Modeling the Role of Negative Cooperativity in Metabolic Regulation and Homeostasis

A significant proportion of enzymes display cooperativity in binding ligand molecules, and such effects have an important impact on metabolic regulation. This is easiest to understand in the case of positive cooperativity. Sharp responses to changes in metabolite concentrations can allow organisms to better respond to environmental changes and maintain metabolic homeostasis. However, despite the fact that negative cooperativity is almost as common as positive, it has been harder to imagine what advantages it provides. Here we use computational models to explore the utility of negative cooperativity in one particular context: that of an inhibitor binding to an enzyme. We identify several factors which may contribute, and show that acting together they can make negative cooperativity advantageous.     

Immersion staining of coarse fish in the Thames

Thirty-one vital dyes were screened for marking bleak, roach and gudgeon by total body immersion in aqueous solutions of the dye. Only six dyes stained without killing, and of these Nile blue, neutral red and Bismarck brown were used successfully in the field. This approach to estimation of population size was abandoned because (1) the toxicity of the dyes varied at different times of year, (2) the numbers needed for release were impractically high and (3) fingerlings showed extremely high mortality on handling.     

Essential oil of Ayapana triplinervis from Reunion Island: A good natural source of thymohydroquinone dimethyl ether

Three specimens of Ayapana triplinervis (Vahl) R.M. King & H. Rob from Reunion Island (Indian Ocean) collected at two distant locations (North of the island; samples 1 and 2, South of the island; sample 3), in different growth phases (flowering; samples 1 and 3, vegetative; sample 2) were investigated for their leaf essential oil composition. This study reports the chemical character of this species on the island and investigates the relationship between essential oil composition, developmental stage and geographic location. Analysis by GC–FID and GC–MS enabled us to identify and quantify a total of 39 constituents accounting for 97.1–98.0% of the oils. The three essential oil samples, all obtained by hydrodistillation, showed a high percentage of the aromatic compound thymohydroquinone dimethyl ether (89.9–92.8%). All other minor components remained more or less unchanged both qualitatively and quantitatively with respect to the stage of growth. On the contrary, variations were observed with geographic distribution. The geographical variation of the chemical composition of the volatile oil of A. triplinervis from several sites in the world is also briefly discussed.     

Isolation and Pathogenicity of Rhizosphere Fungi of Cocoyam in Relation to Cocoyam Root Rot Disease

Cocoyam is the second most important staple crop of Cameroon and root rot is a destructive disease of this plant. Pythium myriotylum (Pm), Fusarium solani (Fs), and Rhizoctonia solani (Rs) were isolated from the rhizosphere of root rot affected cocoyams and from the soil of a cocoyam experimental field plot temporarily devoid of same in Mamu, Cameroon. Pm was isolated from the above soil by the cocoyam leaf disc baits. Fs and Rs were also isolated from the same soils by the water dilution method and from the roots of diseased cocoyams but were always associated with mycelial growth of Pm. Pathogenicity of Pm and in combinations with Fs or Rs or Fs + Rs all developed cocoyam root rot disease (CRRD) symptoms on 3– and 7–month old cocoyam plantlets 2–7 days after inoculation. Symptoms included rotted roots and wilting with general chlorosis of inoculated plantlets. No symptoms of CRRD were noted on cocoyam plantlets inoculated with Fs, Rs, Fs + Rs, and distilled water. Results indicated that CRRD is not caused by several pathogens but only by Pm. Pm isolates from the soils and roots of diseased cocoyams and those maintained in the ROTREP laboratory have significantly bigger diameter of mycelial colony growth in 24 h–period at 31 °C on lima bean sucrose agar, V–8 juice sucrose agar, and potato sucrose agar than on potato dextrose agar and 2 % water agar. The cocoyam plantlets were raised axenically from tissue culture of explants in the laboratory.     

Learning to Produce Syllabic Speech Sounds via Reward-Modulated Neural Plasticity

At around 7 months of age, human infants begin to reliably produce well-formed syllables containing both consonants and vowels, a behavior called canonical babbling. Over subsequent months, the frequency of canonical babbling continues to increase. How the infant’s nervous system supports the acquisition of this ability is unknown. Here we present a computational model that combines a spiking neural network, reinforcement-modulated spike-timing-dependent plasticity, and a human-like vocal tract to simulate the acquisition of canonical babbling. Like human infants, the model’s frequency of canonical babbling gradually increases. The model is rewarded when it produces a sound that is more auditorily salient than sounds it has previously produced. This is consistent with data from human infants indicating that contingent adult responses shape infant behavior and with data from deaf and tracheostomized infants indicating that hearing, including hearing one’s own vocalizations, is critical for canonical babbling development. Reward receipt increases the level of dopamine in the neural network. The neural network contains a reservoir with recurrent connections and two motor neuron groups, one agonist and one antagonist, which control the masseter and orbicularis oris muscles, promoting or inhibiting mouth closure. The model learns to increase the number of salient, syllabic sounds it produces by adjusting the base level of muscle activation and increasing their range of activity. Our results support the possibility that through dopamine-modulated spike-timing-dependent plasticity, the motor cortex learns to harness its natural oscillations in activity in order to produce syllabic sounds. It thus suggests that learning to produce rhythmic mouth movements for speech production may be supported by general cortical learning mechanisms. The model makes several testable predictions and has implications for our understanding not only of how syllabic vocalizations develop in infancy but also for our understanding of how they may have evolved.