Ecotoxicity studies of antifungal metabolites of Bacillus sp. IBA 33 / Estudios de la ecotoxicidad de metabolitos antifúngicos de Bacillus sp. IBA 33

The increments of plant diseases caused by the proliferation of fungicide-resistant pathogens intensified the research of new active metabolites against them. The study of biological methods as an alternative to chemical control has reach relevance in recent years. It has been suggested that the use of metabolites from Bacillus, is an alternative or supplementary method to chemical plant protection, if they are not toxic for the consumers and environmentally friendly. The toxicity of different concentrations of antifungal metabolites produced by Bacillus sp. IBA 33 was evaluated. Their ability to induce cytotoxic effects was investigated by different tests as hemolysis, and Artemia salina and Allium cepa L immobilization. With 2.56 mg/ml of antifungal metabolites hemolysis reached 24.07%, to 1.28 mg/ml was 14%. HC50 was 10.41 mg/ml. A. salina nauplii exposed to 3.2, 1.6 and 0.8 mg/ml of antifungal metabolites showed 80, 20 and 10% of mortality respectively; LD50 was 2.24 mg/ml. In Allium cepa L test after 72 h of treatment, the roots lengths were 8.75, 10.35 and 23.75 mm with 3.2, 1.6 and 0.8 mg/ml of antifungal metabolites respectively. The EC50 was 0.078 mg/ml. After 144 h the EC50 was 4.11 mg/ml. Only with 3.2 mg/ml of metabolites, chromosomal aberrations, cytoplasm vacuolization and decentralization of nuclei were observed in the cells of Allium cepa L. No micronuclei were detected. Under the experimental conditions, the antifungal metabolites concentrations assayed are considered non toxic (AU)

El incremento de enfermedades de plantas causado por la proliferación de patógenos resistentes a fungicidas intensificó la investigación de nuevos metabolitos activos contra ellos. El estudio de métodos biológicos como una alternativa al control químico ha alcanzado relevancia en años recientes. Se ha sugerido que el uso de metabolitos de Bacillus, es una alternativa o un método suplementario a la protección química de las plantas, siempre y cuando ellos no sean tóxicos para los consumidores y sean amigables para el medio ambiente. Se ha evaluado la toxicidad de diferentes concentraciones de metabolitos antifúngicos producidos por Bacillus sp. IBA33. Se investigó su capacidad para inducir efectos citotóxicos mediante diferentes tests como hemólisis e inmovilización de Artemia salina y Allium cepa L. Con 2.56 mg/ml de metabolitos antifúngicos la hemólisis alcanzó 24.07%, para 1.28 mg/ml fue 14%. La HC50 fue 10.41 mg/ml. Nauplios de Artemia salina expuestos a 3.2; 1.6 y 0.8 mg/ml de metabolitos antifúngicos mostraron 80; 20 y 10% de mortalidad respectivamente después de 24 h de tratamiento; la LD50 fue 2.24 mg/ml. En el test de Allium cepaL después de 72 h de tratamiento, la longitud de las raíces fueron 8.75; 10.35 y 23.75 mm con 3.2; 1.6 y 0.8 mg/ml de metabolitos antifúngicos respectivamente, con una EC50 de 0.078 mg/ml. Después de 144 h la EC50 fue 4.11 mg/ml. Solamente con 3.2 mg/ml de metabolitos fueron observadas aberraciones cromosómicas, vacualización y descentralización de los núcleos en las células de Allium cepa L. No se observaron micronúcleos. Bajo las condiciones experimentales, las concentraciones de metabolitos antifúngicos ensayadas son consideradas no tóxicas

Infant artificial language learning and language acquisition.

The rapidity with which children acquire language is one of the mysteries of human cognition. A view held widely for the past 30 years is that children master language by means of a language-specific learning device. An earlier proposal, which has generated renewed interest, is that children make use of domain-general, associative learning mechanisms. However, our current lack of knowledge of the actual learning mechanisms involved during infancy makes it difficult to determine the relative contributions of innate and acquired knowledge. A recent approach to studying this problem exposes infants to artificial languages and assesses the resulting learning. In this article, we review studies using this paradigm that have led to a number of exciting discoveries regarding the learning mechanisms available during infancy. These studies raise important issues with respect to whether such mechanisms are general or specific to language, the extent to which they reflect statistical learning versus symbol manipulation, and the extent to which such mechanisms change with development. The fine-grained characterizations of infant learning mechanisms that this approach permits should result in a better understanding of the relative contributions of, and the dynamic between, innate and learned factors in language acquisition.

Transfer and Complexity in Artificial Grammar Learning

Implicit and explicit learning are sensitive to various degrees of complexity and abstractness, ranging from knowledge of first-order dependencies and specific surface structure to second-order dependencies and transfer. Three experiments addressed whether implicit learning is sensitive to this entire range of information or whether explicit knowledge becomes an important factor in cases of more complex learning. Experiment 1 used recognition and prediction to assess deliberate access to knowledge of letter patterns in an artificial grammar learning paradigm. Experiment 2 manipulated stimulus presentation and response in a sequence-based grammar learning paradigm. Learning can occur without awareness in cases of lesser complexity (such as learning first-order dependencies). However, more complex learning, such as that involved in learning second-order dependencies or in transfer to stimuli with the same underlying syntax but new surface features is linked to explicit knowledge. In contrast to Experiments 1 and 2 which assessed deliberate access to knowledge of the acquisition stimuli, Experiment 3 assessed deliberate access to knowledge of the transfer stimuli. Knowledge of initial trigrams in the transfer stimuli appears to play an important role in transfer. These findings are evaluated in terms of postulated implicit learning mechanisms.