MECHANISM OF TOXICITY AND RESISTANCE TO D-MANNOSE AND CERTAIN DERIVATIVES IN SPECIES OF THE GENUS CHLORELLA BEIJ.12

d -Mannose and related derivatives, e.g., d -glucosa-mine and 2-deoxy-<d -glucose, blocked autotrophic and heterotrophic growth of several species of the genus Chlorella. Manometric studies showed differences in the effects of these compounds on substrate-induced O₂ uptake, indicating different modes of action. In a clonal culture, shaken in the light, mannose produced a lag phase of 7 days during which only ca. 0.05% of the cells continued to grow. From, these cells a resistant strain was isolated. Prolonged incubation in glucose media in darkness brought about a reversion to the sensitive condition. These metabolic shifts could not be explained on the basis of adaptation or nuclear gene mutation because of the permanency and high frequency of the resistant cells. The mechanism was suggested to be cytoplasmically controlled. The shift in sensitivity to the inhibitors was considered a reproducible characteristic of certain species. In contrast to the normal, rnannose-sensitive strain of C. infusionum var. acetophila, cells of a resistant strain carried a gelatinous envelope. The resistant strain utilized glucosamine as a source of nitrogen, but lost the capacity to use sugars for dark growth. This was reflected in drastic reductions in glucose and mannose uptake. The hexokinase activities in cell extracts were equivalent for both strains. The resistant strain did not accumulate hexose-6-phos-phates and showed an increased phosphatase activity at an alkaline pH.     

A neural model for conditioned avoidance learning

A mathematical model for learning of a conditioned avoidance behavior is presented. An identification of the net excitation of a neural model (Rashevsky, N., 1960.Mathematical Biophysics. Vol. II. New York: Dover Publications, Inc.) with the instantaneous probability of response is introduced and its usefulness in discussing block-trial learning performances in the conditioned avoidance situation is outlined for normal and brain-operated animals, using experimental data collected by the author. Later, the model is applied to consecutive trial learning and connection is made with the approach of H. D. Landahl (1964. “An Avoidance Learning Situation. A Neural Net Model.”Bull. Math. Biophysics,26, 83–89; and 1965, “A Neural Net Model for Escape Learning.”Bull. Math. Biophysics,27, Special Edition, 317–328) wherein lie further data with which the model can be compared.