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- Author or Editor: Henry R. Stämpfli x
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Abstract
Objective—To determine proglycogen (PG) and macroglycogen (MG) content in equine skeletal muscle and to compare 2 analytical methods (acid hydrolysis [AC] and PG plus MG determination) for measurement of total muscle glycogen content (Glytot) in biopsy specimens.
Sample Population—Muscle biopsy specimens obtained from 41 clinically normal horses.
Procedure—Forty-five muscle biopsy specimens obtained from the middle gluteal (n = 31) or triceps (14) muscle were analyzed, using AC and MG plus PG determination for Glytot. Variability within muscle biopsy specimens for each method was calculated from duplicate analyses of muscle specimens. In a second experiment, variation in MG and PG content between muscle biopsy specimens and the effect of sample collection depth on the concentration of MG and PG in the middle gluteal muscle was evaluated.
Results—There was a strong correlation ( r = 0.99) between Glytot values obtained by use of AC and MG plus PG determination. Coefficients of variation for within- and between-specimen variability of Glytot were approximately 4% for each method. The PG fraction was always in excess of the MG fraction. Biopsy specimens obtained from the superficial part of the middle gluteal muscle contained significantly more Glytot and PG than specimens obtained from deeper parts.
Conclusions and Clinical Relevance—This study confirms that MG and PG exist in equine skeletal muscle and can be measured reliably in biopsy samples. This technique could be applied in future studies to investigate glycogen metabolism in exercising horses and horses with glycogen-storage diseases. (Am J Vet Res 2002;63:570–575)
Abstract
Objective—To identify potential mechanisms for hypokalemia in dairy cows with left-displaced abomasum (LDA), right-displaced abomasum (RDA), or abomasal volvulus (AV).
Design—Retrospective analysis of clinicopathologic data from 2 convenience samples of cows.
Sample—112 lactating dairy cows with AV (group 1); 1,332 lactating dairy cows (group 2) with LDA (n = 1,160) or RDA or AV (172).
Procedures—Data were analyzed via Spearman ρ and multivariate stepwise regression.
Results—78 of 112 (70%) group 1 cows were hypokalemic (mean serum potassium concentration, 3.5 mEq/L; reference range, 3.9 to 5.8 mEq/L). For group 1 cows, serum chloride concentration had the strongest positive association with serum potassium concentration, and serum potassium concentration was negatively associated with plasma bicarbonate and serum glucose, creatinine, and urea concentrations. Six hundred thirty-six of 1,160 (55%) of group 2 cows with LDA were hypokalemic (mean serum potassium concentration, 3.7 mEq/L). Ninety-two of 172 (53%) group 2 cows with RDA or AV were hypokalemic (mean serum potassium concentration, 3.8 mEq/L). For group 2 cows, serum chloride concentration had the strongest positive association with serum potassium concentration, and serum potassium concentration was negatively associated with indices of feed intake (serum bilirubin concentration) and hydration status.
Conclusions and Clinical Relevance—Results suggested hypokalemia was associated with hypochloremia, alkalemia, low feed intake with high amount of milk produced, hypovolemia, and hyperglycemia in lactating dairy cows. Treatment of hypokalemia should include surgical correction of abomasal displacement, increased dietary potassium intake via dietary dry matter intake or oral administration of KCl, and correction of hypochloremia, alkalemia, metabolic alkalosis, and dehydration.
Abstract
Objective—To develop an equation expressing urine pH in terms of independent variables, derive an equation relating urine pH to net acid excretion (NAE), and apply this new knowledge to determine the role that monitoring urine pH should play when diets with low cationanion difference are fed to dairy cattle.
Animals—11 Holstein-Friesian cows.
Procedures—A physicochemical strong ion approach was used to develop a general electroneutrality equation for urine that involved urine pH and strong ion difference (SID [difference between strong cation and strong anion concentrations]), PCO 2, the concentration of ammonium ([NH4 +]) and phosphate ([PO4]), and 3 constants. The general electroneutrality equation was simplified for use in bovine urine and applied to 321 data points from 11 cows fed different diets.
Results—Urine pH was dependent on 4 independent variables (urine SID, [NH4 +], PCO 2, and [PO4]) and 3 constants. The simplified electroneutrality equation for bovine urine was pH ≈ {pK1′ − log10(S PCO 2)} + log10([K+] + [Na+] + [Mg2+] + [Ca2+] + [NH4 +] − [Cl−] − [SO4 2−]). The relationship between urine pH and NAE (in mEq/L) for cattle fed different diets was pH = 6.12 + log10(−NAE + [NH4 +] + 2.6).
Conclusions and Clinical Relevance—A change in urine SID, [NH4 +], PCO 2, or [PO4] independently and directly led to a change in urine pH. Urinary [K+] had the greatest effect on urine pH in cattle, with high urine [K+] resulting in alkaline urine and low urine [K+] resulting in acidic urine. Urine pH provided an accurate assessment of NAE in cattle when pH was > 6.3.
