Biology subjects

Shaikh, S.

Publications and source records attributed to Shaikh, S..

10 recordsLinked to original sources

bioRxiv2026

Spatial Orchestration of Skin Fibrosis by a CD8+ T cell-Myofibroblast Axis

Fibrosing skin diseases are highly morbid conditions with diverse clinical and histopathologic features. Prior work, primarily in systemic sclerosis (SSc), has yielded mixed data regarding the immune drivers of fibrosis, as well as the identity and spatial localization of pro-fibrotic fibroblast cell subsets. Here, we focus on morphea and eosinophilic fasciitis (EF), which cause more acutely inflammatory skin fibrosis. Using multimodal single-nucleus and spatial transcriptomics, we find that effector CD8+ T cells are highly enriched in fibrotic skin. These cells are particularly abundant in inflammatory tissue domains bordering fibrotic stroma, which are marked by expression of interferon-{gamma} stimulated genes. Inflammatory domains feature a loss of local homeostatic fibroblast populations and replacement with ADAM12-expressing inflammatory fibroblasts and myofibroblasts, which co-localize closely with CD8+ T cells. All subtypes of morphea featured similar patterns of CD8+ T-cell-associated fibro-inflammatory zonation and fibroblast transformation, suggesting that shared mechanisms can drive fibrosis across stromal compartments of skin. We apply these findings to a large publicly available scleroderma dataset and find that similar processes occur in SSc. Mechanistically, ablation of CD8+ T cells in mice ameliorates bleomycin-driven inflammation and fibrosis, as does fibroblast-intrinsic abrogation of IFN-{gamma} signaling. These data establish CD8+ T cell-driven fibrogenesis as a key feature of fibrosing skin diseases and raise the prospect of targeting CD8+ T cells in autoimmune fibrosis more broadly. One sentence summarySpatial profiling of morphea-spectrum diseases reveals CD8 T cells as key drivers of fibrosis through fibroblast IFN-{gamma} signaling.

immunology↗

bioRxiv2025

Spatial Transcriptomics Reveals CXCL12+ Fibroblasts as Central Immune Organizers through CXCR4 Signaling in Abdominal Aortic Aneurysm

BACKGROUNDAbdominal aortic aneurysm (AAA) is characterized by sterile inflammation, immune cell infiltration, and stromal remodeling that progressively weaken the aortic wall, leading to life-threatening aortic rupture. The molecular mechanisms and spatial organization of immune-stromal interactions in human tissue are poorly understood, limiting the potential to develop effective pharmacological therapy for AAA. METHODSIn this observational cross-sectional study, formalin-fixed, paraffin-embedded tissues from 11 AAA patients and 12 controls were analyzed by Xenium spatial transcriptomics. Cellular states and localization within tissue architecture were mapped to identify cellular neighborhoods and infer cell-cell communication. RESULTSWe generated a high-resolution spatial transcriptomics atlas of 581,664 cells in 26 clusters. AAAs showed a significant loss of contractile smooth muscle cells, expansion of pro-angiogenic endothelial subsets, and broad infiltration of immune cells. These inflammatory changes were accompanied by expansion of activated, universal, and CXCL12 adventitial fibroblasts. Spatial transcriptomic analysis revealed fibroblast-immune colocalization and adventitial tertiary lymphoid organs. Inferred signaling pathway analysis identified increased interactions between CXCL12 fibroblasts and CXCR4 T and B cells in the adventitia of AAAs. Fibroblasts that expressed CXCL12 had significantly more immune cell neighbors than fibroblasts that did not, suggesting that they serve as stromal hubs for adaptive immune clustering. Genome-wide association analysis linked AAA heritability to fibroblasts, modulated smooth muscle cells, and foamy macrophages. CONCLUSIONOur novel high-resolution spatial transcriptomic atlas of human AAAs revealed coordinated pathogenic reprogramming of stromal and immune cells, defined by smooth muscle cell depletion, fibroblast activation, endothelial remodeling, and disproportionate expansion of immune cells. Through CXCR4 signaling, CXCL12 fibroblasts serve as central organizers of immune niches, suggesting stromal-immune crosstalk as a therapeutic target in AAA. CLINICAL PERSPECTIVESWhat Is New? O_LIWe generated the first subcellular-resolution spatial transcriptomic atlas of human abdominal aortic aneurysm (AAA), with >580,000 cells identified from aortic tissue sections C_LIO_LIWe identified CXCL12+ fibroblasts as central stromal hubs that organize adaptive immune niches through CXCR4-mediated crosstalk with B and T cells C_LIO_LIWe discovered that stromal populations carry the strongest genetic enrichment for AAA risk, notably fibroblast and modulated smooth muscle cell populations C_LI What Are The Clinical Implications? O_LIThese findings position stromal-immune interactions, particularly the CXCL12-CXCR4 axis, as a potential therapeutic target to slow AAA progression C_LIO_LIThe spatial atlas provides a framework for mechanistic studies and drug-discovery efforts, guiding future interventions aimed at modifying the microenvironment that destabilizes the aneurysmal aortic wall C_LI

cell biology↗

bioRxiv2025

Painless Nav1.7 mutations reveal function-critical residuesin the outer vestibule and N-terminus

Chronic pain is a common condition, placing a large cost on society and a heavy burden on the individual. Nav1.7 has emerged as a non-redundant and axiomatically important part of human pain pathways. Biallelic loss-of-function (LOF) mutations in SCN9A, encoding voltage-gated sodium channel Nav1.7, cause the Mendelian disorder Congenital Insensitivity to Pain (CIP). Studying novel missense mutations in this channel has the potential to uncover unrealised functions of critical residues that could enable new strategies for analgesia. Here we describe detailed functional studies of six SCN9A missense variants found in individuals with typical SCN9A-CIP: c.224T>C/p.Leu75Pro, c.1025C>T/p.Thr342Met, c.2686C>T/p.Arg896Trp, c.2732G>A/p.Arg911His, c.5059G>C/p.Ala1687Pro, and c.5173G>C/p.Gly1725Arg. While all variants were extremely rare and predicted to alter function, current tools cannot specify the extent or direction of change in function, nor provide information about the mechanism(s) of pathogenicity. Stable cell lines were generated for each variant, using the isogenic Jump-In T-REx HEK293 system. We investigated how each variant caused molecular dysfunction using multiple approaches: sequence conservation analysis and 3D modelling to examine the structural importance of the affected residues; automated whole-cell patch clamp electrophysiology to assess channel biophysics; and finally, immunocytochemistry along with cell-surface biotinylation to detect any alterations in subcellular localisation. Our studies revealed that all mutations reached the cell membrane but caused a complete LOF through small localised structural changes in the extracellular vestibule, ion selectivity filter and N-terminus that abolished sodium conductance. Functional analysis remains the most reliable method of classifying SCN9A missense variants and can help to pinpoint important subdomains. Online SummaryVoltage-gated sodium channel Nav1.7 is a key modulator of nociceptor excitability and associated with congenital painlessness. Functional analysis and in silico modelling reveal critical roles for residues in the extracellular vestibule, ion selectivity filter and unexpectedly, the N-terminus.

molecular biology↗

bioRxiv2024

Breast cancer spheroids prefer activated macrophages as an accomplice: An in vitro study

Cancer, a heterogeneous disease in nature, often requires help from diverse pro-tumor or tumor-associated- cells, which are recruited and persevered within the stroma. Pro-tumor stromal cells provide the essential support needed for tumor growth, metastasis, and development of drug resistance in due time. Tumor-associated macrophages, one of such cells, are essential to tumor microenvironment and tumor survival. In recent years, TAMs have been identified as potential drug targets and therapeutic agents, which encourages the in-depth characterization of their crosstalk with the tumors. The current study has successfully developed a cost-effective in vitro platform for Chemokine Assisted Recruitment of Macrophages to spheroids mimicking the physiology of TAM recruitment. Firstly, monocytic cell line (U937) were converted into activated naive macrophages (M0) and pro-and anti-inflammatory (M1 and M2) subtypes. Monocytes, M0, M1, and M2 macrophages are characterized extensively. Secondly, the naive and polarized macrophages were subjected to chemokine-dependent recruitment into monotypic and heterotypic breast cancer spheroids. The nature of the recruitment is further investigated by assessing the profile of chemokines and chemokine receptors. Recruited macrophages are also observed to manipulate spheroid behavior in many ways. The recruited macrophages also exhibit an increased level of Siglec-1 (CD169), one of the potential TAM markers. The current platforms potential for application can be extended to understand the recruitment process of other immune/stromal cells to solid tumors. It could be a potential addition to the arrays of in vitro platforms developed to screen the efficiency of cell-based immunotherapeutics in the future.

cancer biology↗

bioRxiv2022

Flavor Classification/Categorization and Differential Toxicity of Oral Nicotine Pouches (ONPs) in Lung Epithelial Cells

The prevalence of flavored tobacco product usage amongst youth in the United States is partly due to the emergence of non-combustible nicotine-containing products (NCNPs), including oral nicotine pouches (ONPs) and smokeless tobacco products. ONPs are available in various different flavors (mint, fruity, tobacco, dessert, citrus, coffee, wintergreen, and berry) and may use either Tobacco-Derived Nicotine (TDN) or Tobacco-Free Nicotine (TFN). Currently, several brands of ONPs are sold in the U.S and comprise a significant portion of NCNP sales in the U.S. There is a growing concern that flavored ONPs may not only induce oral health effects, but may also induce systemic toxic effects due to nicotine and other ONP byproducts being absorbed into systemic circulation through the oral mucosa. These byproducts can act locally on other tissues and may potentially cause redox dysregulation and heightened inflammatory responses systemically in the respiratory, cardiovascular, and/or renal systems. Hence, we determined the effects of flavored ONPs from four of the most widely sold brands in the U.S in inducing toxicological effects on the respiratory epithelium. Prior to analyzing the effects ONPs, we first classified ONPs sold in the US based on their flavor and the flavor category to which they belong to using a wheel diagram. Subsequently, using human bronchial epithelial cells (16-HBE and BEAS-2B) exposed to extracts of flavored ONPs, we assessed the levels of ONP-induced inflammatory cytokine release (IL-6 and IL-8), cellular Reactive Oxygen Species (ROS) production, and cytotoxicity in the airway epithelium. Our data showed that cells exposed to the lowest concentration treatments showed increased cytotoxicity, differential cellular ROS production, and proinflammatory cytokine release. The most striking response was observed among cells treated with the spearmint ONP, whereas ONPs containing original tobacco and fruity flavors showed varied levels of ROS release in 16-HBE cells. Our data suggest that flavored ONPs are unsafe and likely to cause systemic and local toxicological responses during chronic usage. Our study is a part of ongoing efforts to use in vitro, ex-vivo, and in vivo systems to understand how the usage of various flavored ONPs may cause both oral and pulmonary toxicity, and impact human periodontal health.

pharmacology and toxicology↗

bioRxiv2020

Lightweight Reinforcement Algorithms for autonomous, scalable intra-cortical Brain Machine Interfaces

Intra-cortical Brain Machine Interfaces (iBMIs) with wireless capability could scale the number of recording channels by integrating an intention decoder to reduce data rates. However, the need for frequent retraining due to neural signal non-stationarity is a big impediment. This paper presents an alternate paradigm of online reinforcement learning (RL) with a binary evaluative feedback in iBMIs to tackle this issue. This paradigm eliminates time-consuming calibration procedures. Instead, it relies on updating the model on a sequential sample-by-sample basis based on an instantaneous evaluative binary feedback signal. However, batch updates of weight in popular deep networks is very resource consuming and incompatible with constraints of an implant. In this work, using offline open-loop analysis on pre-recorded data, we show application of a simple RL algorithm - Banditron -in discrete-state iBMIs and compare it against previously reported state of the art RL algorithms - Hebbian RL, Attention gated RL, deep Q-learning. Owing to its simplistic single-layer architecture, Banditron is found to yield at least two orders of magnitude of reduction in power dissipation compared to state of the art RL algorithms. At the same time, post-hoc analysis performed on four pre-recorded experimental datasets procured from the motor cortex of two non-human primates performing joystick-based movement-related tasks indicate Banditron performing significantly better than state of the art RL algorithms by at least 5%, 10%, 7% and 7% in experiments 1, 2, 3 and 4 respectively. Furthermore, we propose a non-linear variant of Banditron, Banditron-RP, which gives an average improvement of 6%, 2% in decoding accuracy in experiments 2,4 respectively with only a moderate increase in power consumption.

bioengineering↗

bioRxiv2020

The DCC receptor regulates astroglial development essential for telencephalic morphogenesis and corpus callosum formation

The forebrain hemispheres are predominantly separated during embryogenesis by the interhemispheric fissure (IHF). Radial astroglia remodel the IHF to form a continuous substrate between the hemispheres for midline crossing of the corpus callosum (CC) and hippocampal commissure (HC). DCC and NTN1 are molecules that have an evolutionarily conserved function in commissural axon guidance. The CC and HC are absent in Dcc and Ntn1 knockout mice, while other commissures are only partially affected, suggesting an additional aetiology in forebrain commissure formation. Here, we find that these molecules play a critical role in regulating astroglial development and IHF remodelling during CC and HC formation. Human subjects with DCC mutations display disrupted IHF remodelling associated with CC and HC malformations. Thus, axon guidance molecules such as DCC and NTN1 first regulate the formation of a midline substrate for dorsal commissures prior to their role in regulating axonal growth and guidance across it.

neuroscience↗

bioRxiv2020

Towards Autonomous Intra-cortical Brain Machine Interfaces: Applying Bandit Algorithms for Online Reinforcement Learning

This paper presents application of Banditron - an online reinforcement learning algorithm (RL) in a discrete state intra-cortical Brain Machine Interface (iBMI) setting. We have analyzed two datasets from non-human primates (NHPs) - NHP A and NHP B each performing a 4-option discrete control task over a total of 8 days. Results show average improvements of {approx} 15%, 6% in NHP A and 15%, 21% in NHP B over state of the art algorithms - Hebbian Reinforcement Learning (HRL) and Attention Gated Reinforcement Learning (AGREL) respectively. Apart from yielding a superior decoding performance, Banditron is also the most computationally friendly as it requires two orders of magnitude less multiply-and-accumulate operations than HRL and AGREL. Furthermore, Banditron provides average improvements of at least 40%, 15% in NHPs A, B respectively compared to popularly employed supervised methods - LDA, SVM across test days. These results pave the way towards an alternate paradigm of temporally robust hardware friendly reinforcement learning based iBMIs.

bioengineering↗

bioRxiv2019

Sparse Ensemble Machine Learning to improve robustness of long-term decoding in iBMIs

This paper presents a novel sparse ensemble based machine learning approach to enhance robustness of intracortical Brain Machine Interfaces (iBMIs) in the face of non-stationary distribution of input neural data across time. Each classifier in the ensemble is trained on a randomly sampled (with replacement) set of input channels. These sparse connections ensure that with a high chance, few of the base classifiers should be less affected by the variations in some of the recording channels. We have tested the generality of this technique on different base classifiers - linear discriminant analysis (LDA), support vector machine (SVM), extreme learning machine (ELM) and multilayer perceptron (MLP). Results show decoding accuracy improvements of up to {approx} 21%, 13%, 19%, 10% in non-human primate (NHP) A and 7%, 9%, 7%, 9% in NHP B across test days while using the sparse ensemble approach over a single classifier model for LDA, SVM, ELM and MLP algorithms respectively. The technique also holds ground when the most informative electrode on the test day is dropped. Accordingly, improvements of up to {approx} 24%, 11%, 22%, 9% in NHP A and 14%, 19%, 7%, 28% in NHP B are obtained for LDA, SVM, ELM and MLP respectively.

bioengineering↗

bioRxiv2019

Towards Intelligent Intra-cortical BMI (i2BMI):Low-power Neuromorphic Decoders that outperform Kalman Filters

Fully implantable wireless intra-cortical Brain Machine Interfaces (iBMI) is one of the most promising next frontiers in the nascent field of neurotechnology. However, scaling the number of channels in such systems by another 10X is difficult due to power and bandwidth requirements of the wireless transmitter. One promising solution for that is to include more processing, up to the decoder, in the implant so that transmission data rate is reduced drastically. Earlier work on neuromorphic decoders only showed classification of discrete states. We present results for continuous state decoding using a low power neuromorphic decoder chip termed Spike-input Extreme Learning Machine (SELMA). We compared SELMA against state of the art Steady State Kalman Filter (SSKF) across two different datasets involving a total of 4 non-human primates (NHPs). Results show at least a 10% or more increase in the fraction of variance accounted for by SELMA over SSKF across the datasets. Furthermore, estimated energy consumption comparison shows SELMA consuming {approx} 9 nJ/update against SSKFs {approx} 7.4 nJ/update for an iBMI with a 10 degree of freedom control. Thus, SELMA yields better performance against SSKF with a marginal increase in energy consumption paving the way for reducing transmission data rates in future scaled BMI systems.

bioengineering↗