Research and development on lactoferrin and its derivatives in China from 2011–2015
Bibliographic record
Abstract
Lactoferrin (Lf), a multifunctional glycoprotein, is an important antimicrobial and immune regulatory protein present in neutrophils and most exocrine secretions of mammals. Lactoferricin (Lfcin) is located in the N-terminal region of this protein. In this review, the current state of research into Lf and Lfcin in China is described. Searching with HistCite software in Web Sci located 118 papers published by Chinese researchers from 2011-2015, making China one of the top 3 producers of Lf research and development in the world. The biological functions of Lf and Lfcin are discussed, including antibacterial, antiviral, antifungal, anticarcinogenic, and anti-inflammatory activities; targeted drug delivery, induction of neurocyte, osteoblast, and tenocyte growth, and possible mechanisms of action. The preparation and heterologous expression of Lf in animals, bacteria, and yeast are discussed in detail. Five Lf-related food additive factories and 9 Lf-related health food production companies are certified by the China Food and Drug Administration (CFDA). The latest progress in the generation of transgenic livestock in China, the safety of the use of transgenic animals, and future prospects for the uses of Lf and Lfcin are also covered.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".