Cover Picture: Proteomics 20'11
Bibliographic record
Abstract
Abstract A cell of two minds Stem cells have two principal tasks: (i) being prepared to replicate vegetatively on command, and (ii) being prepared to replicate differentially on command. It is always helpful if there is a way of recognizing the small pools of cells with these capabilities, preferably biomarkers that can be recognized quickly, cleanly and sensitively. One source that has not been thoroughly explored is very small peptides, MW <5 kDa. Maltman et al. report here on an enhanced protocol that has some interesting properties when used with neural progenitor cells. The procedure does not require a label, and uses LC‐MALDI‐TOF/TOF for analysis. It identified 12 different proteins on the basis of differentiated abundance, including nestin, vimentin, and GFAP, which are associated with neural development, some up‐regulated, some down‐regulated. Maltman, D. J. et al., Proteomics 2011, 11, 3992–4006. Re‐virginized mouse mammary glands You might think the mouse mammary gland system was designed by Richard Branson but we cannot give Sir Richard credit for this one. The mouse system, unlike the human mammary gland can, in large part, be recycled. During pregnancy, the luminal cells are directed to re‐differentiate into the milk‐producing aveoli (MaSC) until the end of lactation. The MaSC niche also directs neural cell reprogramming. Ji et al. purified fractions from cultured mammary tissue, adherent plasma membrane and sub‐fractions. Comparative proteomic analysis revealed a number of molecules and signaling pathways were involved, such as Wnt and Eph/ephrin signaling, and integrin‐mediated interactions. The analysis hinted at a number of solutions, but none answers all the issues all the time. Ji, H. et al., Proteomics 2011, 11, 4029–4039. The mystery in the can kicked down the road If you were a small boy who lived in a small US town in the 1950s, an image from the recent US congressional hearings resonated. You, too, kicked a can all the way home. You also wore blue jeans with pre‐patched knees and had to wait until Saturday for the next episode of “Sergeant Preston of the Yukon” at the only movie theater in town. You shared your bedroom with your younger brother, so the mess was always his. Moving to the future now with SAHA (a potent blocker of histone deacetylase inhibitor) and HDAC (a histone deacetylase), they too, exhibit can‐can interactions if examined closely, so Fischer et al. created a small, three‐pronged binding molecule that could selectively identify a non‐canonical SAHA binder. The most interesting target found was isochorismatase (ISOC2), which has been implicated in regulation of tumor suppressor p16(INK4A). Interesting soup in that can... Fischer, J. J. et al., Proteomics 2011, 11, 4096–4104.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.545 | 0.476 |
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".