Comparison of molecular signatures from multiple skin diseases identifies mechanisms of immunopathogenesis.

The ability to obtain gene expression profiles from human disease specimens provides an opportunity to identify relevant gene pathways, but is limited by the absence of data sets spanning a broad range of conditions. Here, we analyzed publicly available microarray data from 16 diverse skin conditions in order to gain insight into disease pathogenesis. Unsupervised hierarchical clustering separated samples by disease as well as common cellular and molecular pathways. Disease-specific signatures were leveraged to build a multi-disease classifier, which predicted the diagnosis of publicly and prospectively collected expression profiles with 93% accuracy. In one sample, the molecular classifier differed from the initial clinical diagnosis and correctly predicted the eventual diagnosis as the clinical presentation evolved. Finally, integration of IFN-regulated gene programs with the skin database revealed a significant inverse correlation between IFN-β and IFN-γ programs across all conditions. Our study provides an integrative approach to the study of gene signatures from multiple skin conditions, elucidating mechanisms of disease pathogenesis. In addition, these studies provide a framework for developing tools for personalized medicine toward the precise prediction, prevention, and treatment of disease on an individual level.

Automated segmentation of multiple red blood cells with digital holographic microscopy.

We present a method to automatically segment red blood cells (RBCs) visualized by digital holographic microscopy (DHM), which is based on the marker-controlled watershed algorithm. Quantitative phase images of RBCs can be obtained by using off-axis DHM along to provide some important information about each RBC, including size, shape, volume, hemoglobin content, etc. The most important process of segmentation based on marker-controlled watershed is to perform an accurate localization of internal and external markers. Here, we first obtain the binary image via Otsu algorithm. Then, we apply morphological operations to the binary image to get the internal markers. We then apply the distance transform algorithm combined with the watershed algorithm to generate external markers based on internal markers. Finally, combining the internal and external markers, we modify the original gradient image and apply the watershed algorithm. By appropriately identifying the internal and external markers, the problems of oversegmentation and undersegmentation are avoided. Furthermore, the internal and external parts of the RBCs phase image can also be segmented by using the marker-controlled watershed combined with our method, which can identify the internal and external markers appropriately. Our experimental results show that the proposed method achieves good performance in terms of segmenting RBCs and could thus be helpful when combined with an automated classification of RBCs.

Efficiency and significance of multiple vocal signals in sibling competition

Animals can compete for resources by displaying various acoustic signals that may differentially affect the outcome of competition. We propose the hypothesis that the most efficient signal to deter opponents should be the one that most honestly reveals motivation to compete. We tested this hypothesis in the barn owl (Tyto alba) in which nestlings produce more calls of longer duration than siblings to compete for priority access to the indivisible prey item their parents will deliver next. Because nestlings increase call rate to a larger extent than call duration when they become hungrier, call rate would signal more accurately hunger level. This leads us to propose three predictions. First, a high number of calls should be more efficient in deterring siblings to compete than long calls. Second, the rate at which an individual calls should be more sensitive to variation in the intensity of the sibling vocal competition than the duration of its calls. Third, call rate should influence competitors' vocalization for a longer period of time than call duration. To test these three predictions we performed playback experiments by broadcasting to singleton nestlings calls of varying durations and at different rates. According to the first prediction, singleton nestlings became less vocal to a larger extent when we broadcasted more calls compared to longer calls. In line with the second prediction, nestlings reduced vocalization rate to a larger extent than call duration when we broadcasted more or longer calls. Finally, call rate had a longer influence on opponent's vocal behavior than call duration. Young animals thus actively and differentially use multiple signaling components to compete with their siblings over parental resources.

Effect of neighborhood and plot size on experiments with multiple-harvest oleraceous crops

The objective of this work was to determine the efficiency of the Papadakis method on the quality evaluation of experiments with multiple-harvest oleraceous crops, and on the estimate of the covariate and the ideal plot size. Data from nine uniformity trials (five with bean pod, two with zucchini, and two with sweet pepper) and from one experiment with treatments (with sweet pepper) were used. Through the uniformity trials, the best way to calculate the covariate was defined and the optimal plot size was calculated. In the experiment with treatments, analyses of variance and covariance were performed, in which the covariate was calculated by the Papadakis method, and experimental precision was evaluated based on four statistics. The use of analysis of covariance with the covariate obtained by the Papadakis method increases the quality of experiments with multiple-harvest oleraceous crops and allows the use of smaller plot sizes. The best covariate is the one that considers a neighboring plot of each side of the reference plot.

Identification of Multiple Mechanisms of Resistance to Vemurafenib in a Patient with BRAFV600E-Mutated Cutaneous Melanoma Successfully Rechallenged after Progression.

PURPOSE: To investigate the mechanism(s) of resistance to the RAF-inhibitor vemurafenib, we conducted a comprehensive analysis of the genetic alterations occurring in metastatic lesions from a patient with a BRAF(V600E)-mutant cutaneous melanoma who, after a first response, underwent subsequent rechallenge with this drug. EXPERIMENTAL DESIGN: We obtained blood and tissue samples from a patient diagnosed with a BRAF(V600E)-mutant cutaneous melanoma that was treated with vemurafenib and achieved a near-complete response. At progression, he received additional lines of chemo/immunotherapy and was successfully rechallenged with vemurafenib. Exome and RNA sequencing were conducted on a pretreatment tumor and two subcutaneous resistant metastases, one that was present at baseline and previously responded to vemurafenib (PV1) and one that occurred de novo after reintroduction of the drug (PV2). A culture established from PV1 was also analyzed. RESULTS: We identified two NRAS-activating somatic mutations, Q61R and Q61K, affecting two main subpopulations in the metastasis PV1 and a BRAF alternative splicing, involving exons 4-10, in the metastasis PV2. These alterations, known to confer resistance to RAF inhibitors, were tumor-specific, mutually exclusive, and were not detected in pretreatment tumor samples. In addition, the oncogenic PIK3CA(H1047R) mutation was detected in a subpopulation of PV1, but this mutation did not seem to play a major role in vemurafenib resistance in this metastasis. CONCLUSIONS: This work describes the coexistence within the same patient of different molecular mechanisms of resistance to vemurafenib affecting different metastatic sites. These findings have direct implications for the clinical management of BRAF-mutant melanoma. Clin Cancer Res; 19(20); 5749-57. ©2013 AACR.

Multiple introductions boosted genetic diversity in the invasive range of black cherry (Prunus serotina; Rosaceae).

BACKGROUND AND AIMS: Black cherry (Prunus serotina) is a North American tree that is rapidly invading European forests. This species was introduced first as an ornamental plant, then it was massively planted by foresters in many countries, but its origins and the process of invasion remain poorly documented. Based on a genetic survey of both native and invasive ranges, the invasion history of black cherry was investigated by identifying putative source populations and then assessing the importance of multiple introductions on the maintenance of gene diversity. METHODS: Genetic variability and structure of 23 populations from the invasive range and 22 populations from the native range were analysed using eight nuclear microsatellite loci and five chloroplast DNA regions. KEY RESULTS: Chloroplast DNA diversity suggests there were multiple introductions from a single geographic region (the north-eastern United States). A low reduction of genetic diversity was observed in the invasive range for both nuclear and plastid genomes. High propagule pressure including both the size and number of introductions shaped the genetic structure in Europe and boosted genetic diversity. Populations from Denmark, The Netherlands, Belgium and Germany showed high genetic diversity and low differentiation among populations, supporting the hypothesis that numerous introduction events, including multiple individuals and exchanges between sites, have taken place during two centuries of plantation. CONCLUSIONS: This study postulates that the invasive black cherry has originated from east of the Appalachian Mountains (mainly the Allegheny plateau) and its invasiveness in north-western Europe is mainly due to multiple introductions containing high numbers of individuals.