Evidence map›Paper›PMID 40622505›Full record

ArticleJournal of neurovirology2025

Designing a cellular MicroRNA-based approach to silence bat-borne Nipah virus genes.

Nikita Kar, Supriyo Chakraborty

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Article in Journal of neurovirology, 2025. 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
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Nikita KarDepartment of Biotechnology, Assam University, Silchar, Assam, 788011, India.
Supriyo ChakrabortyDepartment of Biotechnology, Assam University, Silchar, Assam, 788011, India. chakrabortysupriyo2024@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The bat-borne Nipah virus, known for causing high mortality rates in humans, has been reported in India (Megaderma spasma), Bangladesh (Pteropus medius), and Malaysia (Pteropus vampyrus) with different bat species serving as reservoirs. The virus also infects various animals, which often act as intermediate hosts in the transmission to humans. Due to the high fatality rates associated with Nipah virus outbreaks, the World Health Organization has flagged it as a significant public health concern, prompting extensive research into the development of antiviral therapeutics and vaccines. However, no effective vaccine or therapeutic agent has yet been established. In this context, we propose a miRNA-based approach to identify key human cellular miRNAs capable of binding to and potentially cleaving or degrading Nipah virus genes implicated in human infections. Our study revealed a substantial number of miRNA binding sites across various viral genes, suggesting a potential mechanism for gene silencing. Furthermore, the calculated free energy values (< 4 kcal/mol) for all three regions; downstream, upstream and target indicate that the thermodynamically favorable binding could facilitate effective miRNA-mediated repressions of viral gene expression. Additionally, the translational efficiency and COSM values suggested swift miRNA-mediated cleavage or degradation of the viral genes. Moreover, analysis of the miRNA-mRNA duplex free energy and secondary structures, as predicted by RNAFold, indicated that the interactions between human miRNAs and Nipah virus genes were thermodynamically stable. These stable duplex formations support the potential for efficient binding, leading to effective gene silencing through cleavage or degradation mechanisms.

Indexed as

ChiropteraHenipavirus InfectionsMicroRNAsNipah VirusRNA, ViralAnimalsBinding SitesGene SilencingHumansMicroRNAsRNA, ViralGenesmiRNA-mediated repressionNipah virus (or NiV)Target sites

Identifiers

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Registered trials

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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.