Components of a mammalian protein disaggregation/refolding machine are targeted to nuclear speckles following thermal stress in differentiated human neuronal cells
Bibliographic record
Abstract
Heat shock proteins (Hsps) are a set of highly conserved proteins involved in cellular repair and protective mechanisms. They counter protein misfolding and aggregation that are characteristic features of neurodegenerative diseases. Hsps act co-operatively in disaggregation/refolding machines that assemble at sites of protein misfolding and aggregation. Members of the DNAJ (Hsp40) family act as "holdases" that detect and bind misfolded proteins, while members of the HSPA (Hsp70) family act as "foldases" that refold proteins to biologically active states. HSPH1 (Hsp105α) is an important additional member of the mammalian disaggregation/refolding machine that acts as a disaggregase to promote the dissociation of aggregated proteins. Components of a disaggregation/refolding machine were targeted to nuclear speckles after thermal stress in differentiated human neuronal SH-SY5Y cells, namely: HSPA1A (Hsp70-1), DNAJB1 (Hsp40-1), DNAJA1 (Hsp40-4), and HSPH1 (Hsp105α). Nuclear speckles are rich in RNA splicing factors, and heat shock disrupts RNA splicing which recovers after stressful stimuli. Interestingly, constitutively expressed HSPA8 (Hsc70) was also targeted to nuclear speckles after heat shock with elements of a disaggregation/refolding machine. Hence, neurons have the potential to rapidly assemble a disaggregation/refolding machine after cellular stress using constitutively expressed Hsc70 without the time lag needed for synthesis of stress-inducible Hsp70. Constitutive Hsc70 is abundant in neurons in the mammalian brain and has been proposed to play a role in pre-protecting neurons from cellular stress.
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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 | 0.000 | 0.000 |
| 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".