Diabetes mellitus in dogs and cats: diagnosis and therapy

Diabetes mellitus (DM) is a disease of humans and animals, which causes increased levels of blood sugar (glucose). Normally,glucose is brought into the cells by a hormone - insulin.The cells then metabolize glucose to make energy used for all functions of the body. Animals suffering from DM either lack insulin, or the cells cannotuse the insulin that is there. As a result, blood glucose levels increase, and the cells have to use other substances for energy. When blood glucose levels become too high, glucose is found in the urine, causing increased frequency of urination and increased drinking. When blood glucose remains elevated over a period of time, other metabolic changes can occur, such as weight loss, acidosis, seizures, coma, blindness, cataracts, and nerve damage. Animals that are eating normally and not showing signs of illness may only require a blood or urine test to diagnose DM. Concurrent diseases (such as infection, Cushing’s disease, hyperthyroidism, pancreatitis, gastroenteritis, inflammatory bowel disease, hepatic lipidosis, or kidney disease) make diabetes more difficult to diagnose and manage. A complete blood screen and other specific tests may be recommended to obtain the diagnosis and baseline values for treatment and future monitoring. The treatment for diabetes in dogs is similar to the treatment for diabetes in humans, through diet and insulin therapy. Dogs and cats with DM are usually treated with insulin. Insulin is a protein and, as such, not suitable for oral administration. Thus, it is administered once or several times daily by the subcutaneous route. Adjustment of the blood glucose concentration demands long hospital care, and subsequently the owner constantly has to keep a strict schedule at home. In veterinary practice the main groups of oral antidiabetic (used in human medicine either) are: carbohydrate absorption inhibitors (e.g. acarbose); insulin sensitisers (biguanides such as metformin, thiazolidinedions, peroxisome proliferator-activated gamma receptor agonists)

Verification and application of multi-source focus quantification

International audienceThe concept of the multi-source focus correlation method was presented in 2015 [1, 2]. A more accurate understanding of real on-product focus can be obtained by gathering information from different sectors: design, scanner short loop monitoring, scanner leveling, on-product focus and topography. This work will show that chip topography can be predicted from reticle density and perimeter density data, including experimental proof.Different pixel sizes are used to perform the correlation in-line with the minimum resolution, correlation length of CMP effects and the spot size of the scanner level sensor.Potential applications of the topography determination will be evaluated, includingoptimizing scanner leveling by ignoring non-critical parts of the field, and without the need for time-consuming offline topography measurements

THE INFLUENCE OF PROTEIN, METHIONINE AND LYSINE FEEDED LEVEL, IN HENS PERFORMANCES DURING THE PLATEAU PART OF THE LAYING CURVE

The experiment has been carried out in the Poultry Department from the Didactic Station of Banat`s University of Agricultural Sciences and Veterinary Medicine Timişoara, on laying hens - the Shaver 579 hybrid, being in the plateau part of the laying curve. We have distributed the hens in 4 groups (n=25), with fodder recipes including two protein levels (16.2% - group 1 and respectively 15.2% groups 2,3 and 4) and different amino acid contents (about 0.77% lysine and 0.38% methionine – groups 1 and 2; only 0.70% lysine and 0.34% methionine group 3, respectively 0.82% lysine and 0.42% methionine group 4). For the entire studied period, the highest egg production and the lower specific consumption, was registered for group 4 and the lowest production performances were assigned in group 3, which had been fed with a diet containing 15.2% crude protein and an amino-acids level lower with 10% than the NRC 1994 requirements. A strong positive correlation (r=0.80, p=0.015) for the egg production versus protein, lysine and methionine intake was obtained in lot 3