Compost biodegradation of recalcitrant hoof keratin by bacteria and fungi
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIMS: Compost activities efficiently break down a wide range of organic substances over time. In this study, bovine hoof was used as recalcitrant protein model to gain so far cryptic information on biodegradation during livestock mortalities composting. METHODS AND RESULTS: Bovine hooves (black and white), containing different amounts of melanin, placed into nylon bags were monitored during composting of cattle mortalities for up to 230 days. Besides physiochemical analysis, bacterial 16S and fungal 18S DNA fragments were amplified by PCR and profiles were separated by DGGE. Sequence analysis of separated fragments revealed various bacterial and fungal identities during composting. The microbial diversity was affected by a time-temperature interaction and by the hoof colour. Our molecular data, supported by electron microscopy, suggest hoof colonization by shifting bacteria and fungi communities. CONCLUSION: During composting, microbial communities work collaboratively in the degradation of recalcitrant organic matter such as keratin over time. SIGNIFICANCE AND IMPACT OF THE STUDY: A number of biomolecules including recalcitrant proteins may persist in environmental reservoirs, but breakdown can occur during composting. A combination of bioactivity and physiochemical conditions appear to be decisive for the fate of persistent biomolecules.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it