Proteomic discovery in sickle cell disease: Elevated neurogranin levels in children with sickle cell disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Sickle cell disease (SCD) is an inherited hemoglobinopathy that causes stroke and silent cerebral infarct (SCI). Our aim was to identify markers of brain injury in SCD. EXPERIMENTAL DESIGN: Plasma proteomes were analyzed using a sequential separation approach of hemoglobin (Hb) and top abundant plasma protein depletion, followed by reverse phase separation of intact proteins, trypsin digestion, and tandem mass spectrometry. We compared plasma proteomes of children with SCD with and without SCI in the Silent Cerebral Infarct Multi-Center Clinical Trial (SIT Trial) to age-matched, healthy non-SCD controls. RESULTS: From the SCD group, 1172 proteins were identified. Twenty-five percent (289/1172) were solely in the SCI group. Twenty-five proteins with enriched expression in the human brain were identified in the SCD group. Neurogranin (NRGN) was the most abundant brain-enriched protein in plasma of children with SCD. Using a NRGN sandwich immunoassay and SIT Trial samples, median NRGN levels were higher at study entry in children with SCD (0.28 ng/mL, N = 100) compared to control participants (0.12 ng/mL, N = 25, p < 0.0004). CONCLUSIONS AND CLINICAL RELEVANCE: NRGN levels are elevated in children with SCD. NRGN and other brain-enriched plasma proteins identified in plasma of children with SCD may provide biochemical evidence of neurological injury.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it