Evidence map›Paper›PMID 23930011›Full record

ArticlePharmacognosy magazine2013

Identification of ethnomedicinal plants (Rauvolfioideae: Apocynaceae) through DNA barcoding from northeast India.

Pradosh Mahadani, Gouri Dutta Sharma, Sankar Kumar Ghosh

Open access · bronzeAbstract read
In one paragraph

Article in Pharmacognosy magazine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

11 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
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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 1 institution in 1 country.

Pradosh MahadaniDepartment of Biotechnology, Assam University, Silchar - 788 011, Assam, India.
Gouri Dutta Sharma
Sankar Kumar Ghosh
Assam University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDNA barcode-based molecular characterization is in practice for plants, but yet lacks total agreement considering the selection of marker. Plant species of subfamily Rauvolfioideae have long been used as herbal medicine by the majority of tribal people in Northeast (NE) India and at present holds mass effect on the society. Hence, there is an urgent need of correct taxonomic inventorization vis-à-vis species level molecular characterization of important medicinal plants.

objectiveTo test the efficiency of matK in species delineation like DNA barcoding in Rauvolfiadae (Apocynaceae). MATERIALS AND

methodsIn this study, the core DNA barcode matK and trnH-psbA sequences are examined for differentiation of selected ethnomedicinal plants of Apocynaceae. DNA from young leaves of selected species was isolated, and matK gene (~800 bp) and trnH-psbA spacer (~450 bp) of Chloroplast DNA was amplified for species level identification.

resultsThe ~758 bp matK sequence in comparison to the trnH-psbA showed easy amplification, alignment, and high level of discrimination value among the medicinal Rauvolfioidae species. Intergenic spacer trnH-psbA is also exhibited persistent problem in obtaining constant bidirectional sequences. Partial matK sequences exhibited 3 indels in multiple of 3 at 5 end. Evidently, generated matK sequences are clustered cohesively, with their conspecific Genbank sequences. However, repeat structures with AT-rich regions, possessing indels in multiple of 3, could be utilized as qualitative molecular markers in further studies both at the intra-specific and shallow inter-specific levels like the intergenic spacers of CpDNA.

conclusionmatK sequence information could help in correct species identification for medicinal plants of Rauvolfioideae.

Indexed as

ApocynaceaeDNA barcodingethnomedicinalindelsmatK

Identifiers

PMID23930011
PMCPMC3732430
OpenAlexW2041941930

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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.