Evidence map›Paper›PMID 34136097›Full record

ArticleComputational and structural biotechnology journal2021

Zhanshan Sam Ma, Aaron M Ellison

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Dysbiosis of vaginal and cervical microbiome is associated with uterine fibroids.Frontiers in cellular and infection microbiology · 2023
    Observational
  7. Power law analysis of the human milk microbiome.Archives of microbiology · 2022
    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

2 authors.

Zhanshan Sam MaComputational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, China.
Aaron M EllisonHarvard University, Harvard Forest, 324 North Main Street, Petersham, MA 01366, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BV (bacterial vaginosis) influences 20%-40% of women but its etiology is still poorly understood. An open question about the BV is which of the hundreds of bacteria found in the human vaginal microbiome (HVM) are the major force driving the vaginal microbiota dysbiosis. Here, we recast the question of microbial causality of BV by asking if there are any prevalent 'signatures' (network motifs) in the vaginal microbiome networks associated with it? We apply a new framework [species dominance network analysis by Ma & Ellison (2019):

Indexed as

ABV, asymptomatic bacterial vaginosisBVAB, BV-associated anaerobic bacteriaBV-associated anaerobic bacteria (BVAB)BV, bacterial vaginosisBV (Bacterial vaginosis)Community dominanceCore/periphery network (CPN)CPN, core/periphery networkCST, community state typeDiversity-stability relationship (DSR)DSR, diversity-stability relationshipHEA, healthy treatmentHigh-salience skeleton networks (HSN)HSN, high-salience skeleton networkHVM, human vaginal microbiomeMAO, most abundant species or OTUMDO, most dominant species or OTUOTU, operational taxonomic unitSBV, symptomatic BVSDN, species dominance networkSpecies dominanceSpecies dominance network (SDN)

Identifiers

PMID34136097
PMCPMC8170074

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.