Bibliographic record
Abstract
Neuraminidase 1 (NEU1) is considered to be the most abundant and ubiquitous mammalian enzyme, with a broad tissue distribution. It plays a crucial role in a variety of cellular mechanisms. The deficiency of NEU1 has been implicated in various pathological manifestations of sialidosis and neurodegeneration. Thus, it is a novel therapeutic target for neurodegenerative changes in the Alzheimer's brain. However, to manipulate NEU1 as a therapeutic target, it is imperative to understand that, although NEU1 is commonly known for its lysosomal catabolic function, it is also involved in other pathways. NEU1 is involved in immune response modulation, elastic fiber assembly modulation, insulin signaling, and cell proliferation. In recent years, our knowledge of NEU1 has continued to grow, yet, at the present moment, current data is still limited. In addition, the unique biochemical properties of NEU1 make it challenging to target it as an effective therapeutic option for sialidosis, which is a rare disease but has an enormous patient burden. However, the fact that NEU1 has been linked to the pathology of Alzheimer's disease, which is rapidly growing worldwide, makes it more relevant to be studied and explored. In the present study, the authors have discussed various cellular mechanisms involving NEU1 and how they are relevant to sialidosis and Alzheimer's disease.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".