Editorial: Special 2021 Frontiers in Endocrinology collection for the 100th anniversary of insulin discovery
Bibliographic record
Abstract
Special 2021 Frontiers in Endocrinology collection for the 100th anniversary of insulin discoveryTo commemorate the 100th anniversary of the discovery and successful purification of insulin (1) at the University of Toronto by Banting, Best, Collip and McLeod in 1921 (earning the Nobel Prize to Banting and McLeod in 1923), Frontiers in Endocrinology organized a special collection related to insulin and insulin-like peptides, with Jeff M.P. Holly and Pierre De Meyts as supervisory editors.The aim was to bring together a collection of articles to celebrate the anniversary and the continued breadth of studies of this remarkable hormone.The articles could be submitted to the various sections of the journal.The review by Irwin discusses the evolution of the insulin gene in the superfamily of insulin-like genes in multicellular invertebrates and vertebrates, as well as the recent discovery of insulin-like peptides in some fish viruses (2).Initial efforts to study the evolutionary aspects of insulin-like sequences relied on the sequencing of isolated peptides, but in the past 20 years, an increasing number of protein sequences have been predicted from the complete genome sequences of organisms.In most vertebrates a single insulin gene has been found, however multiple copies, some with differing gene structures, have been found in some species (e.g.rats, mice, Xenopus laevis, as well as teleost fishes that have undergone an ancestral whole genome duplication).In the vertebrate suborder hystricomorphs (guinea pigs and relatives), highly divergent insulin sequences are due to an accelerated rate of evolution.This is also the case in some species of New World monkeys.Several species of fish and mammals have accumulated increased amounts of sequence changes that affected sites of proteolytic processing of the prohormone precursor, resulting in either a single protein chain or two-chain proteins with an A-or B-chain that is extended to include the complete C-peptide sequence but remain biologically functional.The author concludes: "As we complete more genomes and microbiomes, it is certain that we will discover more insulin-like sequences with novel aspects to their sequences, structures, and functions.However, sequence will not tell us function.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.033 | 0.032 |
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".