The Shemita Effect, How a Jewish agricultural law prompted fear for Evangelical investors: Confirmation Bias and Bandwagoning in Action

This paper examines how Shemita, a Jewish agricultural law only applicable in Israel came to be viewed by Evangelical Christian Investors as a signal of a potential stock market crash in September, 2015 purportedly as a consequence of G-d’s displeasure with the United States. In 2014 Johnathan Cahn, a popular Evangelical preacher, published “The Shemita Effect†which claimed that the seven year Shemita cycle mirrored stock market patterns over the last 50 years and suggested an impending crash. This theory was quickly taken up by conservative Christian Evangelical media and at least one man was convinced enough to start an entire investment company based on it despite the fact that it is easily disproven using basic statistical analysis of freely available data. This bizarre incident illustrates confirmation bias and bandwagoning effects in action, amplified with religious fervor

Image-Level and Group-Level Models for Drosophila Gene Expression Pattern Annotation

Background: Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison. Results: We present a computational framework to perform anatomical keywords annotation for Drosophila gene expression images. The spatial sparse coding approach is used to represent local patches of images in comparison with the well-known bag-of-words (BoW) method. Three pooling functions including max pooling, average pooling and Sqrt (square root of mean squared statistics) pooling are employed to transform the sparse codes to image features. Based on the constructed features, we develop both an image-level scheme and a group-level scheme to tackle the key challenges in annotating Drosophila gene expression pattern images automatically. To deal with the imbalanced data distribution inherent in image annotation tasks, the undersampling method is applied together with majority vote. Results on Drosophila embryonic expression pattern images verify the efficacy of our approach. Conclusion: In our experiment, the three pooling functions perform comparably well in feature dimension reduction. The undersampling with majority vote is shown to be effective in tackling the problem of imbalanced data. Moreover, combining sparse coding and image-level scheme leads to consistent performance improvement in keywords annotation

A Mesh Generation and Machine Learning Framework for Drosophila Gene Expression Pattern Image Analysis

Background: Multicellular organisms consist of cells of many different types that are established during development. Each type of cell is characterized by the unique combination of expressed gene products as a result of spatiotemporal gene regulation. Currently, a fundamental challenge in regulatory biology is to elucidate the gene expression controls that generate the complex body plans during development. Recent advances in high-throughput biotechnologies have generated spatiotemporal expression patterns for thousands of genes in the model organism fruit fly Drosophila melanogaster. Existing qualitative methods enhanced by a quantitative analysis based on computational tools we present in this paper would provide promising ways for addressing key scientific questions. Results: We develop a set of computational methods and open source tools for identifying co-expressed embryonic domains and the associated genes simultaneously. To map the expression patterns of many genes into the same coordinate space and account for the embryonic shape variations, we develop a mesh generation method to deform a meshed generic ellipse to each individual embryo. We then develop a co-clustering formulation to cluster the genes and the mesh elements, thereby identifying co-expressed embryonic domains and the associated genes simultaneously. Experimental results indicate that the gene and mesh co-clusters can be correlated to key developmental events during the stages of embryogenesis we study. The open source software tool has been made available at http://compbio.cs.odu.edu/fly/. Conclusions: Our mesh generation and machine learning methods and tools improve upon the flexibility, ease-of-use and accuracy of existing methods

New resources for the Drosophila 4th chromosome : FRT101F enabled mitotic clones and Bloom syndrome helicase enabled meiotic recombination

Genes on the long arm of the Drosophila melanogaster 4th chromosome are difficult to study because the chromosome lacks mitotic and meiotic recombination. Without recombination numerous standard methods of genetic analysis are impossible. Here, we report new resources for the 4th. For mitotic recombination, we generated a chromosome with an FRT very near the centromere in 101F and a derivative that carries FRT101F with a distal ubiquitously expressed GAL80 transgene. This pair of chromosomes enables both unmarked and MARCM clones. For meiotic recombination, we demonstrate that a Bloom syndrome helicase and recombination defective double mutant genotype can create recombinant 4th chromosomes via female meiosis. All strains will be available to the community via the Bloomington Drosophila Stock Center. Additional resources for studies of the 4th are in preparation and will also be made available. The goal of the 4th Chromosome Resource Project is to accelerate the genetic analysis of protein-coding genes on the 4th, including the 44 genes with no demonstrated function. Studies of these previously inaccessible but largely conserved genes will close longstanding gaps in our knowledge of metazoan development and physiology.Peer reviewe

Distinct Molecular Evolutionary Mechanisms Underlie the Functional Diversification of the Wnt and TGFβ Signaling Pathways

The canonical Wnt pathway is one of the oldest and most functionally diverse of animal intercellular signaling pathways. Though much is known about loss-of-function phenotypes for Wnt pathway components in several model organisms, the question of how this pathway achieved its current repertoire of functions has not been addressed. Our phylogenetic analyses of 11 multigene families from five species belonging to distinct phyla, as well as additional analyses employing the 12 Drosophila genomes, suggest frequent gene duplications affecting ligands and receptors as well as co-evolution of new ligand–receptor pairs likely facilitated the expansion of this pathway’s capabilities. Further, several examples of recent gene loss are visible in Drosophila when compared to family members in other phyla. By comparison the TGFβ signaling pathway is characterized by ancient gene duplications of ligands, receptors, and signal transducers with recent duplication events restricted to the vertebrate lineage. Overall, the data suggest that two distinct molecular evolutionary mechanisms can create a functionally diverse developmental signaling pathway. These are the recent dynamic generation of new genes and ligand–receptor interactions as seen in the Wnt pathway and the conservative adaptation of ancient pre-existing genes to new roles as seen in the TGFβ pathway. From a practical perspective, the former mechanism limits the investigator’s ability to transfer knowledge of specific pathway functions across species while the latter facilitates knowledge transfer

A Mesh Generation and Machine Learning Framework for Drosophila Gene Expression Pattern Image Analysis

Background: Multicellular organisms consist of cells of many different types that are established during development. Each type of cell is characterized by the unique combination of expressed gene products as a result of spatiotemporal gene regulation. Currently, a fundamental challenge in regulatory biology is to elucidate the gene expression controls that generate the complex body plans during development. Recent advances in high-throughput biotechnologies have generated spatiotemporal expression patterns for thousands of genes in the model organism fruit fly Drosophila melanogaster. Existing qualitative methods enhanced by a quantitative analysis based on computational tools we present in this paper would provide promising ways for addressing key scientific questions. Results: We develop a set of computational methods and open source tools for identifying co-expressed embryonic domains and the associated genes simultaneously. To map the expression patterns of many genes into the same coordinate space and account for the embryonic shape variations, we develop a mesh generation method to deform a meshed generic ellipse to each individual embryo. We then develop a co-clustering formulation to cluster the genes and the mesh elements, thereby identifying co-expressed embryonic domains and the associated genes simultaneously. Experimental results indicate that the gene and mesh co-clusters can be correlated to key developmental events during the stages of embryogenesis we study. The open source software tool has been made available at http://compbio.cs.odu.edu/fly/. Conclusions: Our mesh generation and machine learning methods and tools improve upon the flexibility, ease-of-use and accuracy of existing methods

daf-7-related TGF-beta homologues from Trichostrongyloid nematodes show contrasting life-cycle expression patterns

OBJECTIVE: The transforming growth factor-β (TGF-β) gene family regulates critical processes in animal development, and plays a crucial role in regulating the mammalian immune response. We aimed to identify TGF-β homologues from two laboratory model nematodes (Heligmosomoides polygyrus and Nippostrongylus brasiliensis) and two major parasites of ruminant livestock (Haemonchus contortus and Teladorsagia circumcincta). METHODS: Parasite cDNA was used as a template for gene-specific PCR and RACE. RESULTS: Homologues of the TGH-2 subfamily were isolated, and found to differ in length (301, 152, 349 and 305 amino acids respectively), with variably truncated N-terminal pre-proteins. All contain conserved C-terminal active domains (>85% identical over 115 amino acids) containing 9 cysteine residues, as in C. elegans DAF-7, Brugia malayi TGH-2 and mammalian TGF-β. Surprisingly, only the H. contortus homologue retains a conventional signal sequence, absent from shorter proteins of other species. RT-PCR assays of transcription show that in H. contortus and N. brasiliensis expression is maximal in the infective larval stage, and very low in adult worms. In contrast, in H. polygyrus and T. circumcincta, tgh-2 transcription is higher in adults than infective larvae. CONCLUSION: The molecular evolution of this gene family in parasitic nematodes has diversified the pre-protein and life-cycle expression patterns of TGF-β homologues while conserving the structure of the active domain

Cross-Talk and Information Transfer in Mammalian and Bacterial Signaling

In mammalian and bacterial cells simple phosphorylation circuits play an important role in signaling. Bacteria have hundreds of two-component signaling systems that involve phosphotransfer between a receptor and a response regulator. In mammalian cells a similar pathway is the TGF-beta pathway, where extracellular TGF-beta ligands activate cell surface receptors that phosphorylate Smad proteins, which in turn activate many genes. In TGF-beta signaling the multiplicity of ligands begs the question as to whether cells can distinguish signals coming from different ligands, but transduced through a small set of Smads. Here we use information theory with stochastic simulations of networks to address this question. We find that when signals are transduced through only one Smad, the cell cannot distinguish between different levels of the external ligands. Increasing the number of Smads from one to two significantly improves information transmission as well as the ability to discriminate between ligands. Surprisingly, both total information transmitted and the capacity to discriminate between ligands are quite insensitive to high levels of cross-talk between the two Smads. Robustness against cross-talk requires that the average amplitude of the signals are large. We find that smaller systems, as exemplified by some two-component systems in bacteria, are significantly much less robust against cross-talk. For such system sizes phosphotransfer is also less robust against cross-talk than phosphorylation. This suggests that mammalian signal transduction can tolerate a high amount of cross-talk without degrading information content. This may have played a role in the evolution of new functionalities from small mutations in signaling pathways, allowed for the development of cross-regulation and led to increased overall robustness due to redundancy in signaling pathways. On the other hand the lack of cross-regulation observed in many bacterial two-component systems may partly be due to the loss of information content due to cross-talk

SMAD4 is a predictive marker for 5-fluorouracil-based chemotherapy in patients with colorectal cancer

The gene for the transducer of transforming growth factor-beta/bone morphogenetic protein signalling SMAD4, a potential suppressor of colorectal carcinogenesis, is located at the chromosomal region 18q21. In order to evaluate the clinical relevance of SMAD4 deletion, gene copy alterations were determined by copy dosage using real-time quantitative PCR in 202 colorectal tumour biopsies from a previous randomised study of adjuvant chemotherapy. Patients with normal SMAD4 diploidy turned out to have a three-fold higher benefit of 5-fluorouracil-based adjuvant chemotherapy with a border line significance (overall survival: 3.23, P=0.056; disease-free survival: 2.89, P=0.045). These data are consistent with the previous observation that patients whose cancer had retention of the 18q21 region had a significantly higher benefit from 5-fluorouracil-based therapy. Moreover, these results may provide a refinement at the gene level of the clinical relevance of 18q21 deletion, thereby suggesting SMAD4 as a predictive marker in colorectal cancer. This data also indicate that integrity of this component of the transforming growth factor-beta/bone morphogenetic protein signalling pathway may be a critical factor for benefit of chemotherapy in patients with colorectal cancer