Proteomic Profile Associated With Loss of Spontaneous Human Immunodeficiency Virus Type 1 Elite Control
Bibliographic record
Abstract
BACKGROUND: Elite controllers (ECs) spontaneously control plasma human immunodeficiency virus type 1 (HIV-1) RNA without antiretroviral therapy. However, 25% lose virological control over time. The aim of this work was to study the proteomic profile that preceded this loss of virological control to identify potential biomarkers. METHODS: Plasma samples from ECs who spontaneously lost virological control (transient controllers [TCs]), at 2 years and 1 year before the loss of control, were compared with a control group of ECs who persistently maintained virological control during the same follow-up period (persistent controllers [PCs]). Comparative plasma shotgun proteomics was performed with tandem mass tag (TMT) isobaric tag labeling and nanoflow liquid chromatography coupled to Orbitrap mass spectrometry. RESULTS: Eighteen proteins exhibited differences comparing PC and preloss TC timepoints. These proteins were involved in proinflammatory mechanisms, and some of them play a role in HIV-1 replication and pathogenesis and interact with structural viral proteins. Coagulation factor XI, α-1-antichymotrypsin, ficolin-2, 14-3-3 protein, and galectin-3-binding protein were considered potential biomarkers. CONCLUSIONS: The proteomic signature associated with the spontaneous loss of virological control was characterized by higher levels of inflammation, transendothelial migration, and coagulation. Galectin-3 binding protein could be considered as potential biomarker for the prediction of virological progression and as therapeutic target in ECs.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".