Detection of leukemia markers using long-range surface plasmon waveguides functionalized with Protein G
Bibliographic record
Abstract
A novel optical biosensor based on long-range surface plasmon-polariton (LRSPP) waveguides is demonstrated for the detection of leukemia markers in patient serum using a functionalization strategy based on Protein G. The sensor consists of thin straight Au waveguides (5 μm × 35 nm × 3.2 mm) embedded in fluoropolymer CYTOP™ with a fluidic channel etched into the top cladding. B-cell leukemia is characterized by a high B-cell count and abnormal distribution of immunoglobulin G kappa (IgGκ) and lambda (IgGλ) light chains in serum. The detection of leukemic abnormalities in serum was performed based on determining IgGκ-to-IgGλ ratios (κ : λ). Three patient sera were tested: high kappa (HKS, κ : λ ~12.7 : 1), high lambda (HLS, λ : κ ~6.9 : 1) and normal (control) sera (NS, κ : λ ~1.7 : 1). Au waveguides were functionalized with Protein G and two complementary immobilization approaches were investigated: a) the reverse approach, where the Protein G surface is functionalized with patient serum and then tested against goat anti-human IgG light chains in buffer, and b) the direct approach, where the Protein G surface is functionalized with goat anti-human IgGs first and then tested against patient serum. The reverse approach was found to be more effective and robust because Protein G-functionalized surface performs as an "immunological filter" by capturing primarily IgGs out of the pool of serum proteins. For the reverse approach, the ratios measured were 3.7 : 1(κ : λ), 9.7 : 1(λ : κ) and 1.9 : 1(κ : λ) for HKS, HLS and NS, respectively, which compare favorably with corresponding protein densitometry measurements. The respective ratios for the direct approach were 2.6 : 1(κ : λ), 2.6 : 1(λ : κ) and 1.7 : 1(κ : λ). The binding strength and cross-reactivity of goat anti-human IgGs light chains were also determined using pure solutions. The LRSPP biosensor along with the innovative "reverse approach" can provide a low-cost and compact solution to B-cell leukemia screening.
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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 | 0.000 | 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) | 0.000 | 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".