Dynamics of the association of heat shock protein HSPA6 (Hsp70B’) and HSPA1A (Hsp70–1) with stress-sensitive cytoplasmic and nuclear structures in differentiated human neuronal cells
Bibliographic record
Abstract
Heat shock proteins (Hsps) are cellular repair agents that counter the effects of protein misfolding that is a characteristic feature of neurodegenerative diseases. HSPA1A (Hsp70-1) is a widely studied member of the HSPA (Hsp70) family. The little-studied HSPA6 (Hsp70B') is present in the human genome and absent in mouse and rat; hence, it is missing in current animal models of neurodegenerative diseases. Differentiated human neuronal SH-SY5Y cells were employed to compare the dynamics of the association of YFP-tagged HSPA6 and HSPA1A with stress-sensitive cytoplasmic and nuclear structures. Following thermal stress, live-imaging confocal microscopy and Fluorescence Recovery After Photobleaching (FRAP) demonstrated that HSPA6 displayed a prolonged and more dynamic association, compared to HSPA1A, with centrioles that play critical roles in neuronal polarity and migration. HSPA6 and HSPA1A also targeted nuclear speckles, rich in RNA splicing factors, and the granular component of the nucleolus that is involved in rRNA processing and ribosomal subunit assembly. HSPA6 and HSPA1A displayed similar FRAP kinetics in their interaction with nuclear speckles and the nucleolus. Subsequently, during the recovery from neuronal stress, HSPA6, but not HSPA1A, localized with the periphery of nuclear speckles (perispeckles) that have been characterized as transcription sites. The stress-induced association of HSPA6 with perispeckles displayed the greatest dynamism compared to the interaction of HSPA6 or HSPA1A with other stress-sensitive cytoplasmic and nuclear structures. This suggests involvement of HSPA6 in transcriptional recovery of human neurons from cellular stress that is not apparent for HSPA1A.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".