Evidence map›Paper›PMID 36840801›Full record

ReviewInternational urology and nephrology2023

NETosis and kidney disease: what do we know?

Demet Alaygut, Ilyas Ozturk, Sena Ulu, Ozkan Gungor

Abstract readReview
PubMed Publisher
In one paragraph

Review in International urology and nephrology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. 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

4 authors.

Demet AlaygutDepartment of Pediatric Nephrology, University of Health Sciences, Izmir Faculty of Medicine, Tepecik Training and Research Hospital, Izmir, Turkey.
Ilyas OzturkDepartment of Internal Medicine, Division of Nephrology, Kahramanmaras Sutcu Imam University Faculty of Medicine, Kahramanmaras, Turkey. drilyasozturk@gmail.com.ORCID http://orcid.org/0000-0001-9431-8068
Sena UluDepartment of Internal Medicine, Division of Nephrology, Bahcesehir University Faculty of Medicine, Istanbul, Turkey.
Ozkan GungorDepartment of Internal Medicine, Division of Nephrology, Kahramanmaras Sutcu Imam University Faculty of Medicine, Kahramanmaras, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neutrophils are the most abundant leukocytes in the blood. They are rapidly mobilized from the circulation to sites of inflammation and/or infection. In affected tissues, neutrophils exhibit some dramatic antimicrobial functions, including degranulation, reactive oxygen species (ROS) production, phagocytosis, and formation of neutrophil extracellular traps (NETs). Like other cells of the immune system, after fulfilling their biological duties, they enter the path of death. Depending on the conditions, they may undergo different types of cell death (apoptosis, necrosis, necroptosis, autophagy, NETosis, and pyroptosis) that require the participation of multiple signaling pathways. NETosis is a unique neutrophil cell death mechanism that gives rise to different inflammatory and autoimmune pathological conditions. Recent studies have shown that NETosis also plays a role in the formation and/or progression of kidney diseases. This review discusses the underlying mechanism of NETosis and its relationship with some major kidney diseases in light of the current knowledge.

Indexed as

Autoimmune DiseasesExtracellular TrapsApoptosisHumansNecrosisNeutrophilsReactive Oxygen SpeciesReactive Oxygen SpeciesInflammationKidneyNETosisNETsNeutrophils

Identifiers

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.