Kinetic mechanism of the interaction of D-cycloserine with serine hydroxymethyltransferase

The kinetic mechanism for the interaction of D-cycloserine with serine hydroxymethyltransferase (EC 2.1.2.1) from sheep liver was established by measuring changes in the activity, absorbance, and circular dichoism (CD) of the enzyme. The irreversible inhibition of the enzyme was characterized by three detectable steps: an initial rapid step followed by two successive steps with rate constants of 5.4 X 10(-3) s-1 and 1.4 X 10(-4) s-1. The first step was distinguished by a rapid disappearance of the enzyme absorbance peak at 425 nm, a decrease in the enzyme activity to 25% of the uninhibited velocity, and a lowering of the CD intensity at 432 nm to about 65% of the original value. The second step of the interaction was accompanied by a complete loss of enzyme activity and a marginal increase in the CD intensity at 432 nm. The final step resulted in the complete loss of the enzyme absorbance at 425 nm and of the CD band at 432 nm. The products of the reaction were identified as (a) apoenzyme by absorbance measurements, CD spectra, and reconstitution with pyridoxal 5'-phosphate and (b) a pyridoxal 5'-phosphate-D-cycloserine Schiff's base complex identified by its fluorescence and absorbance spectra. The Schiff base complex was expelled from the enzyme active site in the final step of the reaction. The proposed mechanism, which is different from those operative in other pyridoxal phosphate dependent enzymes, probably accounts for the selective inhibition of serine hydroxymethyltransferase by the drug in vivo.     

Temporal changes in the physical properties of healing fractures in rabbits

Temporal changes in the physical properties of healing fractures in rabbits were studied. The mechanical environment at the fracture site was measured and monitored during healing. Animals were sacrificed after 3 to 8 weeks. The results of healing were quantified by whole bone dynamic torsional strength tests. Torque-angle curves were recorded by computer. At maximum torque four parameters were calculated: torque, angle, energy absorbed and stiffness. Torque and stiffness increased while energy remained constant and angle decreased with time. However, values calculated by a constant deformation criteria showed the three strength parameters to increase with time. The rate of increase was highest for stiffness followed by torque and energy.     

Novel secopyrrolizidine alkaloids from Crotalaria verrucosa

Crotaverrine and O-acetylcrotaverrine, isolated from the seeds of C. verrucosa Linn., have been shown by spectroscopy and chemical evidence to be the macrocyclic diesters of otonecine and diastereoisomeric integerrinecic acid. Hitherto, diastereoisomeric integerrinecic acid esters were not known to occur in nature.     

Uncertainty–guided learning with scaled prediction errors in the basal ganglia

To accurately predict rewards associated with states or actions, the variability of observations has to be taken into account. In particular, when the observations are noisy, the individual rewards should have less influence on tracking of average reward, and the estimate of the mean reward should be updated to a smaller extent after each observation. However, it is not known how the magnitude of the observation noise might be tracked and used to control prediction updates in the brain reward system. Here, we introduce a new model that uses simple, tractable learning rules that track the mean and standard deviation of reward, and leverages prediction errors scaled by uncertainty as the central feedback signal. We show that the new model has an advantage over conventional reinforcement learning models in a value tracking task, and approaches a theoretic limit of performance provided by the Kalman filter. Further, we propose a possible biological implementation of the model in the basal ganglia circuit. In the proposed network, dopaminergic neurons encode reward prediction errors scaled by standard deviation of rewards. We show that such scaling may arise if the striatal neurons learn the standard deviation of rewards and modulate the activity of dopaminergic neurons. The model is consistent with experimental findings concerning dopamine prediction error scaling relative to reward magnitude, and with many features of striatal plasticity. Our results span across the levels of implementation, algorithm, and computation, and might have important implications for understanding the dopaminergic prediction error signal and its relation to adaptive and effective learning.     

Understanding the binding interaction between phenyl boronic acid P1 and sugars: determination of association and dissociation constants using S–V plots,steady‐state spectroscopic methods and molecular docking

Continuous monitoring of glucose and sugar sensing plays a vital role in diabetes control. The drawbacks of the present enzyme‐based sugar sensors have encouraged the investigation into alternate approaches to design new sensors. The popularity of fluorescence sensors is due to their ability to bind reversibly to compounds containing diol. In this study we investigated the binding ability of phenyl boronic acid P1 for monosaccharides and disaccharides (sugars) in aqueous medium at physiological pH 7.4 using steady‐state fluorescence and absorbance. P1 fluorescence was quenched due to formation of esters with sugars. Absorbance and fluorescence measurements led to results that indicated that the sugars studied could be ordered in terms of their affinity to P1, as stated: sucrose > lactose > galactose > xylose > ribose > arabinose. In each case, the slope of modified Stern–Volmer plots was nearly 1, indicating the presence of only a single binding site in boronic acids for sugars. Docking studies were carried out using Schrodinger Maestro v.11.2 software. The binding affinity of phenyl boronic acid P1 with periplasmic protein (PDB ID 2IPM and 2IPL) was estimated using GlideScore.