Bibliographic record
Abstract
Duncan E. K. Sutherland and Martin J. Stillman Department of Chemistry, The University of Western Ontario, London, Ontario, Canada N6A 5B7 Metallothioneins (MTs), first discovered in 1957 (Margoshes and Vallee, 1957), are a family of small cysteine rich proteins found in all organisms. MTs have been implicated in toxic metal detoxification (Liu et al., 2000), protection against oxidative stress (Kang, 2006) and as metallochaperones (Tapia et al., 2004; Maret, 2008a), supplying both Zn2+ and Cu+ to their respective apo-enzymes. Zinc and copper are essential for the normal function of the brain and significant amounts are present in both the normal and diseased state. Zinc levels are critical for normal physical and mental development with numerous symptoms being reported in the cases of zinc deficiency. Copper is essential in the redox-based enzyme chemistry, for example the superoxide dismutases. Metallothionein is widely considered to play a significant role in the homeostasis of both these metals in other organs, particularly, in the liver, and in vitro studies show well-defined metallation chemistry. Metallothioneins are also implicated in the redox balance of cells as a result of the 20 cysteine thiols present and the variable metallation status possible. Therefore, the metallation of MT is intimately connected with both the concentrations of these metals and the ability to act as a metalchaperone, aiding in cellular metal buffering. Further, MT is most likely a key component in the mechanistic pathways that describe absorption, function and excretion of zinc and copper. Mammals produce four metallothionein isoforms (MT-1 to MT-4), of which MT-1 and MT-2 are expressed in all organs, MT-3 is found predominantly in the central nervous system, and MT-4 is present in some stratified tissues. However, despite 50 years of intense research, the exact function(s) remain unknown and the mechanistic details of the metallation reactions and subsequent metal transfer reactions are poorly understood.
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 | 0.000 | 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) | 0.008 | 0.010 |
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".