Evidence map›Paper›PMID 39345741›Full record

ArticleToxicological research2024

Unveiling the link between arsenic toxicity and diabetes: an in silico exploration into the role of transcription factors.

Kaniz Fatema, Zinia Haidar, Md Tamzid Hossain Tanim, Sudipta Deb Nath, Abu Ashfaqur Sajib

Abstract read
In one paragraph

Article in Toxicological research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. From environmental exposure to retinal pathology: epidemiological and mechanistic insights into multi-metal driven ocular diseases.Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine · 2026
    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

5 authors.

Kaniz Fatema *Department of Genetic Engineering & Biotechnology, University of Dhaka, Dhaka, 1000 Bangladesh.
Zinia Haidar *Department of Genetic Engineering & Biotechnology, University of Dhaka, Dhaka, 1000 Bangladesh.
Md Tamzid Hossain TanimDepartment of Genetic Engineering & Biotechnology, University of Dhaka, Dhaka, 1000 Bangladesh.
Sudipta Deb NathDepartment of Genetic Engineering & Biotechnology, University of Dhaka, Dhaka, 1000 Bangladesh.
Abu Ashfaqur SajibDepartment of Genetic Engineering & Biotechnology, University of Dhaka, Dhaka, 1000 Bangladesh.ORCID 0000-0003-1710-9865

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Arsenic-induced diabetes, despite being a relatively newer finding, is now a growing area of interest, owing to its multifaceted nature of development and the diversity of metabolic conditions that result from it, on top of the already complicated manifestation of arsenic toxicity. Identification and characterization of the common and differentially affected cellular metabolic pathways and their regulatory components among various arsenic and diabetes-associated complications may aid in understanding the core molecular mechanism of arsenic-induced diabetes. This study, therefore, explores the effects of arsenic on human cell lines through 14 transcriptomic datasets containing 160 individual samples using in silico tools to take a systematic, deeper look into the pathways and genes that are being altered. Among these, we especially focused on the role of transcription factors due to their diverse and multifaceted roles in biological processes, aiming to comprehensively investigate the underlying mechanism of arsenic-induced diabetes as well as associated health risks. We present a potential mechanism heavily implying the involvement of the TGF-β/SMAD3 signaling pathway leading to cell cycle alterations and the NF-κB/TNF-α, MAPK, and Ca Supplementary Information: The online version contains supplementary material available at 10.1007/s43188-024-00255-y.

Indexed as

ArsenicDiabetesDifferentially expressed genesSignaling pathwaysTranscription factors

Identifiers

PMID39345741
PMCPMC11436564

What Socratic holds

Textmetadata
Read underepoch 390

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 Socratic graph.