Evidence map›Paper›PMID 38309727›Full record

ArticleSaudi medical journal2024

Ras-related associated with diabetes genes for biomarker-based therapeutics in cancer: A comparative evolutionary genomic study.

Mohammed A Hakami

Open access · diamondAbstract read
In one paragraph

Article in Saudi medical journal, 2024. 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
0.3field-weighted citation impact, top 45% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  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

1 author at 1 institution in 1 country.

Mohammed A HakamiFrom the Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Shaqra University, Al-Quwayiyah, Riyadh, Kingdom of Saudi Arabia.ORCID https://orcid.org/0000-0002-1747-1277
Shaqra University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo compare Ras-related associated with diabetes (RRAD) across different species and to identify specific biomarkers for cancer therapy.

methodsThe study involves comparing the coding sequences, genes, messenger ribonucleic acid (RNA), non-coding RNA, open reading frame, short- and long-sequence repeats, and transcription factors of RRAD genes from 82 species. Various tools and software are employed for these comparisons, and evolutionary analysis was carried out to understand the gene's evolutionary history. The data are classified based on forward and reverse sequences.

resultsOur analysis indicates that ACTG1 may function as a downstream effector of RRAD, offering potential avenues for diabetes and cancer treatments. By collecting RRAD sequences from 82 species and carrying out comparative genomics, this study provides diverse strategies for developing biomarker-based therapeutics. Furthermore, it suggests using RRAD in other organisms as a model for studying the knockdown effects of specific sequence sets. The study presents RRAD sequences from 82 organisms across different families, contributing to a diverse knowledge base for identifying drug-designing biomarkers.

conclusionThis research offers insights into the potential of RRAD as a therapeutic target in various organisms and highlights the importance of biomarker identification in drug development.

Indexed as

Diabetes MellitusNeoplasmsBiomarkersGenomicsHumansras ProteinsBiomarkersras Proteinscomparative annotationsdiabetesphylogenomicRRADSSRstranscription factors

Identifiers

PMID38309727
PMCPMC11115408
OpenAlexW4391511458

What OpenQuestion holds

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LicenceCC BY-NC
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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.