Poster Sessions Wednesday/Thursday
Bibliographic record
Abstract
Early-onset Alzheimer's disease (EOAD) is characterized by the presence of neurological symptoms in patients with Alzheimer's disease (AD) before 65 years of age.Mutations in pathological genes, including amyloid protein precursor (APP), presenilin-1 (PSEN1), and presenilin-2 (PSEN2), were associated with EOAD.Seventysix mutations in PSEN2 have been found around the world, which could affect the activity of γ-secretase in amyloid beta processing.Here, a heterozygous PSEN2 point mutation from G to A nucleotide change at position 166 (codon 56; c.166G>A, Gly56Ser) was identified in a 64-year-old Korean female with AD with progressive cognitive memory impairment for the 4 years prior to the hospital visit.Hippocampal atrophy was observed from magnetic resonance imaging-based neuroimaging analyses.Temporal and parietal cortex hypometabolism were identified using fluorodeoxyglucose positron emission tomography.This mutation was at the N-terminal portion of the presenilin 2 protein on the cytosolic side.Therefore, the serine substitution may have promoted AD pathogenesis by perturbing the mutation region through altered phosphorylation of presenilin.In silico analysis revealed that the mutation altered protein bulkiness with increased hydrophilicity and reduced flexibility of the mutated region of the protein.Structural changes were likely caused by intramolecular interactions between serine and other residues, which may have affected APP processing.The functional study will clarify the pathogenicity of the mutation in the future.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.775 | 0.531 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".