Evidence map›Paper›PMID 25364208›Full record

ArticleAyu2014

Phytochemical screening of five medicinal legumes and their evaluation for in vitro anti-tubercular activity.

J Komal Kumar, A G Devi Prasad, Vinita Chaturvedi

Open access · greenAbstract read
In one paragraph

Article in Ayu, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.4field-weighted citation impact, top 15% 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

4 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. 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

3 authors at 3 institutions in 2 countries.

J Komal KumarDepartment of Clinical and Experimental Medicine, University of Linkoping, Sweden, India.
A G Devi PrasadDepartment of Environmental Science, University of Mysore, Karnataka, India.
Vinita ChaturvediDrug Target Discovery and Development Division, Central Drug Research Institute, Lucknow, Uttar Pradesh, India.
Central Drug Research Institute · INLinköping University · SEUniversity of Mysore · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTuberculosis is a leading cause of death in the world. A new alternative for the treatment of tuberculosis is urgently required, due to the emergence of multidrug resistant Mycobacterium tuberculosis.

aimThere is currently considerable interest in developing potential drugs from medicinal plants for treating tuberculosis. To evaluate anti-tubercular activity in the leaves of Kingiodendron pinnatum Rox. Hams., Humboldtia brunonis Wall., Indigofera cassioides Rottl.ex DC., Derris scandens Benth. and Ceasalpinia mimosoides Lamk. MATERIALS AND

methodsNon-polar and polar solvent extracts of leaves of these medicinal legumes were tested against M. tuberculosis H37RV and minimum inhibitory concentrations (MICs) were determined by the agar based proportion assay.

resultsPhytochemical screening for secondary metabolites revealed the presence of saponins, steroids, anthro-quinones, terpinods, flavonoids and phlabotanins. Crude leaf extracts of these plants have shown MIC value of 50 μg/ml as against the standard drug Isoniazid value of 0.025 μg/ml.

conclusionResults showed that crude extracts of legume leaves screened exhibited potential anti-tubercular activity against M. tuberculosis and further work is required to identify the active molecule of these legumes, to get a novel anti-tubercular drug. This is the maiden finding on anti-tubercular activity of these medicinal legumes.

Indexed as

Bioactive compoundsmedicinal legumessecondary metabolitestuberculosis

Identifiers

PMID25364208
PMCPMC4213978
OpenAlexW2020446491

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.