We report a water-soluble and non-toxic method to incorporate additional extracellular matrix proteins into gelatin hydrogels, while obviating the use of chemical crosslinkers such as glutaraldehyde.

Engineering cardiac tissues with physiological architectural and mechanical properties on microelectrode arrays enables long term culture and non-invasive collection of electrophysiological readouts.

Although preclinical experiments are ultimately required to evaluate new therapeutic ultrasound exposures and devices prior to clinical trials, in vitro experiments can play an important role in the developmental process. A variety of in vitro methods have been developed, where each of these has demonstrated their utility for various test purposes. These include inert tissue-mimicking phantoms, which can incorporate thermocouples or cells and ex vivo tissue. Cell-based methods have also been used, both in monolayer and suspension. More biologically relevant platforms have also shown utility, such as blood clots and collagen gels. Each of these methods possesses characteristics that are well suited for various well-defined investigative goals. None, however, incorporate all the properties of real tissues, which include a 3D environment and live cells that may be maintained long-term post-treatment. This review is intended to provide an overview of the existing application-specific in vitro methods available to therapeutic ultrasound investigators, highlighting their advantages and limitations. Additional reporting is presented on the exciting and emerging field of 3D biological scaffolds, employing methods and materials adapted from tissue engineering. This type of platform holds much promise for achieving more representative conditions of those found in vivo, especially important for the newest sphere of therapeutic applications, based on molecular changes that may be generated in response to non-destructive exposures.

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Electrophysiological techniques to characterize the functionality of islets of Langerhans have been limited to short-term, one-time recordings such as a patch clamp recording. We describe the use of microelectrode arrays (MEAs) to better understand the electrophysiology of dissociated islet cells in response to glucose in a real-time, non-invasive method over prolonged culture periods. Human islets were dissociated into singular cells and seeded onto MEA, which were cultured for up to 7 days. Immunofluorescent imaging revealed that several cellular subtypes of islets; β, δ, and γ cells were present after dissociation. At days 1, 3, 5, and 7 of culture, MEA recordings captured higher electrical activities of islet cells under 16.7 mM glucose (high glucose) than 1.1 mM glucose (low glucose) conditions. The fraction of the plateau phase (FOPP), which is the fraction of time with spiking activity recorded using the MEA, consistently showed distinguishably greater percentages of spiking activity with high glucose compared to the low glucose for all culture days. In parallel, glucose stimulated insulin secretion was measured revealing a diminished insulin response after day 3 of culture. Additionally, MEA spiking profiles were similar to the time course of insulin response when glucose concentration is switched from 1.1 to 16.7 mM. Our analyses suggest that extracellular recordings of dissociated islet cells using MEA is an effective approach to rapidly assess islet functionality, and could supplement standard assays such as glucose stimulate insulin response.

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In this study, we present a sensorless, robust, and physiological tracking control method to drive the operational speed of implantable rotary blood pumps (IRBPs) for patients with heart failure (HF). The method used sensorless measurements of the pump flow to track the desired reference flow (Qr). A dynamical estimator model was used to estimate the average pump flow (Q^est) based on pulse-width modulation (PWM) signals. A proportional-integral (PI) controller integrated with a fuzzy logic control (FLC) system was developed to automatically adapt the pump flow. The Qr was modeled as a constant and trigonometric function using an elastance function (E(t)) to achieve a variation in the metabolic demand. The proposed method was evaluated in silico using a lumped parameter model of the cardiovascular system (CVS) under rest and exercise scenarios. The findings demonstrated that the proposed control system efficiently updated the pump speed of the IRBP to avoid suction or overperfusion. In all scenarios, the numerical results for the left atrium pressure (Pla), aortic pressure (Pao), and left ventricle pressure (Plv) were clinically accepted. The Q^est accurately tracked the Qr within an error of 0.25 L/min.

Malaria is a severe disease caused by Plasmodium parasites, which can be detected through blood smear images. The early identification of the disease can effectively reduce the severity rate. Deep learning (DL) models can be widely employed to analyze biomedical images, thereby minimizing the misclassification rate. With this objective, this study developed an intelligent deep-transfer-learning-based malaria parasite detection and classification (IDTL-MPDC) model on blood smear images. The proposed IDTL-MPDC technique aims to effectively determine the presence of malarial parasites in blood smear images. In addition, the IDTL-MPDC technique derives median filtering (MF) as a pre-processing step. In addition, a residual neural network (Res2Net) model was employed for the extraction of feature vectors, and its hyperparameters were optimally adjusted using the differential evolution (DE) algorithm. The k-nearest neighbor (KNN) classifier was used to assign appropriate classes to the blood smear images. The optimal selection of Res2Net hyperparameters by the DE model helps achieve enhanced classification outcomes. A wide range of simulation analyses of the IDTL-MPDC technique are carried out using a benchmark dataset, and its performance seems to be highly accurate (95.86%), highly sensitive (95.82%), highly specific (95.98%), with a high F1 score (95.69%), and high precision (95.86%), and it has been proven to be better than the other existing methods.