Evidence map›Paper›PMID 22907125›Full record

ReviewExtremophiles : life under extreme conditions2012

Emergence of antibiotic-resistant extremophiles (AREs).

Prashant Gabani, Dhan Prakash, Om V Singh

Abstract readReview
PubMed Publisher
In one paragraph

Review in Extremophiles : life under extreme conditions, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 50% 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

3 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. 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 at 3 institutions in 2 countries.

Prashant GabaniDivision of Biological and Health Sciences, University of Pittsburgh, 300 Campus Drive, Bradford, PA 16701, USA.
Dhan Prakash
Om V Singh
Institute of Microbial Technology · INUniversity of Pittsburgh · USUniversity of Pittsburgh at Bradford · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Excessive use of antibiotics in recent years has produced bacteria that are resistant to a wide array of antibiotics. Several genetic and non-genetic elements allow microorganisms to adapt and thrive under harsh environmental conditions such as lethal doses of antibiotics. We attempt to classify these microorganisms as antibiotic-resistant extremophiles (AREs). AREs develop strategies to gain greater resistance to antibiotics via accumulation of multiple genes or plasmids that harbor genes for multiple drug resistance (MDR). In addition to their altered expression of multiple genes, AREs also survive by producing enzymes such as penicillinase that inactivate antibiotics. It is of interest to identify the underlying molecular mechanisms by which the AREs are able to survive in the presence of wide arrays of high-dosage antibiotics. Technologically, "omics"-based approaches such as genomics have revealed a wide array of genes differentially expressed in AREs. Proteomics studies with 2DE, MALDI-TOF, and MS/MS have identified specific proteins, enzymes, and pumps that function in the adaptation mechanisms of AREs. This article discusses the molecular mechanisms by which microorganisms develop into AREs and how "omics" approaches can identify the genetic elements of these adaptation mechanisms. These objectives will assist the development of strategies and potential therapeutics to treat outbreaks of pathogenic microorganisms in the future.

Indexed as

Anti-Bacterial AgentsAdaptation, PhysiologicalBacteriaBacterial ProteinsDrug Resistance, Multiple, BacterialGenes, BacterialProteomeProteomicsAnti-Bacterial AgentsBacterial ProteinsProteome

Identifiers

PMID22907125
OpenAlexW1972886765

What OpenQuestion holds

Textmetadata
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.