PSII-8 Comparison of Different Fattening Stages on Rumen Microbiota and Physiological Characteristics in Japanese Black Cattle
Bibliographic record
Abstract
Abstract This study aimed to investigate the relationship between rumen microbiota and physiological characteristics in Japanese Black cattle during the fattening period, which are known for their distinctive physiological characteristics due to prominent intramuscular fat deposition. The experimental period was categorized into three stages: early (12 to 14 months of age; T1), middle (15 to 22 months; T2), and late fattening phases (23 to 30 months; T3). We analyzed the rumen microbiota of 21 Japanese Black cattle in each phase using 16S rRNA gene amplicon sequencing. In addition, we examined the correlation between the rumen microbiota and various physiological parameters, such as blood metabolites, hormones, and rumen fermentation characteristics. Our results showed that rumen microbial diversity was greater in T1, and the inter-group distribution of rumen microbiota in T1 was differentiated from T2 and T3. At the genus level, Flexilinea, Streptococcus, Butyrivibrio, Selenomonas and Kandleria were the most abundant in T1. Bifidobacterium, Shuttleworthia and Sharpea were the most abundant in T2. Acetitomaculum, Mycoplasma, Atopobium and Howardella were the most abundant in T3. In correlation analysis, Monoglobus and Olsenella negatively correlated with IGF-1 and positively correlated with cortisol in T1. Firmicutes/Bacteroidota ratio positively correlated with daily gain, blood total cholesterol, and lactic acid dehydrogenase in T3. Planctomycetota correlated with volatile fatty acid components during the entire period, while Verrucomicrobiota positively correlated with carcass traits in T1. Additionally, functional genetic profiles indicated that rumen microbiota related to carbohydrate metabolism and nucleotide biosynthesis was significantly enriched in T1 and T3, respectively. The composition of rumen microbial in Japanese Black cattle varied depending on fattening stages, and this variation is likely attributable to changes in feed composition. Furthermore, specific microorganisms were significantly associated with physiological parameters. Our findings could help in the development of strategies to enhance gut health and productivity by manipulating the rumen microbiota through the changes in diet compositions considering the fattening stages of Japanese Black cattle.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".