Biochemical and hematological study of goats envenomed with natural and 60Co-irradiated bothropic venom

Venoms from snakes of the Bothrops genus are proteolytic, coagulant, hemorrhagic and nephrotoxic, causing edema, necrosis, hemorrhage and intense pain at the bite site, besides systemic alterations. Many adjuvants have been added to the venom used in the sensitization of antiserum-producer animals to increase antigenic induction and reduce the envenomation pathological effects. Gamma radiation from 60Co has been used as an attenuating agent of the venoms toxic properties. The main objective was to study, comparatively, clinical and laboratory aspects of goats inoculated with bothropic (Bothrops jararaca) venom, natural and irradiated from a 60Co source. Twelve goats were divided into two groups of six animals: GINV, inoculated with 0.5mg/kg of natural venom; and GIIV, inoculated with 0.5mg/kg of irradiated venom. Blood samples were collected immediately before and one, two, seven, and thirty days after venom injection. Local lesions were daily evaluated. The following exams were carried out: blood tests; biochemical tests of urea, creatinine, creatine kinase (CK), aspartate amino-transferase (AST) and alanine amino-transferase (ALT); clotting time; platelets count; and total serum immunoglobulin measurement. In the conditions of the present experiment, irradiated venom was less aggressive and more immunogenic than natural venom.(AU)

[Comparing predictions of type of pregnancy using artificial neural networks and multinomial logistic regression]

Some medical and epidemiological surveys have been designed to predict a nominal response variable with several levels. Type of pregnancy is one of them such that it has four possible states: wanted, wife unwanted, husband unwanted and couple unwanted. In this paper we have predicted type of pregnancy as influencing factors on it, using two different models and compared them together. Regarding type of pregnancy with several levels, we developed a multinomial logistic regression and a neural network based on data and compared their results using three statistical indices: sensitivity, Specificity and kappa. Based on three indices, neural network showed a better fit and prediction on data in comparison to multinomial logistic regression. When relations between variables are complex, one can use neural networks instead of multinomial logistic regression to predict nominal response variables with several levels in order to gain more accurate predictions

Evaluación del sistema incremental como estrategia para la atención en salud oral de los niños de las escuelas primarias públicas del Distrito de San Miguelito / Incremental System's Evaluation as Strategy for Oral Health Attention in Children of Public Elementary School in San Miguelito

Propósito primordial de este estudio fue determinar la cantidad de cumplimiento del sistema incremental en salud oral de los niños de las escuelas primarias del área de San Miguelito tomándose está área por ser el distrito que posee la más alta concentración de población en el país, con características propias de taza de crecimiento demográfico distribución urbano-rural, distribución por edades, las condiciones educacionales, etc. Los servicios tanto preventivo como curativo se prestan a través de 5 centros de salud y 2 policlínicas. La selección de la muestra se realizó tomando en consideración las escuelas que estaban en programa de salud escolar, y las que no habían estado en programa para efecto de comparar el índice CPO.D de ambos grupos de estudiantes y de esta manera, observar el comportamiento de c/u de los componentes del índice CPO.D. Se llegó a la conclusión que las escuelas con programas los niños al llegar a 6§ grado nos presentan 3.3 dientes cariados como promedio y los niños de escuelas sin programas, nos presentan 4.4 dientes cariados