Assessment of a multisite standardized biospecimen collection protocol for immune phenotyping in neurodevelopmental disorders
Bibliographic record
Abstract
Multisite collection and preservation of peripheral blood mononuclear cells (PBMCs) for centralized analysis is an indispensable strategy for large cohort immune phenotyping studies. However, the absence of cross-site standardized protocols introduces unnecessary sample variance. Here we describe the protocol implemented by the Province of Ontario Neurodevelopmental Disorders (POND) Network's immune platform for the multisite collection, processing, and cryopreservation of PBMCs. We outline quality control standards and evaluate the performance of our PBMC processing and storage protocol. We also describe the Child Immune History Questionnaire results, an assessment tool evaluating pre-existing immune conditions in children with neurodevelopmental disorders (NDDs). Cell viability was assessed in samples from 178 participants based on strict quality control criteria. Overall, 83.1% of samples passed quality control standards. Samples collected and processed at the same site had higher quality control pass rates than samples that were collected and subsequently shipped to another site for processing. We investigated if freezer time impacted sample viability and found no difference in mean freezer time between samples that passed and failed quality control. The Child Immune History Questionnaire had a response rate of 87.1%. The described protocol produces viable samples that may be used in future immune phenotyping experiments.
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 | 0.056 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".