Relationship of plasma leptin concentration to intramuscular fat content in beef from crossbred Wagyu cattle
Bibliographic record
Abstract
Plasma leptin concentrations and beef cattle carcass characteristics in eight Continental Crossbred steers [0% Wagyu Cattle (WC)] were compared to crossbred cattle with 50 and 75% WC (eight steers each) genetic makeup to determine if a relationship exists between plasma leptin concentrations and intramuscular fat content (marbling) in beef cattle. Plasma leptin concentrations were measured at two stages of cattle growth, 16 and 4 wk prior to slaughter (W P S). Beef cattle characteristics including marbling score, ribeye area, i.m. total lipid content, and backfat depth were determined, and correlation coefficients obtained between these traits and leptin concentration at both sampling dates. Plasma leptin concentrations increased relative to the lipid content in the 24 steers based on the significant positive correlation observed between plasma leptin and total lipids (% wet weight) from both pars costalis diaphragmatis (p.c.d.)(16 WPS: r = 0.69, P = 0.0004; 4 WPS: r = 0.35, P = 0.104) and longissimus (16 WPS: r = 0.59, P = 0.002; 4 WPS: r = 0.51, P = 0.011) muscles. A trend was observed, however, at 4 WPS when the groups of varying Wagyu genetics were compared. Plasma leptin was positively correlated with muscle lipid content for the 0% Wagyu cattle (longissimus: r = 0.62, P = 0.103; p.c.d.:r = 0.40, P = 0.410)but there was almost no correlation in these parameters for the 50% WC (longissimus: r = 0.11, P = 0.797; p.c.d.: r = 0.005, P = 0.990). Plasma leptin concentration was negatively correlated with lipid content in the 75% WC (longissimus: r = –0.60, P = 0.120; p.c.d.: r = –0.65, P = 0.164). The results suggest that increasing Wagyu genetics negates any relationship between leptin concentrations and i.m. fat content in cattle. Key words: Wagyu crossbred cattle, meat quality, intramuscular fat, marbling, leptin
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".