The phosphoinositide regulatory network in Trypanosoma brucei: Implications for cell-wide regulation in eukaryotes
Bibliographic record
Abstract
The unicellular eukaryote Trypanosoma brucei undergoes extensive cellular and developmental changes during its life cycle. These include regulation of mammalian stage surface antigen variation and surface composition changes between life stages; switching between glycolysis and oxidative phosphorylation; differential mRNA editing; and changes in posttranscriptional gene expression, protein trafficking, organellar function, and cell morphology. These diverse events are coordinated and controlled throughout parasite development, maintained in homeostasis at each life stage, and are essential for parasite survival in both the host and insect vector. Described herein are the enzymes and metabolites of the phosphatidylinositol (PI) cellular regulatory network, its integration with other cellular regulatory systems that collectively control and coordinate these numerous cellular processes, including cell development and differentiation and the many associated complex processes in multiple subcellular compartments. We conclude that this regulation is the product of the organization of these enzymes within the cellular architecture, their activities, metabolite fluxes, and responses to environmental changes via signal transduction and other processes. We describe a paradigm for how these enzymes and metabolites could function to control and coordinate multiple cellular functions. The significance of the PI system's regulatory functions in single-celled eukaryotes to metazoans and their potential as chemotherapeutic targets are indicated.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".