Variable Combinations of Specific Ephrin Ligand/Eph Receptor Pairs Control Embryonic Tissue Separation

Ephrins and Eph receptors are involved in the establishment of vertebrate tissue boundaries. The complexity of the system is puzzling, however in many instances, tissues express multiple ephrins and Ephs on both sides of the boundary, a situation that should in principle cause repulsion between cells within each tissue. Although co-expression of ephrins and Eph receptors is widespread in embryonic tissues, neurons, and cancer cells, it is still unresolved how the respective signals are integrated into a coherent output. We present a simple explanation for the confinement of repulsion to the tissue interface: Using the dorsal ectoderm–mesoderm boundary of the Xenopus embryo as a model, we identify selective functional interactions between ephrin–Eph pairs that are expressed in partial complementary patterns. The combined repulsive signals add up to be strongest across the boundary, where they reach sufficient intensity to trigger cell detachments. The process can be largely explained using a simple model based exclusively on relative ephrin and Eph concentrations and binding affinities. We generalize these findings for the ventral ectoderm–mesoderm boundary and the notochord boundary, both of which appear to function on the same principles. These results provide a paradigm for how developmental systems may integrate multiple cues to generate discrete local outcomes.     

A Hybrid Color Space for Skin Detection Using Genetic Algorithm Heuristic Search and Principal Component Analysis Technique

Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space in terms of skin and face classification performance which can address issues like illumination variations, various camera characteristics and diversity in skin color tones has remained an open issue. This research proposes a new three-dimensional hybrid color space termed SKN by employing the Genetic Algorithm heuristic and Principal Component Analysis to find the optimal representation of human skin color in over seventeen existing color spaces. Genetic Algorithm heuristic is used to find the optimal color component combination setup in terms of skin detection accuracy while the Principal Component Analysis projects the optimal Genetic Algorithm solution to a less complex dimension. Pixel wise skin detection was used to evaluate the performance of the proposed color space. We have employed four classifiers including Random Forest, Naïve Bayes, Support Vector Machine and Multilayer Perceptron in order to generate the human skin color predictive model. The proposed color space was compared to some existing color spaces and shows superior results in terms of pixel-wise skin detection accuracy. Experimental results show that by using Random Forest classifier, the proposed SKN color space obtained an average F-score and True Positive Rate of 0.953 and False Positive Rate of 0.0482 which outperformed the existing color spaces in terms of pixel wise skin detection accuracy. The results also indicate that among the classifiers used in this study, Random Forest is the most suitable classifier for pixel wise skin detection applications.     

PtdIns(3,5)P2 is required for delivery of endocytic cargo into the multivesicular body

The endocytic pathway transports cargo from the plasma membrane to early endosomes, where certain cargoes are sorted to the late endosome/multivesicular body. Biosynthetic cargo destined for the lysosome is also trafficked through the multivesicular body. Once delivered to the multivesicular body, cargo destined for the interior of the lysosome is selectively sorted into vesicles that bud into the lumen of the multivesicular body. These vesicles are released into the lumen of the lysosome upon the fusion of the multivesicular body and lysosomal limiting membranes. The yeast protein Fab1, which catalyzes the production of phosphatidylinositol (3,5) bisphosphate [PtdIns(3,5)P₂], is necessary for proper sorting of biosynthetic cargo in the multivesicular body. Utilizing an endocytosis screen, we isolated a novel allele of FAB1 that contains a point mutation in the lipid kinase domain. Characterization of this allele revealed reduced PtdIns(3,5)P₂ production, altered vacuole morphology, and biosynthetic protein sorting defects. We also found that endocytosis of the plasma membrane protein Ste3 is partially blocked downstream of the internalization step, and that delivery of the dye FM4-64 to the vacuole is delayed in fab1 mutants. Additionally, Ste3 is not efficiently sorted into multivesicular body vesicles in fab1 mutants and instead localizes to the vacuolar limiting membrane. These data show that PtdIns(3,5)P₂ is necessary for proper trafficking and sorting of endocytic cargo through the late endosome/multivesicular body.     

Extremely high Tp53 mutation load in esophageal squamous cell carcinoma in Golestan Province, Iran

Background

Golestan Province in northeastern Iran has one of the highest incidences of esophageal squamous cell carcinoma (ESCC) in the world with rates over 50 per 100,000 person-years in both sexes. We have analyzed TP53 mutation patterns in tumors from this high-risk geographic area in search of clues to the mutagenic processes involved in causing ESCC.

Methodology/Principal Findings

Biopsies of 119 confirmed ESCC tumor tissue from subjects enrolled in a case-control study conducted in Golestan Province were analyzed by direct sequencing of TP53 exons 2 through 11. Immunohistochemical staining for p53 was carried out using two monoclonal antibodies, DO7 and 1801. A total of 120 TP53 mutations were detected in 107/119 cases (89.9%), including 11 patients with double or triple mutations. The mutation pattern was heterogeneous with infrequent mutations at common TP53 “hotspots” but frequent transversions potentially attributable to environmental carcinogens forming bulky DNA adducts, including 40% at bases known as site of mutagenesis by polycyclic aromatic hydrocarbons (PAHs). Mutations showed different patterns according to the reported temperature of tea consumption, but no variation was observed in relation to ethnicity, tobacco or opium use, and alcoholic beverage consumption or urban versus rural residence.

Conclusion/Significance

ESCC tumors in people from Golestan Province show the highest rate of TP53 mutations ever reported in any cancer anywhere. The heterogeneous mutation pattern is highly suggestive of a causative role for multiple environmental carcinogens, including PAHs. The temperature and composition of tea may also influence mutagenesis.     

Appropriate models for the management of infectious diseases

BackgroundMathematical models have become invaluable management tools for epidemiologists, both shedding light on the mechanisms underlying observed dynamics as well as making quantitative predictions on the effectiveness of different control measures. Here, we explain how substantial biases are introduced by two important, yet largely ignored, assumptions at the core of the vast majority of such models.ConclusionThis work aims to highlight that, when developing models for public health use, we need to pay careful attention to the intrinsic assumptions embedded within classical frameworks.     

Avoidable errors in the modelling of outbreaks of emerging pathogens, with special reference to Ebola

As an emergent infectious disease outbreak unfolds, public health response is reliant on information on key epidemiological quantities, such as transmission potential and serial interval. Increasingly, transmission models fit to incidence data are used to estimate these parameters and guide policy. Some widely used modelling practices lead to potentially large errors in parameter estimates and, consequently, errors in model-based forecasts. Even more worryingly, in such situations, confidence in parameter estimates and forecasts can itself be far overestimated, leading to the potential for large errors that mask their own presence. Fortunately, straightforward and computationally inexpensive alternatives exist that avoid these problems. Here, we first use a simulation study to demonstrate potential pitfalls of the standard practice of fitting deterministic models to cumulative incidence data. Next, we demonstrate an alternative based on stochastic models fit to raw data from an early phase of 2014 West Africa Ebola virus disease outbreak. We show not only that bias is thereby reduced, but that uncertainty in estimates and forecasts is better quantified and that, critically, lack of model fit is more readily diagnosed. We conclude with a short list of principles to guide the modelling response to future infectious disease outbreaks.     

Intrinsically generated coloured noise in laboratory insect populations

What are the mechanisms responsible for generating the erratic fluctuations observed in natural populations? This question has been at the centre of a long debate in contemporary ecology. The irregularities in the patterns of population abundance were initially mostly attributed to environmental factors. In the mid-1970s, however, it was proposed that these fluctuations may be generated intrinsically, by the underlying nonlinearities inherent in population processes. More recently, the focus of this argument has turned increasingly towards the statistical properties of population fluctuations, with many studies showing that ecological systems tend to be dominated by low-frequency or long-term dynamics, termed ''red'' noise. Currently, the source of the ''redness'' in ecological time-series is hotly debated, with the general consensus being that environmental variables are the major driving force. Here we show that three classic laboratory populations known to display irregular fluctuations also have reddened spectra. Furthermore, the dynamics of these populations show very well-defined generic scaling properties in the form of power laws. These results imply that long-term influences in ecological systems can be the product of intrinsic dynamics.