Learning to Address Intra-segment Misclassification in Retinal Imaging

Accurate multi-class segmentation is a long-standing challenge in medical imaging, especially in scenarios where classes share strong similarity. Segmenting retinal blood vessels in retinal photographs is one such scenario, in which arteries and veins need to be identified and differentiated from each other and from the background. Intra-segment misclassification, i.e. veins classified as arteries or vice versa, frequently occurs when arteries and veins intersect, whereas in binary retinal vessel segmentation, error rates are much lower. We thus propose a new approach that decomposes multi-class segmentation into multiple binary, followed by a binary-to-multi-class fusion network. The network merges representations of artery, vein, and multi-class feature maps, each of which are supervised by expert vessel annotation in adversarial training. A skip-connection based merging process explicitly maintains class-specific gradients to avoid gradient vanishing in deep layers, to favor the discriminative features. The results show that, our model respectively improves F1-score by 4.4%, 5.1%, and 4.2% compared with three state-of-the-art deep learning based methods on DRIVE-AV, LES-AV, and HRF-AV data sets. Code: https://github.com/rmaphoh/Learning-AVSegmentatio

Learning to Address Intra-segment Misclassification in Retinal Imaging

Accurate multi-class segmentation is a long-standing challenge in medical imaging, especially in scenarios where classes share strong similarity. Segmenting retinal blood vessels in retinal photographs is one such scenario, in which arteries and veins need to be identified and differentiated from each other and from the background. Intra-segment misclassification, i.e. veins classified as arteries or vice versa, frequently occurs when arteries and veins intersect, whereas in binary retinal vessel segmentation, error rates are much lower. We thus propose a new approach that decomposes multi-class segmentation into multiple binary, followed by a binary-to-multi-class fusion network. The network merges representations of artery, vein, and multi-class feature maps, each of which are supervised by expert vessel annotation in adversarial training. A skip-connection based merging process explicitly maintains class-specific gradients to avoid gradient vanishing in deep layers, to favor the discriminative features. The results show that, our model respectively improves F1-score by 4.4%, 5.1%, and 4.2% compared with three state-of-the-art deep learning based methods on DRIVE-AV, LES-AV, and HRF-AV data sets. Code: https://github.com/rmaphoh/Learning-AVSegmentatio

Increased Risk of Respiratory Mortality Associated with the High-Tech Manufacturing Industry: A 26-Year Study

Global high-tech manufacturers are mainly located in newly industrialized countries, raising concerns about adverse health consequences from industrial pollution for people living nearby. We investigated the ecological association between respiratory mortality and the development of Taiwan's high-tech manufacturing, taking into account industrialization and socioeconomic development, for 19 cities and counties-6 in the science park group and 13 in the control group-from 1982 to 2007. We applied a linear mixed-effects model to analyze how science park development over time is associated with age-adjusted and sex-specific mortality rates for asthma and chronic obstructive pulmonary disease (COPD). Asthma and female COPD mortality rates decreased in both groups, but they decreased 9%-16% slower in the science park group. Male COPD mortality rates increased in both groups, but the rate increased 10% faster in the science park group. Science park development over time was a significant predictor of death from asthma (p ≤ 0.0001) and COPD (p = 0.0212). The long-term development of clustered high-tech manufacturing may negatively affect nearby populations, constraining health advantages that were anticipated, given overall progress in living standards, knowledge, and health services. National governments should incorporate the long-term health effects on local populations into environmental impact assessments

Model study of tropospheric trace species distributions during PEM-West A

A three-dimensional mesoscale transport/photochemical model is used to study the transport and photochemical transformation of trace species over eastern Asia and western Pacific for the period from September 20 to October 6, 1991, of the Pacific Exploratory Mission-West A experiment. The influence of emissions from the continental boundary layer that was evident in the observed trace species distributions in the lower troposphere over the ocean is well simulated by the model. In the upper troposphere, species such as O3, NOy (total reactive nitrogen species), and SO2 which have a significant source in the stratosphere are also simulated well in the model, suggesting that the upper tropospheric abundances of these species are strongly influenced by stratospheric fluxes and upper tropospheric sources. In the case of SO2 the stratospheric flux is identified to be mostly from the Mount Pinatubo eruption. Concentrations in the upper troposphere for species such as CO and hydrocarbons, which are emitted in the continental boundary layer and have a sink in the troposphere, are significantly underestimated by the model. Two factors have been identified to contribute significantly to the underestimate: one is emissions upwind of the model domain (eastern Asia and western Pacific); the other is that vertical transport is underestimated in the model. Model results are also grouped by back trajectories to study the contrast between compositions of marine and continental air masses. The model-calculated altitude profiles of trace species in continental and marine air masses are found to be qualitatively consistent with observations. However, the difference in the median values of trace species between continental air and marine air is about twice as large for the observed values as for model results. This suggests that the model underestimates the outflow fluxes of trace species from the Asian continent and the Pacific rim countries to the ocean. Observed altitude profiles for species like CO and hydrocarbons show a negative gradient in continental air and a positive gradient in marine air. A mechanism which may be responsible for the altitude gradients is proposed

Electrophysiological modeling in generalized epilepsy using surface EEG and anatomical brain structures

Deep brain structures involve significantly in the pathology of brain diseases such as epilepsy, Alzheimer, and Parkinson. Physiological brain modeling has become an emerging approach to investigate the coupling dynamics of the brain activity ofthese diseases. We propose a method using the surface EEG signals integrated with the anatomical individual brain to build the electrophysiological model of the epileptic patient’s brain. The EEG-driven model is used to investigate the deep brain activities of 23 patients diagnosed with generalized epilepsy from CHB-MIT Scalp EEG Database. Significant changes in the electrical activities in hippocampus, accumbens, amygdala, provide us insights into the dynamics ofactive brain regions during epilepsy. All of these brain regions show the significant energy variation defined by 5 features (Mean, Max, Min, Standard deviation, Power spectral density) with the p-value < 0.05 in both pre-ictal vs ictal and ictal vs post-ictal. Such result shows the potential of using EEG as a tool to capture the deep brain activity of epilepsy and other diseases that alter deep brain structures. The proposed model may be used to enhance the sensitivity of detecting and predicting epilepsy, detect the progression of the brain lesion, and support the decision-making for a brain medical intervention

Coexistence of the topological state and a two-dimensional electron gas on the surface of Bi2Se3

Topological insulators are a recently discovered class of materials with fascinating properties: While the inside of the solid is insulating, fundamental symmetry considerations require the surfaces to be metallic. The metallic surface states show an unconventional spin texture, electron dynamics and stability. Recently, surfaces with only a single Dirac cone dispersion have received particular attention. These are predicted to play host to a number of novel physical phenomena such as Majorana fermions, magnetic monopoles and unconventional superconductivity. Such effects will mostly occur when the topological surface state lies in close proximity to a magnetic or electric field, a (superconducting) metal, or if the material is in a confined geometry. Here we show that a band bending near to the surface of the topological insulator Bi$_2$Se$_3$ gives rise to the formation of a two-dimensional electron gas (2DEG). The 2DEG, renowned from semiconductor surfaces and interfaces where it forms the basis of the integer and fractional quantum Hall effects, two-dimensional superconductivity, and a plethora of practical applications, coexists with the topological surface state in Bi$_2$Se$_3$. This leads to the unique situation where a topological and a non-topological, easily tunable and potentially superconducting, metallic state are confined to the same region of space.Comment: 12 pages, 3 figure

The relationship between the systemic inflammatory response, tumour proliferative activity, T-lymphocytic and macrophage infiltration, microvessel density and survival in patients with primary operable breast cancer

The significance of the inter-relationship between tumour and host local/systemic inflammatory responses in primary operable invasive breast cancer is limited. The inter-relationship between the systemic inflammatory response (pre-operative white cell count, C-reactive protein and albumin concentrations), standard clinicopathological factors, tumour T-lymphocytic (CD4+ and CD8+) and macrophage (CD68+) infiltration, proliferative (Ki-67) index and microvessel density (CD34+) was examined using immunohistochemistry and slide-counting techniques, and their prognostic values were examined in 168 patients with potentially curative resection of early-stage invasive breast cancer. Increased tumour grade and proliferative activity were associated with greater tumour T-lymphocyte (P&lt;0.05) and macrophage (P&lt;0.05) infiltration and microvessel density (P&lt;0.01). The median follow-up of survivors was 72 months. During this period, 31 patients died; 18 died of their cancer. On univariate analysis, increased lymph-node involvement (P&lt;0.01), negative hormonal receptor (P&lt;0.10), lower albumin concentrations (P&lt;0.01), increased tumour proliferation (P&lt;0.05), increased tumour microvessel density (P&lt;0.05), the extent of locoregional control (P&lt;0.0001) and limited systemic treatment (Pless than or equal to0.01) were associated with cancer-specific survival. On multivariate analysis of these significant covariates, albumin (HR 4.77, 95% CI 1.35–16.85, P=0.015), locoregional treatment (HR 3.64, 95% CI 1.04–12.72, P=0.043) and systemic treatment (HR 2.29, 95% CI 1.23–4.27, P=0.009) were significant independent predictors of cancer-specific survival. Among tumour-based inflammatory factors, only tumour microvessel density (P&lt;0.05) was independently associated with poorer cancer-specific survival. The host inflammatory responses are closely associated with poor tumour differentiation, proliferation and malignant disease progression in breast cancer

The Bantam microRNA Is Associated with Drosophila Fragile X Mental Retardation Protein and Regulates the Fate of Germline Stem Cells

Fragile X syndrome, a common form of inherited mental retardation, is caused by the loss of fragile X mental retardation protein (FMRP). We have previously demonstrated that dFmr1, the Drosophila ortholog of the fragile X mental retardation 1 gene, plays a role in the proper maintenance of germline stem cells in Drosophila ovary; however, the molecular mechanism behind this remains elusive. In this study, we used an immunoprecipitation assay to reveal that specific microRNAs (miRNAs), particularly the bantam miRNA (bantam), are physically associated with dFmrp in ovary. We show that, like dFmr1, bantam is not only required for repressing primordial germ cell differentiation, it also functions as an extrinsic factor for germline stem cell maintenance. Furthermore, we find that bantam genetically interacts with dFmr1 to regulate the fate of germline stem cells. Collectively, our results support the notion that the FMRP-mediated translation pathway functions through specific miRNAs to control stem cell regulation