A Novel Applicator Design for Contact-Free Delivery of Aqueous Reagent to Individual Biopsies in a Tissue Microarray
Bibliographic record
Abstract
The use of molecular techniques to inform diagnosis, prognosis, and treatment design will play an important role in the future of medicine. Each new test, however, represents a new cost to the health care system, and significant effort is required to move new techniques to the clinical setting in the most cost-effective and efficient manner. Consequently, there is a compelling need for technological improvements that will facilitate clinical application of novel assays, by reducing cost and complexity in implementation. This is particularly important in cancer pathology. Here, we present a novel applicator technology that enables staining of individual biopsies in a tissue microarray (TMA) to provide low-cost, multiplexed biomarker testing at the level of intact tissue. The applicator is designed to deliver tens of nanoliters of aqueous reagent to arrayed tissue biopsies kept under a layer of oil-based Liquid Coverslip without contacting the biopsies. A pin consisting of concentric stainless steel electrodes separated by a hydrophobic insulator provides a balance between hydrophobicity and hydrophilicity to hold a reagent droplet on the tip of the pin, whereas a small electrical current passed through the droplet spanning the electrodes is used for drop sensing. This design is more amenable to repeatable manufacturing than a previous prototype, which in initial testing demonstrated successful immunohistochemical and in situ hybridization staining of individual biopsies in a TMA, but was difficult to produce. This new design was tested to investigate the factors affecting its operation, in terms of the volume of reagent picked up and its ability to successfully deliver reagent to the biopsies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".