Se reporta el caso de un Beagle hembra de 5 meses con cojera del miembro anterior derecho y un defecto de separación entre el segundo y tercer dedo. En el examen radiográfico se observó hipoplasia del hueso carporradial y del segundo metacarpiano, y ausencia del primer dedo. Además, presentó una hendidura con contenido de tejido blando entre el segundo y tercer metacarpiano. Los hallazgos fueron compatibles con ectrodactilia unilateral. Se realizó una cirugía reconstructiva mediante una artrodesis pancarpal, con relleno de hueso esponjoso y utilizando un sistema de fijación esquelética externa. Se restableció completamente la función del miembro a las 10 semanas.

The case of a 5-month-old female Beagle with lameness of the right anterior limb and a separation defect between the second and third fingers is reported. In the radiographic examination, hypoplasia of the carporradial bone and of the second metacarpal, and absence of the first finger was observed. In addition, the patient presented a cleft with soft tissue content between the second and third metacarpal. The findings were compatible with unilateral ectrodactyly. Reconstructive surgery was performed through a pancarpal arthrodesis, with cancellous bone filling and using an external skeletal fixation system. The limb’s function was completely restored at 10 weeks.

The objective of this research was to predict the live weight of Corriedale lambs using morphological measurements and machine learning algorithms. A total of 291 five-month-old lambs from the Corpacancha Production Unit of SAIS PACHACÚTEC SAC were used. These animals represented a homogeneous group in terms of age, sex, and genetics, as they belonged to the Corriedale breed and were offspring of "Category A" ewes. Morphological measurements recorded included Body Length (BL), Withers Height (WH), Thoracic Girth (TG), Rump Width (RW), Abdominal Girth (AG), Cannon Bone Length (CBL), Chest Depth (CD), and Live Weight (LW). The models evaluated were Multiple Linear Regression, Ridge Regression, Decision Trees, Random Forest, and XGBoost. The comparative analysis of the machine learning models identified ModG and Ridge as the most accurate and stable options, standing out for their low Mean...