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.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".