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Record W2318601888 · doi:10.1097/coh.0000000000000098

Editorial overview

2014· editorial· en· W2318601888 on OpenAlexaff
Nabila Seddiki, Daniel E. Kaufmann

Bibliographic record

VenueCurrent Opinion in HIV and AIDS · 2014
Typeeditorial
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersNational Heart, Lung, and Blood Institute
KeywordsMedicineIntensive care medicineAntiretroviral therapyDiseasePsychological interventionImmune systemOptimismImmunologyHuman immunodeficiency virus (HIV)PsychologyViral loadPsychotherapistPsychiatryPathology

Abstract

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Since the initial descriptions of CD4 T cell depletion as a critical factor associated with progression to AIDS, our understanding of immune dysfunction in HIV infection has dramatically evolved. Over the past decade, in particular, technical progress and conceptual advances have allowed the exploration of a wide array of qualitative and functional changes that occur in multiple cell types and several compartments of the body. The realization that chronic immune activation is a major driving force in disease progression and associated with clinical complications even in patients on antiretroviral therapy has fostered progress in clarifying the complex interplay between the virus and the infected host. Unfortunately, although improvement in antiretroviral therapy has been dramatic since the mid 1990s, the better understanding of immune impairment has yet to result in therapeutic interventions that efficiently complement antiretroviral therapy (ART) or improve the efficacy of HIV vaccine candidates. However, recent progress in other fields of medicine gives reasons for optimism. In particular, new immunotherapies have shown dramatic results in treatment of several autoimmune diseases and previously refractory types of cancer, with, in many cases, very good tolerance by the patients. The efficacy of these clinical interventions suggests that in the field of chronic infectious diseases – in particular HIV – the knowledge gained in animal models and human studies will translate into better patient care and preventive strategies. In this issue, a series of reviews cover new progress in the understanding of immune cell dysfunction in HIV infection. Several themes are also addressed in the perspective of studies of other chronic viral infections in humans, nonhuman primates or mice. The importance of both cell-extrinsic factors provided by the altered microenvironment of HIV infection and cell-intrinsic factors, including genetic exhaustion programs, is addressed. These articles provide an overview of mechanisms that affect function of both the innate and adaptive immunity. The critical importance of inhibitory coreceptors in the functional impairment of T cells in chronic infection has been well demonstrated over recent years. Kuchroo et al. (pp. 439–445) review recent findings on their role in CD8 T cell exhaustion and discuss their interplay. However, recent data show that CD4 T cell dysfunction is not a copycat of T cell impairment and is, in part, governed by distinct mechanisms. Morou et al. (pp. 446–451) underline the importance of CD4 T cell plasticity in infectious diseases and the contributing roles of both skewing of CD4 T cell differentiation and exhaustion mechanisms. Seddiki and Draenert (pp. 452–458) describe recent advances on suppressor cells and the availability of new markers and functional assays to investigate regulatory T cells, regulatory B cells and myeloid-derived suppressor cells. A critical component of T cell dysfunction resides in a complex network of transcription factors, discussed by Collins and Henderson (pp. 459–463). Major progress has been made recently in the understanding of the role of noncoding microRNA (miRNA) in regulating cell function in both physiologic and pathological conditions. Swaminathan and Kelleher (pp. 464–471) discuss microRNAs as potential new important players in the T cell dysfunction observed with HIV-1 infection and their potential as therapeutic targets. The B cell compartment is also affected in HIV infection. Moir and Fauci (pp. 472–477) review the role played by immune activation in B cell exhaustion, and compare it to T cell exhaustion and B cell alterations in other diseases. Antigen-presenting cells are profoundly altered in HIV infection, and Piguet et al. (pp. 478–484) review the adverse effects of chronic hyperactivation of this critical population. It is only in the early 2000s that T follicular helper cells have been identified as a critical population for B cell help. Tremendous progress has been made in this area since then. Cubas and Perreau (pp. 485–491) report on recent findings addressing the role of T follicular helper cells (Tfh) cells in HIV infection as well as the impact HIV infection has on germinal center Tfh and circulating memory Tfh cell frequency and function. The precise links between these populations still need to be fully defined, and studies in animal models are particularly informative in this regard. In line with this, McGary et al. (pp. 492–499) describe the most recent advances in the use of animal models for the study of cell exhaustion following HIV or simian immunodeficiency virus (SIV) infection, and their critical role on the path to possible new immunotherapeutic approaches. Finally, Mudd and Lederman (pp. 500–505) describe the adverse effects of the expansion of the CD8 compartment in HIV infection that is associated with adverse clinical events, even in ART-treated individuals. Our understanding of the complexity of immune cell dysfunction – here defined as exhaustion in a broad sense – has expanded dramatically in recent years. There are reasons to be optimistic and to hope that the time is near when this knowledge will be translated into new therapeutic approaches to complement ART and into better patient care. Acknowledgements None. Conflicts of interest There are no conflicts of interest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.311
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2014
Admission routes1
Has abstractyes

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