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Record W4402340811 · doi:10.1093/labmed/lmae076

Dihydrorhodamine-123 flow cytometry method: time for substantial revision in technical procedure

2024· article· en· W4402340811 on OpenAlexaff
Mahdi Zavvar, Sina Zargaran, Hamed Baghdadi, Peyvand Poopak, Amir Hossein Poopak, Fariba Nabatchian, Yousef Fatahi, Gelareh Khosravipour

Bibliographic record

VenueLaboratory Medicine · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsUniversity of Toronto
FundersTehran University of Medical Sciences and Health Services
KeywordsFlow cytometryStopped flowComputer scienceChemistryBiological systemChromatographyMedicineImmunologyBiologyKineticsPhysics

Abstract

fetched live from OpenAlex

The dihydrorhodamine 123 assay is generally applied to measure the production of intracellular reactive oxygen species in neutrophils using flow cytometry and is considered a diagnostic evaluation for chronic granulomatous disease. In fact, there is a broad range of variables that can directly or indirectly affect test results, either individually or collectively. It is therefore crucial to identify the ideal requirements to achieve reliable results as well as using these requirements to provide standard operating procedures that should be taken into account. Therefore, we focus on aligning optimum results by comparing preanalytical and analytical phases that influence test results, such as the effect of various anticoagulants, transport and maintaining temperature (24°C or 4°C) of samples, test prime run time, appropriate solution concentrations, and effect of incubation temperature (24°C or 37°C) during the test run.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.023
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.977
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.045
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0040.002
Science and technology studies0.0030.003
Scholarly communication0.0030.002
Open science0.0040.004
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0360.045

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 head0.013
GPT teacher head0.306
Teacher spread0.293 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainMethods
GenreMethods

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

Citations2
Published2024
Admission routes1
Has abstractyes

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