Structure, interaction, and nervous connectivity of beta cell primary cilia
Bibliographic record
Abstract
Primary cilia are sensory organelles present in many cell types. Based on an array of microtubules termed axoneme they form a specialized membrane compartment partaking in various signaling processes. Primary cilia of pancreatic islet beta cells play a role in autocrine and paracrine signaling and are linked to diabetes. Yet, the structural basis for their functions is unclear. We present three-dimensional reconstructions of complete mouse and human beta cell cilia, revealing a disorganized 9+0 axoneme structure. Within the islet, cilia are spatially confined within deep ciliary pockets or squeezed into narrow extracellular spaces between adjacent cells. Beta and alpha cell cilia physically interact with neighboring islet cells pushing and strongly bending their plasma membranes. Furthermore, beta cells can contain multiple cilia that can meet with other islet cell cilia in the extracellular space. Additionally, beta cell cilia establish connections with islet-projecting nerves. These findings highlight the pivotal role of beta cell primary cilia in islet cell connectivity, pointing at their potential functional role in integrating islet intrinsic and extrinsic signals. These novel insights contribute to understanding their significance in health and diabetes.
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 | 0.000 |
| 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".