Human fibrocytes coexpress thyroglobulin and thyrotropin receptor
Bibliographic record
Abstract
Thyroglobulin (Tg) is the macromolecular precursor of thyroid hormones and is thought to be uniquely expressed by thyroid epithelial cells. Tg and the thyroid-stimulating hormone receptor (TSHR) are targets for autoantibody generation in the autoimmune disorder Graves disease (GD). Fully expressed GD is characterized by thyroid overactivity and orbital tissue inflammation and remodeling. This process is known as thyroid-associated ophthalmopathy (TAO). Early reports suggested that in TAO, both Tg and TSHR become overexpressed in orbital tissues. Previously, we found that CD34(+) progenitor cells, known as fibrocytes, express functional TSHR, infiltrate the orbit, and comprise a large subset of orbital fibroblasts in TAO. We now report that fibrocytes also express Tg, which resolves as a 305-kDa protein on Western blots. It can be immunoprecipitated with anti-Tg Abs. Further, (125)iodine and [(35)S]methionine are incorporated into Tg expressed by fibrocytes. De novo Tg synthesis is attenuated with a specific small interfering RNA targeting the protein. A fragment of the Tg gene promoter fused to a luciferase reporter exhibits substantial activity when transfected into fibrocytes. Unlike fibrocytes, GD orbital fibroblasts, which comprise a mixture of CD34(+) and CD34(-) cells, express much lower levels of Tg and TSHR. When sorted into pure CD34(+) and CD34(-) subsets, Tg and TSHR mRNA levels become substantially higher in CD34(+) cells. These findings indicate that human fibrocytes express multiple "thyroid-specific" proteins, the levels of which are reduced after they infiltrate tissue. Our observations establish the basis for Tg accumulation in orbital GD.
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) | 0.003 | 0.002 |
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".