Evidence map›Paper›PMID 36619166›Full record

ReviewFrontiers in molecular biosciences2022

The

Meysam Sarshar, Daniela Scribano, Anna Teresa Palamara, Cecilia Ambrosi, Andrea Masotti

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 13% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. 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

5 authors at 4 institutions in 1 country.

Meysam SarsharResearch Laboratories, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy.
Daniela ScribanoDepartment of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy.
Anna Teresa PalamaraLaboratory Affiliated to Institute Pasteur Italia-Cenci Bolognetti Foundation, Department of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy.
Cecilia AmbrosiDepartment of Human Sciences and Promotion of the Quality of Life, San Raffaele Roma Open University, Rome, Italy.
Andrea MasottiResearch Laboratories, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy.
Bambino Gesù Children's Hospital · ITIRCCS Ospedale San Raffaele · ITIstituto Pasteur · ITSapienza University of Rome · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacterial small RNAs (sRNAs) research has accelerated over the past decade, boosted by advances in RNA-seq technologies and methodologies for capturing both protein-RNA and RNA-RNA interactions. The emerging picture is that these regulatory sRNAs play important roles in controlling complex physiological processes and are required to survive the antimicrobial challenge. In recent years, the RNA content of OMVs/EVs has also gained increasing attention, particularly in the context of infection. Secreted RNAs from several bacterial pathogens have been characterized but the exact mechanisms promoting pathogenicity remain elusive. In this review, we briefly discuss how secreted sRNAs interact with targets in infected cells, thus representing a novel perspective of host cell manipulation during bacterial infection. During the last decade,

Indexed as

Acinetobacter baumanniiantibiotic-resistancehost-pathogen interactionsnon-coding RNAsouter membrane vesicles (OMVs)small RNAs (sRNAs)

Identifiers

PMID36619166
PMCPMC9810633
OpenAlexW4313461282

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.