Biology subjects

Gupta, D.

Publications and source records attributed to Gupta, D..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Identification of Disease-relevant, Sex-based Proteomic Differences in iPSC-derived Vascular Smooth Muscle

The prevalence of cardiovascular disease varies with sex, and the impact of intrinsic sex-based differences on vasculature is not well understood. Animal models can provide important insight into some aspects of human biology, however not all discoveries in animal systems translate well to humans. To explore the impact of chromosomal sex on proteomic phenotypes, we used iPSC-derived vascular smooth muscle cells from healthy donors of both sexes to identify sex-based proteomic differences and their possible effects on cardiovascular pathophysiology. Our analysis confirmed that differentiated cells have a proteomic profile more similar to healthy primary aortic smooth muscle than iPSCs. We also identified sex-based differences in iPSC- derived vascular smooth muscle in pathways related to ATP binding, glycogen metabolic process, and cadherin binding as well as multiple proteins relevant to cardiovascular pathophysiology and disease. Additionally, we explored the role of autosomal and sex chromosomes in protein regulation, identifying that proteins on autosomal chromosomes also show sex-based regulation that may affect the protein expression of proteins from autosomal chromosomes. This work supports the biological relevance of iPSC-derived vascular smooth muscle cells as a model for disease, and further exploration of the pathways identified here can lead to the discovery of sex-specific pharmacological targets for cardiovascular disease. SignificanceIn this work, we have differentiated 4 male and 4 female iPSC lines into vascular smooth muscle cells, giving us the ability to identify statistically-significant sex-specific proteomic markers that are relevant to cardiovascular disease risk (such as PCK2, MTOR, IGFBP2, PTGR2, and SULTE1).

molecular biology↗

bioRxiv2024

Disentangling the Roles of Distinct Cell Classes with Cell-Type Dynamical Systems

Latent dynamical systems have been widely used to characterize the dynamics of neural population activity in the brain. However, these models typically ignore the fact that the brain contains multiple cell types. This limits their ability to capture the functional roles of distinct cell classes, and to predict the effects of cell-specific perturbations on neural activity or behavior. To overcome these limitations, we introduce the "cell-type dynamical systems" (CTDS) model. This model extends latent linear dynamical systems to contain distinct latent variables for each cell class, with biologically inspired constraints on both dynamics and emissions. To illustrate our approach, we consider neural recordings with distinct excitatory (E) and inhibitory (I) populations. The CTDS model defines separate latents for both cell types, and constrains the dynamics so that E (I) latents have a strictly positive (negative) effects on other latents. We applied CTDS to recordings from rat frontal orienting fields (FOF) and anterior dorsal striatum (ADS) during an auditory decision-making task. The model achieved higher accuracy than a standard linear dynamical system (LDS), and revealed that the animals choice can be decoded from both E and I latents and thus is not restricted to a single cell-class. We also performed in-silico optogenetic perturbation experiments in the FOF and ADS, and found that CTDS was able to replicate the experimentally observed effects of different perturbations on behavior, whereas a standard LDS model--which does not differentiate between cell types--did not. Crucially, our model allowed us to understand the effects of these perturbations by revealing the dynamics of different cell-specific latents. Finally, CTDS can also be used to identify cell types for neurons whose class labels are unknown in electrophysiological recordings. These results illustrate the power of the CTDS model to provide more accurate and more biologically interpretable descriptions of neural population dynamics and their relationship to behavior.

neuroscience↗

bioRxiv2024

A multi-region recurrent circuit for evidence accumulation in rats

Decision-making based on noisy evidence requires accumulating evidence and categorizing it to form a choice. Here we evaluate a proposed feedforward and modular mapping of this process in rats: evidence accumulated in anterodorsal striatum (ADS) is categorized in prefrontal cortex (frontal orienting fields, FOF). Contrary to this, we show that both regions appear to be indistinguishable in their encoding/decoding of accumulator value and communicate this information bidirectionally. Consistent with a role for FOF in accumulation, silencing FOF to ADS projections impacted behavior throughout the accumulation period, even while nonselective FOF silencing did not. We synthesize these findings into a multi-region recurrent neural network trained with a novel approach. In-silico experiments reveal that multiple scales of recurrence in the cortico-striatal circuit rescue computation upon nonselective FOF perturbations. These results suggest that ADS and FOF accumulate evidence in a recurrent and distributed manner, yielding redundant representations and robustness to certain perturbations.

neuroscience↗

bioRxiv2024

Clonal spheroids capture functional and genetic heterogeneity of head and neck cancer

Head and neck cancer squamous cell carcinoma (HNSCC) cells exhibit both structural and functional diversity, making them valuable models for understanding tumor heterogeneity at clinical levels. In this study, we generated single-cell-derived spheroids (SCDS) from HNSCC cell lines and patient tumor cells using scaffold- and non-scaffold-based methods to assess this variability. A distinct structural variability among these SCDS, categorized as hypo- and hyperproliferative spheroids based on size, was observed. Hyperproliferative spheroids demonstrated heightened proliferative and tumorigenic potential and increased sensitivity to cisplatin and radiation, while hypoproliferative spheroids exhibited enhanced migratory capabilities. Single-cell RNA sequencing (scRNA-seq) of hypo- and hyperproliferative spheroids provided insights into the transcriptional landscape of HNSCC cells, validating the observed structural and functional heterogeneities within primary tumors. These functionally and genetically characterized spheroids offer valuable tools for the development of next-generation therapeutics. Statement of SignificanceEstablishment and characterization of single-cell-derived spheroids from head and neck cancer cells, employing scaffold and non-scaffold materials, demonstrate functional and genetic heterogeneity. Single-cell analysis reveals correlations between genetic diversity and spheroid functionality. These characterized spheroids offer potential for advancing therapeutics development.

cancer biology↗

bioRxiv2024

Snorkel-tag Based Affinity Chromatography for Recombinant Extracellular Vesicle Purification

Extracellular vesicles (EVs) are lipid nanoparticles and play an important role in cell-cell communications, making them potential therapeutic agents and allowing to engineer for targeted drug delivery. The expanding applications of EVs in next generation medicine are still limited by existing tools for scaling standardized EV production, single EV tracing and analytics, and thus provide only a snapshot of tissue-specific EV cargo information. Here, we present CD81, an EV surface marker protein, genetically fused to series of tags with additional transmembrane domain to be displayed on the EV surface, which we term Snorkel-tag. This system enables to affinity purify EVs from complex matrices in a non-destructive form. In future applications, this strategy will allow generating transgenic animals to enable tracing and analyzing EVs, and their cargo in physiological and pathophysiological set-ups, and facilitate the development of EV based diagnostic tools in murine models which can be translated to humans.

bioengineering↗

bioRxiv2024

Inactive Parp2 causes Tp53-dependent lethal anemia by blocking replication-associated nick ligation in erythroblasts

PARP1&2 enzymatic inhibitors (PARPi) are promising cancer treatments. But recently, their use has been hindered by unexplained severe anemia and treatment-related leukemia. In addition to enzymatic inhibition, PARPi also trap PARP1&2 at DNA lesions. Here, we report that unlike Parp2-/- mice, which develop normally, mice expressing catalytically-inactive Parp2 (E534A, Parp2EA/EA) succumb to Tp53- and Chk2-dependent erythropoietic failure in utero, mirroring Lig1-/- mice. While DNA damage mainly activates PARP1, we demonstrate that DNA replication activates PARP2 robustly. PARP2 is selectively recruited and activated by 5-phosphorylated nicks (5p-nicks) between Okazaki fragments, typically resolved by Lig1. Inactive PARP2, but not its active form or absence, impedes Lig1- and Lig3-mediated ligation, causing dose-dependent replication fork collapse, particularly harmful to erythroblasts with ultra-fast forks. This PARylation-dependent structural function of PARP2 at 5p-nicks explains the detrimental effects of PARP2 inhibition on erythropoiesis, revealing the mechanism behind the PARPi-induced anemia and leukemia, especially those with TP53/CHK2 loss. SignificanceThis work shows that the hematological toxicities associated with PARP inhibitors stem not from impaired PARP1 or PARP2 enzymatic activity but rather from the presence of inactive PARP2 protein. Mechanistically, these toxicities reflect a unique role of PARP2 at 5-phosphorylated DNA nicks during DNA replication in erythroblasts.

genetics↗

bioRxiv2024

Human-in-the-loop approach to identify functionally important residues of proteins from literature

We present a novel system that leverages curators in the loop to develop a dataset and model for detecting residue-level functional annotations and other protein structure features from standard publication text. Our approach involves the integration of data from multiple resources, including PDBe, EuropePMC, PubMedCentral, and PubMed, combined with annotation guidelines from UniProt, while employing LitSuggest and Huggingface models as tools in the annotation process. A team of seven annotators manually curated ten articles for named entities, which we utilized to train a starting PubmedBert model from Huggingface. Using a human-in-the-loop annotation system, we developed the best model with commendable performance metrics of 0.90 for precision, 0.92 for recall, and 0.91 for F1-measure. Our proposed system showcases a successful synergy of machine learning techniques and human expertise in curating a dataset for residue-level functional annotations and protein structure features. The results demonstrate the potential for broader applications in protein research, bridging the gap between advanced machine learning models and the indispensable insights of domain experts.

bioinformatics↗

bioRxiv2023

A Tale of Two Parasites: A Glimpse into the clinical RNA Methylome of P. falciparum and P. vivax isolates

BackgroundUnderstanding the molecular mechanisms of the malarial parasites in hosts is crucial for developing effective treatments. Epitranscriptomic research on pathogens has unveiled the significance of RNA methylation in gene regulation and pathogenesis. We present the first report investigating methylation signatures and alternative splicing events using Nanopore Direct RNA Sequencing to single-base resolution in Plasmodium falciparum and P. vivax clinical isolates with hepatic dysfunction complications. MethodologyWe performed direct RNA Sequencing using Nanopore from clinical isolates of P. falciparum and P. vivax showing hepatic dysfunction manifestation. Subsequently we performed transcriptome reconstruction using FLAIR and transcript classification using SQANTI3 followed by methylation detection using CHEUI and m6Anet to identify N6-methyladenosine (m6A) and 5-methylcytosine (m5C) methylation signatures. We also documented alternative splicing events from both the datasets. ResultsThe reference genome of Plasmodium reports >5000 genes out of which we have identified [~]50% as expressed in the two sequenced isolates, including novel isoforms and intergenic transcripts, highlighting extensive transcriptome diversity. The distinct RNA methylation profiles of m6A and m5C from the expressed transcripts were observed in sense, Natural Antisense Transcripts (NATs) and intergenic categories hinting at species-specific regulatory mechanisms. Modified transcripts originating from apicoplast and mitochondrial genomes have also been detected. These modifications are unevenly present in the annotated regions of the mRNA, potentially influencing mRNA export and translation. We have observed several splicing events, with alternative 3and 5end splicing predominating in our datasets suggesting differences in translational kinetics and possible protein characteristics in these disease conditions. ConclusionIn our data we are showing the presence of modified sense, NATs and alternatively spliced transcripts. These phenomena together suggest the presence of multiple regulatory layers which decides the post-translational proteome of the parasites in particular disease conditions. Studies like these will help to decipher the post-translational environments of malaria parasites in vivo and elucidate their inherent proteome plasticity, thus allowing the conceptualization of novel strategies for interventions.

genomics↗

bioRxiv2023

Next-Gen Profiling of Tumor-resident Stem Cells using Machine learning

Tumor-resident stem cells, also known as cancer stem cells (CSCs), constitute a subgroup within tumors, play a crucial role in fostering resistance to treatment and the recurrence of tumors, and pose significant challenges for conventional therapeutic methods. Existing approaches for identifying CSCs face notable hurdles related to scalability, reproducibility, and technical consistency across different cancer types due to the adaptable nature of CSCs. In this context, we introduce OSCORP, an innovative machine-learning-driven approach. This methodology quantifies and identifies CSCs, achieving almost 99% accuracy using biopsy bulk RNAseq data. OSCORP leverages genetic similarities between normal and cancer stem cells. By categorizing CSCs into four distinct yet dynamic potency states, this approach provides insights into the differentiation landscape of CSCs, unveiling previously undisclosed facets of tumor heterogeneity. In evaluations conducted on patient samples across 22 cancer types, OSCORP revealed clinical, transcriptomic, and immunological signatures associated with each CSC state. It has emerged as a comprehensive tool for understanding and addressing the complexities of cancer stem cells. Ultimately, OSCORP opens up new possibilities for more effective personalized cancer therapies and holds the potential to serve as a clinical tool for monitoring patient-specific CSC changes during treatment or follow-up care.

cancer biology↗

bioRxiv2023

Non-canonical attractor dynamics underlie perceptual decision-making

Perceptual decision-making is the process by which an animal uses sensory stimuli to choose an action or mental proposition. This process is thought to be mediated by neurons organized as attractor networks1,2. However, whether attractor dynamics underlie decision behavior and the complex neuronal responses remains unclear. Here we use simultaneous recordings from hundreds of neurons, together with an unsupervised, deep learning-based method, to discover decision-related neural dynamics in frontal cortex and striatum of rats while the subjects accumulate pulsatile auditory evidence. We found that trajectories evolved along two sequential regimes, the first dominated by sensory inputs, and the second dominated by the autonomous dynamics, with flow in a direction (i.e., "neural mode") largely orthogonal to that in the first regime. We propose that the transition to the second regime corresponds to the moment of decision commitment. We developed a simplified model that approximates the coupled transition in dynamics and neural mode and allows precise inference, from each trials large-scale neural population activity, of a putative neurally-inferred time of commitment ("nTc") on that trial. The simplified model captures diverse and complex single-neuron temporal profiles, such as ramping and stepping3-5, as well as trial-averaged curved trajectories6-8, and reveals distinctions between brain regions. The estimated nTc times were not time-locked to stimulus onset or offset, or to response onset, but were instead broadly distributed across trials. If nTc marks the moment of decision commitment, sensory evidence before nTc should affect the decision, while evidence afterward should not. Behavioral analysis of trials aligned to their estimated nTc times confirmed this prediction. Our results show that the formation of a perceptual choice involves a rapid, coordinated transition in both the dynamical regime and the neural mode of the decision process that corresponds to commitment to a decision, and suggest this moment as a useful entry point for dissecting mechanisms underlying rapid changes in internal state.

neuroscience↗

bioRxiv2023

Nested biofabrication: Matryoshka-inspired Intra-embedded Bioprinting

Engineering functional tissues and organs remains a fundamental pursuit in biofabrication. However, the accurate constitution of complex shapes and internal anatomical features of specific organs, including their intricate blood vessels and nerves, remains a significant challenge. Inspired by the Matryoshka doll, we here introduce a new method called Intra-Embedded Bioprinting (IEB), building upon existing embedded bioprinting methods. We used a xanthan gum-based material, which served a dual role as both a bioprintable ink and a support bath, due to its unique shear-thinning and self-healing properties. We demonstrated IEBs capabilities in organ modelling, creating a miniaturized replica of a pancreas using a photocrosslinkable silicone composite. Further, a head phantom and a Matryoshka doll were 3D printed, exemplifying IEBs capability to manufacture intricate, nested structures. Towards the use case of IEB and employing innovative coupling strategy between extrusion-based and aspiration-assisted bioprinting, we developed a breast tumor model that included a central channel mimicking a blood vessel, with tumor spheroids bioprinted in proximity. Validation using a clinically-available chemotherapeutic drug illustrated its efficacy in reducing the tumor volume via perfusion over time. This method opens a new way of bioprinting enabling the creation of complex-shaped organs with internal anatomical features.

bioengineering↗

bioRxiv2023

An extracellular vesicle delivery platform based on the PTTG1IP protein

Extracellular vesicles (EVs) hold great promise as therapeutic delivery vehicles, although their potential is limited by a lack of efficient EV engineering strategies to enhance loading and functional delivery of therapeutic cargo. Here, we identified N-glycosylation as a putative EV- sorting feature using a novel bioinformatics analysis strategy. We exploited this finding to develop a platform for EV-mediated delivery of macromolecular cargoes based on PTTG1IP, a small N- glycosylated, single spanning transmembrane protein. We demonstrate that PTTG1IP EV enrichment is dependent on its N-glycosylation at two sites, and that PTTG1IP is a suitable scaffold for EV loading of therapeutic cargoes. To achieve functional delivery, cargoes were fused to PTTG1IP, separated by various self-cleaving sequences intended to promote cargo release from the scaffold after EV loading. In addition, the fusogenic VSVG protein was co-expressed to enhance endosomal escape. This PTTG1IP-based strategy enabled highly efficient functional delivery of Cre protein to recipient cells and mouse xenograft tumors, as well as Cas9 and Cas9/sgRNA complex delivery to reporter cells. Importantly, PTTG1IP exhibited improved protein delivery potential relative to a scaffold based on CD63 (a common EV marker). Moreover, we developed various PTTG1IP variants with improved properties, demonstrating the versatility of PTTG1IP as an EV scaffold. The EV-loading platform described in this study offers significant advantages over other strategies, such as favourable membrane topology, the potential for further engineering, and functional delivery capability, which will enable the development of improved EV-based therapeutics.

molecular biology↗

bioRxiv2023

Decrease in reaction time for volleyball athletes during saccadic eye movement task: An associative analysis with evoked potentials

AimThe current study investigated the differences to event-related potential and reaction time under two groups (athletes vs. non-athletes). Material and MethodsThe P300 was analyzed for Fz, Cz and Pz electrodes in thirty-one healthy volunteers divided into two groups (volleyball athletes and non-athletes). In addition, the participants performed a saccadic eye movement task to measure reaction time. ResultsThe EEG analysis showed that the athletes in comparison to the no-athletes has differences of the P300 in the frontal area (p=0.021). In relation to reaction time, the results show lower reaction time for athletes (p=0.001). ConclusionsThe volleyball athletes may present a greater allocation of attention during the execution of the inhibition task, since they have a lower reaction time for responses when compared to non-athletes.

neuroscience↗

bioRxiv2023

A Versatile Photocrosslinkable Silicone Composite for 3D Printing Applications

Embedded printing has emerged as a valuable tool for fabricating complex structures and microfluidic devices. Currently, an ample of amount of research is going on to develop new materials to advance its capabilities and increase its potential applications. Here, we demonstrate a novel, transparent, 3D printable, photocrosslinkable, and tuneable silicone composite that can be utilized as a support bath or an extrudable ink for embedded printing. The proposed silicone composite can be tuned to achieve ideal rheological properties, such as optimal self-recovery and yield stress, for use in 3D printing. When used as a support bath, it facilitated the generation microfluidic devices with circular channels of diameter up to 30 {micro}m. To demonstrate its utility, flow focusing microfluidic devices were fabricated for generation of Janus microrods, which can be easily modified for multitude of applications. When used as an extrudable ink, 3D printing of complex-shaped micro- and macro-constructs were achieved with integrated electronics, which greatly extends its potential applications towards developing complex flexible parts for soft robotics and prosthetics. Further, its biocompatibility was tested with multiple cell types to validate its applicability for medical and tissue engineering use. Altogether, this material offers a myriad of potential applications in material and medical fields by providing a facile approach to develop complicated 3D structures and interconnected channels that can further advance microfluidics and soft-robotics research.

bioengineering↗

bioRxiv2023

Spatial and Temporal Analysis of SARS-CoV-2 Genome Evolutionary Patterns

The spread of SARS-CoV-2 virus accompanied by availability of abundant sequence data publicly, provides a window for determining the spatio-temporal patterns of viral evolution in response to vaccination. In this study, SARS-CoV-2 genome sequences were collected from seven countries in the period January 2020-December 2022. The sequences were classified into three phases, namely: pre-vaccination, post-vaccination, and recent period. Comparison was performed between these phases based on parameters like mutation rates, selection pressure (dN/dS ratio), and transition to transversion ratios (Ti/Tv). Similar comparisons were performed among SARS-CoV-2 variants. Statistical significance was tested using Graphpad unpaired t-test. The comparative analysis showed an increase in the percent genomic mutation rates post-vaccination and in recent periods across different countries from the pre-vaccination phase. The dN/dS ratios showed positive selection that increased after vaccination, and the Ti/Tv ratios decreased after vaccination. C[->]U and G[->]U were the most frequent transitions and transversions in all the countries. However, U[->]G was the most frequent transversion in recent period. The Omicron variant had the highest genomic mutation rates, while Delta showed the highest dN/dS ratio. Mutation rates were highest in NSP3, S, N and NSP12b before and increased further after vaccination. NSP4 showed the largest change in mutation rates after vaccination. N, ORF8, ORF3a and ORF10 were under highest positive selection before vaccination. They were overtaken by E, S and NSP1 in the after vaccination as well as recent sequences, with the largest change observed in NSP1. Protein-wise dN/dS ratio was also seen to vary across the different variants. ImportanceIrrespective of the different vaccine technologies used, geographical regions and host genetics, variations in the SARS-CoV-2 genome have maintained similar patterns worldwide. To the best of our knowledge, there exists no other large-scale study of the genomic and protein-wise mutation patterns during the time course of evolution in different countries. Analysing the SARS-CoV-2 evolution patterns in response to spatial, temporal, and biological signals is important for diagnostics, therapeutics, and pharmacovigilance of SARS-CoV-2.

bioinformatics↗

bioRxiv2023

Identification of Novel Scaffold Proteins for Improved Endogenous Engineering of Extracellular Vesicles

Extracellular vesicles (EVs) are gaining ground as next-generation drug delivery modalities. Genetic fusion of the protein of interest to a scaffold protein with high EV-sorting ability represents a robust cargo loading strategy. To address the paucity of such scaffold proteins we conducted a large-scale comparative study involving 244 candidate proteins. Their EV-sorting potential was evaluated using a simple but reliable assay that can distinguish intravesicular cargo proteins from surface and non-vesicular proteins. Notably, 24 proteins with conserved EV-sorting abilities across five types of producer cells were identified. Most of these are first to be reported including TSPAN2 and TSPAN3, which emerged as lead candidates, outperforming the well-known CD63 scaffold. Importantly, these engineered EVs show promise as delivery vehicles as demonstrated by in vitro and in vivo internalization studies with luminal cargo proteins as well as surface display of functional domains. The discovery of these novel scaffolds provides a new platform for EV-based engineering.

synthetic biology↗

bioRxiv2023

Annotating Macromolecular Complexes in the Protein Data Bank: Improving the FAIRness of Structure Data

Macromolecular complexes are essential functional units in nearly all cellular processes, and their atomic-level understanding is critical for elucidating and modulating molecular mechanisms. The Protein Data Bank (PDB) serves as the global repository for experimentally determined structures of macromolecules. Structural data in the PDB offer valuable insights into the dynamics, conformation, and functional states of biological assemblies. However, the current annotation practices lack standardised naming conventions for assemblies in the PDB, complicating the identification of instances representing the same assembly. In this study, we introduce a method leveraging resources external to PDB, such as the Complex Portal, UniProt and Gene Ontology, to describe assemblies and contextualise them within their biological settings accurately. Employing the proposed approach, we assigned standard names and provided value-added annotations to over 90% of unique assemblies in the PDB. This standardisation of assembly data enhances the PDB, facilitating a deeper understanding of these cellular components. Furthermore, the data standardisation improves the PDBs FAIR attributes, fostering more effective basic and translational research and education across scientific disciplines.

bioinformatics↗

bioRxiv2023

17 β-estradiol impedes aortic root dilation and rupture in male Marfan mice

Marfan syndrome causes a hereditary form of thoracic aortic aneurysms with dilation of the aortic root. Human and animal models suggest a worse phenotype for males compared to females with respect to aneurysm size and risk of dissection. In this study we examine the effects of 17 {beta}-estradiol on aortic dilation and rupture in a Marfan mouse model. Marfan male mice were administered 17 {beta}-estradiol and the growth in aortic root size along with the risk of aortic rupture or dissection with the addition of angiotensin II was measured. Transcriptomic profiling was used to identify enriched pathways from 17 {beta}-estradiol treatment. Aortic smooth muscle cells were then treated with cytokines in order to validate the mechanism of 17 {beta}-estradiol protection. We show that 17 {beta}-estradiol decreased the size and rate of aortic root dilation and improved survival from rupture and dissection after treatment with angiotensin II. The Marfan transcriptome was enriched in inflammatory genes and the addition of 17 {beta}-estradiol modulated a set of genes that function through TNF mediated NF-{kappa}B signaling. These included many proteins known to play a role in the phenotypic shift of aortic smooth muscle cells from a contractile to a more inflammatory-like state such as Vcam-1, Mcp-1, Lgals3, Il-6, Il-1b, and C3. In addition, 17 {beta}-estradiol suppressed the induction of these TNF induced genes in aortic smooth muscle cells in vitro and this effect appears to be NF-{kappa}B dependent. In conclusion, 17 {beta}-estradiol protects against the dilation and rupture of aortic roots in Marfan male mice through the inhibition of TNF -NF-{kappa}B signaling and thus prevents the phenotypic switch of aortic smooth muscle cells from a contractile to an inflammatory state.

genetics↗