GFP Production and Purification
Bibliographic record
Abstract
Huntington’s Disease (HD) is a hereditary neurodegenerative disease. The cause of this disease is a CAG repeat extension in the HTT Gene. This extension is then translated into an elongation of exon 1 which is primarily composed of a disordered PolyQ repeat. Although the cause is known, the mechanism by which this extension affects the function of Huntingtin (HTT), the protein produced by the HTT Gene, has yet to be understood. A part of this difficulty is our lack of understanding of the role of normal HTT in our cells. During the production of pure HTT sample, we began to notice an accumulation of nucleic acid material. To test the identity of this material, we sent it to one of our collaborators who told us it was RNA. Now, we are interested in preforming CLIP-seq to identify the specific sequence bound to HTT. Standard expression methods have been found to have minimal success due to the sheer size of HTT so other methods are being explored. One of which, is inserting formed protein into the neuronal cells via electroporation as described by Lambert, H. et. al. in Electroporation - mediated uptake of proteins into mammalian cells . By importing tagged protein into neuronal cells, we hope to capture a more readable RNA sequence, giving us a clue about its cellular function. To get the protein into the cell, we are planning to use electroporation. This process can be quite variable dependent upon the equipment used and the cells used, etc. we are using GFP to optimize conditions as it is quite easy to image in cells. In order to continue with this, a concentrated GFP sample must be made.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.036 |
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".