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Record W4403072309 · doi:10.1093/clinchem/hvae106.584

B-224 Rapid, Extraction-Free, and Portable Molecular Detection of HIV-1 and HCV Directly From Whole Blood

2024· article· en· W4403072309 on OpenAlexaff
Krystyna Michalak, Dean G. Tang, Kim-Anh Nguyen, Philip Lacap, John Kim, P J McLaren

Bibliographic record

VenueClinical Chemistry · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Biosensing Techniques and Applications
Canadian institutionsPublic Health Agency of Canada
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)Extraction (chemistry)Whole bloodVirologyMedicineChromatographyChemistryImmunology

Abstract

fetched live from OpenAlex

Abstract Background Early diagnosis of human immunodeficiency virus-1 (HIV-1) and hepatitis C virus (HCV) is key to preventing viral transmission and improving linkage to treatment. Isothermal amplification methods, such as reverse transcription looped-mediated amplification (RT-LAMP), have enabled molecular diagnostics to expand beyond centralized laboratories. Despite the advances in molecular point-of-care (POC) testing, many of these tests are costly and still depend on a reliable power-source, specialized equipment, and cold-chain storage, making them impractical for resource-limited settings. To overcome these barriers, there is a need for innovative molecular diagnostics for blood-borne pathogens. Here, we propose a simple, extraction-free, portable workflow for detecting HIV-1 and HCV from whole blood within 40 minutes. Methods We developed singleplex RT-LAMP-based tests using modified published primer sets. Contrived whole blood samples containing HIV-1 or HCV virions were diluted in equal parts water and loaded directly into optimized RT-LAMP master mixes. To mitigate cold-chain storage dependence, RT-LAMP reactions were performed using a lyophilized master mix. The reactions were heated for 30 minutes using a hand-held, battery-powered heating device for simultaneous virion lysis and amplification. For simple visual detection, amplification was coupled with a lateral flow-based dipstick test. The analytical sensitivity of each detection test was evaluated using contrived whole blood samples ranging in HIV-1 and HCV 1a viral loads. Additionally, HCV detection was evaluated on genotypes 1b, 2b, and 3a. For result confirmation, a custom CRISPR-Cas12a-based assay was used to verify the presence or absence of pathogen-specific amplicons following amplification. Results The diagnostic workflow can be completed within 40 minutes, including less than 10 minutes of hands-on time. At optimal conditions, the HIV-1 and HCV 1a singleplex tests had lower limits of detections of 4.89 log10 cp/mL and 3.77 log10 IU/mL, respectively. Evaluation of the published literature showed that these viral loads are within the ranges observed during acute HIV-1 and HCV infection. HCV detection was also observed for genotypes 1b and 3a, albeit at a lower sensitivity than genotype 1a. No detection was observed for genotype 2b, presumably due to the lower viral loads of the samples. No cross-reactivity between the two tests was observed. Conclusions Our proposed workflow allows for rapid detection of blood-borne pathogens without the need for complex equipment or cold-chain storage, showing potential for application in resource-limited settings. Additional validation within a clinical setting using fingerstick blood remains to be tested.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.004

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 head0.011
GPT teacher head0.310
Teacher spread0.300 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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