ReviewFrontiers in immunology2018
Cytokine-Mediated Tissue Injury in Non-human Primate Models of Viral Infections.
Review in Frontiers in immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed, 15 citations in OpenAlex.
- Apoptotic body based biomimetic hybrid nanovesicles to attenuate cytokine storms for sepsis treatment.Journal of nanobiotechnology · 2024Article
- Regional brain activation during rectal distention and attenuation with alosetron in a nonhuman primate model of irritable bowel syndrome.FASEB bioAdvances · 2022Article
- Peritoneal M2 macrophage-derived extracellular vesicles as natural multitarget nanotherapeutics to attenuate cytokine storms after severe infections.Journal of controlled release : official journal of the Controlled Release Society · 2022Article
- Article
- Role of NKG2a/ciScience · 2021Article
- Pathogenesis of Influenza A(H7N9) Virus in Aged Nonhuman Primates.The Journal of infectious diseases · 2020Article
- Crocetin Improves Dengue Virus-Induced Liver Injury.Viruses · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Viral infections trigger robust secretion of interferons and other antiviral cytokines by infected and bystander cells, which in turn can tune the immune response and may lead to viral clearance or immune suppression. However, aberrant or unrestricted cytokine responses can damage host tissues, leading to organ dysfunction, and even death. To understand the cytokine milieu and immune responses in infected host tissues, non-human primate (NHP) models have emerged as important tools. NHP have been used for decades to study human infections and have played significant roles in the development of vaccines, drug therapies and other immune treatment modalities, aided by an ability to control disease parameters, and unrestricted tissue access. In addition to the genetic and physiological similarities with humans, NHP have conserved immunologic properties with over 90% amino acid similarity for most cytokines. For example, human-like symptomology and acute respiratory syndrome is found in cynomolgus macaques infected with highly pathogenic avian influenza virus, antibody enhanced dengue disease is common in neotropical primates, and in NHP models of viral hepatitis cytokine-induced inflammation induces severe liver damage, fibrosis, and hepatocellular carcinoma recapitulates human disease. To regulate inflammation, anti-cytokine therapy studies in NHP are underway and will provide important insights for future human interventions. This review will provide a comprehensive outline of the cytokine-mediated exacerbation of disease and tissue damage in NHP models of viral infections and therapeutic strategies that can aid in prevention/treatment of the disease syndromes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.