Building Disease Detection Algorithms with Very Small Numbers of Positive Samples

Although deep learning can provide promising results in medical image analysis, the lack of very large annotated datasets confines its full potential. Furthermore, limited positive samples also create unbalanced datasets which limit the true positive rates of trained models. As unbalanced datasets are mostly unavoidable, it is greatly beneficial if we can extract useful knowledge from negative samples to improve classification accuracy on limited positive samples. To this end, we propose a new strategy for building medical image analysis pipelines that target disease detection. We train a discriminative segmentation model only on normal images to provide a source of knowledge to be transferred to a disease detection classifier. We show that using the feature maps of a trained segmentation network, deviations from normal anatomy can be learned by a two-class classification network on an extremely unbalanced training dataset with as little as one positive for 17 negative samples. We demonstrate that even though the segmentation network is only trained on normal cardiac computed tomography images, the resulting feature maps can be used to detect pericardial effusion and cardiac septal defects with two-class convolutional classification networks

Training Korean speakers on English vowels and prosody: Individual differences in perception, production and vowel epenthesis

This paper investigates whether intangibles might explain the UK productivity puzzle. We note that since the recession: (a) firms have upskilled faster than before; (b) intangible investment in R&D and software has risen whereas tangible investment has fallen; and (c) intangible and telecoms equipment investment slowed in advance of the recession. We have therefore tested to see if: (a) what looks like labour hoarding is actually firms keeping workers who are employed in creating intangible assets; (b) the current slowdown in TFP growth is due to the spillover effects of the past slowdown in R&D and telecoms equipment investment. Our main findings are: (a) measured market sector real value added growth since the start of 2008 is understated by 1.6% due to the omission of intangibles; (b) 0.75pppa of the TFP growth slowdown can be accounted for by the slowdown in intangible and telecoms investment in the early 2000s. Taken together intangible investment can therefore account for around 5 percentage points of the 16% productivity puzzle

Prediction and validation of a mechanism to control the threshold for inhibitory synaptic plasticity

Synaptic plasticity, neuronal activity-dependent sustained alteration of the efficacy of synaptic transmission, underlies learning and memory. Activation of positive-feedback signaling pathways by an increase in intracellular Ca2+ concentration ([Ca2+]i) has been implicated in synaptic plasticity. However, the mechanism that determines the [Ca2+]i threshold for inducing synaptic plasticity is elusive. Here, we developed a kinetic simulation model of inhibitory synaptic plasticity in the cerebellum, and systematically analyzed the behavior of intricate molecular networks composed of protein kinases, phosphatases, etc. The simulation showed that Ca2+/calmodulin-dependent protein kinase II (CaMKII), which is essential for the induction of synaptic plasticity, was persistently activated or suppressed in response to different combinations of stimuli. The sustained CaMKII activation depended on synergistic actions of two positive-feedback reactions, CaMKII autophosphorylation and CaMKII-mediated inhibition of a CaM-dependent phosphodiesterase, PDE1. The simulation predicted that PDE1-mediated feedforward inhibition of CaMKII predominantly controls the Ca2+ threshold, which was confirmed by electrophysiological experiments in primary cerebellar cultures. Thus, combined application of simulation and experiments revealed that the Ca2+ threshold for the cerebellar inhibitory synaptic plasticity is primarily determined by PDE1

A ferroelectric memristor

Memristors are continuously tunable resistors that emulate synapses. Conceptualized in the 1970s, they traditionally operate by voltage-induced displacements of matter, but the mechanism remains controversial. Purely electronic memristors have recently emerged based on well-established physical phenomena with albeit modest resistance changes. Here we demonstrate that voltage-controlled domain configurations in ferroelectric tunnel barriers yield memristive behaviour with resistance variations exceeding two orders of magnitude and a 10 ns operation speed. Using models of ferroelectric-domain nucleation and growth we explain the quasi-continuous resistance variations and derive a simple analytical expression for the memristive effect. Our results suggest new opportunities for ferroelectrics as the hardware basis of future neuromorphic computational architectures

Short-wavelength infrared photodetector on Si employing strain-induced growth of very tall InAs nanowire arrays

One-dimensional crystal growth enables the epitaxial integration of III-V compound semiconductors onto a silicon (Si) substrate despite significant lattice mismatch. Here, we report a short-wavelength infrared (SWIR, 1.4-3 mu m) photodetector that employs InAs nanowires (NWs) grown on Si. The wafer-scale epitaxial InAs NWs form on the Si substrate without a metal catalyst or pattern assistance; thus, the growth is free of metal-atom-induced contaminations, and is also cost-effective. InAs NW arrays with an average height of 50 mu m provide excellent anti-reflective and light trapping properties over a wide wavelength range. The photodetector exhibits a peak detectivity of 1.9 x 10(8) cm.Hz(1/2)/W for the SWIR band at 77 K and operates at temperatures as high as 220 K. The SWIR photodetector on the Si platform demonstrated in this study is promising for future low-cost optical sensors and Si photonicsopen0

Activation and modulation of recombinant glycine and GABAA receptors by 4-halogenated analogues of propofol

BACKGROUND AND PURPOSE: Glycine receptors are important players in pain perception and movement disorders, and therefore an important therapeutic target. Glycine receptors can be modulated by the intravenous anesthetic propofol (2,6-diisopropylphenol); however, the drug is more potent, by at least one order of magnitude, on GABAA receptors. It has been proposed that halogenation of the propofol molecule generates compounds with selective enhancement of glycinergic modulatory properties. EXPERIMENTAL APPROACH: We synthesized 4-bromopropofol, 4-chloropropofol, and 4-fluoropropofol. The direct activating and modulatory effects of these drugs and propofol were compared on recombinant rat glycine and human GABAA receptors expressed in oocytes. Behavioral effects of the compounds were compared in the tadpole loss-of-righting assay. KEY RESULTS: The concentration-response curves for potentiation of homomeric α1, α2, and α3 glycine receptors were shifted to lower drug concentrations by 2-10-fold for the halogenated compounds. Direct activation by all compounds was minimal with all subtypes of the glycine receptor. The four compounds were essentially equally potent modulators of the α1β3γ2L GABAA receptor with EC50 s between 4 and 7 μM. The EC50 s for loss-of-righting in Xenopus tadpoles, a proxy for loss of consciousness and considered to be mediated by actions on GABAA receptors, ranged from 0.35 to 0.87 μM. Conclusions and Implications We confirm that halogenation of propofol more strongly affects modulation of homomeric glycine receptors than α1β3γ2L GABAA receptors. However, the effective concentrations of all tested halogenated compounds remained lower for GABAA receptors. We infer that 4-bromo-, 4-chloro, or 4-fluoropropofol are not selective homomeric glycine receptor modulators

Early Outcomes of MDR-TB Treatment in a High HIV-Prevalence Setting in Southern Africa

BACKGROUND: Little is known about treatment of multidrug-resistant tuberculosis (MDR-TB) in high HIV-prevalence settings such as sub-Saharan Africa. METHODOLOGY/PRINCIPAL FINDINGS: We did a retrospective analysis of early outcomes of the first cohort of patients registered in the Lesotho national MDR-TB program between July 21, 2007 and April 21, 2008. Seventy-six patients were included for analysis. Patient follow-up ended when an outcome was recorded, or on October 21, 2008 for those still on treatment. Fifty-six patients (74%) were infected with HIV; the median CD4 cell count was 184 cells/microl (range 5-824 cells/microl). By the end of the follow-up period, study patients had been followed for a median of 252 days (range 12-451 days). Twenty-two patients (29%) had died, and 52 patients (68%) were alive and in treatment. In patients who did not die, culture conversion was documented in 52/54 patients (96%). One patient had defaulted, and one patient had transferred out. Death occurred after a median of 66 days in treatment (range 12-374 days). CONCLUSIONS/SIGNIFICANCE: In a region where clinicians and program managers are increasingly confronted by drug-resistant tuberculosis, this report provides sobering evidence of the difficulty of MDR-TB treatment in high HIV-prevalence settings. In Lesotho, an innovative community-based treatment model that involved social and nutritional support, twice-daily directly observed treatment and early empiric use of second-line TB drugs was successful in reducing mortality of MDR-TB patients. Further research is urgently needed to improve MDR-TB treatment outcomes in high HIV-prevalence settings

IFNAR1-Signalling Obstructs ICOS-mediated Humoral Immunity during Non-lethal Blood-Stage Plasmodium Infection

Funding: This work was funded by a Career Development Fellowship (1028634) and a project grant (GRNT1028641) awarded to AHa by the Australian National Health & Medical Research Council (NHMRC). IS was supported by The University of Queensland Centennial and IPRS Scholarships. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD