Influence of electric field on IgG positioning and its immobilization for solid biosensing substrates
Bibliographic record
Abstract
Abstract Most of the proteins are polar by their structural configuration, their stereochemistry entails overall charge of the molecule. In this study, Immunoglobulin G (IgG) is evaluated for its dipolar nature. An exclusive immunoassay pattern is designed to validate the idea by controlling the IgG orientation with external application of the electric field (EF). It includes mathematical estimations of the torque produced and the EF strength required to orient a single IgG molecule in normal room temperatures.In current pandemic scenario, the necessity of tests that provide clinical analysis of an individual is inevitable; thereby the use of immunoassay based rapid invitro diagnostic (IVD) test devices have become the most sort after point of care devices. The device configured in this study also explains the IgG orientation and immobilization post influence of EF in two dimensional geometry of flowchannel; and how it provides a platform for detection of the analytes with higher sensitivity. Therefore, this is also an attempt towards miniaturization of biosensor and to improve the signal intensity while optimizing the signal to noise ratio (SNR). Imparting qualities that suffice a stable, robust, portable sensing platform for a biosensor remains an added objective of this research.
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 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".