LKP : Rancang Bangun Aplikasi Wajib Lapor Perusahaan Pada Dinas Tenaga Kerja Pemkot Surabaya
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
Converging lines of evidence have now highlighted the key role for post-transcriptional regulation in the neuromuscular system. In particular, several RNA-binding proteins are known to be misregulated in neuromuscular disorders including myotonic dystrophy type 1, spinal muscular atrophy and amyotrophic lateral sclerosis. In this study, we focused on the RNA-binding protein Staufen1, which assumes multiple functions in both skeletal muscle and neurons. Given our previous work that showed a marked increase in Staufen1 expression in various physiological and pathological conditions including denervated muscle, in embryonic and undifferentiated skeletal muscle, in rhabdomyosarcomas as well as in myotonic dystrophy type 1 muscle samples from both mouse models and humans, we investigated the impact of sustained Staufen1 expression in postnatal skeletal muscle. To this end, we generated a skeletal muscle-specific transgenic mouse model using the muscle creatine kinase promoter to drive tissue-specific expression of Staufen1. We report that sustained Staufen1 expression in postnatal skeletal muscle causes a myopathy characterized by significant morphological and functional deficits. These deficits are accompanied by a marked increase in the expression of several atrophy-associated genes and by the negative regulation of PI3K/AKT signaling. We also uncovered that Staufen1 mediates PTEN expression through indirect transcriptional and direct post-transcriptional events thereby providing the first evidence for Staufen1-regulated PTEN expression. Collectively, our data demonstrate that Staufen1 is a novel atrophy-associated gene, and highlight its potential as a biomarker and therapeutic target for neuromuscular disorders and conditions.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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