Defining The Role of Primary Cilia on Skin Derived Precursors.
Bibliographic record
Abstract
Isolated in 2001, Skin Derived Precursors (SKPs) represent a novel population of multipotent stem cells 1,2 residing at the base of hair follicle where they play a key role in defining the physiology and regeneration capacity of hair follicles and skin (Biernaskie et al. 2009). In order to understand how SKPs behavior is regulated in the skin, we asked whether primary cilia, microtubule bundles projected from the cell surface that transmit chemical signals between cells 4 , are present in the dermal papilla and dermal sheath in-vivo and in the population of isolated SKPs. In our investigation, we performed immunohistochemistry for acetylated tubulin and showed that SKPs do have cilia. We then tested whether these cilia can be elongated following treatments of lithium chloride on these dermal precursors. We then asked whether elongation of cilia has an effect on the self-renewal capacity of SKPs and whether drugs elongating cilia can work synergistically with Platelet Derived Growth Factor (PDGF), a growth factor that we have previously shown to improve cell growth and cell division. Experiments assessing the self-renewal capacity of SKPs suggested significant increase in the diameter and the number of spherical presence when treated with lithium chloride and when lithium chloride is added in combination with PDGF β when compared to PDGFβ alone. This suggests that signaling in cilia may influence PDGF signals causing an enhanced effect on SKP proliferation. Further experiments including knocking down primary cilia by blocking the transcription of ciliary protein using shRNA and in-vivo transplantations of lithium chloride and PDGF treated SKPs in a hair follicle formation assays will be executed to understand the key roles of primary cilia on SKPs. These studies will ultimately aim to answer whether drugs affecting cilia can function as potential therapeutic targets for autologous adult stem cell based therapies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".