Valproate-Induced Hyperammonemic Encephalopathy Causing New-Onset Seizures.

Valproate-induced hyperammonemic encephalopathy (VHE) is a rare and severe side effect that can occur with valproic acid (VPA) therapy, despite therapeutic doses and normal serum levels of valproate. The typical signs of this condition include a sudden onset of impaired consciousness, focal neurologic symptoms, and an increase in seizure frequency. The exact cause of VHE is unknown, but it is believed to be related to the accumulation of toxic VPA metabolites and increased levels of ammonia that can cause swelling of the astrocytes and cerebral edema. We present a case of a 19-year-old male patient with a history of bipolar disorder on valproic acid 250 mg daily, admitted to the hospital after a new-onset seizure. He was found to have elevated levels of ammonia in his blood, despite having therapeutic levels of valproate and no liver dysfunction. His symptoms improved with discontinuation of the medication and his ammonia levels decreased. We discuss possible mechanisms and risk factors leading to encephalopathy while on valproate therapy. VHE should be considered a possibility when patients treated with valproate show signs of impaired consciousness.

Reliability analysis of smart laminated composite plates under static loads using artificial neural networks.

The applications of smart structures with integrated piezoelectric elements have been expanding in the last few decades due to the abilities of such structures to withstand mechanical loads and operate as sensors or actuators using their electromechanical coupling. The available manufacturing techniques can result in uncertainties in the structure's geometric parameters, which, coupled with uncertainties in material properties, can lead to unexpected failures or unreliable performance. This paper presents a reliability analysis of a smart laminated composite plate made of a graphite/epoxy cross-ply substrate with a piezoelectric fiber-reinforced composite (PFRC) actuator layer under static electrical and mechanical loads. A coupled finite element (FE) model was developed in COMSOL Multiphysics, from which nondimensional stresses and displacements were calculated. To investigate the effects of randomness in the material and geometric properties, an artificial neural network (ANN) model was developed and trained using generated FE data. Monte Carlo Simulation (MCS) and First- and Second-Order Reliability Methods (FORM/SORM) were then used to shed light on the significance of considering randomness in the various material and geometric parameters and the effect of such uncertainty on the resulting nondimensional stresses and displacements. A coefficient of variation (CV) study identified the piezoelectric stress coefficient as the most significant contributing factor to the variation of all nondimensional parameters. Variation in the nondimensional parameters also increases under the application of an electric load. ANN-based FORM, SORM, and MCS all indicate a pattern of low probability of failure until a threshold value of about 3% of input parameter variation is reached, beyond which there is a rapid nonlinear increase in failure probability with increasing input parameter variation.

Maximizing fluid delivered by bubble-free electroosmotic pump with optimum pulse voltage waveform.

In generating high electroosmotic (EO) flows for use in microfluidic pumps, a limiting factor is faradaic reactions that are more pronounced at high electric fields. These reactions lead to bubble generation at the electrodes and pump efficiency reduction. The onset of gas generation for high current density EO pumping depends on many parameters including applied voltage, working fluid, and pulse duration. The onset of gas generation can be delayed and optimized for maximum volume pumped in the minimum time possible. This has been achieved through the use of a novel numerical model that predicts the onset of gas generation during EO pumping using an optimized pulse voltage waveform. This method allows applying current densities higher than previously reported. Optimal pulse voltage waveforms are calculated based on the previous theories for different current densities and electrolyte molarity. The electroosmotic pump performance is investigated by experimentally measuring the fluid volume displaced and flow rate.