Orientación de la Política Económica en el 2013
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
The ribonuclease Dicer plays a central role in the microRNA pathway by processing microRNA precursors (pre-microRNAs) into microRNAs, a class of 19- to 24-nucleotide non-coding RNAs that regulate expression of ≈60% of the genes in humans. To gain further insights into the function and regulation of Dicer in human cells, we performed a yeast two-hybrid (Y2HB) screen using human Dicer double-stranded RNA-binding domain (dsRBD) as bait. This approach identified tumor necrosis factor (TNF)-like weak inducer of apoptosis (TWEAK) as a Dicer-interacting protein candidate. Confocal immunofluorescence microscopy revealed the colocalization of Dicer and TWEAK proteins at the perinuclear region of HeLa cells. The Dicer-TWEAK protein interaction was confirmed by coimmunoprecipitation and found not likely to be mediated by RNA. TWEAK dose-dependently reduced pre-microRNA conversion into mature microRNA in Dicer activity assays using extracts of transfected human HEK 293 cells. TWEAK expression also impaired microRNA-guided RNA silencing of a reporter gene induced by a pre-microRNA. These findings suggest a role for TWEAK-a pro-inflammatory cytokine-in regulating Dicer function and microRNA biogenesis, and its possible involvement in regulating gene expression during inflammatory processes and diseases.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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