Validation of endotoxin‐core antibodies in dried blood spots as a measure of environmental enteropathy and intestinal permeability
Bibliographic record
Abstract
OBJECTIVE: To validate a method for measuring endotoxin-core antibodies (EndoCAb) from dried blood spots (DBS)-drops of capillary whole blood collected and dried on filter paper-as an indicator of environmental enteropathy (EE) in infancy and early childhood. METHODS: A commercially available enzyme immunoassay kit was adapted for use with DBS, with optimized steps for sample elution. Technical validation included analysis of linearity/recovery, precision and reliability, lower limit of detection, and correspondence between matched plasma and DBS samples. Validation in a field-based setting was implemented with samples from Peruvian infants (n = 82; age = 2-33 months) collected at two time points six months apart. RESULTS: = 0.93, P < .001). The lower limit of detection was found to be 0.01 GMU/mL. Interassay coefficient of variation (CV) was 10.9% and 8.06% for low and high controls, respectively. Mean intra-assay CVs were 3.22% and 1.83%, respectively. In a sample of Peruvian infants, EndoCAb levels increased with age as expected (P < .001). Age explained nearly 34.6% of the variance in EndoCAb across the sample. CONCLUSION: These findings demonstrate the validity and feasibility of measuring EndoCAb in remote field settings using minimally invasive DBS sampling.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".