Evidence map›Paper›PMID 38281210›Full record

ReviewMolecular biology reports2024

Regulation of gene expression by modulating microRNAs through Epigallocatechin-3-gallate in cancer.

Loganathan Chandramani Priya Dharshini, Abul Kalam Azad Mandal

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular biology reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.4field-weighted citation impact, top 8% of its field
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

5 citing papers in PubMed, 8 citations in OpenAlex.

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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 at 1 institution in 1 country.

Loganathan Chandramani Priya DharshiniDepartment of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Abul Kalam Azad MandalDepartment of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India. akamandal@rediffmail.com.ORCID http://orcid.org/0000-0002-7792-9219
Vellore Institute of Technology University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is an intricate ailment that has a higher death rate globally and is characterized by aberrant cell proliferation and metastasis in nature. Since the beginning of healthcare, natural products, especially those derived from plants, have been utilized to support human health. Green tea contains an essential catechin called epigallocatechin gallate, which has anti-proliferative, anti-mutagenic, anti-inflammatory, and antioxidative properties. The anticancer properties of EGCG have been extensively studied using pre-clinical cell culture and animal model systems. Dysregulated miRNA may be a biomarker since it influences the different characteristics of cancer like upholding proliferative signaling, cell death, invasiveness, metastasis, and angiogenesis. EGCG either elevates or lowers the expression of dysregulated miRNAs in cancer. Nonetheless, due to its anticancer properties, greater attention has been paid towards the development of efficient strategies for utilizing EGCG in cancer chemotherapy. This review summarizes the modifying effect of EGCG on miRNAs in cancer after briefly discussing the anticancer mechanisms of EGCG and the function of miRNAs in cancer.

Indexed as

CatechinMicroRNAsNeoplasmsAnimalsAnti-Inflammatory AgentsGene Expression RegulationHumansAnti-Inflammatory AgentsCatechinepigallocatechin gallateMicroRNAsAnticancer propertiesBioavailabilityBiomarkerNatural compoundsTherapeutic efficacy

Identifiers

PMID38281210
OpenAlexW4391298041

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.