outliers and non-propagating depressions on the scalp. We show the feasibility of detecting SD events (700 total SDs) in continuous, low-density scalp EEG recording (95{+/-}42.2 hours with 19 electrodes) acquired from 12 severe TBI patients who underwent decompressive hemicraniectomy (DHC) and intracranial EEG that could be used as a ground truth for event detection. We quantify the performance of WAVEFRONT in terms of SD detection accuracy, including true positive rate (TPR) and false positive rate (FPR), as well as the accuracy of estimating the frequency of SDs. ResultsWAVEFRONT achieves the best average validation accuracy of 74% TPR (with 95% confidence interval of 70.8%-76.7%), with less than 1.5% FPR using Delta band EEG. Preliminary evidence suggests that WAVEFRONT can achieve a very good performance (regression with R2 [~=]0.71) in the estimation of SD frequencies. ConclusionsWe demonstrate feasibility and quantify the performance of noninvasive SD detection after severe TBI using an automated algorithm. WAVEFRONT can potentially be used for diagnosis and monitoring of worsening brain injuries to guide treatments by providing a measure of SD frequency. Extension of these results to patients with intact skulls requires further study.

neuroscience↗

bioRxiv2020

Quantifying a Frequency Modulation Response Biomarker in Responsive Neurostimulation

ObjectiveResponsive Neurostimulation (RNS) is an effective treatment for controlling seizures in patients with drug-resistant focal epilepsy who are not suitable candidates for resection surgery. A lack of tools for detecting and characterizing potential response biomarkers, however, contributes to a limited understanding of mechanisms by which RNS improves seizure control. We developed a method to quantify ictal frequency modulation, previously identified as a biomarker of clinical responsiveness to RNS. ApproachFrequency modulation is characterized by shifts in power across spectral bands during ictal events, over several months of neurostimulation. This effect was quantified by partitioning each seizure pattern into segments with distinct spectral content and measuring the extent change from the baseline distribution of spectral content using the squared Earthmovers distance. Main resultsWe analyzed intracranial electroencephalography data from 13 patients who received RNS therapy, six of whom exhibited frequency modulation on expert evaluation. Subjects in the frequency modulation group had, on average, significantly larger and more sustained changes in their Earthmovers distances (mean = 13.97x10-3 {+/-} 1.197x10-3). In contrast, those subjects without expert-identified frequency modulation exhibited statistically insignificant or negligible distances (mean = 4.994x10-3 {+/-} 0.732x10-3). SignificanceThis method is the first step towards a quantitative, feedback-driven system for systematically optimizing RNS stimulation parameters, with an ultimate goal of truly personalized closed-loop therapy for epilepsy.

neuroscience↗

bioRxiv2020

Neural silences can be localized rapidly using noninvasive scalp EEG

A rapid and cost-effective noninvasive tool to detect and characterize suppressed neural activity can be of significant benefit for the diagnosis and treatment of many disorders. We propose a novel algorithm, SilenceMap, for uncovering the absence of electrophysiological signals, or neural "silences", using noninvasive scalp electroencephalography (EEG) signals. By accounting for the contributions of different sources to the power of the recorded signals, and using a novel hemispheric baseline approach and a convex spectral clustering framework, SilenceMap permits rapid detection and localization of regions of silence in the brain using a relatively small amount of EEG data. SilenceMap substantially outperformed existing source localization algorithms in estimating the center-of-mass of the silence for three pediatric patients with lobectomy, using less than 3 minutes of EEG recordings (13, 2, and 11mm vs. 25, 62, and 53mm), as well for 70 different simulated regions of silence based on a real human head model (11{+/-}0.5mm vs. 54{+/-}2.2mm). SilenceMap paves the way towards accessible early diagnosis and continuous monitoring of altered physiological properties of human cortical function.

neuroscience↗

bioRxiv2020

Tumor -Associated MUC1 Regulates TGF-β Signaling and Function in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDA) is one of the most lethal human cancers. Transforming Growth Factor Beta (TGF-{beta}) is a cytokine that switches from a tumor-suppressor to a tumor promoter throughout tumor development, by a yet unknown mechanism. Tumor associated MUC1 (tMUC1) is aberrantly glycosylated and overexpressed in >80% of PDAs and is associated with poor prognosis. The cytoplasmic tail of MUC1 (MUC1-CT) interacts with other oncogenic proteins promoting tumor progression and metastasis. We hypothesize that tMUC1 levels regulate TGF-{beta} functions in PDA in vitro and in vivo. We report that high-tMUC1 expression positively correlates to TGF-{beta}RII and negatively to TGF-{beta}RI receptors. In response to TGF-{beta}1, high tMUC1 expressing PDA cells undergo c-Src phosphorylation, and activation of the Erk/MAPK pathway; while low tMUC1 expressing cells activate the Smad2/3 pathway, enhancing cell death. Correspondingly, mice bearing tMUC1-high tumors responded to TGF-{beta}1 neutralizing antibody in vivo showing significantly retarded tumor growth. Analysis of clinical data from TCGA revealed significant alterations in gene-gene correlations in the TGF-{beta} pathway in tMUC1 high versus tMUC1 low samples. This study deepens our understanding of tMUC1-regulated TGF-{beta}s paradoxical function in PDA and establishes tMUC1 as a potential biomarker to predict response to TGF-{beta}-targeted therapies.

cancer biology↗

bioRxiv2020

The mechanics of Temporal Interference stimulation

We utilize single neuron models to understand mechanisms behind Temporal Interference (TI) stimulation (also called "Interferential Stimulation"). We say that a neuron exhibits TI stimulation if it does not fire for a high-frequency sinusoidal input, but fires when the input is a low-frequency modulation of the high-frequency sinusoid (specifically that generated by addition of two high frequency sinusoids with a small difference in their frequencies), while the maximum amplitude is kept the same in both cases. Our key observation - that holds for both FitzHugh-Nagumo and Hodgkin-Huxley neuron models - is that for neuron models that do exhibit TI stimulation, a high frequency pure sinusoidal input results in a current balance between inward and outward currents. This current balance leads to a subthreshold periodic orbit that keeps the membrane potential from spiking for sinusoidal inputs. However, the balance is disturbed when the envelope of the sinusoids is modulated with a high slope: the fast-changing envelope activates fast depolarizing currents without giving slow outward currents time to respond. This imbalance causes the membrane potential to build up, causing the neuron to fire. This mechanistic understanding can help design current waveforms for neurons that exhibit TI stimulation, and also help classify which neuron-types may or may not exhibit TI stimulation.

neuroscience↗

bioRxiv2020

Novel Electrodes for Reliable EEG Recordings on Coarse and Curly Hair

EEG is a powerful and affordable brain sensing and imaging tool used extensively for the diagnosis of neurological disorders (e.g. epilepsy), brain computer interfacing, and basic neuroscience. Unfortunately, most EEG electrodes and systems are not designed to accommodate coarse and curly hair common in individuals of African descent. This can lead to poor quality data that might be discarded in scientific studies after recording from a broader population set, and for clinical diagnoses, lead to an uncomfortable and/or emotionally taxing experience, and, in the worst cases, misdiagnosis. In this work, we design a system to explicitly accommodate coarse and curly hair, and demonstrate that, across time, our electrodes, in conjunction with appropriate braiding, attain substantially (~10x) lower impedance than state-of-the-art systems. This builds on our prior work that demonstrated that braiding hair in patterns consistent with the clinical standard 10-20 arrangement leads to improved impedance with existing systems.

bioengineering↗

bioRxiv2019

Overcoming Immunological Resistance Enhances the Efficacy of a Novel anti-tMUC1 CAR T Cell Treatment Against Pancreatic Ductal Adenocarcinoma

Chimeric antigen receptor engineered T cells (CAR T cells) have shown remarkable success in treating hematologic cancers. However, this efficacy has yet to translate to treatment in solid tumors. Pancreatic ductal adenocarcinoma (PDA) is a fatal malignancy with poor prognosis. Treatment options are limited and commonly associated with severe side effects. We have developed and characterized a second generation CAR engineered T cell using the light and heavy chain sequence derived from a novel monoclonal antibody, TAB004, that specifically binds the tumor associated antigen, tMUC1. tMUC1 is overexpressed in varying levels on ~85% of all human PDA. We present data showing that the TAB004 derived CAR T cells (tMUC1-CAR T cells) specifically bind to tMUC1 on PDA cells and is cytotoxic against the majority of the PDA cell lines. The tMUC1-CAR T cells do not bind or kill normal epithelial cells. We further demonstrate that the tMUC1-CAR T cells control the growth of orthotopic pancreatic tumors in vivo. PDAs are generally cold tumors with resistance to many standard treatment modalities, thus, it was not surprising that some of the PDA cell lines were refractory to CAR T cell treatment. qPCR analysis of several genes known to be associated with immune resistance revealed overexpression of indoleamine 2, 3-dioxygenases-1 (IDO1), Cyclooxygenase 1 and 2 (COX1 and COX2), Adenosine deaminases acting on RNA (ADAR1) and galectin-9 (Gal-9). We treated resistant PDA cells with a combination of CAR T cells and biological inhibitors of IDO1, COX1/2, ADAR1, and Gal-9. Results showed a significant enhancement of CAR T cell cytotoxicity against PDA cells when inhibiting IDO1, COX1/2, and Gal-9 but not ADAR1 or COX2. Overcoming CAR T cell resistance in PDA is a significant advancement in the field and may lead to future combination therapies that are less toxic but more efficient against this deadly disease.

cancer biology↗

bioRxiv2018

An algorithm for automated, noninvasive detection of cortical spreading depolarizations based on EEG simulations

We present a novel signal processing algorithm for automated, noninvasive detection of Cortical Spreading Depolarizations (CSDs) using electroencephalography (EEG) signals and validate the algorithm on simulated EEG signals. CSDs are waves of neurochemical changes that suppress neuronal activity as they propagate across the brains cortical surface. CSDs are believed to mediate secondary brain damage after brain trauma and cerebrovascular diseases like stroke. We address key challenges in detecting CSDs from EEG signals: (i) decay of high spatial frequencies as they travel from the cortical surface to the scalp surface; and (ii) presence of sulci and gyri, which makes it difficult to track the CSD waves as they travel across the cortex. Our algorithm detects and tracks \"wavefronts\" of the CSD wave, and stitches together data across space and time to decide on the presence of a CSD wave. To test our algorithm, we provide different models and complex patterns of CSD waves, including different widths of CSD suppressions, and use these models to simulate scalp EEG signals using head models of 4 subjects from the OASIS dataset. Our results suggest that the average width of suppression that a low-density EEG grid of 40 electrodes can detect is 1.1 cm, which includes a vast majority of CSD suppressions, but not all. A higher density EEG grid having 340 electrodes can detect complex CSD patterns as thin as 0.43 cm (less than minimum widths reported in prior works), among which single-gyrus propagation is the hardest to detect because of its small suppression area.

bioengineering↗

bioRxiv2017

STIMULUS: Noninvasive Dynamic Patterns of Neurostimulation using Spatio-Temporal Interference

Using a systematic computational and modeling framework, we provide a novel Spatio-Temporal Interference-based stiMULation focUsing Strategy (STIMULUS) for high spatial precision noninvasive neurostimulation deep inside the brain. To do so, we first replicate the results of the recently proposed temporal interference (TI) stimulation (which was only tested in-vivo) in a computational model based on a Hodgkin-Huxley model for neurons and a model of current dispersion in the head. Using this computational model, we obtain a nontrivial extension of the 2-electrode-pair TI proposed originally to multielectrode TI (> 2 electrode pairs) that yields significantly higher spatial precision. To further improve precision, we develop STIMULUS techniques for generating spatial interference patterns in conjunction with temporal interference, and demonstrate strict and significant improvements over multielectrode TI. Finally, we utilize the adaptivity that is inherent in STIMULUS to create multisite neurostimulation patterns that can be dynamically steered over time.

neuroscience↗

bioRxiv2017

Very high density EEG elucidates spatiotemporal aspects of early visual processing

Standard human EEG systems based on spatial Nyquist estimates suggest that 20-30 mm electrode spacing suffices to capture neural signals on the scalp, but recent studies posit that increasing sensor density can provide higher resolution neural information. Here, we compared \"super-Nyquist\" density EEG (\"SND\") with Nyquist density (\"ND\") arrays for assessing the spatiotemporal aspects of early visual processing. EEG was measured from 128 electrodes arranged over occipitotemporal brain regions (14 mm spacing) while participants viewed flickering checkerboard stimuli. Analyses compared SND with ND-equivalent subsets of the same electrodes. Frequency-tagged stimuli were classified more accurately with SND than ND arrays in both the time and the frequency domains. Representational similarity analysis revealed that a computational model of V1 correlated more highly with the SND than the ND array. Overall, SND EEG captured more neural information from visual cortex, arguing for increased development of this approach in basic and translational neuroscience.\n\nAbbreviations

neuroscience↗