VENTILATOR CONDUIT FOR REVERSIBLE AIRWAY DEVICE

    公开(公告)号:US20210290878A1

    公开(公告)日:2021-09-23

    申请号:US15764108

    申请日:2016-09-30

    Inventor: Rafi Avitsian

    Abstract: A ventilator conduit for a reversible airway device (RAD) is provided. The RAD can include a supra-glottic support member connected to a tubular guide (TG) having oppositely disposed proximal and distal end portions and TG lumen, which extends between the ends and is defined by an inner surface. The RAD can be physically free of an endotracheal tube. The ventilator conduit can include a hollow tube having first and second ends, and a ventilator conduit lumen extending between the ends. The first and second ends can be adapted for connection to a ventilator circuit and insertion into the TG lumen, respectively. At least the second end of the hollow tube can be sized and dimensioned so that, upon insertion into the TG, an outer surface of the second end is brought into direct contact with a portion of the inner surface to form an air-tight seal therebetween.

    Endovascular grafts and methods for extended aortic repair

    公开(公告)号:US11076945B2

    公开(公告)日:2021-08-03

    申请号:US16155176

    申请日:2018-10-09

    Abstract: An endovascular graft including a stent graft and a surgical graft is provided. The stent graft can include an elongated body having a collapsed and expanded configuration and include a frame structure covered by a compression sleeve that retains the elongated body in the collapsed configuration until deployment of the stent graft. The endovascular graft can include a first cuff member sized and dimensioned to extend into a lumen of an aortic arch branch vessel when the endovascular graft is implanted in a subject. The frame structure can include a backstop sized and dimensioned to extend into the first cuff member when the endovascular graft is implanted in the subject. The surgical graft can be partially attached to the stent graft at a proximal end portion thereof.

    Method and apparatuses for accessing and/or modifying a target patient tissue site

    公开(公告)号:US11020573B2

    公开(公告)日:2021-06-01

    申请号:US16341975

    申请日:2017-10-13

    Abstract: A modular dilation device (100) is provided for inserting multiple dilators into a target patient tissue site. The modular dilation device includes a first dilator (104) and a second dilator (530). The first dilator has a first dilator distal end (108) and a first dilator inner lumen (114). The first dilator has a first dilator side wall opening (118). The first dilator distal end has a first dilator open tip (116). The first dilator has a first dilator open slit (120). The first dilator open slit extends between the first dilator side wall opening and the first dilator open tip. The second dilator has a second dilator distal end and a second dilator inner lumen. The second dilator distal end has a second dilator open tip. When the second dilator is joined to the first dilator, the second dilator open tip is adjacent to the first dilator side wall opening.

    NETWORK-BASED DEEP LEARNING TECHNOLOGY FOR TARGET IDENTIFICATION AND DRUG REPURPOSING

    公开(公告)号:US20210142173A1

    公开(公告)日:2021-05-13

    申请号:US17096712

    申请日:2020-11-12

    Inventor: Feixiong Cheng

    Abstract: A system to implement a deep learning network model is disclosed. The system includes machine-readable instructions and data that include a biomedical information library comprising information that includes a plurality of drugs, a plurality of biological targets, a plurality of diseases, and a plurality of adverse effects, a biomedical network system comprising a plurality of networks covering chemical, genomic, phenotypic, and cellular profiles, a score prioritizer to determine new targets for the plurality of drugs based on a concatenation of a low-dimensional vector representation for each drug vertex and each biological target vertex, and a model generator configured to generate a deep learning network model that defines a plurality of relationships between the drugs, the biological targets, and the adverse effects. The plurality of relationships defined by the deep learning network model predict drug target identification and drug repurposing.

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