Evidence map›Paper›PMID 41180662›Full record

ReviewAnnals of medicine and surgery (2012)2025

Potential role of different animal models for the evaluation of bioactive compounds.

Anirban Debnath, Manojit Bhattacharya, Chiranjib Chakraborty, Arpita Das

Abstract readReview
In one paragraph

Review in Annals of medicine and surgery (2012), 2025. 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. A High Proportion ofMicroorganisms · 2026
    Article
  2. Review
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

4 authors.

Anirban DebnathDepartment of Biotechnology, School of Life Science and Biotechnology, Adamas University, Kolkata, West Bengal, India.
Manojit BhattacharyaDepartment of Zoology, Fakir Mohan University, Vyasa Vihar, Balasore, Odisha, India.
Chiranjib ChakrabortyDepartment of Biotechnology, School of Life Science and Biotechnology, Adamas University, Kolkata, West Bengal, India.ORCID https://orcid.org/0000-0002-3958-239X
Arpita DasDepartment of Biotechnology, School of Life Science and Biotechnology, Adamas University, Kolkata, West Bengal, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Animal models are crucial in biomedical research, facilitating the understanding of human diseases at the molecular and cellular levels. At the same time, animal models aid in molecular screening for drug discovery and development. In this review article, we extensively discuss two critical points: the importance of animal models and the bioactive compounds. During the discussion of the importance of animal models, we explore how they aid in understanding disease mechanisms and progression, as well as genetic diseases, drug discovery and development, and drug repurposing. To discuss the importance of bioactive compounds, we illustrate their impact on human health and disease, as well as their industrial applications. Finally, we discuss the various studies on bioactive compounds that have been conducted using different animal models. To highlight the various studies on bioactive compounds using animal models, we categorized them under two headings: mammalian animal models and non-mammalian animal models. Again, for mammalian animal models, we explained various studies on bioactive compounds in mice, rats, rabbits, guinea pigs, hamsters, ferrets, and gerbils. Similarly, for non-mammalian animal models, we illustrated the different studies on bioactive compounds using zebrafish,

Indexed as

animal modelbioactive compoundsdisease mechanismdrug discovery

Identifiers

PMID41180662
PMCPMC12578086

What OpenQuestion holds

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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.