Evidence map›Paper›PMID 23798890›Full record

ArticlePharmacognosy research2013

Isolation and identification of bacterial endophytes from pharmaceutical agarwood-producing Aquilaria species.

Subhash J Bhore, Jagadesan Preveena, Kodi I Kandasamy

Abstract read
In one paragraph

Article in Pharmacognosy research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. SaprophyticMolecules (Basel, Switzerland) · 2022
    Article
  7. Exploring endophytes forAIMS microbiology · 2021
    Review
  8. Article
  9. Fungal and Bacterial Diversity Isolated fromFrontiers in microbiology · 2017
    Article
  10. 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

3 authors.

Subhash J BhoreDepartment of Biotechnology, Faculty of Applied Sciences, AIMST University, Bedong Semeling Road, Semeling 08100, Kedah, Malaysia.
Jagadesan Preveena
Kodi I Kandasamy

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundResins and gums are used in traditional medicine and do have potential applications in pharmacy and medicine. Agarwood is the fragrant resinous wood, which is an important commodity from Aquilaria species and has been used as a sedative, analgesic, and digestive in traditional medicine. Endophytic bacteria are potentially important in producing pharmaceutical compounds found in the plants. Hence, it was important to understand which types of endophytic bacteria are associated with pharmaceutical agarwood-producing Aquilaria species.

objectiveThis study was undertaken to isolate and identify endophytic bacteria associated with agarwood-producing seven (7) Aquilaria species from Malaysia. MATERIALS AND

methodsBotanical samples of seven Aquilaria species were collected, and endophytic bacteria were isolated from surface-sterilized-tissue samples. The 16S rRNA gene fragments were amplified using PCR method, and endophytic bacterial isolates (EBIs) were identified based on 16S rRNA gene sequence similarity based method.

resultsCulturable, 77 EBIs were analyzed, and results of 16S rRNA gene sequences analysis suggest that 18 different types of endophytic bacteria are associated with (seven) Aquilaria species. From 77 EBIs, majority (36.4%) of the isolates were of Bacillus pumilus.

conclusionThese findings indicate that agarwood-producing Aquilaria species are harboring 18 different types of culturable endophytic bacteria.

Indexed as

16S rRNAbiodiversityendophytesMalaysiamedicinenatural productsribosomal DNAtraditional medicine

Identifiers

PMID23798890
PMCPMC3685763

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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.