1C1400 New colorimetric sandwich assay for detection of pathogens by using antimicrobial peptides as detection probes(Proteins: Measurement, Analysis, Engineering,Oral Presentation,The 50th Annual Meeting of the Biophysical Society of Japan)
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
TheBiophysicalSociety of Japan General IncorporatedAssociation Protein folding is often hampeTed by protein aggregation, which can be prevented by a variety of chaperones in the cell.A dataset that evaluates which chaperones are effective for aggregation-prone proteins would provide an invaluable resource not on]y for understanding the roles ofchaperones, but also for broader applications in protein science and engineering.Previous]y, we conducted comprehensive aggregation analysis of rnore than 3,OOO Escheriehia co]i pToteins by using a reconstituted cell-free translation system (PURE system).which does not contain any chaperones (Niwa et al,, PNAS. 2009).A histogram of the so]ubilities revealed a c]ear bimodal distribution, implying that the many aggregation-prone proteins require ehaperones to fotd corrcctly.Then, we cemprehensively evaluuted the effects of the majoT E. coli chaperones, trigger factor, DnaKVDnalIGrpE, and GroELIGroES, on --80e aggregation-prone cytosotic E. coli proteins, using the PURE system.Statistical analyses revealed the robustness and the intriguing properties ofchaperones.The DnaK and GroEL systerns drastically increased the so]ubilities of hundreds of proteins with weak biases, whereas trigger factor had only a marginal effect on solubility.The combined addition of the chaperones was effective for a subset ofproteins that were not rescued by any single chaperone system.supponing the synergistic effect ofthese
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| 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