Evidence map›Paper›PMID 35422954›Full record

ReviewAmerican journal of translational research2022

Non-coding RNAs: are they the protagonist or antagonist in the regulation of leukemia?

Mrinnanda Bhattacharya, Ravi Kumar Gutti

Open access · greenAbstract readReview
In one paragraph

Review in American journal of translational research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.5field-weighted citation impact, top 39% 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

7 citing papers in PubMed, 6 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.

Mrinnanda BhattacharyaDepartment of Systems and Computational Biology, School of Life Sciences, University of Hyderabad (PO) Gachibowli, Hyderabad 500046 (TS), India.
Ravi Kumar GuttiDepartment of Biochemistry, School of Life Sciences, University of Hyderabad (PO) Gachibowli, Hyderabad 500046 (TS), India.
University of Hyderabad · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The idea of functional non-coding RNAs is taking precedence over the previous notion which believed that they only comprise the auxiliary and junk material of the genome. Newer technologies and studies have proven their importance in regulating and affecting several cellular processes. One such area of research wherein their importance has started to take light is in cancer research, particularly leukemia. Myeloid leukemia is a blood malignancy birthed from mutations in hematopoiesis that disable myeloid progenitor cells from proper differentiation. This review will compile the most recent findings regarding the effects of these regulatory non-coding RNAs on the two types of myeloid leukemia. In particular, the effects of circular RNAs, micro RNAs and long non-coding RNAs, on the pathogenesis and proliferation of Acute and Chronic myeloid leukemia will be revealed in a molecular, cellular and prognostic light. The mechanisms of proliferation, gene-to-gene interactions and possible therapeutic effects will also be discussed. Finally, an understanding of the overall "goodness" and "badness" of these non-coding RNAs will be summarised. This review hopes to provide a platform for easy access to data regarding the current non-coding RNAs in myeloid leukemia, for faster and easier research. Finally, the review will summarize a few key players that have protagonistic and antagonistic functions, and those that regulate multiple pathways in leukemia simultaneously.

Indexed as

AMLcircRNAsCMLlncRNAsMiRNAs

Identifiers

PMID35422954
PMCPMC8991171
OpenAlexW4226075243

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.