Loss of Membrane Targeting of Vangl Proteins Causes Neural Tube Defects
Bibliographic record
Abstract
Cathepsin D was purified from the lactating rabbit mammary gland by a rapid procedure, which included fractionation with (NH4)2SO4, acid precipitation, double affinity chromatography on pepstatin-Sepharose 4B and gel filtration on Sephadex G-100, resulting in approximately 360-fold purification of the enzyme over the homogenate and approximately 16% recovery. After isoelectric focusing, the enzyme dissociated into four (pI 5.8, 6.3, 6.5 and 7.2) multiple forms, but appeared homogeneous on polyacrylamide gel electrophoresis. Cathepsin D has a Mr of 45 kDa as determined by Sephadex G-100 column chromatography. On sodium dodecylsulfate/polyacrylamide gel electrophoresis the enzyme gave a single protein band, corresponding to Mr of 45 kDa. The amino acid composition of the enzyme is similar to that of cathepsins D from other tissues. A single N-terminal amino acid was glycine. Cathepsin D contains 6.4% carbohydrates consisting of mannose, galactose, fucose and glucosamine at a ratio of 3:9:2:2. Cathepsin D is inhibited by pepstatin with Ki of 2.5 X 10(-9) M and irreversibly by N-diazoacetyl-N'-2.4-dinitrophenyl-ethylene diamine. The enzyme hydrolyzes bovine hemoglobin with the maximal activity at pH 3.0 with Km = 10(-5) M and HLeu-Ser-Phe(NO2)-Nle-Ala-Leu-OMe with Km = 4 X 10(-5) M and Rcat = 0.95 s-1. The major cleavage sites were Leu15-Tyr16, Phe24-Phe25 and Phe25-Tyr26 during hydrolysis of the oxidized insulin B-chain by cathepsin D.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".