ReviewCurrent opinion in HIV and AIDS2021
The single-cell landscape of immunological responses of CD4+ T cells in HIV versus severe acute respiratory syndrome coronavirus 2.
Review in Current opinion in HIV and AIDS, 2021. 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, 9 citations in OpenAlex.
- Chain management reduces inflammation (IL-1b, IL-6, IL-8, TNF-a, PCT) and improves vascular (NO, DD, VWF, and ET-1)/immune function in acute respiratory failure: A retrospective cohort study.Journal of medical biochemistry · 2025Article
- CD4 + Count: a Variable to Be Considered to Prioritize COVID-19 Vaccination in PLHIV.Current pharmacology reports · 2023Review
- CASA: a comprehensive database resource for the COVID-19 Alternative Splicing Atlas.Journal of translational medicine · 2022Article
- Enigma of the high prevalence of anti-SARS-CoV-2 antibodies in HIV-positive people with no symptoms of COVID-19 in Burkina Faso.Journal of public health in Africa · 2022Article
- Single-cell analysis of COVID-19, sepsis, and HIV infection reveals hyperinflammatory and immunosuppressive signatures in monocytes.Cell reports · 2021Article
- Review
- Follicular Helper T Cells in the Immunopathogenesis of SARS-CoV-2 Infection.Frontiers in immunology · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
purpose of reviewCD4 T cell loss is the hallmark of uncontrolled HIV-1 infection. Strikingly, CD4 T cell depletion is a strong indicator for disease severity in the recently emerged coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We reviewed recent single-cell immune profiling studies in HIV-1 infection and COVID-19 to provide critical insight in virus-induced immunopathogenesis. RECENT
findingsCytokine dysregulation in HIV-1 leads to chronic inflammation, while severe SARS-CoV-2 infection induces cytokine release syndrome and increased mortality. HIV-1-specific CD4 T cells are dysfunctional, while SARS-CoV-2-specific CD4 T cells exhibit robust Th1 function and correlate with protective antibody responses. In HIV-1 infection, follicular helper T cells (TFH) are susceptible to HIV-1 infection and persist in immune-sanctuary sites in lymphoid tissues as an HIV-1 reservoir. In severe SARS-CoV-2 infection, TFH are absent in lymphoid tissues and are associated with diminished protective immunity. Advancement in HIV-1 DNA, RNA, and protein-based single-cell capture methods can overcome the rarity and heterogeneity of HIV-1-infected cells and identify mechanisms of HIV-1 persistence and clonal expansion dynamics. SUMMARY: Single-cell immune profiling identifies a high-resolution picture of immune dysregulation in HIV-1 and SARS-CoV-2 infection and informs outcome prediction and therapeutic interventions.
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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.