Evidence map›Paper›PMID 41459385›Full record

ArticleData in brief2026

Data of small molecule compounds and insulin-like growth factor-1 (IGF-1) detected in Deer Antler Velvet of Malayan Deer (

Khairani Idah Mokhtar, Nur Sazwi Nordin, Basma Ezzat Mustafa, Azlini Ismail, Mohamad Zakkirun Abdullah, Norzaiti Mohd Kenali, Ahmad Muzammil Zuberdi, Ismail Zainol, Azlina Ahmad

Abstract read
In one paragraph

Article in Data in brief, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Khairani Idah MokhtarDepartment of Fundamental Dental and Medical Sciences, Kulliyyah of Dentistry, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia.
Nur Sazwi NordinKulliyyah of Medicine, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia.
Basma Ezzat MustafaDepartment of Fundamental Dental and Medical Sciences, Kulliyyah of Dentistry, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia.
Azlini IsmailDepartment of Fundamental Dental and Medical Sciences, Kulliyyah of Dentistry, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia.
Mohamad Zakkirun AbdullahDepartment of Fundamental Dental and Medical Sciences, Kulliyyah of Dentistry, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia.
Norzaiti Mohd KenaliDepartment of Paediatric Dentistry and Dental Public Health, Kulliyyah of Dentistry, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia.
Ahmad Muzammil ZuberdiDepartment of Biotechnology, Kulliyyah of Science, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia.
Ismail ZainolFaculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, 35900 Tanjong Malim, Perak, Malaysia.
Azlina AhmadSchool of Dental Sciences, Universiti Sains Malaysia, Health Campus, 16150 Kubang Kerian, Kelantan, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deer antler velvet (DAV); obtained from the male deer, is commonly used in traditional Asian medicine, has been valued for centuries for its various health benefits. DAV extract contains bioactive compounds, including growth hormones, minerals, and amino acids. This data reveals the presence of small molecules detected in the DAV extracts obtained from the antler of the local male Malayan deer (

Indexed as

Crude extractLC-MS/MS-QTOF, Nontargeted compounds, IGF-1Male deer

Identifiers

PMID41459385
PMCPMC12741453

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.