Catastrophic health care expenditure due to septic shock and dengue shock in Vietnam

BACKGROUND: The cost of treatment for infectious shock in intensive care in Vietnam is unknown. METHODS: We prospectively investigated hospital bills for adults treated for septic and dengue shock in Vietnam and calculated the proportion who faced catastrophic health care expenditures. RESULTS: The median hospital bills were US$617 for septic shock (n=100) and US$57 for dengue shock (n=88). Catastrophic payments were incurred by 47% (47/100) and 13% (11/88) of patients with septic shock and dengue shock, respectively, and 56% (25/45) and 84% (5/6) fatal cases of septic shock and dengue shock respectively. CONCLUSIONS: Further advocacy is required to moderate insurance co-payments for costly critical care interventions

Mode division multiplexing using an orbital angular momentum mode sorter and MIMO-DSP over a graded-index few-mode optical fibre

Mode division multiplexing (MDM)– using a multimode optical fiber’s N spatial modes as data channels to transmit N independent data streams – has received interest as it can potentially increase optical fiber data transmission capacity N-times with respect to single mode optical fibers. Two challenges of MDM are (1) designing mode (de)multiplexers with high mode selectivity (2) designing mode (de)multiplexers without cascaded beam splitting’s 1/N insertion loss. One spatial mode basis that has received interest is that of orbital angular momentum (OAM) modes. In this paper, using a device referred to as an OAM mode sorter, we show that OAM modes can be (de)multiplexed over a multimode optical fiber with higher than −15 dB mode selectivity and without cascaded beam splitting’s 1/N insertion loss. As a proof of concept, the OAM modes of the LP11 mode group (OAM−1,0 and OAM+1,0), each carrying 20-Gbit/s polarization division multiplexed and quadrature phase shift keyed data streams, are transmitted 5km over a graded-index, few-mode optical fibre. Channel crosstalk is mitigated using 4 × 4 multiple-input-multiple-output digital-signal-processing with <1.5 dB power penalties at a bit-error-rate of 2 × 10−3

Using Neural Networks for Relation Extraction from Biomedical Literature

Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems. The primary comprehensive source of these relations is biomedical literature. Several relation extraction approaches have been proposed to identify relations between concepts in biomedical literature, namely, using neural networks algorithms. The use of multichannel architectures composed of multiple data representations, as in deep neural networks, is leading to state-of-the-art results. The right combination of data representations can eventually lead us to even higher evaluation scores in relation extraction tasks. Thus, biomedical ontologies play a fundamental role by providing semantic and ancestry information about an entity. The incorporation of biomedical ontologies has already been proved to enhance previous state-of-the-art results.Comment: Artificial Neural Networks book (Springer) - Chapter 1

Mixed Supervision of Histopathology Improves Prostate Cancer Classification from MRI

Non-invasive prostate cancer detection from MRI has the potential to revolutionize patient care by providing early detection of clinically-significant disease (ISUP grade group >= 2), but has thus far shown limited positive predictive value. To address this, we present an MRI-based deep learning method for predicting clinically significant prostate cancer applicable to a patient population with subsequent ground truth biopsy results ranging from benign pathology to ISUP grade group~5. Specifically, we demonstrate that mixed supervision via diverse histopathological ground truth improves classification performance despite the cost of reduced concordance with image-based segmentation. That is, where prior approaches have utilized pathology results as ground truth derived from targeted biopsies and whole-mount prostatectomy to strongly supervise the localization of clinically significant cancer, our approach also utilizes weak supervision signals extracted from nontargeted systematic biopsies with regional localization to improve overall performance. Our key innovation is performing regression by distribution rather than simply by value, enabling use of additional pathology findings traditionally ignored by deep learning strategies. We evaluated our model on a dataset of 973 (testing n=160) multi-parametric prostate MRI exams collected at UCSF from 2015-2018 followed by MRI/ultrasound fusion (targeted) biopsy and systematic (nontargeted) biopsy of the prostate gland, demonstrating that deep networks trained with mixed supervision of histopathology can significantly exceed the performance of the Prostate Imaging-Reporting and Data System (PI-RADS) clinical standard for prostate MRI interpretation

Persistence length of a polyelectrolyte in salty water: a Monte-Carlo study

We address the long standing problem of the dependence of the electrostatic persistence length $l_e$ of a flexible polyelectrolyte (PE) on the screening length $r_s$ of the solution within the linear Debye-Huckel theory. The standard Odijk, Skolnick and Fixman (OSF) theory suggests $l_e \propto r_s^2$, while some variational theories and computer simulations suggest $l_e \propto r_s$. In this paper, we use Monte-Carlo simulations to study the conformation of a simple polyelectrolyte. Using four times longer PEs than in previous simulations and refined methods for the treatment of the simulation data, we show that the results are consistent with the OSF dependence $l_e \propto r_s^2$. The linear charge density of the PE which enters in the coefficient of this dependence is properly renormalized to take into account local fluctuations.Comment: 7 pages, 6 figures. Various corrections in text and reference

OnGuard3e: a predictive, ecophysiology‐ready tool for gas exchange and photosynthesis research

Gas exchange across the stomatal pores of leaves is a focal point in studies of plant-environmental relations. Stomata regulate atmospheric exchange with the inner air spaces of the leaf. They open to allow CO2 entry for photosynthesis and close to minimize water loss. Models that focus on the phenomenology of stomatal conductance generally omit the mechanics of the guard cells that regulate the pore aperture. The OnGuard platform fills this gap and offers a truly mechanistic approach with which to analyse stomatal gas exchange, whole-plant carbon assimilation and water-use efficiency. Previously, OnGuard required specialist knowledge of membrane transport, signalling and metabolism. Here we introduce OnGuard3e, a software package accessible to ecophysiologists and membrane biologists alike. We provide a brief guide to its use and illustrate how the package can be applied to explore and analyse stomatal conductance, assimilation and water use efficiencies, addressing a range of experimental questions with truly predictive outputs

Effect Of Leaf Surface Chemical Properties On Efficacy Of Sanitizer For Rotavirus Inactivation

The use of sanitizers is essential for produce safety. However, little is known about how sanitizer efficacy varies with respect to the chemical surface properties of produce. To answer this question, the disinfection efficacies of an oxidant-based sanitizer and a new surfactant-based sanitizer for porcine rotavirus (PRV) strain OSU were examined. PRV was attached to the leaf surfaces of two kale cultivars with high epicuticular wax contents and one cultivar of endive with a low epicuticular wax content and then treated with each sanitizer. The efficacy of the oxidant-based sanitizer correlated with leaf wax content as evidenced by the 1-log10 PRV disinfection on endive surfaces (low wax content) and 3-log10 disinfection of the cultivars with higher wax contents. In contrast, the surfactant-based sanitizer showed similar PRV disinfection efficacies (up to 3 log10) that were independent of leaf wax content. A statistical difference was observed with the disinfection efficacies of the oxidant-based sanitizer for suspended and attached PRV, while the surfactant-based sanitizer showed similar PRV disinfection efficacies. Significant reductions in the entry and replication of PRV were observed after treatment with either disinfectant. Moreover, the oxidant-based-sanitizer-treated PRV showed sialic acid-specific binding to the host cells, whereas the surfactant-based sanitizer increased the nonspecific binding of PRV to the host cells. These findings suggest that the surface properties of fresh produce may affect the efficacy of virus disinfection, implying that food sanitizers should be carefully selected for the different surface characteristics of fresh produce

4 X 20 Gbit/s mode division multiplexing over free space using vector modes and a q-plate mode (de)multiplexer

Vector modes are spatial modes that have spatially inhomogeneous states of polarization, such as, radial and azimuthal polarization. They can produce smaller spot sizes and stronger longitudinal polarization components upon focusing. As a result, they are used for many applications, including optical trapping and nanoscale imaging. In this work, vector modes are used to increase the information capacity of free space optical communication via the method of optical communication referred to as mode division multiplexing. A mode (de)multiplexer for vector modes based on a liquid crystal technology referred to as a q-plate is introduced. As a proof of principle, using the mode (de)multiplexer four vector modes each carrying a 20 Gbit/s quadrature phase shift keying signal on a single wavelength channel (~1550nm), comprising an aggregate 80 Gbit/s, were transmitted ~1m over the lab table with <-16.4 dB (<2%) mode crosstalk. Bit error rates for all vector modes were measured at the forward error correction threshold with power penalties < 3.41dB