Improving High Resolution Histology Image Classification with Deep Spatial Fusion Network

Histology imaging is an essential diagnosis method to finalize the grade and stage of cancer of different tissues, especially for breast cancer diagnosis. Specialists often disagree on the final diagnosis on biopsy tissue due to the complex morphological variety. Although convolutional neural networks (CNN) have advantages in extracting discriminative features in image classification, directly training a CNN on high resolution histology images is computationally infeasible currently. Besides, inconsistent discriminative features often distribute over the whole histology image, which incurs challenges in patch-based CNN classification method. In this paper, we propose a novel architecture for automatic classification of high resolution histology images. First, an adapted residual network is employed to explore hierarchical features without attenuation. Second, we develop a robust deep fusion network to utilize the spatial relationship between patches and learn to correct the prediction bias generated from inconsistent discriminative feature distribution. The proposed method is evaluated using 10-fold cross-validation on 400 high resolution breast histology images with balanced labels and reports 95% accuracy on 4-class classification and 98.5% accuracy, 99.6% AUC on 2-class classification (carcinoma and non-carcinoma), which substantially outperforms previous methods and close to pathologist performance.Comment: 8 pages, MICCAI workshop preceeding

Shape invariant potential formalism for photon-added coherent state construction

An algebro-operator approach, called shape invariant potential method, of constructing generalized coherent states for photon-added particle system is presented. Illustration is given on Poschl-Teller potential

Mechanical Resistance in Decapod Claw Denticles: Contribution of Structure and Composition

The decapod crustacean exoskeleton is a multi-layered structure composed of chitin-protein fibers embedded with calcium salts. Decapod claws display tooth-like denticles, which come into direct contact with predators and prey. They are subjected to more regular and intense mechanical stress than other parts of the exoskeleton and therefore must be especially resistant to wear and abrasion. Here, we characterized denticle properties in five decapod species. Dactyls from three brachyuran crabs (Cancer borealis, Callinectes sapidus, and Chionoecetes opilio) and two anomuran crabs (Paralomis birsteini and Paralithodes camtschaticus) were sectioned normal to the contact surface of the denticle, revealing the interior of the denticle and the bulk endocuticle in which it is embedded. Microhardness, micro- and ultrastructure, and elemental composition were assessed along a transect running the width of the cuticle using microindentation hardness testing, optical and electron microscopy (SEM), and energy dispersive X-ray spectroscopy (EDS), respectively. In all species tested, hardness was dramatically higher—up to ten times—in the denticle than in the bulk endocuticle. Likewise, in all species there was an increase in packing density of mineralized chitin-protein fibers, a decrease in width of the pore canals that run through the cuticle, and a decrease in phosphorous content from endocuticle to denticle. The changes in hardness across the cuticle, and the relationship between hardness, calcium, and magnesium content, however, varied among species. Although mechanical resistance of the denticles was exceptionally high in all species, the basis for resistance appears to differ among species

Deathly Drool: Evolutionary and Ecological Basis of Septic Bacteria in Komodo Dragon Mouths

Komodo dragons, the world's largest lizard, dispatch their large ungulate prey by biting and tearing flesh. If a prey escapes, oral bacteria inoculated into the wound reputedly induce a sepsis that augments later prey capture by the same or other lizards. However, the ecological and evolutionary basis of sepsis in Komodo prey acquisition is controversial. Two models have been proposed. The “bacteria as venom” model postulates that the oral flora directly benefits the lizard in prey capture irrespective of any benefit to the bacteria. The “passive acquisition” model is that the oral flora of lizards reflects the bacteria found in carrion and sick prey, with no relevance to the ability to induce sepsis in subsequent prey. A third model is proposed and analyzed here, the “lizard-lizard epidemic” model. In this model, bacteria are spread indirectly from one lizard mouth to another. Prey escaping an initial attack act as vectors in infecting new lizards. This model requires specific life history characteristics and ways to refute the model based on these characteristics are proposed and tested. Dragon life histories (some details of which are reported here) prove remarkably consistent with the model, especially that multiple, unrelated lizards feed communally on large carcasses and that escaping, wounded prey are ultimately fed on by other lizards. The identities and evolutionary histories of bacteria in the oral flora may yield the most useful additional insights for further testing the epidemic model and can now be obtained with new technologies

Patterns of longitudinal brain atrophy in the logopenic variant of primary progressive aphasia

The logopenic variant of primary progressive aphasia (PPA) is characterised by impaired sentence repetition and word retrieval difficulties. Post mortem studies, amyloid imaging and CSF tau/Aβ measurements suggest Alzheimer's disease (AD) pathology as the underlying cause. Relatively little is known about patterns of progression in patients with the logopenic variant of PPA. 21 patients (3 with post mortem confirmation of AD and 5 with positive amyloid PIB-PET scans) were studied with longitudinal T1-weighted MR imaging (mean interscan interval 1.2years) using volumetric analysis and voxel-based morphometry (VBM). Baseline imaging showed asymmetrical (left greater than right) involvement of the posterior superior temporal and inferior parietal lobes as well as posterior cingulate and medial temporal lobes. The whole brain rate of volume loss was 2.0% per year with a greater rate of left hemisphere atrophy (2.3%/year) than right hemisphere (1.6%/year). Longitudinal VBM analysis showed increasing involvement of other areas in the left hemisphere (temporal, parietal, frontal and caudate) and atrophy of areas in the right hemisphere that had been involved earlier in the disease in the left hemisphere, particularly posterior cingulate/precuneus. With disease progression there was worsening of anomia, sentence repetition and sentence comprehension but consistent with the spread of imaging changes also deficits in single word comprehension, single word repetition and verbal memory. This study shows that the logopenic variant of PPA remains an asymmetrical disease, with spread through the left hemisphere language network but also involvement to a lesser degree of regions in the right hemisphere that mirror the earlier left hemisphere changes

The central region of the msp gene of Treponema denticola has sequence heterogeneity among clinical samples, obtained from patients with periodontitis

<p>Abstract</p> <p>Background</p> <p><it>Treponema denticola </it>is an oral spirochete involved in the pathogenesis and progression of periodontal disease. Of its virulence factors, the major surface protein (MSP) plays a role in the interaction between the treponeme and host. To understand the possible evolution of this protein, we analyzed the sequence of the <it>msp </it>gene in 17 <it>T. denticola </it>positive clinical samples.</p> <p>Methods</p> <p>Nucleotide and amino acid sequence of MSP have been determined by PCR amplification and sequencing in seventeen <it>T. denticola </it>clinical specimens to evaluate the genetic variability and the philogenetic relationship of the <it>T. denticola msp </it>gene among the different amplified sequence of positive samples. In silico antigenic analysis was performed on each MSP sequences to determined possible antigenic variation.</p> <p>Results</p> <p>The <it>msp </it>sequences showed two highly conserved 5' and 3' ends and a central region that varies substantially. Phylogenetic analysis categorized the 17 specimens into 2 principal groups, suggesting a low rate of evolutionary variability and an elevated degree of conservation of <it>msp </it>in clinically derived genetic material. Analysis of the predicted antigenic variability between isolates, demonstrated that the major differences lay between amino acids 200 and 300.</p> <p>Conclusion</p> <p>These findings showed for the first time, the nucleotide and amino acids variation of the <it>msp </it>gene in infecting <it>T. denticola</it>, <it>in vivo</it>. This data suggested that the antigenic variability found in to the MSP molecule, may be an important factor involved in immune evasion by <it>T. denticola</it>.</p

Prediction of Antibacterial Activity from Physicochemical Properties of Antimicrobial Peptides

Consensus is gathering that antimicrobial peptides that exert their antibacterial action at the membrane level must reach a local concentration threshold to become active. Studies of peptide interaction with model membranes do identify such disruptive thresholds but demonstrations of the possible correlation of these with the in vivo onset of activity have only recently been proposed. In addition, such thresholds observed in model membranes occur at local peptide concentrations close to full membrane coverage. In this work we fully develop an interaction model of antimicrobial peptides with biological membranes; by exploring the consequences of the underlying partition formalism we arrive at a relationship that provides antibacterial activity prediction from two biophysical parameters: the affinity of the peptide to the membrane and the critical bound peptide to lipid ratio. A straightforward and robust method to implement this relationship, with potential application to high-throughput screening approaches, is presented and tested. In addition, disruptive thresholds in model membranes and the onset of antibacterial peptide activity are shown to occur over the same range of locally bound peptide concentrations (10 to 100 mM), which conciliates the two types of observations