Bibliographic record
Abstract
Liquid crystals play an important role in biology because the combination of order and mobility is a basic requirement for self-organisation and structure formation in living systems. Cholesteric liquid crystals are omnipresent in living matter under both in vivo and in vitro conditions and address the major types of molecules essential to life. In the animal and plant kingdoms, the cholesteric structure is a recurring design, suggesting a convergent evolution to an optimised left-handed helix. Herein, we review the recent advances in the cholesteric organisation of DNA, chromatin, chitin, cellulose, collagen, viruses, silk and cholesterol ester deposition in atherosclerosis. Cholesteric structures can be found in bacteriophages, archaea, eukaryotes, bacterial nucleoids, chromosomes of unicellular algae, sperm nuclei of many vertebrates, cuticles of crustaceans and insects, bone, tendon, cornea, fish scales and scutes, cuttlebone and squid pens, plant cell walls, virus suspensions, silk produced by spiders and silkworms, and arterial wall lesions. This article specifically aims at describing the consequences of the cholesteric geometry in living matter, which are far from being fully defined and understood, and discusses various perspectives. The roles and functions of biological cholesteric liquid crystals include maximisation of packing efficiency, morphogenesis, mechanical stability, optical information, radiation protection and evolution pressure.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".