Composition and origin of lung fluid proteome in premature infants and relationship to respiratory outcome
Bibliographic record
Abstract
BACKGROUND: Infants born at extremely low gestational age are at high risk for bronchopulmonary dysplasia and continuing lung disease. There are no early clinical biomarkers for pulmonary outcome and limited therapeutic interventions. OBJECTIVES: We performed global proteomics of premature infant tracheal aspirate (TA) and plasma to determine the composition and source of lung fluid proteins and to identify potential biomarkers of respiratory outcome. METHODS: TA samples were collected from intubated infants in the TOLSURF cohort before and after nitric oxide treatment, and plasma was collected from NO CLD infants. Protein abundance was assayed by HPLC/tandem mass spectrometry and Protein Prospector software. mRNA abundance in mid-gestation fetal lung was assessed by RNA sequencing. Pulmonary morbidity was defined as a need for ventilatory support at term and during the first year. RESULTS: Abundant TA proteins included albumin, hemoglobin, and actin-related proteins. 96 of 137 detected plasma proteins were present in TA (r = 0.69, p<0.00001). Based on lung RNAseq data, ~88% of detected TA proteins in injured infant lung are derived at least in part from lung epithelium with overrepresentation in categories of cell membrane/secretion and stress/inflammation. Comparing 37 infants at study enrollment (7-14 days) who did or did not develop persistent pulmonary morbidity, candidate biomarkers of both lung (eg., annexin A5) and plasma (eg., vitamin D-binding protein) origin were identified. Notably, levels of free hemoglobin were 2.9-fold (p = 0.03) higher in infants with pulmonary morbidity. In time course studies, hemoglobin decreased markedly in most infants after enrollment coincident with initiation of inhaled nitric oxide treatment. CONCLUSIONS: We conclude that both lung epithelium and plasma contribute to the lung fluid proteome in premature infants with lung injury. Early postnatal elevation of free hemoglobin and heme, which are both pro-oxidants, may contribute to persistent lung disease by depleting nitric oxide and increasing oxidative/nitrative stress.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".