Morphometric and Quantitative Behavioral Analysis of Inbred Medaka Lines

With advances in genotyping and cost-effective sequencing technologies, Genome-wide association studies (GWAS) have emerged as approaches to study the genetics of natural variation. GWAS are particularly useful when inbred lines are available (as once they are genotyped, these lines can be phenotyped multiple times) and also with the availability of automated image acquisition and analysis systems for rapid phenotyping. The objective of this thesis is to identify a variety of phenotypic traits from the inbred lines of the teleost fish Medaka (Oryzias latipes) which will then assist in the investigation of the genetic basis for such a variety. Medaka is chosen as the model organism because of the presence of still free living wild populations in Japan and East Asia and for the ability to generate new inbred strains from these wild fish. Moreover, Quantitative Trait Loci (QTL) analysis done so far on craniofacial traits in adult Medaka shows that a substantial genetic component underlies the variance seen between two inbred strains. In this study different southern and northern Japanese Medaka hatchlings at 10 days post fertilization (dpf) and 20 dpf were characterized. The focus is on the two elements that essentially define an organism: morphology and behavior. Gross morphological features were extracted and quantified using custom developed algorithms. In addition, behavioral patterns of the different inbred lines are studied since behavior provides a link and a perspective of how an organism relates to its environment. Specifically, locomotion, feeding, and prey capture behavior were analyzed and quantified. To our knowledge, this is the first characterization of prey capture behavior in Medaka. This behavior reveals interesting prey capture strategies and a comparison with a related teleost fish, the zebrafish, suggests that prey capture is not necessarily conserved. This combination of morphometric and behavioral features provides a large phenotype parameter set that will be used as a basis for genotyping to study the degree of polymorphism and to eventually establish a phenotype-genotype map for the inbred lines

Comparative Mining of B2C Web Sites by Discovering Web Database Schemas

Discovering potentially useful and previously unknown historical knowledge from heterogeneous E-Commerce (B2C) web site contents to answer comparative queries such as “list all laptop prices from Walmart and Staples between 2013 and 2015 including make, type, screen size, CPU power, year of make”, would require the difficult task of finding the schema of web documents from different web pages, extracting target information and performing web content data integration, building their virtual or physical data warehouse and mining from it. Automatic data extractors (wrappers) such as the WebOMiner system use data extraction techniques based on parsing the web page html source code into a document object model (DOM) tree, traversing the DOM for pattern discovery to recognize and extract different web data types (e.g., text, image, links, and lists). Some limitations of the existing systems include using complicated matching techniques such as tree matching, non-deterministic finite state automata (NFA), domain ontology and inability to answer complex comparative historical and derived queries. This thesis proposes building the WebOMiner_S which uses web structure and content mining approaches on the DOM¬ tree html code to simplify and make more easily extendable the WebOMiner system data extraction process. We propose to replace the use of NFA in the WebOMiner with a frequent structure finder algorithm which uses regular expression matching in Java XPATH parser with its methods to dynamically discover the most frequent structure (which is the most frequently repeated blocks in the html code represented as tags \u3c div class = “ ′′ \u3e) in the Dom tree. This approach eliminates the need for any supervised training or updating the wrapper for each new B2C web page making the approach simpler, more easily extendable and automated. Experiments show that the WebOMiner_S achieves a 100% precision and 100% recall in identifying the product records, 95.55% precision and 100% recall in identifying the data columns

Chronic constipation in the elderly: an unusual presentation of colonic dysmotility in an elderly patient.

Introduction. Chronic constipation is common in the elderly, and often no underlying pathology is found. Primary colonic dysmotility has been described in children but is rare in the elderly. Case report. We present an 82-year-old female with long standing constipation presenting acutely with large bowel obstruction. Laparotomy and Hartman's procedure was performed, and a grossly distended sigmoid colon was resected. Histology revealed a primary myopathic process. Conclusion. Primary colonic myopathy should be considered in elderly patients presenting with large bowel obstruction and a long preceding history of constipation, particularly when previous endoscopic examinations were normal

High‐Throughput Screening of Cell Transfection Enhancers Using Miniaturized Droplet Microarrays

DNA delivery is a powerful research tool for biological research and clinical therapies. However, many nonviral transfection reagents have relatively low transfection efficiency. It is hypothesized that by treating cells with small molecules, the transfection efficiency can be improved. However, in order to identify such transfection-enhancing molecules, thousands of molecules must be tested. Current high-throughput screening (HTS) technologies based on microtiter plates are not suitable for such screenings due to the prohibitively high costs of reagents and operation. Here, the use of the droplet microarray (DMA) platform to screen 774 FDA-approved drugs with CHO-K1, Jurkat and HEK293T cells is reported. The volume of individual aqueous compartments is 20 nL, requiring 0.84 mL of cell suspension and 200 pmoles of each drug (total 0.02 moles) to perform the screening. Thus, the requirement for cells and reagents is 2500 times less than that for the same experiment performed in 384-well plates. The results reveal the potential of the DMA platform as a more cost-effective and less labor-intensive approach to HTS. Furthermore, an increase (approximately two- to fivefold) in transfection efficiency is achieved by treating cells with some molecules. This study clearly demonstrates the potential of the DMA platform for miniaturization of biochemical and cellular HTS

Higginsianins A and B, two fungal diterpenoid α-pyrones with cytotoxic activity against human cancer cells

Two new diterpenoid α-pyrones, named higginsianins A and B, were isolated from the mycelium of the microbial fungus Colletotrichum higginsianum grown in liquid culture. In previous studies, we have shown that both compounds reduce viability of different types of cancer cells in culture. Here, we extend our previous observations and explore, at a deeper level, the cellular effects of higginsianins treatment. Higginisianins A and B reduce viability of A431, HeLa and H1299 cancer cells. Both compounds increase the level of the cell cycle inhibitor p21WAF and reduce the rate of cell proliferation. Cell cycle analyses reveal that higginsianins arrest cancer cells in S-phase. Furthermore, cells incubated with higginsianins reveal discrete γ-H2AX positive nuclear foci indicating the occurrence of DNA lesions. At longer incubation times, higginsianins induce massive cell detachment and non-apoptotic cell death. Human primary keratinocytes and spontaneously immortalized Hacat cells, a preneoplastic cell line model, are less sensitive to higginsianins effects. These findings suggest that higginsianins exhibit considerable cytotoxicity against a wide spectrum of malignant cells and may be considered as promising anticancer agents

Automated phenotype pattern recognition of zebrafish for high-throughput screening

Over the last years, the zebrafish (Danio rerio) has become a key model organism in genetic and chemical screenings. A growing number of experiments and an expanding interest in zebrafish research makes it increasingly essential to automatize the distribution of embryos and larvae into standard microtiter plates or other sample holders for screening, often according to phenotypical features. Until now, such sorting processes have been carried out by manually handling the larvae and manual feature detection. Here, a prototype platform for image acquisition together with a classification software is presented. Zebrafish embryos and larvae and their features such as pigmentation are detected automatically from the image. Zebrafish of 4 different phenotypes can be classified through pattern recognition at 72 h post fertilization (hpf), allowing the software to classify an embryo into 2 distinct phenotypic classes: wild-type versus variant. The zebrafish phenotypes are classified with an accuracy of 79–99% without any user interaction. A description of the prototype platform and of the algorithms for image processing and pattern recognition is presented

Droplet Microarray Based Screening Identifies Proteins for Maintaining Pluripotency of hiPSCs

Human induced pluripotent stem cells (hiPSCs) are crucial for disease modeling, drug discovery, and personalized medicine. Animal-derived materials hinderapplications of hiPSCs in medical fields. Thus, novel and well-defined substrate coatings capable of maintaining hiPSC pluripotency are important for advancing biomedical applications of hiPSCs. Here a miniaturized droplet microarray (DMA) platform to investigate 11 well-defined proteins, their 55 binary and 165 ternary combinations for their ability to maintainpluripotency of hiPSCs when applied as a surface coating, is used. Using this screening approach, ten protein group coatings are identified, which promote significantly higher NANOG expression of hiPSCs in comparison with Matrigel coating. With two of the identified coatings, long-term pluripotency maintenance of hiPSCs and subsequent differentiation into three germ layers are achieved. Compared with conventional high-throughput screening (HTS) in 96-well plates, the DMA platform uses only 83 µL of protein solution (0.83 µg total protein) and only ≈2.8 × 10$^5$ cells, decreasing the amount of proteins and cells ≈860 and 25-fold, respectively. The identified proteins will be essential for research and applications using hiPSCs, while the DMA platform demonstrates great potential for miniaturized HTS of scarce cells or expensive materials such as recombinant proteins