Additional file 1 of Variant in NHLRC2 leads to increased hnRNP C2 in developing neurons and the hippocampus of a mouse model of FINCA disease
Bibliographic record
Abstract
Additional file 1: Detailed description of the materials and methods, supplementary figures S1- S11, and supplementary tables S1-S6. Materials and methods include generation of FINCA mouse, used animals, genotyping, Sanger equencing, histology, blood analysis, ISH, NPC culture, 2DE-DIGE, mass spectrometry, qPCR, immunoblotting, ICC, data analysis, and statistical considerations. Fig. S1 Genotyping and Sanger sequencing of three founders obtained from microinjections of Cas9 ribonucleoprotein and ssODN into mouse zygotes. Fig. S2 SDS-PAGE immunoblotting showing decrease of NHLRC2 in different brain regions and different tissues of Nhlrc2FINCA/− mice compared to wild type mice. Fig. S3 SDS-PAGE immunoblotting comparing the amount of NHLRC2 between wildtype, homozygous Nhlrc2FINCA/FINCA and compound heterozygous Nhlrc2FINCA/− mice. Fig. S4 Representative images of Nhlrc2+/+ and Nhlrc2FINCA/− mouse lung and liver sections. Fig. S5 NPC isolation and culture. Fig. S6 Representative 2D gel of NPCs (wild type). Fig. S7 STRING network analysis of identified proteins. Fig S8 SDS-PAGE immunoblot and 2D gel immunoblotof Nhlrc2+/+ and Nhlrc2FINCA/− NPC lysates with VCP antibodies. Fig. S9 hnRNP C2 ICC image of Nhlrc2+/+ and Nhlrc2FINCA/− NPCs showing normal cellular localization. Fig. S10 SDS-PAGE immunoblotting of Nhlrc2+/+ and Nhlrc2FINCA/− cerebellum and brainstem. Fig. S11 ISH of Nhlrc2FINCA/− mouse brain. Table S1 Genotyping primers. Table S2 qPCR primers. Table S3 Genotype distribution of Nhlrc2+/+ and Nhlrc2FINCA/− mouse offspring. Table S4 Blood values of Nhlrc2+/+ and Nhlrc2FINCA/− mice. Table S5 Detailed statistical and MS data about the proteins identified from 2DE-DIGE. Table S6. qPCR results of expression levels of genes identified in 2DE-DIGE.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.826 | 0.111 |
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".