Improving Palliative Care with Deep Learning

Improving the quality of end-of-life care for hospitalized patients is a priority for healthcare organizations. Studies have shown that physicians tend to over-estimate prognoses, which in combination with treatment inertia results in a mismatch between patients wishes and actual care at the end of life. We describe a method to address this problem using Deep Learning and Electronic Health Record (EHR) data, which is currently being piloted, with Institutional Review Board approval, at an academic medical center. The EHR data of admitted patients are automatically evaluated by an algorithm, which brings patients who are likely to benefit from palliative care services to the attention of the Palliative Care team. The algorithm is a Deep Neural Network trained on the EHR data from previous years, to predict all-cause 3-12 month mortality of patients as a proxy for patients that could benefit from palliative care. Our predictions enable the Palliative Care team to take a proactive approach in reaching out to such patients, rather than relying on referrals from treating physicians, or conduct time consuming chart reviews of all patients. We also present a novel interpretation technique which we use to provide explanations of the model's predictions.Comment: IEEE International Conference on Bioinformatics and Biomedicine 201

On quaternionic functional analysis

In this article, we will show that the category of quaternion vector spaces, the category of (both one-sided and two sided) quaternion Hilbert spaces and the category of quaternion $B^*$-algebras are equivalent to the category of real vector spaces, the category of real Hilbert spaces and the category of real $C^*$-algebras respectively. We will also give a Riesz representation theorem for quaternion Hilbert spaces and will extend two results of Kulkarni (namely, we will give the full versions of the Gelfand-Naimark theorem and the Gelfand theorem for quaternion $B^*$-algebras). On our way to these results, we compare, clarify and unify the term "quaternion Hilbert spaces" in the literatures.Comment: to appear in the Mathematical Proceedings of the Cambridge Philosophical Societ

Glucocorticoid Compounds Modify Smoothened Localization and Hedgehog Pathway Activity

The Hedgehog signaling pathway is linked to a variety of diseases, notably a range of cancers. The first generation of drug screens identified Smoothened (Smo), a membrane protein essential for signaling, as an attractive drug target. Smo localizes to the primary cilium upon pathway activation, and this transition is critical for the response to Hedgehog ligands. In a high content screen directly monitoring Smo distribution in Hedgehog-responsive cells, we identified different glucocorticoids as specific modulators of Smo ciliary accumulation. One class promoted Smo accumulation, conferring cellular hypersensitivity to Hedgehog stimulation. In contrast, a second class inhibited Smo ciliary localization and signaling activity by both wild-type Smo, and mutant forms of Smo, SmoM2, and SmoD473H, that are refractory to previously identified Smo antagonists. These findings point to the potential for developing glucocorticoid-based pharmacological modulation of Smo signaling to treat mutated drug-resistant forms of Smo, an emerging problem in long-term cancer therapy. They also raise a concern about potential crosstalk of glucocorticoid drugs in the Hedgehog pathway, if therapeutic administration exceeds levels associated with on-target transcriptional mechanisms of glucocorticoid action.Chemistry and Chemical BiologyMolecular and Cellular BiologyStem Cell and Regenerative Biolog

Flow-induced HDAC1 phosphorylation and nuclear export in angiogenic sprouting

Angiogenesis requires the coordinated growth and migration of endothelial cells (ECs), with each EC residing in the vessel wall integrating local signals to determine whether to remain quiescent or undergo morphogenesis. These signals include vascular endothelial growth factor (VEGF) and flow-induced mechanical stimuli such as interstitial flow, which are both elevated in the tumor microenvironment. However, it is not clear how VEGF signaling and mechanobiological activation due to interstitial flow cooperate during angiogenesis. Here, we show that endothelial morphogenesis is histone deacetylase-1- (HDAC1) dependent and that interstitial flow increases the phosphorylation of HDAC1, its activity, and its export from the nucleus. Furthermore, we show that HDAC1 inhibition decreases endothelial morphogenesis and matrix metalloproteinase-14 (MMP14) expression. Our results suggest that HDAC1 modulates angiogenesis in response to flow, providing a new target for modulating vascularization in the clinic

Nanovolume optimization of protein crystal growth using the microcapillary protein crystallization system

The Microcapillary Protein Crystallization System (MPCS) is used to successfully optimize protein crystals from 28 out of 29 tested proteins. Six protein structures have been determined from diffraction-ready crystals grown inside and harvested directly from the MPCS CrystalCards, which are compatible with the recently commercialized and automated MPCS Plug Maker instrument

Crossbow Volume 1

Student Integrated ProjectIncludes supplementary materialDistributing naval combat power into many small ships and unmanned air vehicles that capitalize on emerging technology offers a transformational way to think about naval combat in the littorals in the 2020 time frame. Project CROSSBOW is an engineered systems of systems that proposes to use such distributed forces to provide forward presence to gain and maiantain access, to provide sea control, and to project combat power in the littoral regions of the world. Project CROSSBOW is the result of a yearlong, campus-wide, integrated research systems engineering effort involving 40 student researchers and 15 supervising faculty members. This report (Volume I) summarizes the CROSSBOW project. It catalogs the major features of each of the components, and includes by reference a separate volume for each of the major systems (ships, aircraft, and logistics). It also prresents the results of the mission and campaign analysis that informed the trade-offs between these components. It describes certain functions of CROSSBOW in detail through specialized supporting studies. The student work presented here is technologically feasible, integrated and imaginative. The student project cannot by itself provide definitive designs or analyses covering such a broad topic. It does strongly suggest that the underlying concepts have merit and deserve further serious study by the Navy as it transforms itself

Niagara, County of and Niagara County White Collar Employee Unit, CSEA Local 1000, AFSCME, AFL-CIO, Local 832 (2012) (MOA)

Liquid chromatography–tandem mass spectrometry (LC–MS/MS) and multiple reaction monitoring mass spectrometry (MRM-MS) proteomics analyses were performed on eccrine sweat of healthy controls, and the results were compared with those from individuals diagnosed with schizophrenia (SZ). This is the first large scale study of the sweat proteome. First, we performed LC–MS/MS on pooled SZ samples and pooled control samples for global proteomics analysis. Results revealed a high abundance of diverse proteins and peptides in eccrine sweat. Most of the proteins identified from sweat samples were found to be different than the most abundant proteins from serum, which indicates that eccrine sweat is not simply a plasma transudate and may thereby be a source of unique disease-associated biomolecules. A second independent set of patient and control sweat samples were analyzed by LC–MS/MS and spectral counting to determine qualitative protein differential abundances between the control and disease groups. Differential abundances of selected proteins, initially determined by spectral counting, were verified by MRM-MS analyses. Seventeen proteins showed a differential abundance of approximately 2-fold or greater between the SZ pooled sample and the control pooled sample. This study demonstrates the utility of LC–MS/MS and MRM-MS as a viable strategy for the discovery and verification of potential sweat protein disease biomarkers