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Crimean-Congo hemorrhagic fever (CCHF) is a deadly hemorrhagic fever having a high mortality rate. The disease results from infection of an individual by Crimean-Congo hemorrhagic fever virus (CCHFV), which is a tick-borne bunyavirus endemic in Southern and Eastern Europe, Africa, the Middle East, and Asia. Geographically, case distribution is consistent with the range of Hyalomma genus ticks, the main reservoir of CCHFV, and is likely to expand due to climate change. Humans may be infected from tick bites, through contact with infected animals or animal tissue.

Researchers at the Vaccine Research Center (“VRC”) of the National Institute of Allergy and Infectious Diseases (“NAID”) continue to pursue a safe and effective HIV-1 vaccine to combat the HIV-1/AIDS pandemic.

This technology includes a novel method to train deep learning convolution neural network model to improve the signal-noise-ratio for the magnetic resonance (MR) imaging. The novelty lies on the fact that actual MR imaging physics information is used in the deep learning training. The resulting model achieves significant signal-to-noise ratio (SNR) improved for different acceleration factors in MR imaging. The resulting model can be used for many body anatomies (e.g., brain, heart, liver, spine, etc.) to significantly improve the SNR.

Scientists at NIAID have developed two immortalized stable B cell lines from rhesus macaques that can have value as research tools for the discovery of neutralizing antibodies of simian origin against HIV and that may have value in the development of an HIV vaccine. These B cell lines encode human Bcl-6 and Bcl-xL proteins, which are major regulators of apoptosis. These B cell lines are derived from the lymph node of a rhesus macaque (RM) that was infected with SHIV.CH505.

This technology includes a method for performing cardiac imaging without the need for the patient to hold their breath. Free breathing pixel-wise myocardial T1 parameter mapping includes performing a free-breathing scan of a cardiac region at a plurality of varying saturation recovery times to acquire a k-space dataset; generating an image dataset based on the k-space dataset; and performing a respiratory motion correction process on the image dataset.

This technology includes a fully automatic 3D image processing system to segment the heart as well as other organs from contrast-enhanced cardiac computed tomography (CCT) images. Our method detects four cardiac chambers including left ventricle, right ventricle, left atrium, right atrium, as well as the ascending aorta and left ventricular myocardium. It also classifies noncardiac tissue structures in the CCT images such as lung, chest wall, spine, descending aorta, and liver.

This technology includes a computer-implemented method for determining magnetic field inversion time of a tissue species using a T1-mapping image, information about the region of interest, and a tissue classification algorithm. This method includes T1-mapping image comprising a plurality of T1 values within an expected range of T1 values for the tissue of interest. An image mask is created based on predetermined identification information about the tissue of interest. Next, an updated image mask is created based on a largest connected region in the image mask.

This technology includes a transgenic reporter mouse that expresses a fluorescent protein called mt-Keima, to be used to detect and quantify in vivo mitophagy. This fluorescent protein was originally described by a group in Japan and shown to be able to measure both the general process of autophagy and mitophagy. We extended these results by creating a living animal so that we could get a measurement for in vivo mitophagy. Our results demonstrate that our mt-Keima mouse allows for a straightforward and practical way to quantify mitophagy in vivo.

This technology includes a method to reduce scanning time while retaining high image quality during MRI scans. A reconstructed image is rendered from a set of MRI data by first estimating an image with an area which does not contain artifacts or has an artifact with a relatively small magnitude. Corresponding data elements in the estimated image and a trial image are processed, for instance by multiplication, to generate an intermediate data set.

This technology includes part of transcatheter aortic valve replacement and to enable non-surgical thoracic aortic aneurysm endograft repair. The invention enables a completely new way to access the arterial circulation to allow introduction of large devices, such as transcatheter aortic valve replacement, percutaneous left ventricular assist devices, and thoracic aortic endografts. It also can be used in most labeled and off-label applications of Amplatzer (AGA Medical, St Jude) nitinol occluder devices to occlude intracardiac holes and to allow non-surgical direct access to the heart.