GP-Unet: Lesion Detection from Weak Labels with a 3D Regression Network

We propose a novel convolutional neural network for lesion detection from weak labels. Only a single, global label per image - the lesion count - is needed for training. We train a regression network with a fully convolutional architecture combined with a global pooling layer to aggregate the 3D output into a scalar indicating the lesion count. When testing on unseen images, we first run the network to estimate the number of lesions. Then we remove the global pooling layer to compute localization maps of the size of the input image. We evaluate the proposed network on the detection of enlarged perivascular spaces in the basal ganglia in MRI. Our method achieves a sensitivity of 62% with on average 1.5 false positives per image. Compared with four other approaches based on intensity thresholding, saliency and class maps, our method has a 20% higher sensitivity.Comment: Article published in MICCAI 2017. We corrected a few errors from the first version: padding, loss, typos and update of the DOI numbe

Soft eSkin:distributed touch sensing with harmonized energy and computing

Inspired by biology, significant advances have been made in the field of electronic skin (eSkin) or tactile skin. Many of these advances have come through mimicking the morphology of human skin and by distributing few touch sensors in an area. However, the complexity of human skin goes beyond mimicking few morphological features or using few sensors. For example, embedded computing (e.g. processing of tactile data at the point of contact) is centric to the human skin as some neuroscience studies show. Likewise, distributed cell or molecular energy is a key feature of human skin. The eSkin with such features, along with distributed and embedded sensors/electronics on soft substrates, is an interesting topic to explore. These features also make eSkin significantly different from conventional computing. For example, unlike conventional centralized computing enabled by miniaturized chips, the eSkin could be seen as a flexible and wearable large area computer with distributed sensors and harmonized energy. This paper discusses these advanced features in eSkin, particularly the distributed sensing harmoniously integrated with energy harvesters, storage devices and distributed computing to read and locally process the tactile sensory data. Rapid advances in neuromorphic hardware, flexible energy generation, energy-conscious electronics, flexible and printed electronics are also discussed. This article is part of the theme issue ‘Harmonizing energy-autonomous computing and intelligence’

MiR-155 has a protective role in the development of non-alcoholic hepatosteatosis in mice

Hepatic steatosis is a global epidemic that is thought to contribute to the pathogenesis of type 2 diabetes. MicroRNAs (miRs) are regulators that can functionally integrate a range of metabolic and inflammatory pathways in liver. We aimed to investigate the functional role of miR-155 in hepatic steatosis. Male C57BL/6 wild-type (WT) and miR-155−/− mice were fed either normal chow or high fat diet (HFD) for 6 months then lipid levels, metabolic and inflammatory parameters were assessed in livers and serum of the mice. Mice lacking endogenous miR-155 that were fed HFD for 6 months developed increased hepatic steatosis compared to WT controls. This was associated with increased liver weight and serum VLDL/LDL cholesterol and alanine transaminase (ALT) levels, as well as increased hepatic expression of genes involved in glucose regulation (Pck1, Cebpa), fatty acid uptake (Cd36) and lipid metabolism (Fasn, Fabp4, Lpl, Abcd2, Pla2g7). Using miRNA target prediction algorithms and the microarray transcriptomic profile of miR-155−/− livers, we identified and validated that Nr1h3 (LXRα) as a direct miR-155 target gene that is potentially responsible for the liver phenotype of miR-155−/− mice. Together these data indicate that miR-155 plays a pivotal role regulating lipid metabolism in liver and that its deregulation may lead to hepatic steatosis in patients with diabetes

Comparison of different NAT assays for the detection of microorganisms belonging to the class Mollicutes

Abstract Background Mollicutes detection can be cumbersome due to their slow growth in vitro. For this reason, the use of DNA based on generic molecular tests represents an alternative for rapid, sensitive and specific detection of these microorganism. For this reason, six previously described nucleic acid testing assays were compared to evaluate their ability to detect microorganisms belonging to the class Mollicutes. Methods A panel of 61 mollicutes, including representatives from the Mycoplasma, Acholeplasma, Mesoplasma, Spiroplasma and Ureaplasma genus, were selected to evaluate the sensitivity and specificity of these assays. A total of 21 non-mollicutes, including closely related non-mollicutes species, were used to evaluate specificity. Limits of detection were calculated to determine the analytical sensitivity of the assays. The two best performing assays were subsequently adapted into real-time PCR format, followed by melting curve analysis. Results Both assays performed satisfactorily, with a 100% specificity described for both assays. The detection limits were found to be between 10−4 and 10−5 dilutions, equivalent to 15 to 150 genome copies approximately. Based on our work, both van Kuppeveld and Botes real-time PCR assays were found to be the best performing tests in terms of sensitivity and specificity. Furthermore, Botes real-time PCR assay could detect phytoplasmas as well. Conclusions These assays can be very useful for the rapid, specific and sensitive screening cell line contaminants, clinical samples as well as detecting non-culturable, unknown species of mollicutes or mollicutes whose growth is slow or difficult

Ovarian cancer symptom awareness and anticipated delayed presentation in a population sample

Background: While ovarian cancer is recognised as having identifiable early symptoms, understanding of the key determinants of symptom awareness and early presentation is limited. A population-based survey of ovarian cancer awareness and anticipated delayed presentation with symptoms was conducted as part of the International Cancer Benchmarking Partnership (ICBP). Methods: Women aged over 50 years were recruited using random probability sampling (n = 1043). Computer-assisted telephone interviews were used to administer measures including ovarian cancer symptom recognition, anticipated time to presentation with ovarian symptoms, health beliefs (perceived risk, perceived benefits/barriers to early presentation, confidence in symptom detection, ovarian cancer worry), and demographic variables. Logistic regression analysis was used to identify the contribution of independent variables to anticipated presentation (categorised as < 3 weeks or ≥ 3 weeks). Results: The most well-recognised symptoms of ovarian cancer were post-menopausal bleeding (87.4%), and persistent pelvic (79.0%) and abdominal (85.0%) pain. Symptoms associated with eating difficulties and changes in bladder/bowel habits were recognised by less than half the sample. Lower symptom awareness was significantly associated with older age (p ≤ 0.001), being single (p ≤ 0.001), lower education (p ≤ 0.01), and lack of personal experience of ovarian cancer (p ≤ 0.01). The odds of anticipating a delay in time to presentation of ≥ 3 weeks were significantly increased in women educated to degree level (OR = 2.64, 95% CI 1.61 – 4.33, p ≤ 0.001), women who reported more practical barriers (OR = 1.60, 95% CI 1.34 – 1.91, p ≤ 0.001) and more emotional barriers (OR = 1.21, 95% CI 1.06 – 1.40, p ≤ 0.01), and those less confident in symptom detection (OR = 0.56, 95% CI 0.42 – 0.73, p ≤ 0.001), but not in those who reported lower symptom awareness (OR = 0.99, 95% CI 0.91 – 1.07, p = 0.74). Conclusions: Many symptoms of ovarian cancer are not well-recognised by women in the general population. Evidence-based interventions are needed not only to improve public awareness but also to overcome the barriers to recognising and acting on ovarian symptoms, if delays in presentation are to be minimised

Catastrophizing mediates the relationship between the personal belief in a just world and pain outcomes among chronic pain support group attendees

Health-related research suggests the belief in a just world can act as a personal resource that protects against the adverse effects of pain and illness. However, currently, little is known about how this belief, particularly in relation to one’s own life, might influence pain. Consistent with the suggestions of previous research, the present study undertook a secondary data analysis to investigate pain catastrophizing as a mediator of the relationship between the personal just world belief and chronic pain outcomes in a sample of chronic pain support group attendees. Partially supporting the hypotheses, catastrophizing was negatively correlated with the personal just world belief and mediated the relationship between this belief and pain and disability, but not distress. Suggestions for future research and intervention development are made

Extraordinarily high biomass benthic community on Southern Ocean seamounts

We describe a previously unknown assemblage of seamount-associated megabenthos that has by far the highest peak biomass reported in the deep-sea outside of vent communities. The assemblage was found at depths of 2–2.5 km on rocky geomorphic features off the southeast coast of Australia, in an area near the Sub-Antarctic Zone characterised by high rates of surface productivity and carbon export to the deep-ocean. These conditions, and the taxa in the assemblage, are widely distributed around the Southern mid-latitudes, suggesting the high-biomass assemblage is also likely to be widespread. The role of this assemblage in regional ecosystem and carbon dynamics and its sensitivities to anthropogenic impacts are unknown. The discovery highlights the lack of information on deep-sea biota worldwide and the potential for unanticipated impacts of deep-sea exploitation

Genome wide analysis of gene expression changes in skin from patients with type 2 diabetes

Non-healing chronic ulcers are a serious complication of diabetes and are a major healthcare problem. While a host of treatments have been explored to heal or prevent these ulcers from forming, these treatments have not been found to be consistently effective in clinical trials. An understanding of the changes in gene expression in the skin of diabetic patients may provide insight into the processes and mechanisms that precede the formation of non-healing ulcers. In this study, we investigated genome wide changes in gene expression in skin between patients with type 2 diabetes and non-diabetic patients using next generation sequencing. We compared the gene expression in skin samples taken from 27 patients (13 with type 2 diabetes and 14 non-diabetic). This information may be useful in identifying the causal factors and potential therapeutic targets for the prevention and treatment of diabetic related diseases

Precision Measurement of the Mass of the h_c(1P1) State of Charmonium

A precision measurement of the mass of the h_c(1P1) state of charmonium has been made using a sample of 24.5 million psi(2S) events produced in e+e- annihilation at CESR. The reaction used was psi(2S) -> pi0 h_c, pi0 -> gamma gamma, h_c -> gamma eta_c, and the reaction products were detected in the CLEO-c detector. Data have been analyzed both for the inclusive reaction and for the exclusive reactions in which eta_c decays are reconstructed in fifteen hadronic decay channels. Consistent results are obtained in the two analyses. The averaged results of the present measurements are M(h_c)=3525.28+-0.19 (stat)+-0.12(syst) MeV, and B(psi(2S) -> pi0 h_c)xB(h_c -> gamma eta_c)= (4.19+-0.32+-0.45)x10^-4. Using the 3PJ centroid mass, Delta M_hf(1P)= - M(h_c) = +0.02+-0.19+-0.13 MeV.Comment: 9 pages, available through http://www.lns.cornell.edu/public/CLNS/, submitted to PR