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Record W4389573987 · doi:10.3390/diagnostics13243639

Evaluation of a Point-of-Need Molecular Diagnostic Tool Coupled with Rapid DNA Extraction Methods for Visceral Leishmaniasis

2023· article· en· W4389573987 on OpenAlexfundno aff
Prakash Ghosh, Rajashree Chowdhury, Khaledul Faisal, Md Anik Ashfaq Khan, Faria Hossain, Md. Abu Rahat, Md. Arko Ayon Chowdhury, Nishad Tasnim Mithila, Mostafa Kamal, Shomik Maruf, Rupen Nath, Rea Maja Kobialka, Arianna Ceruti, Mary Cameron, Malcolm S. Duthie, Ahmed Abd El Wahed, Dinesh Mondal

Bibliographic record

VenueDiagnostics · 2023
Typearticle
Languageen
FieldMedicine
TopicResearch on Leishmaniasis Studies
Canadian institutionsnot available
FundersGlobal Affairs CanadaDepartment for International DevelopmentInternational Centre for Diarrhoeal Disease Research, BangladeshStyrelsen för Internationellt Utvecklingssamarbete
KeywordsRecombinase Polymerase AmplificationDNA extractionVisceral leishmaniasisMolecular biologyPolymerase chain reactionDNAReal-time polymerase chain reactionNucleic acidBiologyAssay sensitivityLeishmania donovaniLoop-mediated isothermal amplificationLeishmaniasisMedicineImmunologyPathologyGeneticsGene

Abstract

fetched live from OpenAlex

A rapid, cost-effective, and simple nucleic acid isolation technique coupled with a point-of-need DNA amplification assay is a desirable goal for programmatic use. For diagnosis of Visceral Leishmaniasis (VL), Recombinase Polymerase Amplification (RPA) rapid tests for the detection of Leishmania DNA are versatile and have operational advantages over qPCR. To facilitate the delivery of the RPA test at point-of-need for VL diagnosis, we compared two rapid DNA extraction methods, SwiftDx (SX) and an in-house Boil and Spin (BS) method, coupled with RPA amplification, versus more widely used methods for DNA extraction and amplification, namely Qiagen (Q) kits and qPCR, respectively. A total of 50 confirmed VL patients and 50 controls, matched for age and gender, were recruited from Mymensingh, Bangladesh, a region highly endemic for VL. Blood samples were collected from each participant and DNA was extracted using Q, SX and BS methods. Following DNA extraction, qPCR and RPA assays were performed to detect L. donovani in downstream analysis. No significant differences in sensitivity of the RPA assay were observed between DNA extraction methods, 94.00% (95% CI: 83.45–98.75%), 90% (95% CI: 78.19–96.67%), and 88% (95% CI: 75.69–95.47%) when using Q, SX, and BS, respectively. Similarly, using qPCR, no significant differences in sensitivity were obtained when using Q or SX for DNA extraction, 94.00% (95% CI: 83.45–98.75%) and 92.00% (80.77–97.78%), respectively. It is encouraging that RPA and qPCR showed excellent agreement (k: 0.919–0.980) when different extraction methods were used and that the DNA impurities using BS had no inhibitory effect on the RPA assay. Furthermore, significantly higher DNA yields were obtained using SX and BS versus Q; however, a significantly higher parasite load was detected using qPCR when DNA was extracted using Q versus SX. Considering the cost, execution time, feasibility, and performance of RPA assay, rapid extraction methods such as the Boil and Spin technique appear to have the potential for implementation in resource-limited endemic settings. Further clinical research is warranted prior to broader application.

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)0.004
metaresearch head score (Gemma)0.063
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.609
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.063
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.065
GPT teacher head0.420
Teacher spread0.355 · 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 designOther design
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

Citations4
Published2023
Admission routes1
Has abstractyes

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