The Use of Androgen Receptor Amino/Carboxyl-Terminal Interaction Assays to Investigate Androgen Receptor Gene Mutations in Subjects with Varying Degrees of Androgen Insensitivity
Bibliographic record
Abstract
Five mutations in the ligand-binding domain (LBD) of the human androgen receptor (hAR) found in patients with varying degrees of androgen insensitivity syndrome (AIS) were investigated for their effects on receptor dynamics. These were Arg(871)Gly (mild), Ser(814)Asn (partial), Glu(772)Ala (partial), Val(866)Met (complete), and Arg(774)Cys (complete). Previous analysis showed that the mutant receptors exhibited near-normal kinetics, except Arg(774)Cys, which had severely reduced androgen binding, and Val(866)Met, which showed increased equilibrium dissociation constant (K(d)) and elevated dissociation rate (k) values. Ser(814)Asn exhibited ligand-selective k values, i.e. increased for dihydrotestosterone and mibolerone, but normal for methyltrenolene. Using mammalian two-hybrid assays, hAR amino/carboxyl (N/C)-terminal interactions of the mutant receptors were analyzed in the presence and absence of the hAR coactivator transcription intermediary factor 2 (TIF2). The mutations conferred decreased hAR N/C-terminal interaction, i.e. mild (approximately 1.5-fold), partial (2-fold), and complete (10-fold), that mirrored the degree of AIS. All mutant LBDs showed a 2- to 3-fold increase in N/C-terminal interactions when TIF2 was cotransfected, although of a magnitude still less than that of wild-type LBD with TIF2. The ligand-selective properties of the Ser(814)Asn mutant were also clearly reflected by the N/C-terminal interactions. Thus, measurement of N/C-terminal interactions may assist in the molecular analysis of mutant hARs associated with AIS.
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) | 0.001 | 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".