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Record W2127697580 · doi:10.1186/1475-2875-13-179

A lab-on-chip for malaria diagnosis and surveillance

2014· article· en· W2127697580 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMalaria Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsCanadian Blood ServicesProvincial Laboratory of Public HealthUniversity of Alberta
FundersAlberta InnovatesGrand Challenges Canada
KeywordsMalariaPlasmodium falciparumParasitologyCommunicable diseaseRapid diagnostic testPlasmodium vivaxPlasmodium (life cycle)MedicineDiagnostic testAmpliconComputer sciencePathologyBiologyVeterinary medicinePolymerase chain reactionPublic healthParasite hosting

Abstract

fetched live from OpenAlex

BACKGROUND: Access to timely and accurate diagnostic tests has a significant impact in the management of diseases of global concern such as malaria. While molecular diagnostics satisfy this need effectively in developed countries, barriers in technology, reagent storage, cost and expertise have hampered the introduction of these methods in developing countries. In this study a simple, lab-on-chip PCR diagnostic was created for malaria that overcomes these challenges. METHODS: The platform consists of a disposable plastic chip and a low-cost, portable, real-time PCR machine. The chip contains a desiccated hydrogel with reagents needed for Plasmodium specific PCR. Chips can be stored at room temperature and used on demand by rehydrating the gel with unprocessed blood, avoiding the need for sample preparation. These chips were run on a custom-built instrument containing a Peltier element for thermal cycling and a laser/camera setup for amplicon detection. RESULTS: This diagnostic was capable of detecting all Plasmodium species with a limit of detection for Plasmodium falciparum of 2 parasites/μL of blood. This exceeds the sensitivity of microscopy, the current standard for diagnosis in the field, by ten to fifty-fold. In a blind panel of 188 patient samples from a hyper-endemic region of malaria transmission in Uganda, the diagnostic had high sensitivity (97.4%) and specificity (93.8%) versus conventional real-time PCR. The test also distinguished the two most prevalent malaria species in mixed infections, P. falciparum and Plasmodium vivax. A second blind panel of 38 patient samples was tested on a streamlined instrument with LED-based excitation, achieving a sensitivity of 96.7% and a specificity of 100%. CONCLUSIONS: These results describe the development of a lab-on-chip PCR diagnostic from initial concept to ready-for-manufacture design. This platform will be useful in front-line malaria diagnosis, elimination programmes, and clinical trials. Furthermore, test chips can be adapted to detect other pathogens for a differential diagnosis in the field. The flexibility, reliability, and robustness of this technology hold much promise for its use as a novel molecular diagnostic platform in developing countries.

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.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.284
Teacher spread0.265 · 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