Molecular confirmation of alpha 1-antitrypsin deficiency in liver transplant setting: A province-wide experience
Bibliographic record
Abstract
Background and Aim: Patients suspected of Alpha 1-Antitrypsin (A1AT) abnormality based on low serum concentration are routinely confirmed through polymerase chain reaction (PCR) testing of peripheral blood. Genotyping formalin-fixed paraffin-embedded (FFPE) tissue is a novel approach that could aid in detecting variant A1AT. We performed qPCR on FFPE liver explants with Periodic Acid Schiff after Diastase (PASD)- and A1AT-positive globules to confirm and estimate the frequency of A1AT deficiency in transplant cases. Materials and Methods: Eighteen (12.68%) of 142 patients with end-stage liver disease showed PASD/A1AT positive globules. FFPE of the explants was tested through qPCR to detect S and Z alleles. A second age- and sex-matched control group consisting of five liver transplant patients with negative globules was included in the study. Results: qPCR assay was successful with all the samples meeting QC parameters. All patients included in the study elucidated Z allele variants; 2 homozygous (11.1%) and 16 heterozygous (88.9%). The control group demonstrated normal wild-type MM allele. Conclusion: Screening for A1AT deficiency using serum levels is not sufficiently sensitive to detect deficiency, especially in carriers. If A1AT testing was not performed preoperatively and the risk is high based on the PASD/A1AT-positive globules in the explants, then molecular testing of FFPE tissue can be a viable method for confirming the diagnosis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".