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Record W2951174125 · doi:10.3791/59427

Processing of Bronchoalveolar Lavage Fluid and Matched Blood for Alveolar Macrophage and CD4<sup>+</sup> T-cell Immunophenotyping and HIV Reservoir Assessment

2019· article· en· W2951174125 on OpenAlexafffund
Syim Salahuddin, Elaine Thomson, Oussama Méziane, Omar Farnós, Amélie Pagliuzza, Nicolas Chomont, Ron Olivenstein, Cecilia T. Costiniuk, Mohammad‐Ali Jenabian

Bibliographic record

VenueJournal of Visualized Experiments · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsCentre Hospitalier de l’Université de MontréalMcGill UniversityUniversité du Québec à MontréalUniversité de MontréalMcGill University Health Centre
FundersCanadian Institutes of Health ResearchMcGill UniversityStyrelsen för Internationellt Utvecklingssamarbete
KeywordsBronchoalveolar lavageImmunophenotypingFlow cytometryImmunologyPathologyMedicineLungContext (archaeology)Immune systemBiologyInternal medicine

Abstract

fetched live from OpenAlex

Bronchoscopy is a medical procedure whereby normal saline is injected into the lungs via a bronchoscope and then suction is applied, removing bronchoalveolar lavage (BAL) fluid. The BAL fluid is rich in cells and can thus provide a 'snapshot' of the pulmonary immune milieu. CD4 T cells are the best characterized HIV reservoirs, while there is strong evidence to suggest that tissue macrophages, including alveolar macrophages (AMs), also serve as viral reservoirs. However, much is still unknown about the role of AMs in the context of HIV reservoir establishment and maintenance. Therefore, developing a protocol for processing BAL fluid to obtain cells that may be used in virological and immunological assays to characterize and evaluate the cell populations and subsets within the lung is relevant for understanding the role of the lungs as HIV reservoirs. Herein, we describe such a protocol, employing standard techniques such as simple centrifugation and flow cytometry. The CD4 T cells and AMs may then be used for subsequent applications, including immunophenotyping and HIV DNA and RNA quantification.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.358
Teacher spread0.343 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations10
Published2019
Admission routes2
Has abstractyes

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