Evidence map›Paper›PMID 35554911›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Animal Models of COVID-19: Nonhuman Primates.

Dhiraj K Singh, Journey Cole, Ruby A Escobedo, Kendra J Alfson, Bindu Singh, Tae-Hyung Lee, Xavier Alvarez, Shashank R Ganatra, Ricardo Carrion, Deepak Kaushal

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Clinical Translation of Engineered Pulmonary Vascular Models.Advances in experimental medicine and biology · 2023
    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

10 authors.

Dhiraj K SinghSouthwest National Primate Research Center, San Antonio, TX, USA.
Journey ColeSouthwest National Primate Research Center, San Antonio, TX, USA.
Ruby A EscobedoSouthwest National Primate Research Center, San Antonio, TX, USA.
Kendra J AlfsonTexas Biomedical Research Institute, San Antonio, TX, USA.
Bindu SinghSouthwest National Primate Research Center, San Antonio, TX, USA.
Tae-Hyung LeeSouthwest National Primate Research Center, San Antonio, TX, USA.
Xavier AlvarezSouthwest National Primate Research Center, San Antonio, TX, USA.
Shashank R GanatraSouthwest National Primate Research Center, San Antonio, TX, USA.
Ricardo CarrionTexas Biomedical Research Institute, San Antonio, TX, USA.
Deepak KaushalSouthwest National Primate Research Center, San Antonio, TX, USA. dkaushal@txbiomed.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the advent of the novel SARS-CoV-2, the entire world has been thrown into chaos with severe disruptions from a normal life. While the entire world was going chaotic, the researchers throughout the world were struggling to contribute to the best of their capabilities to advance the understanding of this new pandemic and fast track the development of novel therapeutics and vaccines. While various animal models have helped a lot to understand the basic physiology, nonhman primates have been promising and much more successful in modelling human diseases compared to other available clinical models. Here we describe the different aspects of modelling the SARS-CoV-2 infection in NHPs along with the associated methods used in NHP immunology.

Indexed as

COVID-19AnimalsDisease Models, AnimalPandemicsPrimatesSARS-CoV-2Animal modelsBALComputed tomographyCone beamConfocal microscopyCOVID-19FACSFlow cytometryIHCIn vivo imagingNHPNonhuman primatesRhesus macaquesSARS-CoV-2X-rays

What OpenQuestion holds

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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.