Subjective figures and texture perception

A texture discrimination task using the Ehrenstein illusion demonstrates that subjective brightness effects can play an essential role in early vision. The subjectively bright regions of the Ehrenstein can be organized either as discs or as stripes, depending on orientation. The accuracy of discrimination between variants of the Ehrenstein and control patterns was a direct function of the presence of the illusory brightness stripes, being high when they were present and low otherwise. It is argued that neither receptive field structure nor spatial-frequency content can adequately account for these results. We suggest that the subjective brightness illusions, rather than being a high-level, cognitive aspect of vision, are in fact the result of an early visual process.     

Synergy of two thermophiles enables decomposition of poly-epsilon-caprolactone under composting conditions

The ultimate degradation (i.e. complete mineralization) of biodegradable polymers proceeds through hydrolysis to the production of degradation intermediates (primary degradation) that are then taken into the microbial cell and further degraded to CO2 and water. We first isolated thermophilic actinomycete (Streptomyces thermonitrificans PDS-1), which has the activity of ultimate degradability, from compost in which poly-epsilon-caprolactone (PCL) degraded vigorously. We next tried to investigate the detailed mechanisms of degradation of the PCL in compost by developing a new experimental method in which isolated microorganisms are used to inoculate sterilized compost raw materials containing PCL. It was confirmed that the ultimate degradation of PCL could not be achieved by the action of the strain PDS-1 alone, and that a supplementary microorganism (Bacillus licheniformis HA1) isolated from compost utilizes the degradation intermediates and also increases the activity of the other primary microorganism (PDS-1) by adjusting the pH. We could thus show experimental proof of synergy between two thermophiles in the ultimate degradation of a biodegradable polymer in compost.     

Effect of zooming on texture features of ultrasonic images

Background

The effect of age on common carotid artery diameter is unclear for varying atherosclerosis risk levels.

Methods

Cross-sectional data from the Atherosclerosis Risk in Communities Limited Access Data set were used to estimate the association of age with B-mode ultrasound common carotid artery diameter for three atherosclerosis risk levels. Based on information from clinical examinations, B-mode ultrasounds, questionnaires, blood and other tests, participants were categorized into three groups: pre-existing disease (prevalent stroke and/or coronary heart disease), high risk group (no pre-existing disease, but prevalent diabetes, hypertension, plaques/shadowing, body mass index >= 30, current smoking, or hyperlipidemia), and a low risk group (no pre-existing disease, no plaques/shadowing, and no major elevated risk factors). Multivariable linear regression analyses modeled the common carotid artery diameter relationship with age.

Results

Age was positively and significantly associated with common carotid artery diameter after risk factor adjustment in the overall sample, but age had a larger effect among persons with evidence of atherosclerosis (interaction p < 0.05). Each year of older age was associated with 0.03 mm larger diameter/year among persons with pre-existing disease, with 0.027 mm larger diameter/year in the high risk group, but only 0.017 mm/year among the low risk group. Results were qualitatively similar using plaques/shadowing status to indicate atherosclerosis severity.

Conclusion

The significant impact of age on common carotid artery diameter among low risk, middle-aged, black and white men and women suggests arterial remodelling may occur in the absence of identified risk factors. The significantly larger impact of age among persons with, compared to persons without identified atherosclerosis or its risk factors, suggests that arterial remodelling may be an indicator of exposure duration.     

Neural mechanisms of human texture processing: texture boundary detection and visual search

Texture of various appearances, geometric distortions, spatial frequency content and densities is utilized by the human visual system to segregate items from background and to enable recognition of complex geometric forms. For automatic, or pre-attentive, segmentation of a visual scene, sophisticated analysis and comparison of surface properties over wide areas of the visual field are required. We investigated the neural substrate underlying human texture processing, particularly the computational mechanisms of texture boundary detection. We present a neural network model which uses as building blocks model cortical areas that are bi-directionally linked to implement cycles of feedforward and feedback interaction for signal detection, hypothesis generation and testing within the infero-temporal pathway of form processing. In the spirit of Jake Beck's early investigations our model particularly builds upon two key hypotheses, namely that (i) texture segregation is based on boundary detection, rather than clustering homogeneous items, and (ii) texture boundaries are detected mainly on the basis of larger scenic contexts mediated by higher cortical areas, such as area V4. The latter constraint provides a basis for element grouping in accordance to the Gestalt laws of similarity and good continuation. It is shown through simulations that the model integrates a variety of psychophysical findings on texture processing and provides a link to the underlying physiology. The functional role of feedback processing is demonstrated by context dependent modulation of V1 cell activation, leading to sharply localized detection of texture boundaries. It furthermore explains why pre-attentive processing in visual search tasks can be directly linked to texture boundary processing as revealed by recent EEG studies on visual search.     

A new repeat-masking method enables specific detection of homologous sequences

Biological sequences are often analyzed by detecting homologous regions between them. Homology search is confounded by simple repeats, which give rise to strong similarities that are not homologies. Standard repeat-masking methods fail to eliminate this problem, and they are especially ill-suited to AT-rich DNA such as malaria and slime-mould genomes. We present a new repeat-masking method, tantan, which is motivated by the mechanisms that create simple repeats. This method thoroughly eliminates spurious homology predictions for DNA–DNA, protein–protein and DNA–protein comparisons. Moreover, it enables accurate homology search for non-coding DNA with extreme A + T composition.     

Selection of relevant features from amino acids enables development of robust classifiers

Machine learning (ML) has been extensively applied to develop models and to understand high-throughput data of biological processes. However, new ML models, trained with novel experimental results, are required to build regularly for more precise predictions. ML methods can build models from numeric data, whereas biological data are generally textual (DNA, protein sequences) or images and needs feature calculation algorithms to generate quantitative features. Programming skills along with domain knowledge are required to develop these algorithms. Therefore, the process of knowledge discovery through ML is decelerated due to lack of generic tools to construct features and to build models directly from the data. Hence, we developed a schema that calculates about 5,000 features, selects relevant features and develops protein classifiers from the training data. To demonstrate the general applicability and robustness of our method, fungal adhesins and nuclear receptor proteins were used for building classifiers which outperformed existing classifiers when tested on independent data. Next, we built a classifier for mitochondrial proteins of Plasmodium falciparum which causes human malaria because the latest corresponding classifiers are not publically accessible. Our classifier attained 98.18 % accuracy and 0.95 Matthews correlation coefficient by fivefold cross-validation and outperformed existing classifiers on independent test set. We implemented this schema as user-friendly and open source application Pro-Gyan (http://code.google.com/p/pro-gyan/), to build and share executable classifiers without programming knowledge.     

Molecular characteristics and chromatin texture features in acute promyelocytic leukemia

Background

Ezrin is a cytoskeletal protein that is involved in tumor growth and invasion. It has been suggested that Ezrin expression plays an important role in tumor metastasis. This study is aimed to investigate the clinicopathological significance of Ezrin overexpression in gastric adenocarcinomas.

Methods

Ezrin protein expression was examined by immunohistochemistry in 26 normal gastric mucosa, 32 dysplasia, and 277 gastric adenocarcinomas. The relationship between Ezrin expression and the clinicopathological features of gastric cancers was analyzed. In addition, a gastric cancer cell line, MKN-1, was also used for immunofluorescence staining to evaluate the distribution of Ezrin protein.

Results

Ezrin protein located in the cytoplasm and/or membrane in the migrating gastric cancer cells, and it mainly concentrated at the protrusion site; however, only cytoplasmic distribution was observed in the non-migrating cancer cells by immunofluorescence staining. The positive rate of Ezrin protein expression was significantly higher in gastric adenocarcinoma and dysplasia compared with that in the normal gastric mucosa. Moreover, expression frequency of Ezrin protein increased significantly in lymph node metastasis and late clinical stages. Consistently, strong expression of Ezrin was significantly correlated with poor prognosis of gastric cancer.

Conclusion

The detection of Ezrin expression can be used as the marker for early diagnosis and prognosis of gastric adenocarcinoma.

Virtual Slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/2303598677653946     

Interval-coded texture features for artifact rejection in automated cervical cytology

In order to improve the separation between abnormal cells and noncellular artifacts in the CERVIFIP automated cervical cytology prescreening system, 22 different object texture features were investigated. The features were all statistical parameters of the pixel density histograms or one-dimensional filtered values of central and border regions of the object images. The features were calculated for 231 images (100 cells and 131 artifacts) detected as Suspect Cells by the current CERVIFIP and were then tested in hierarchical and linear discriminant classifiers. After selecting the two best features for use in a hierarchical classifier, 83% correct classification was achieved. One of these features was specifically designed to remove poorly focused objects. With maximum likelihood discrimination using all 22 features, an overall correct classification rate of 90% was obtained.     

Molecular characteristics and chromatin texture features in acute promyelocytic leukemia

ABSTRACT: BACKGROUND: Acute promyelocytic leukemia is a cytogenetically well defined entity. Nevertheless, some features observed at diagnosis are related to a worse outcome of the patients. METHODS: In a prospective study, we analyzed peripheral (PB) leukocyte count, immunophenotype, methylation status of CDKN2B, CDKN2A and TP73; FLT3 and NPM1 mutations besides nuclear chromatin texture characteristics of the leukemic cells. We also examined the relation of these features with patient's outcome. RESULTS: Among 19 cases, 4 had a microgranular morphology, 7 presented PB leukocytes >10x109/l, 2 had FLT3-ITD and 3 had FLT3-TKD (all three presenting a methylated CDKN2B). NPM1 mutation was not observed. PB leukocyte count showed an inverse relation with standard deviation of gray levels, contrast, cluster prominence, and chromatin fractal dimension (FD). Cases with FLT3-ITD presented a microgranular morphology, PB leukocytosis and expression of HLA-DR, CD34 and CD11b. Concerning nuclear chromatin texture variables, these cases had a lower entropy, contrast, cluster prominence and FD, but higher local homogeneity, and R245, in keeping with more homogeneously distributed chromatin. In the univariate Cox analysis, a higher leukocyte count, FLT3-ITD mutation, microgranular morphology, methylation of CDKN2B, besides a higher local homogeneity of nuclear chromatin, a lower chromatin entropy and FD were associated to a worse outcome. All these features lost significance when the cases were stratified for FLT3-ITD mutation. Methylation status of CDNK2A and TP73 showed no relation to patient's survival. CONCLUSION: in APL, patients with FLT3-ITD mutation show different clinical characteristics and have blasts with a more homogeneous chromatin texture. Texture analysis demonstrated that FLTD-ITD was accompanied not only by different cytoplasmic features, but also by a change in chromatin structure in routine cytologic preparations. Yet we were not able to detect chromatin changes by nuclear texture analysis of patients with the FTLD-TKD or methylation of specific genes. Virtual slides http://www.diagnosticpathology.diagnomx.eu/vs/1911416096708265.     

Amplifying the fluorescence of bilirubin enables the real-time detection of heme oxygenase activity

Heme oxygenases (HO) are the rate-limiting enzymes in the degradation of heme to equimolar amounts of antioxidant bile pigments, the signaling molecule carbon monoxide, and ferric iron. The inducible form HO-1 confers protection on cells and tissues that mediates beneficial effects in many diseases. Consequently, measurement of the enzymatic activity is vital in the investigation of the regulatory role of HO. Here we report that the fluorescence characteristics of bilirubin in complex with serum albumin can be used for the real-time detection of HO activity in enzymatic kinetics measurements. We characterized the enzymatic activity of a truncated human HO-1 and measured the HO activity for various cell types and organs, in either the basal naive or the HO-1-induced state. The bilirubin-dependent increase in fluorescence over time monitored by this assay facilitates a very fast, sensitive, and reliable measurement of HO activity. Our approach offers the basis for a highly sensitive high-throughput screening, which provides, inter alia, the opportunity to discover new therapeutic HO-1-inducing agents.     

Horseradish peroxidase embedded in polyacrylamide nanoparticles enables optical detection of reactive oxygen species

We have synthesized and characterized new nanometer-sized polyacrylamide particles containing horseradish peroxidase and fluorescent dyes. Proteins and dyes are encapsulated by radical polymerization in inverse microemulsion. The activity of the encapsulated enzyme has been examined and it maintains its ability to catalyze the oxidation of guaiacol with hydrogen peroxide as the electron acceptor, although at a slightly lower rate compared to that of the free enzyme in solution. The embedded enzyme is also capable of catalyzing the peroxidase-oxidase reaction. However, the rate is decreased by a factor of 2-3 compared to that of the free enzyme. The reduced rate is probably due to limitation of diffusion of substrates and products into and out of the particles. The catalytic activity of horseradish peroxidase in the polyacrylamide matrix demonstrates that the particles have pores which are large enough for substrates to enter and products to leave the polymer matrix containing the enzyme. The polymer matrix protects the embedded enzyme from proteolytic digestion, which is demonstrated by treating the particles with a mixture of the two proteases trypsin and proteinase K. The particles allow for quantification of hydrogen peroxide and other reactive oxygen species in microenvironments, and we propose that the particles may find use as nanosensors for use in, e.g., living cells.     

Image texture features for cell nuclei based on absorbance surface curvature

The absorbance values of a cell nucleus, as measured at each pixel location, can be considered as forming a surface in a three-dimensional space. The principal curvatures of differential geometry can then be evaluated for this surface. From these curvatures, two new variables are computed that, when averaged over all pixels in the nucleus, are viewed as image texture measures. These two measures were found to be effective for differentiating insect populations and compared well with other features used in the TICAS system. This paper presents the results of comparing the performance of these two features with the performance of other features for several populations of cells.     

Probability-based particle detection that enables threshold-free and robust in vivo single-molecule tracking

Single-molecule detection in fluorescence nanoscopy has become a powerful tool in cell biology but can present vexing issues in image analysis, such as limited signal, unspecific background, empirically set thresholds, image filtering, and false-positive detection limiting overall detection efficiency. Here we present a framework in which expert knowledge and parameter tweaking are replaced with a probability-based hypothesis test. Our method delivers robust and threshold-free signal detection with a defined error estimate and improved detection of weaker signals. The probability value has consequences for downstream data analysis, such as weighing a series of detections and corresponding probabilities, Bayesian propagation of probability, or defining metrics in tracking applications. We show that the method outperforms all current approaches, yielding a detection efficiency of >70% and a false-positive detection rate of <5% under conditions down to 17 photons/pixel background and 180 photons/molecule signal, which is beneficial for any kind of photon-limited application. Examples include limited brightness and photostability, phototoxicity in live-cell single-molecule imaging, and use of new labels for nanoscopy. We present simulations, experimental data, and tracking of low-signal mRNAs in yeast cells.     

Chromatin structure analysis enables detection of DNA insertions into the mammalian nuclear genome

BackgroundGenetically modified organisms (GMOs) have numerous biomedical, agricultural and environmental applications. Development of accurate methods for the detection of GMOs is a prerequisite for the identification and control of authorized and unauthorized release of these engineered organisms into the environment and into the food chain. Current detection methods are unable to detect uncharacterized GMOs, since either the DNA sequence of the transgene or the amino acid sequence of the protein must be known for DNA-based or immunological-based detection, respectively.MethodsHere we describe the application of an epigenetics-based approach for the detection of mammalian GMOs via analysis of chromatin structural changes occurring in the host nucleus upon the insertion of foreign or endogenous DNA.ResultsImmunological methods combined with DNA next generation sequencing enabled direct interrogation of chromatin structure and identification of insertions of various size foreign (human or viral) DNA sequences, DNA sequences often used as genome modification tools (e.g. viral sequences, transposon elements), or endogenous DNA sequences into the nuclear genome of a model animal organism.ConclusionsThe results provide a proof-of-concept that epigenetic approaches can be used to detect the insertion of endogenous and exogenous sequences into the genome of higher organisms where the method of genetic modification, the sequence of inserted DNA, and the exact genomic insertion site(s) are unknown.General significanceMeasurement of chromatin dynamics as a sensor for detection of genomic manipulation and, more broadly, organism exposure to environmental or other factors affecting the epigenomic landscape are discussed.     

One-step fractionation of complex proteomes enables detection of low abundant analytes using antibody-based microarrays

Antibody-based microarray is a novel technology with great promise within high-throughput proteomics. The tremendous complexity of all proteomes will, however, pose major technological challenges, especially when targeting low-abundant analytes that remains to be resolved. In this paper, we have shown that antibody microarrays readily could be used for screening of low-abundant low molecular weight analytes in complex proteomes by optimizing the sample format. Focused antibody microarrays, based on human recombinant single-chain Fv anti-cytokine antibodies on Ni2+-NTA functionalized glass slides or black polymer Maxisorp substrates, and crude cell supernatants from activated dendritic cells, containing low levels of secreted cytokines, was used for evaluation. The proteome was pre-fractionated based on size in a simple one-step procedure using centrifugal filter devices of various molecular weight cutoffs. The results showed that the generation of a nondiluted low molecular weight (LMW) fraction, corresponding to less than 2% of the original protein content, was critical for the successful screening of cytokines in the sub pg/mL range. The reduced complexity of the LMW fraction significantly improved the assay sensitivity, by improving the fluorescent tagging step and/or reducing the nonspecific binding to the substrates.     

Semiautomated image segmentation of bone marrow biopsies by texture features and mathematical morphology

OBJECTIVE: To present the preliminary results of a method for semiautomated detection of fat and hematopoietic cells as well as trabecular surfaces in bone marrow biopsies in order to calculate the percentage of each type of tissue or cell area in relation to the whole area. STUDY DESIGN: The results were derived from selected clinical cases. Twenty-six biopsies were used, presenting varied distributions of cellularity and trabecular topography. The approach is based on digital image processing techniques and pattern recognition methods using textural features obtained from biopsy images. The results were improved with mathematical morphology filters. RESULTS: A low computational cost algorithm is obtained that produces highly satisfactory results. The method is faster and more reproducible than conventional ones, such as region growing, edge detection, splitting and merging. CONCLUSION: The results with this computer-assisted technique were compared to those obtained by visual inspection by 2 expert pathologists, and differences of < 9% were observed.     

Use of multiple profiles corresponding to a sequence alignment enables effective detection of remote homologues

MOTIVATION: Position specific scoring matrices (PSSMs) corresponding to aligned sequences of homologous proteins are commonly used in homology detection. A PSSM is generated on the basis of one of the homologues as a reference sequence, which is the query in the case of PSI-BLAST searches. The reference sequence is chosen arbitrarily while generating PSSMs for reverse BLAST searches. In this work we demonstrate that the use of multiple PSSMs corresponding to a given alignment and variable reference sequences is more effective than using traditional single PSSMs and hidden Markov models. RESULTS: Searches for proteins with known 3-D structures have been made against three databases of protein family profiles corresponding to known structures: (1) One PSSM per family; (2) multiple PSSMs corresponding to an alignment and variable reference sequences for every family; and (3) hidden Markov models. A comparison of the performances of these three approaches suggests that the use of multiple PSSMs is most effective. CONTACT: ns@mbu.iisc.ernet.in.