Small heat shock proteins: multifaceted proteins with important implications for life
Bibliographic record
Abstract
Small Heat Shock Proteins (sHSPs) evolved early in the history of life; they are present in archaea, bacteria, and eukaryota. sHSPs belong to the superfamily of molecular chaperones: they are components of the cellular protein quality control machinery and are thought to act as the first line of defense against conditions that endanger the cellular proteome. In plants, sHSPs protect cells against abiotic stresses, providing innovative targets for sustainable agricultural production. In humans, sHSPs (also known as HSPBs) are associated with the development of several neurological diseases. Thus, manipulation of sHSP expression may represent an attractive therapeutic strategy for disease treatment. Experimental evidence demonstrates that enhancing the chaperone function of sHSPs protects against age-related protein conformation diseases, which are characterized by protein aggregation. Moreover, sHSPs can promote longevity and healthy aging in vivo. In addition, sHSPs have been implicated in the prognosis of several types of cancer. Here, sHSP upregulation, by enhancing cellular health, could promote cancer development; on the other hand, their downregulation, by sensitizing cells to external stressors and chemotherapeutics, may have beneficial outcomes. The complexity and diversity of sHSP function and properties and the need to identify their specific clients, as well as their implication in human disease, have been discussed by many of the world's experts in the sHSP field during a dedicated workshop in Québec City, Canada, on 26-29 August 2018.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".