Community structure and fibrolytic activities of anaerobic rumen fungi in dromedary camels
Bibliographic record
Abstract
Anaerobic fungi colonize the rumen and degrade cellulose and hemicellulose, which enable them to be key players in the lignocellulose fermentation. Consequently, an expansion of knowledge about rumen fungi could increase animal productivity, utilization of lignified forages like alfalfa hay, and enhance fibrolytic enzymes production. Here, we used an Internal Transcribed Spacer 1 (ITS1) clone library to investigate the anaerobic rumen fungi in camel and to investigate their ability to produce cellulase and xylanase in vitro. Rumen fluid was collected from camels fed Egyptian clover (n = 14), and wheat straw (n = 7) and fecal samples were collected from camels fed wheat straw and concentrates (n = 5), or natural grazing plants (n = 10). Neocallimastix and Cyllamyces were the most abundant anaerobic fungi in all camel groups. An anaerobic rumen fungi media containing alfalfa hay as a carbon source was inoculated by rumen and fecal samples to assess the ability of anaerobic rumen fungi in camel gut to produce cellulase and xylanase. The anaerobic gut fungi in the camel is diverse and has cellulolytic and xylanolytic activities, fungal culture from rumen samples of camel fed wheat straw (R2) exhibited highest cellulase production. In addition, many of the sequences in the current study have no equivalent cultured representative, indicating a novel diversity within the camel gut.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".