Design and Characterization of Protein E-PilA, a Candidate Fusion Antigen for Nontypeable Haemophilus influenzae Vaccine
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
(NTHi) is a pathogen known for being a frequent cause of acute otitis media in children and respiratory tract infections in adults with chronic obstructive pulmonary disease. In the present study, a vaccine antigen based on the fusion of two known NTHi adhesive proteins, protein E (PE) and a pilin subunit (PilA), was developed. The quality of the combined antigen was investigated through functional, biophysical, and structural analyses. It was shown that the PE and PilA individual structures are not modified in the PE-PilA fusion and that PE-PilA assembles as a dimer in solution, reflecting PE dimerization. PE-PilA was found to bind vitronectin by enzyme-linked immunosorbent assay, as isolated PE does. Disulfide bridges were conserved and homogeneous, which was determined by peptide mapping and top-down analysis of PE, PilA, and PE-PilA molecules. Finally, the PE-PilA crystal showed a PE entity with a three-dimensional (3D) structure similar to that of the recently published isolated PE, while the structure of the PilA entity was similar to that of a 3D model elaborated from two other type 4 pilin subunits. Taken together, our observations suggest that the two tethered proteins behave independently within the chimeric molecule and display structures similar to those of the respective isolated antigens, which are important characteristics for eliciting optimal antibody-mediated immunity. PE and PilA can thus be further developed as a single fusion protein in a vaccine perspective, in the knowledge that tethering the two antigens does not perceptibly compromise the structural attributes offered by the individual antigens.
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.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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