Development of a novel <scp>immunoFET</scp> technology‐based <scp>POC</scp> assay for detection of <i>Leishmania donovani</i> and <i>Leishmania major</i>
Bibliographic record
Abstract
Abstract Leishmaniasis is considered as one of the 20 neglected tropical diseases. Current methods of leishmanial diagnosis depend on conventional laboratory‐based techniques, which are time‐consuming, costly and require special equipment and trained personnel. In this context, we aimed to provide an immuno field effect transistors (ImmunoFET) biosensor that matches the conventional standards for point‐of‐care (POC) monitoring and detection of Leishmania (L.) donovani/Leishmania major. Crude antigens prepared by repeated freeze thawing of L. donovani/L. major stationary phase promastigotes were used for ELISA and ImmunoFETs. Lesishmania‐specific antigens were serially diluted in 1× PBS from a concentration of 106–102 parasites/mL. A specific polyclonal antibody‐based sandwich ELISA was established for the detection of Leishmania antigens. An immunoFET technology‐based POC novel assay was constructed for the detection of Leishmania antigens. Interactions between antigen–antibody at the gate surface generate an electrical signal that can be measured by semiconductor field‐effect principles. Sensitivity was considered and measured as the change in current divided by the initial current. The final L. donovani/L. major crude antigen protein concentrations were measured as 1.50 mg/mL. Sandwich ELISA against the Leishmania 40S ribosomal protein detected Leishmania antigens could detect as few as 100 L. donovani/L. major parasites. An immunoFET biosensor was constructed based on the optimization of aluminium gallium nitride/gallium nitride (AlGaN/GaN) surface oxidation methods. The device surface was composed by an AlGaN/GaN wafer with a 23 nm AlGaN barrier layer, a 2 μm GaN layer on the silicon carbide (SiC) substrate for Leishmania binding, and coated with a specific antibody against the Leishmania 40S ribosomal protein, which was successfully detected at concentrations from 106 to 102 parasites/mL in 1× PBS. At the concentration of 104 parasites, the immunoFETs device sensitivities were 13% and 0.052% in the sub‐threshold regime and the saturation regime, respectively. Leishmania parasites were successfully detected by the ImmunoFET biosensor at a diluted concentration as low as 150 ng/mL. In this study, the developed ImmunoFET biosensor performed well. ImmunoFET biosensors can be used as an alternative diagnostic method to ELISA. Increasing the sensitivity and optimization of immuno‐FET biosensors might allow earlier and faster detection of leishmaniasis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".