47 results match your criteria: "The Institute of Mathematical Sciences (IMSc)[Affiliation]"

Petroleum hydrocarbons (PHs) are compounds composed mostly of carbon and hydrogen, originating from crude oil and its derivatives. PHs are primarily released into the environment through the diffusion of oils, resulting from anthropogenic activities like transportation and offshore drilling, and accidental incidents such as oil spills. Once released, these PHs can persist in different ecosystems and cause long-term detrimental ecological impacts.

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Plastics are widespread pollutants found in atmospheric, terrestrial and aquatic ecosystems due to their extensive usage and environmental persistence. Plastic additives, that are intentionally added to achieve specific functionality in plastics, leach into the environment upon plastic degradation and pose considerable risk to ecological and human health. Limited knowledge concerning the presence of plastic additives throughout plastic life cycle has hindered their effective regulation, thereby posing risks to product safety.

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Boolean models of gene regulatory networks (GRNs) have gained widespread traction as they can easily recapitulate cellular phenotypes via their attractor states. Their overall dynamics are embodied in a state transition graph (STG). Indeed, two Boolean networks (BNs) with the same network structure and attractors can have drastically different STGs depending on the type of Boolean functions (BFs) employed.

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  • Breast milk is crucial for infant nutrition but can be contaminated by environmental chemicals from the mother's exposure, raising health concerns for infants.
  • Machine learning models, especially support vector machines (SVM), can predict which chemicals are likely to transfer from maternal plasma to breast milk by analyzing a large dataset of known milk-to-plasma concentration (M/P) ratios.
  • While the SVM classifier demonstrated strong predictive accuracy (77.33%) on internal data, regression models for M/P ratios faced challenges, indicating the complexity of predicting chemical transfer and the potential utility of computational toxicology in understanding such environmental impacts.
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Boolean networks (BNs) have been extensively used to model gene regulatory networks (GRNs). The dynamics of BNs depend on the network architecture and regulatory logic rules (Boolean functions (BFs)) associated with nodes. Nested canalyzing functions (NCFs) have been shown to be enriched among the BFs in the large-scale studies of reconstructed Boolean models.

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Cadmium is a prominent toxic heavy metal that contaminates both terrestrial and aquatic environments. Owing to its high biological half-life and low excretion rates, cadmium causes a variety of adverse biological outcomes. Adverse outcome pathway (AOP) networks were envisioned to systematically capture toxicological information to enable risk assessment and chemical regulation.

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In human exposome, environmental chemicals can target and disrupt different endocrine axes, ultimately leading to several endocrine disorders. Such chemicals, termed endocrine disrupting chemicals, can promiscuously bind to different endocrine receptors and lead to varying biological end points. Thus, understanding the complexity of molecule-receptor binding of environmental chemicals can aid in the development of robust toxicity predictors.

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ViCEKb: Vitiligo-linked Chemical Exposome Knowledgebase.

Sci Total Environ

February 2024

The Institute of Mathematical Sciences (IMSc), Chennai, India; Homi Bhabha National Institute (HBNI), Mumbai, India. Electronic address:

Vitiligo is a complex disease wherein the environmental factors, in conjunction with the underlying genetic predispositions, trigger the autoimmune destruction of melanocytes, ultimately leading to depigmented patches on the skin. While genetic factors have been extensively studied, the knowledge on environmental triggers remains sparse and less understood. To address this knowledge gap, we present the first comprehensive knowledgebase of vitiligo-triggering chemicals namely, Vitiligo-linked Chemical Exposome Knowledgebase (ViCEKb).

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  • Sesuvium portulacastrum is a halophyte that thrives in salty environments, showing little growth reduction under high salt concentrations (up to 250 mM NaCl) except for minor leaf curling.
  • Seedlings quickly accumulate protective compounds like proline and glycine betaine in response to salt stress, while gene expression initially activates transporters and transcription factors but then shifts to suppressing growth-related genes.
  • The study produced an open-access database, "SesuviumKB," to facilitate research on salt tolerance genes, aiming to help improve crop resilience against salinity.
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Secreted virulence factors play a critical role in bacterial pathogenesis. Virulence effectors not only help bacteria to overcome the host immune system but also aid in establishing infection. , which causes tuberculosis in humans, encodes various virulence effectors.

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Type 9 secretion system (T9SS) is one of the least characterized secretion systems exclusively found in the phylum, which comprises various environmental and economically relevant bacteria. While T9SS plays a central role in bacterial movement termed gliding motility, survival, and pathogenicity, there is an unmet need for a comprehensive tool that predicts T9SS, gliding motility, and proteins secreted via T9SS. In this study, we develop such a computational tool, ype secretion system and liding motility iction (T9GPred).

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The thyroid stimulating hormone receptor (TSHR) is crucial in thyroid hormone production in humans, and dysregulation in TSHR activation can lead to adverse health effects such as hypothyroidism and Graves' disease. Further, animal studies have shown that binding of endocrine disrupting chemicals (EDCs) with TSHR can lead to developmental toxicity. Hence, several such chemicals have been screened for their adverse physiological effects in human cell lines high-throughput assays in the ToxCast project.

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Rift Valley fever is a zoonotic disease that can spread through livestock and mosquitoes, and its symptoms include retinitis, photophobia, hemorrhagic fever and neurological effects. The World Health Organization has identified Rift Valley fever as one of the viral infections that has potential to cause a future epidemic. Hence, efforts are urgently needed toward development of therapeutics and vaccine against this infectious disease.

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Introduction: Geometry-inspired notions of discrete Ricci curvature have been successfully used as markers of disrupted brain connectivity in neuropsychiatric disorders, but their ability to characterize age-related changes in functional connectivity is unexplored.

Methods: We apply Forman-Ricci curvature and Ollivier-Ricci curvature to compare functional connectivity networks of healthy young and older subjects from the Max Planck Institute Leipzig Study for Mind-Body-Emotion Interactions (MPI-LEMON) dataset ( = 225).

Results: We found that both Forman-Ricci curvature and Ollivier-Ricci curvature can capture whole-brain and region-level age-related differences in functional connectivity.

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  • Boolean models are used to represent developmental gene regulatory networks (DGRNs) to understand how cells acquire identities, but many combinations of Boolean functions can yield the same cell fates.
  • Researchers explore the concept of relative stability of biological attractors to improve model selection, highlighting the mean first passage time (MFPT) as an effective measure that also reveals cell state transitions.
  • The study reveals shortcomings in recent Boolean models of Arabidopsis thaliana root development and introduces a new algorithm for finding models that align better with expected hierarchies of cell states, ultimately advancing the accuracy of DGRN reconstructions.
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Ectopic pregnancy (EP) is one of the leading causes of maternal mortality, where the fertilized embryo grows outside of the uterus. Recent experiments on mice have uncovered the importance of genetic factors in the transport of embryos inside the uterus. In the past, efforts have been made to identify possible gene or protein markers in EP in humans through multiple expression studies.

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Compilation, curation, digitization, and exploration of the phytochemical space of Indian medicinal plants can expedite ongoing efforts toward natural product and traditional knowledge based drug discovery. To this end, we present IMPPAT 2.0, an enhanced and expanded database compiling manually curated information on 4010 Indian medicinal plants, 17,967 phytochemicals, and 1095 therapeutic uses.

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Background: Infections associated with nephrotic relapses (NR) are often managed according to physician preferences. A validated prediction tool will aid clinical decision-making and help in rationalizing antibiotic prescriptions. Our objective was to develop a biomarker-based prediction model and a regression nomogram for the prediction of the probability of infection in children with NR.

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Androgen mimicking environmental chemicals can bind to Androgen receptor (AR) and can cause severe effects on the reproductive health of males. Predicting such endocrine disrupting chemicals (EDCs) in the human exposome is vital for improving current chemical regulations. To this end, QSAR models have been developed to predict androgen binders.

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Medicinal fungi, including mushrooms, have well-documented therapeutic uses. In this study, we perform a cheminformatics-based investigation of the scaffold and structural diversity of the secondary metabolite space of medicinal fungi and, moreover, perform a detailed comparison with approved drugs, other natural product libraries, and semi-synthetic libraries. We find that the secondary metabolite space of medicinal fungi has similar or higher scaffold diversity in comparison to other natural product libraries analyzed here.

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The properties of random Boolean networks have been investigated extensively as models of regulation in biological systems. However, the Boolean functions (BFs) specifying the associated logical update rules should not be expected to be random. In this contribution, we focus on types of BFs, and perform a systematic study of their preponderance in a compilation of 2,687 functions extracted from published models.

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The World Health Organization (WHO) recently declared the monkeypox outbreak 'A public health emergency of international concern'. The monkeypox virus belongs to the same Orthopoxvirus genus as smallpox. Although smallpox drugs are recommended for use against monkeypox, monkeypox-specific drugs are not yet available.

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Boolean networks have been widely used to model gene networks. However, such models are coarse-grained to an extent that they abstract away molecular specificities of gene regulation. Alternatively, bipartite Boolean network models of gene regulation explicitly distinguish genes from transcription factors (TFs).

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  • The study explores new geometry-inspired network measures, specifically Forman-Ricci and Ollivier-Ricci curvatures, to analyze brain connectivity differences in individuals with autism spectrum disorder (ASD) compared to typically developing individuals.
  • Significant variations in curvature were found both throughout the brain and in specific regions such as the Default Mode, Somatomotor, and Ventral Attention networks, indicating a distinct connectivity pattern in ASD.
  • The findings suggest that these curvature measures can help identify clinically relevant brain regions and their relationship with cognitive impairments in ASD, highlighting potential targets for non-invasive stimulation therapies.
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Severe fever with thrombocytopenia syndrome virus (SFTSV) causes a highly infectious disease with reported mortality in the range 2.8% to 47%. The replication and transcription of the SFTSV genome is performed by L polymerase, which has both an RNA dependent RNA polymerase domain and an N-terminal endonuclease (endoN) domain.

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