At the crossroads of homoeostasis and disease: roles of the PACS proteins in membrane traffic and apoptosis
Bibliographic record
Abstract
The endomembrane system in mammalian cells has evolved over the past two billion years from a simple endocytic pathway in a single-celled primordial ancestor to complex networks supporting multicellular structures that form metazoan tissue and organ systems. The increased organellar complexity of metazoan cells requires additional trafficking machinery absent in yeast or other unicellular organisms to maintain organ homoeostasis and to process the signals that control proliferation, differentiation or the execution of cell death programmes. The PACS (phosphofurin acidic cluster sorting) proteins are one such family of multifunctional membrane traffic regulators that mediate organ homoeostasis and have important roles in diverse pathologies and disease states. This review summarizes our current knowledge of the PACS proteins, including their structure and regulation in cargo binding, their genetics, their roles in secretory and endocytic pathway traffic, interorganellar communication and how cell-death signals reprogramme the PACS proteins to regulate apoptosis. We also summarize our current understanding of how PACS genes are dysregulated in cancer and how viral pathogens ranging from HIV-1 to herpesviruses have evolved to usurp the PACS sorting machinery to promote virus assembly, viral spread and immunoevasion.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".