Extracellular chaperone networks and the export of J-domain proteins
Bibliographic record
Abstract
An extracellular network of molecular chaperones protects a diverse array of proteins that reside in or pass through extracellular spaces. Proteins in the extracellular milieu face numerous challenges that can lead to protein misfolding and aggregation. As a checkpoint for proteins that move between cells, extracellular chaperone networks are of growing clinical relevance. J-domain proteins (JDPs) are ubiquitous molecular chaperones that are known for their essential roles in a wide array of fundamental cellular processes through their regulation of heat shock protein 70s. As the largest molecular chaperone family, JDPs have long been recognized for their diverse functions within cells. Some JDPs are elegantly selective for their "client proteins," some do not discriminate among substrates and others act cooperatively on the same target. The realization that JDPs are exported through both classical and unconventional secretory pathways has fueled investigation into the roles that JDPs play in protein quality control and intercellular communication. The proposed functions of exported JDPs are diverse. Studies suggest that export of DnaJB11 enhances extracellular proteostasis, that intercellular movement of DnaJB1 or DnaJB6 enhances the proteostasis capacity in recipient cells, whereas the import of DnaJB8 increases resistance to chemotherapy in recipient cancer cells. In addition, the export of DnaJC5 and concurrent DnaJC5-dependent ejection of dysfunctional and aggregation-prone proteins are implicated in the prevention of neurodegeneration. This review provides a brief overview of the current understanding of the extracellular chaperone networks and outlines the first wave of studies describing the cellular export of JDPs.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| 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 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".