Evidence map›Paper›PMID 34630377›Full record

ReviewFrontiers in immunology2021

Pattern Recognition Proteins: First Line of Defense Against Coronaviruses.

Carlos A Labarrere, Ghassan S Kassab

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

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

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  6. Anti-inflammatory and anti-viral actions of anionic pulmonary surfactant phospholipids.Biochimica et biophysica acta. Molecular and cell biology of lipids · 2022
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Carlos A LabarrereCalifornia Medical Innovations Institute, San Diego, CA, United States.
Ghassan S KassabCalifornia Medical Innovations Institute, San Diego, CA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid outbreak of COVID-19 caused by the novel coronavirus SARS-CoV-2 in Wuhan, China, has become a worldwide pandemic affecting almost 204 million people and causing more than 4.3 million deaths as of August 11 2021. This pandemic has placed a substantial burden on the global healthcare system and the global economy. Availability of novel prophylactic and therapeutic approaches are crucially needed to prevent development of severe disease leading to major complications both acutely and chronically. The success in fighting this virus results from three main achievements: (a) Direct killing of the SARS-CoV-2 virus; (b) Development of a specific vaccine, and (c) Enhancement of the host's immune system. A fundamental necessity to win the battle against the virus involves a better understanding of the host's innate and adaptive immune response to the virus. Although the role of the adaptive immune response is directly involved in the generation of a vaccine, the role of innate immunity on RNA viruses in general, and coronaviruses in particular, is mostly unknown. In this review, we will consider the structure of RNA viruses, mainly coronaviruses, and their capacity to affect the lungs and the cardiovascular system. We will also consider the effects of the

Indexed as

AnimalsCardiovascular SystemCoronavirusCoronavirus InfectionsCOVID-19HumansImmunity, InnateImmunotherapyLungReceptors, Pattern RecognitionSARS-CoV-2Severe Acute Respiratory SyndromeReceptors, Pattern Recognitionacute respiratory distress syndromeATH - atherosclerosisCOVID- 19C-reactive proteininnate and adaptive IgM antibodiespattern recognition proteinsSARS-CoV-2surfactant proteins A and D (SP-A and SP-D)

Identifiers

PMID34630377
PMCPMC8494786

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.