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Proteomics in the Study of Qualitative Platelet Defects: Validation of the Approach in the Gray Platelet Syndrome and Quebec Platelet Disorder.

2007· article· en· W2991848929 on OpenAlexaffabout
Raj S. Kasthuri, Lorraine Anderson, LeeAnn Higgins, Jorge Di Paola, Georges E. Rivard, Catherine P.M. Hayward, Nigel S. Key

Bibliographic record

VenueBlood · 2007
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsMcMaster UniversityCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsPlateletProteomeBlood Platelet DisordersProteomicsVon Willebrand factorPlatelet disorderBiologyMedicineInternal medicinePathologyImmunologyBioinformaticsBiochemistryPlatelet aggregation

Abstract

fetched live from OpenAlex

Abstract Qualitative platelet defects are a heterogeneous group of disorders characterized by abnormal platelet function. Currently available laboratory assays lack sensitivity and specificity for detecting Storage Pool and Platelet Secretion defects. The Gray Platelet Syndrome (GPS) is an autosomal recessive disorder characterized by a decrease or absence of alpha granule contents. The Quebec Platelet Disorder (QPD) results from proteolysis of alpha granule proteins due to increased amounts of platelet urokinase. A decrease or deficiency of multimerin is characteristic. Proteomics is a rapidly developing field with great promise in the study of pathophysiology and biomarker development. Recent advances have made measurement of relative protein abundance in multiple samples feasible. We used one such approach, “isotope Tagging for Relative and Absolute Quantitation” (iTRAQ) to characterize the platelet proteome of healthy volunteers and patients with GPS and QPD. iTRAQ allows analysis of up to 4 different samples simultaneously, and differences in protein abundance as low as 20% are reliably detected. The platelet proteomes of 4 healthy volunteers were analyzed. Platelet proteome analysis of study patients was as follows; 2 GPS patients compared to 2 controls; 2 heterozygous GPS patients compared to a homozygote and a control; and 3 QPD patients compared to a control. For comparison, platelet proteins were grouped by location into 3 groups - receptor, alpha granule and cytoskeletal proteins. The results are shown in the figure. Protein abundance in healthy volunteers was very consistent, with inter-individual variability ≤ 20%. Distribution of receptor and cytoskeletal proteins in GPS patients mirrored the controls, but alpha granule proteins were significantly decreased as expected. Comparison of homozygous to heterozygous GPS platelets showed this to be true only in the homozygotes, again, as expected (figure inset). Variable decreases in alpha granule proteins were observed in QPD patients but this was less profound. Multimerin was detected in QPD patients, but at levels significantly lower than controls. While urokinase was not detected in QPD platelets in this study, it was detected in a parallel study evaluating platelet releasates. The iTRAQ technique was reproducible and yielded consistent results, but currently is a relatively expensive and time-consuming approach. In summary, our results suggest that the platelet proteome is tightly regulated and very stable in healthy individuals. A significant decrease in alpha granule proteins was noted in patients with GPS but this was less remarkable in the QPD group, probably because peptides resulting from urokinase-mediated proteolysis are still labeled and quantified. Figure Figure

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score0.634

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.025
GPT teacher head0.300
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes2
Has abstractyes

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