Sensing Dying Cells in Health and Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Kidney injury molecule-1 (KIM-1), also known as T-cell Ig and mucin domain-1 (TIM-1), is a widely recognized biomarker for AKI, but its biological function is less appreciated. KIM-1/TIM-1 belongs to the T-cell Ig and mucin domain family of conserved transmembrane proteins, which bear the characteristic six-cysteine Ig-like variable domain. The latter enables binding of KIM-1/TIM-1 to its natural ligand, phosphatidylserine, expressed on the surface of apoptotic cells and necrotic cells. KIM-1/TIM-1 is expressed in a variety of tissues and plays fundamental roles in regulating sterile inflammation and adaptive immune responses. In the kidney, KIM-1 is upregulated on injured renal proximal tubule cells, which transforms them into phagocytes for clearance of dying cells and helps to dampen sterile inflammation. TIM-1, expressed in T cells, B cells, and natural killer T cells, is essential for cell activation and immune regulatory functions in the host. Functional polymorphisms in the gene for KIM-1/TIM-1, HAVCR1 , have been associated with susceptibility to immunoinflammatory conditions and hepatitis A virus-induced liver failure, which is thought to be due to a differential ability of KIM-1/TIM-1 variants to bind phosphatidylserine. This review will summarize the role of KIM-1/TIM-1 in health and disease and its potential clinical applications as a biomarker and therapeutic target in humans.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it