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Malik, Z.

Publications and source records attributed to Malik, Z..

8 recordsLinked to original sources

Oncostatin M-driven leak in human endothelial cells with preserved tight junctions

Blood vessels must preserve blood volume while permitting exchange of nutrients. Endothelial cells line the lumen of all blood vessels and form the intercellular junctions that govern vascular permeability. In acute critical illness the barrier fails, fluid escapes into tissues, and the resulting loss of volume and impaired nutrient exchange cause organ failure. Several inflammatory cytokines are known to disrupt junctions in cultured cells, yet therapies targeting these models have failed. How blood vessels respond to critical illness has remained largely elusive because endothelial cells are generally inaccessible. Here we profile endothelial cells recovered directly from critically ill children to show that oncostatin M drives a previously unrecognized mode of vascular leak. Oncostatin M increases permeability by forming narrow, nanoscale channels within the overlapping borders of adjacent cells, around intact tight junctions. These channels permit passage of small and intermediate sized solutes. Their formation depends on non-canonical signaling in which the kinase JAK1 activates two required parallel pathways (via ERK1 and AKT1) that converge on the transcription factor c-Fos. Inhibiting JAK1, either parallel pathway or depleting c-Fos, prevents oncostatin M-induced loss of barrier function. These results identify a permeability mechanism distinct from the junction disassembly driven by the cytokines that have dominated this field and implicate kinases already targeted by approved drugs as potential points of intervention. More broadly, vascular barriers are transiently loosened during immune-cell trafficking and metastasis, raising the possibility that diverse forms of vascular permeability arise through regulated nanoscale remodeling rather than junctional breakdown.

cell biology↗

SIGHT: an immersive Virtual Reality platform for reinforced learning of optics and functional neuroanatomy of vision

Virtual reality (VR) offers immersive and interactive learning environments that can improve student engagement and 3D visualization. However, its application in medical education is mostly limited to clinical settings and its potential for better understanding complex concepts, or empathy with the patients, remains underexplored. Here, we describe SIGHT (Simulated Immersive Guidance for Human Training), an immersive VR application, designed to teach core concepts in the physics and functional neuroanatomy, or neurophysiology of human vision. Its two integrated learning modules allow first-person experience of normal and pathological conditions: the optics module enables users to manipulate lenses, experience refractive errors such as myopia, presbyopia, and astigmatism and correct them through appropriate lens selection; the neurophysiology module allows learners to navigate the visual pathways from the retina to the visual cortex and to simulate lesions, experiencing the corresponding visual field deficits. User authentication and interactive evaluation steps provide analytical feedback of the experience and learning process. A pilot group of medical students reported high usability, engagement and deeper understanding of the vision-related concepts, showing how the approach of SIGHT can support experiential learning in medical education.

scientific communication and education↗

Comparative Machine Learning Analysis of Saliva and Plaque Microbiomes in Children with Type 1 Diabetes

BackgroundType 1 diabetes (T1D) is associated with microbial dysbiosis. While most research has focused on the gut microbiome, limited data address the role of the oral microbiome in T1D. The oral and gut microbiomes overlap substantially, and the oral cavity may influence the gut microbial composition. Saliva and dental plaque represent two distinct oral niches with unique microbial communities, but it remains unclear which better reflects systemic disease states such as T1D. This study compared the performance of salivary and plaque microbiomes in classifying pediatric T1D status. MethodsPaired saliva and plaque samples were collected from 46 children (23 with T1D and 23 healthy controls). Microbial DNA was extracted and sequenced to target the 16S rRNA gene. The data were processed via QIIME 2 for taxonomic classification and centered log-ratio transformation. Alpha diversity, microbial abundance, and clustering analyses were performed to compare the oral microbiome between the T1D and control groups. Random forest classifiers were used to evaluate and compare the predictive accuracy of saliva- and plaque-based models, both with and without clinical metadata. ResultsSaliva samples presented lower alpha diversity than plaque samples did but presented significantly greater bacterial loads and total microbial abundances. Saliva-based models outperformed plaque-based models, achieving a classification accuracy of 94.2% with or without clinical metadata, compared with 73.3% accuracy for plaque-based models. ROC curve analysis further supported this difference, with saliva models reaching an AUC of approximately 0.94 versus 0.75 for plaque, indicating superior discriminative performance. UMAP clustering revealed more distinct separation of the T1D and control groups in terms of the salivary profiles than in the plaque profiles. Feature importance analysis revealed both unique and shared taxa predictive of T1D in each niche. The incorporation of clinical and demographic metadata did not enhance model performance, underscoring the robustness and predictive strength of microbiome data alone. ConclusionThe salivary microbiome is a more effective biospecimen than dental plaque for detecting T1D-associated microbial profiles in children. It offers superior classification accuracy and greater sensitivity in distinguishing T1D status, supporting salivas potential as a noninvasive, scalable medium for future microbiome-based monitoring.

microbiology↗

Inference of VEGFR2 dimerization kinetics on the cell surface by integrating single-molecule imaging and mathematical modeling

Inter-receptor interactions play a key role in receptor signaling, which is the first step in cell signaling in response to external stimuli. In the case of Vascular Endothelial Growth Factor Receptor 2 (VEGFR2), dimerization is necessary for activation. VEGFR2 undergoes reversible interactions also in the absence of ligand. For a quantitative understanding of transmembrane signal transduction, it is necessary to quantify the interaction kinetics of VEGFR2 on the cell surface. Live-cell single-molecule imaging (SMI) has the powerful ability to capture receptor interaction events in their native cellular environment with high spatiotemporal resolution. However, it reveals these interactions for only the labeled subset, which is a small fraction of the full population of receptors. We have previously shown that mathematical modeling, combined with SMI data, offers a route to compensate for this lost information and infer the population-level receptor interaction kinetics from SMI data. Here, we applied this approach to VEGFR2, both wildtype full length VEGFR2 (FLR2) and a truncated mutant consisting of its extracellular and transmembrane domains (ECTM), which has been shown to exhibit reduced homotypic interactions in the absence of ligand. We developed a stochastic mathematical model mimicking VEGFR2 diffusion and interactions and determined the unknown model parameters through a combination of direct experimental measurements and stochastic model calibration. We found that a model of dimerization was sufficient to describe VEGFR2 interactions in the absence of ligand. While ECTM was primarily monomeric, FLR2 exhibited a substantial fraction of dimers. Our inference revealed that the difference between FLR2 and ECTM was primarily in the dimer association rate constant, which was about an order of magnitude lower for ECTM than for FLR2. To our knowledge, this is the first time that the interaction kinetics of VEGFR2 have been calculated in live cells. Author summaryInteractions between receptors on the cell surface play a large role in the initiation and modulation of cell signaling. For example, the receptor VEGFR2 in vascular endothelial cells must dimerize as a first step toward signaling. However, many interactions, including VEGFR2 dimerization, also take place in the absence of ligand stimulation. Therefore, elucidating when and where receptor interactions take place, and what their kinetics are, is critical for understanding receptor and cell signaling, especially on a quantitative level. Determining interaction kinetics is particularly challenging, given that membrane proteins do not express well in vitro, and are thus not amenable to traditional biophysical methods that quantify molecular interactions. In addition, the membrane and cellular environment is much more complex than an in vitro setting. To address these challenges, we combine single-molecule imaging, stochastic mathematical modeling, and rigorous model calibration to derive the dimerization kinetics of VEGFR2 (both full-length and a truncation mutant with reduced dimerization) on the surface of live cells. To our knowledge, this is the first time that the interaction kinetics of VEGFR2 have been calculated in live cells. Our approach is generalizable to many other cell surface proteins, opening an avenue for quantifying molecular interaction kinetics in situ.

biophysics↗

Tumor-associated macrophages enhance tumor innervation and spinal cord repair

AO_SCPLOWBSTRACTC_SCPLOWTumor-associated macrophages (TAM) enhance cancer progression by promoting angiogenesis, extracellular matrix (ECM) remodeling, and immune suppression. Nerve infiltration is a hallmark of various cancers and is known to directly contribute to tumor growth. However, the role of TAM in promoting intratumoral nerve growth remains poorly understood. In this study, we demonstrate that TAM expressed a distinct "neural growth" gene signature. TAM actively enhance neural growth within tumors and directly promote neurites outgrowth. We identify secreted phosphoprotein 1 (Spp1) as a key mediator of TAM-driven neural growth activity, which triggers neuronal mTORC2 signaling. Leveraging this new neural growth function, which added to the TAM wound healing properties, we explored TAM potential to repair central nervous system. Adoptive transfer of in vitro-generated TAM in a severe complete-compressive-contusive spinal cord injury (scSCI) model, not only repaired the damaged neural parenchyma by improving tissue oxygenation, ECM remodeling, and dampening chronic inflammation, but also resulted in neural regrowth and partial functional motor recovery. Proteomic analysis and subsequent functional validation confirmed that TAM-induced spinal cord regeneration is mediated through the activation of neural mTORC2 signaling pathways. Collectively, our data unveil a previously unrecognized role of TAM in tumor innervation, neural growth, and neural tissue repair.

neuroscience↗

High Throughput Chromosome Conformation Capture identifies differential genome organization in virulent and avirulent strains of Mycobacterium tuberculosis

Recent studies have shown that three-dimensional architecture of bacterial chromatin plays an important role in gene expression regulation. However, genome topological organization in Mycobacterium tuberculosis (M. tuberculosis), the etiologic agent of tuberculosis, remains unknown. On the other hand, exact mechanism of differential pathogenesis in the canonical strains of M. tuberculosis H37Rv and H37Ra remains poorly understood in terms of their raw sequences. In this context, a detailed contact map from a Hi-C experiment is a candidate for what bridges the gap. Here we present the first comprehensive report on genome-wide contact maps between regions of H37Rv and H37Ra genomes. We tracked differences between the genome architectures of H37Rv and H37Ra, which could possibly explain the virulence attenuation in H37Ra. We confirm the existence of a differential organization between the two strains most significantly a higher Chromosome Interacting Domain (CID) size in attenuated H37Ra strain. CID boundaries are also found enriched with highly expressed genes and with higher operon density in H37Rv. Furthermore, most of the differentially expressed PE/PPE genes were present near the CID boundaries in H37Rv and not in H37Ra. Collectively our study proposes a differential genomic topological pattern between H37Rv and H37Ra, which could explain the virulence attenuation in H37Ra.

genomics↗

Vasoactive Endothelial Growth Factor and Heat Shock Protein Gene Expression Response in Kawasaki Disease Associated Coronary Arteritis

Kawasaki Disease (KD) is a childhood vasculitis primarily affecting medium-sized arteries, which can lead to severe complications, particularly with respect to coronary artery disease (CAD). The impact of thermal stress on KD coronary artery pathogenesis, in association with prolonged fever and inflammation, remains unclear. In this study, we hypothesized that altered gene expression (GE) of angiogenesis-inducing Heat Shock Proteins (HSPs) is associated with KD-CAD through pro-inflammation. Transcriptomic analysis was performed using the three largest KD peripheral blood studies in the clinical literature (KD1-KD3), and one study direct from coronary artery tissue (KD4). The analysis revealed a significant increase in TNF and NFKB1 GE, indicating the presence of inflammation based on gene expression profiles. Gene set enrichment analysis (GSEA) of KD1-KD3 datasets identified inflammatory pathways, including TNFA signaling via NFKB, IL6 JAK STAT 3 Signalling, and p53 (Heat Shock Protein 90). The study also focused on specific HSPs known to be associated with angiogenesis, namely HSPB1, HSPA1A, and HSP90AB1. The temporal transcript model (TTM) consistently showed up-regulation of pro-inflammatory genes VEGF-A, TNF, and NFKB1, as well as up-regulation of HSPA1A. GSEA revealed gene ontology pathways associated with VEGF production. These findings suggest that the binding of VEGF-A or VEGF-B to their receptors could potentially impact the coronary artery in KD. Additionally, the up-regulation of the gene HSPAB1 in KD has not been described previously. In contrast, KD4 showed no differential GE for the studied genes potentially related to end-stage KD. This study provides valuable insights into VEGF and HSPs in KD-associated inflammation. Future research should focus on developing a VEGF-HSP CAD model to explore implications for KD biomarking as well as developing precision management strategies.

genomics↗

CDK1 and HSP90AA1 appears as novel regulatory gene in Non-Small Cell Lung Cancer: A Bioinformatics Approach

Lung cancer is one of the most invasive cancer affecting over a million of population. Non-small cell lung cancer constitutes up to 85% of all lung cancer cases. Therefore, it is important to identify prognostic biomarkers of NSCLC for therapeutic purpose. The complex behaviour of the NSCLC gene-regulatory network interaction is investigated using a network theoretical approach. We used eight NSCLC microarray datasets GSE19188, GSE118370, GSE10072, GSE101929, GSE7670, GSE33532, GSE31547, GSE31210 and meta analyse them to find differentially expressed genes (DEGs), construct protein-protein interaction (PPI) network, analysed its topological properties, significant modules using network analyser with MCODE, construct a PPI-MCODE network using the genes of the significant modules. We used topological properties such as Maximal Clique Centrality (MCC) and bottleneck from the PPI-MCODE network. We compare them with hub genes (those with highest degrees) to find key regulator (KR) gene. This result is also validated by finding of common genes among top twenty hub genes, genes with highest betweenness, closeness centrality and eigenvector values. It was found that two genes, CDK1 and HSP90AA1 were common in PPI-MCODE combined analysis, and it was also found that CDK1, HSP90AA1 and HSPA8 were common among hub and bottle neck properties and suggesting significant regulatory role of CDK1 in non-small cell lung cancer. After validation, the common genes among top twenty hubs and centrality values like Betweenness Centrality, Closeness Centrality and eigen vector properties, CDK1 again appeared as the common gene. Our study as a summary suggested CDK1 as key regulator gene in complex NSCLC network interaction using network theoretical approach and described the complex topological properties of the network.

systems biology↗