Abstract: An aspect of an embodiment or partial embodiment of the present invention (or combinations of various embodiments in whole or in part of the present invention) comprises, but not limited thereto, a method and system (and related computer program product) for continually assessing the risk of hypoglycemia for a patient and then determining what action to take based on that risk assessment. A further embodiment results in two outputs: (1) an attenuation factor to be applied to the insulin rate command sent to the pump (either via conventional therapy or via open or closed loop control) and/or (2) a red/yellow/green light hypoglycemia alarm providing to the patient an indication of the risk of hypoglycemia. The two outputs of the CPHS can be used in combination or individually.

Abstract: Provided are isolated TCRs, TCR-like molecules, and portions thereof that bind to phosphopeptide-HLA-A2 complexes. The isolated TCRs, TCR-like molecules, or portions are optionally soluble TCRs, TCR-like molecules, or portions. Also provided are isolated nucleic acids encoding the disclosed TCRs, TCR-like molecules, or portions; host cells that contain the disclosed TCRs, TCR-like molecules, or portions; pharmaceutical compositions that include the disclosed TCRs, TCR-like molecules, portions, nucleic acids, and/or T cells; kits; and methods of using the same.

Abstract: Microfluidic devices for analyzing cellular components from biological samples which contain more than one cell type are provided. The microdevice separates cells by type, releases cellular components such as DNA (e.g. by cell lysis) and processes the cellular components (for example, by amplification) to generate products of interest for further analysis. Samples that can be analyzed using the microfluidic devices include forensic samples such as samples from sexual assault victims, and the products of interest include short tandem repeat (STR) amplicons for DNA profiling.

Abstract: Disclosed are phototunable hydrogels, compositions that include the same, and methods for using the same for treating wounds and/or injuries, for inhibiting formation of scar tissue at wound sites, for inhibiting fibrosis in subjects in need thereof, for inhibiting lung fibrosis and/or scarring in subject in need thereof, for inhibiting formation of myofibroblasts from fibroblasts, and for inhibiting expression of ?-smooth muscle actin (?-SMA) and/or type I collagen in fibroblasts.

Abstract: The spinal cord stimulation device of this invention is configured for implantation into a patient so as to traverse the dura mater that surrounds the spinal cord. Placing the device in this location provides direct contact between the electrode and the cerebrospinal fluid (CSF), in close proximity to the spinal cord. The device has an intradural portion and an extradural portion that compresses and seals the dural membrane between them, securing the device in position and preventing leakage of CSF. The position of the device may be stabilized in relation to the spinal cord by way of a laminoplasty plate, bridging between the device and a vertebra. The device is electronically powered by an implanted pulse generator that produces a spectrum of signals to interrupt or otherwise attenuate transmission of pain mediating neural signals through the spinal cord.

Abstract: Provided are methods for treating and/or preventing genotoxic stress-induced cardiac toxicity, which in some embodiments include administering to a subject an effective amount of an inhibitor of t-CH, of neutrophil activation, of neutrophil migration, or any combination thereof. In some embodiments, the genotoxic stress-induced cardiac toxicity results from exposure to one or more anti-tumor and/or anti-cancer therapies, including but not limited to treatment with one or more chemotherapeutics (e.g., doxorubicin) and/or treatment with radiation. In some embodiments, the genotoxic stress-induced cardiac toxicity, the chemotherapy-induced cardiac toxicity, the chemotherapy-induced heart damage, and/or the chemotherapy-induced reduction in cardiac function is characterized by a reduction in cardiac contractility, a thinning of a ventricular wall, a reduction in cardiomyocyte size, or any combination thereof.

Abstract: Embodiments can relate to systems and methods for automatically detecting sensor compression in continuous glucose monitoring in real time. A system may include at least one sensor and at least one processor in communication with the at least one sensor. The at least one processor is programmed or configured to cause the processor to retrieve first measurement data including at least one time series of blood glucose (BG) measurements, the at least one time series being measured by the at least one sensor while not subject to compression; receive, from the at least one sensor, second measurement data including at least one BG measurement; determine a clearance value between BG measurements based on the first measurement data and the second measurement data; and generate a signal output indicating that the at least one sensor is subject to compression based on the clearance value between BG measurements exceeding a predefined threshold.

Abstract: Some embodiments relate to imageable radioisotopic microspheres. In some embodiments, the imageable microspheres are radiolabeled with imageable radioisotopes. In some embodiments, the imageable radioisotope is directly coupled to a surface of a substrate of the microsphere. In some embodiments, the imageable microspheres can be used as surrogate particles to predict the distribution of therapeutic microspheres comprising radiotherapeutic isotopes.

Abstract: Embodiments can relate to a system for automatically detecting sensor compression in continuous glucose monitoring including at least one sensor and at least one processor in communication with the at least one sensor, the at least one processor executing at least two machine learning models, wherein the at least one processor is programmed or configured to cause the processor to receive, from the at least one sensor, measurement data including at least one time series of blood glucose (BG) measurements measured by the at least one sensor, determine that the at least one time series of BG measurements is a candidate series including a compression artifact using a first machine learning model, and generate, using a second machine learning model, a signal output indicating that the at least one time series of BG measurements was obtained while the at least one sensor was subject to compression.

Abstract: Embodiments can relate to a system for producing a digital image by automatically correcting for scattering and/or absorption effects in an original digital image. The system can include a processor. The system can include memory containing a computer program that when executed will cause the processor to receive radiance spectra of a digital image, and execute a Gaussian machine learning model. The system can generate a reflectance parameter by predicting a ground reflectance value based on a Gaussian probability distribution of radiance spectra. The system can solve for a conversion coefficient based on the reflectance parameter. The system can produce an altered digital image by at least one or more of removing, filtering, and/or altering data for at least one pixel of a digital image based on the conversion coefficient.

Abstract: A structure, method, and computer program product for a diabetes control system provides, but is not limited thereto, the following: open-loop or closed-loop control of diabetes that adapts to individual physiologic characteristics and to the behavioral profile of each person. An exemplary aspect to this adaptation is biosystem (patient or subject) observation and modular control. Consequently, established is the fundamental architecture and the principal components for a modular system, which may include algorithmic observers of patients' behavior and metabolic state, as well as interacting control modules responsible for basal rate, insulin boluses, and hypoglycemia prevention.

Abstract: An exemplary method and system is disclosed that facilitate the integration of multiplexed single-cell impedance cytometry in a high throughput format, which can be deployed upstream from microfluidic sample preparation and/or downstream to microfluidic cell separation. In exemplary method and system may employ impedance-based quantification of cell electrophysiology on the same microfluidic chip (i.e., “on-chip”) to provide distinguishing phenotypic information on the sample, without the need for additional sample handling, preparation or dilution steps as would be needed for other flow cytometry techniques.

Abstract: Methods of modeling the in vivo efficacy of drug combinations for the treatment or prevention of viral infection are described. The described methods combine data for single drugs and drug combinations from pharmacokinetic, pharmacodynamic, and viral dynamics models under a series of estimated in vivo drug potencies to provide predictions of the in vivo effects of the drug combinations. These predictions can be used to more accurately select drugs and drug treatment regimens that can be successful in controlling viral infection in animal studies, clinical trials and in medical or veterinary interventions. Also described is a method of treating or preventing filovirus infections using combinations of orally available drugs based on predictions from the modeling methods.

Abstract: Compositions and methods are provided that are useful for diagnosing, treating, and monitoring alcohol dependence and disorders, susceptibility to alcohol dependence disorders, as well as drug related dependence and disorders. The methods include treating patients with an antagonist of the serotonin receptor 5-HT3 for such disorders, wherein the patient's serotonin transporter gene SLC6A4 is known to have particular genotypes.

Abstract: In one aspect, the disclosure relates to compounds useful to regulate, limit, or inhibit the expression of AVIL (advillin), methods of making same, pharmaceutical compositions comprising same, and methods of treating disorders associated with AVIL dysregulation using same. In aspects, the disclosed compounds, compositions and methods are useful for treating disorders or diseases in which the regulation, limitation, or inhibition of the expression of AVIL can be clinically useful, such as, for example, the treatment of cancer. This abstract is intended as a scanning tool for purposes of searching in the particular art and is not intended to be limiting of the present disclosure.

Abstract: Embodiments relate to a dynamic spectrum access (DSA) system including a DSA transmitter configured to generate a complex signal for a secondary communication system, the complex signal being within a communication band A that is equal to or falls within a communication band B of a primary communication system. The complex signal includes a first signal and a second signal that is a repeat of the first signal. The power of the complex signal received at the secondary communication receiver is greater than the noise floor of the secondary communication system, but is equal to or less than the interference power from the primary communication. The DSA system includes a DSA receiver including a plurality of DSA antennas and a DSA signal processing module, the DSA signal processing module configured to perform canonical correlation analysis (CCA) on the complex signal.

Abstract: Provided are compositions that include targeting peptides and methods for using the same to treat and/or prevent various diseases, disorders, and/or conditions. In some embodiments, the compositions and methods relate to liposomal compositions that include a liposome, the surface of which is conjugated to a peptide having an amino acid sequence as set forth in any of SEQ ID NOS: 3-38, optionally wherein the liposome encapsulates a therapeutic agent or a detectable agent. In some embodiments, the peptide has an amino acid sequence that is one of SEQ ID NOs: 14, 19, 20, 27, and 28. Also provided are methods treating or preventing fibrosis, for decreasing the incidence of a disease, disorder, or condition associated with chronic pancreatitis (CP), for targeting active agents to targets, including but not limited to collagen III-expressing cells and extracellular matrix, and for decreasing incidence of side effects associated with apigenin treatment.

Abstract: Provided herein is a previously unannotated IncRNA lying within exon six and 3?UTR of the LCK gene, labeled “HULLK” for Hormone-Upregulated IncRNA within LCK. HULLK is a novel IncRNA situated within the LCK gene that can serve as an oncogene in PCa. Accordingly, provided are methods and compositions for diagnosing and treating prostate cancer based on HULLK that regulates prostate cancer cell growth.

Abstract: A computerized system and method of modeling myocardial tissue perfusion can include acquiring a plurality of original frames of magnetic resonance imaging (MRI) data representing images of a heart of a subject and developing a manually segmented set of ground truth frames from the original frames. Applying training augmentation techniques to a training set of the originals frame of MRI data can prepare the data for training at least one convolutional neural network (CNN). The CNN can segment the training set of frames according to the ground truth frames. Applying the respective input test frames to a trained CNN can allow for segmenting an endocardium layer and an epicardium layer within the respective images of the input test frames. The segmented images can be used in calculating myocardial blood flow into the myocardium from segmented images of the input test frames.

Abstract: Systems and methods for denoising a magnetic resonance (MR) image utilize an unsupervised deep convolutional neural network (U-DCNN). Magnetic resonance (MR) image data of an area of interest of a subject can be acquired, which can include noisy input images that comprise noise data and noise free image data. For each of the noisy input images, iterations can be run of a converging sequence in an unsupervised deep convolutional neural network. In each iteration, parameter settings are updated; the parameter settings are used in calculating a series of image feature sets with the U-DCNN. The image feature sets predict an output image. The converging sequence of the U-DCNN is terminated before the feature sets predict a respective output image that replicates all of the noise data from the noisy input image. Based on a selected feature set, a denoised MR image of the area of interest of the subject can be output.