Evidence map›Paper›PMID 37969204›Full record

ArticleAmerican journal of translational research2023

Significance of TLR2 signaling during megakaryocyte development: regulatory cross-talk of miR-125b, cytokine induction, and MAPK pathway during dengue infection.

Mahesh Malleswarapu, Narasaiah Kovuru, Nooruddin Khan, Amit Mishra, Ravi Kumar Gutti

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 72% of its field
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Mahesh MalleswarapuDepartment of Biochemistry, School of Life Sciences, University of Hyderabad Hyderabad 500046, TS, India.
Narasaiah KovuruDepartment of Biochemistry, School of Life Sciences, University of Hyderabad Hyderabad 500046, TS, India.
Nooruddin KhanDepartment of Biotechnology and Bioinformatics, School of Life Sciences, University of Hyderabad Hyderabad 500046, TS, India.
Amit MishraDepartment of Bioscience and Bioengineering, Cellular and Molecular Neurobiology Unit, Indian Institute of Technology Jodhpur Jodhpur 342037, RJ, India.
Ravi Kumar GuttiDepartment of Biochemistry, School of Life Sciences, University of Hyderabad Hyderabad 500046, TS, India.
University of Hyderabad · INIndian Institute of Technology Jodhpur · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDengue is a viral infection endemic in more than 100 countries as per the WHO reports with approximately 5.2 million patients worldwide that spreads from mosquitoes to humans. Severe form of dengue fever can cause serious bleeding (low platelets) and death. Megakaryocytes are the immune cells responsible for the production of platelets. The molecular drivers behind platelet defects are mostly ambiguous. Here, we attempted to understand the distinct pathogen-elicited toll-like receptors (TLRs) functions in megakaryocyte biology. To understand the TLR induction and the molecular events that are governed in the mammalian system during dengue infection and to study TLR2-mediated cellular signaling-associated mechanisms with respect to their dimerization partners during dengue infection.

methodsIn this study, we used the human Megakaryoblastic cells, DAMI, and treated them with TLR agonists (LPS and Zymosan) and Dengue virus (DNV-II). RESULTS AND DISCUSSION: TLR2 could play an important role by dimerizing with TLR1, TLR4, and TLR6, which we induced for functional characterization. We observed that megakaryocyte maturation markers CD-41 and CD-61 were elevated. This augmentation under the LPS and Zymosan system along with DNV Infection was further confirmed. Our analysis also suggested that activation of miR-125b and MAPK signaling led to lipid droplet elevation. This led us to analyze TLR-mediated consequences and their impact on megakaryocyte development under diverse pathogen-elicited conditions.

conclusionPathogenic challenges associated with toll-like receptor system activation could further our understanding of the platelet biogenesis mechanistic pathways under various pathogenic circumstances.

Indexed as

inflammasomelipid dropletsMAPK-signallingmiR-125bToll-like receptors

Identifiers

PMID37969204
PMCPMC10641356
OpenAlexW4388736950

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.