The growing world of small heat shock proteins: from structure to functions
Bibliographic record
Abstract
Small heat shock proteins (sHSPs) are present in all kingdoms of life and play fundamental roles in cell biology. sHSPs are key components of the cellular protein quality control system, acting as the first line of defense against conditions that affect protein homeostasis and proteome stability, from bacteria to plants to humans. sHSPs have the ability to bind to a large subset of substrates and to maintain them in a state competent for refolding or clearance with the assistance of the HSP70 machinery. sHSPs participate in a number of biological processes, from the cell cycle, to cell differentiation, from adaptation to stressful conditions, to apoptosis, and, even, to the transformation of a cell into a malignant state. As a consequence, sHSP malfunction has been implicated in abnormal placental development and preterm deliveries, in the prognosis of several types of cancer, and in the development of neurological diseases. Moreover, mutations in the genes encoding several mammalian sHSPs result in neurological, muscular, or cardiac age-related diseases in humans. Loss of protein homeostasis due to protein aggregation is typical of many age-related neurodegenerative and neuromuscular diseases. In light of the role of sHSPs in the clearance of un/misfolded aggregation-prone substrates, pharmacological modulation of sHSP expression or function and rescue of defective sHSPs represent possible routes to alleviate or cure protein conformation diseases. Here, we report the latest news and views on sHSPs discussed by many of the world's experts in the sHSP field during a dedicated workshop organized in Italy (Bertinoro, CEUB, October 12-15, 2016).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".