University of Kansas

About: University of Kansas is a education organization based out in Lawrence, Kansas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 38183 authors who have published 81381 publications receiving 2986312 citations. The organization is also known as: KU & Univ of Kansas.

Development of a syngeneic mouse model for events related to ovarian cancer

Abstract: Mouse ovarian surface epithelial cells (MOSEC) were obtained from virgin, mature mice by mild trypsinization and were repeatedly passaged in vitro. Early passage cells (<20 passages) exhibited a cobblestone morphology and contact inhibition of growth. After approximately 20 passages in vitro, cobblestone morphology and contact inhibition of growth was lost. Tumor forming potential was determined by s.c. and i.p. injection of early and late passage cells into athymic and syngeneic C57BL6 mice. Subcutaneous tumors formed in approximately 4 months and were present only at the injection site. Intraperitoneal injection of late passage MOSEC into athymic and syngeneic mice resulted in growth of tumor implants throughout the abdominal cavity, and production of hemorrhagic ascitic fluid. Early passage MOSEC did not form tumors in vivo. Histopathologic analysis of tumors revealed a highly malignant neoplasm containing both carcinomatous and sarcomatous components. Late passage MOSEC expressed cytokeratin and did not produce ovarian steroids in response to gonadotropin stimulation in vitro. Ten clonal lines were established from late passage MOSEC. Each clone formed multiple peritoneal tumors and ascitic fluid after i.p. injection into C57BL6 mice. Three cell lines examined cytogenetically were polyploid with near-tetraploid modal chromosome numbers. Common clonal chromosome gains and losses included +5, +15, +19 and -X, -3, -4. One cell line had a clonal translocation between chromosomes 15 and 18 and another had a small marker chromosome; common structural abnormalities were not observed. These data describe the development of a mouse model for the study of events related to ovarian cancer in humans. The ability of the MOSEC to form extensive tumors within the peritoneal cavity, similar to those seen in women with Stage III and IV cancer, and the ability of the MOSEC to produce tumors in mice with intact immune systems, makes this model unique for investigations of molecular and immune interactions in ovarian cancer development.

Ab initio modeling of small proteins by iterative TASSER simulations

Abstract: Predicting 3-dimensional protein structures from amino-acid sequences is an important unsolved problem in computational structural biology. The problem becomes relatively easier if close homologous proteins have been solved, as high-resolution models can be built by aligning target sequences to the solved homologous structures. However, for sequences without similar folds in the Protein Data Bank (PDB) library, the models have to be predicted from scratch. Progress in the ab initio structure modeling is slow. The aim of this study was to extend the TASSER (threading/assembly/refinement) method for the ab initio modeling and examine systemically its ability to fold small single-domain proteins. We developed I-TASSER by iteratively implementing the TASSER method, which is used in the folding test of three benchmarks of small proteins. First, data on 16 small proteins (< 90 residues) were used to generate I-TASSER models, which had an average Cα-root mean square deviation (RMSD) of 3.8A, with 6 of them having a Cα-RMSD < 2.5A. The overall result was comparable with the all-atomic ROSETTA simulation, but the central processing unit (CPU) time by I-TASSER was much shorter (150 CPU days vs. 5 CPU hours). Second, data on 20 small proteins (< 120 residues) were used. I-TASSER folded four of them with a Cα-RMSD < 2.5A. The average Cα-RMSD of the I-TASSER models was 3.9A, whereas it was 5.9A using TOUCHSTONE-II software. Finally, 20 non-homologous small proteins (< 120 residues) were taken from the PDB library. An average Cα-RMSD of 3.9A was obtained for the third benchmark, with seven cases having a Cα-RMSD < 2.5A. Our simulation results show that I-TASSER can consistently predict the correct folds and sometimes high-resolution models for small single-domain proteins. Compared with other ab initio modeling methods such as ROSETTA and TOUCHSTONE II, the average performance of I-TASSER is either much better or is similar within a lower computational time. These data, together with the significant performance of automated I-TASSER server (the Zhang-Server) in the 'free modeling' section of the recent Critical Assessment of Structure Prediction (CASP)7 experiment, demonstrate new progresses in automated ab initio model generation. The I-TASSER server is freely available for academic users http://zhang.bioinformatics.ku.edu/I-TASSER .

Overview of the DESI legacy imaging surveys

Abstract: The DESI Legacy Imaging Surveys (http://legacysurvey.org/) are a combination of three public projects (the Dark Energy Camera Legacy Survey, the Beijing–Arizona Sky Survey, and the Mayall z-band Legacy Survey) that will jointly image ≈14,000 deg2 of the extragalactic sky visible from the northern hemisphere in three optical bands (g, r, and z) using telescopes at the Kitt Peak National Observatory and the Cerro Tololo Inter-American Observatory. The combined survey footprint is split into two contiguous areas by the Galactic plane. The optical imaging is conducted using a unique strategy of dynamically adjusting the exposure times and pointing selection during observing that results in a survey of nearly uniform depth. In addition to calibrated images, the project is delivering a catalog, constructed by using a probabilistic inference-based approach to estimate source shapes and brightnesses. The catalog includes photometry from the grz optical bands and from four mid-infrared bands (at 3.4, 4.6, 12, and 22 μm) observed by the Wide-field Infrared Survey Explorer satellite during its full operational lifetime. The project plans two public data releases each year. All the software used to generate the catalogs is also released with the data. This paper provides an overview of the Legacy Surveys project.

2017 European League Against Rheumatism/American College of Rheumatology Classification Criteria for Adult and Juvenile Idiopathic Inflammatory Myopathies and Their Major Subgroups.

Abstract: Objective To develop and validate new classification criteria for adult and juvenile idiopathic inflammatory myopathies (IIM) and their major subgroups. Methods Candidate variables were assembled from published criteria and expert opinion using consensus methodology. Data were collected from 47 rheumatology, dermatology, neurology, and pediatric clinics worldwide. Several statistical methods were utilized to derive the classification criteria. Results Based on data from 976 IIM patients (74% adults; 26% children) and 624 non-IIM patients with mimicking conditions (82% adults; 18% children), new criteria were derived. Each item is assigned a weighted score. The total score corresponds to a probability of having IIM. Subclassification is performed using a classification tree. A probability cutoff of 55%, corresponding to a score of 5.5 (6.7 with muscle biopsy) “probable IIM,” had best sensitivity/specificity (87%/82% without biopsies, 93%/88% with biopsies) and is recommended as a minimum to classify a patient as having IIM. A probability of ≥90%, corresponding to a score of ≥7.5 (≥8.7 with muscle biopsy), corresponds to “definite IIM.” A probability of <50%, corresponding to a score of <5.3 (<6.5 with muscle biopsy), rules out IIM, leaving a probability of ≥50–<55% as “possible IIM.” Conclusion The European League Against Rheumatism/American College of Rheumatology (EULAR/ACR) classification criteria for IIM have been endorsed by international rheumatology, dermatology, neurology, and pediatric groups. They employ easily accessible and operationally defined elements, and have been partially validated. They allow classification of “definite,” “probable,” and “possible” IIM, in addition to the major subgroups of IIM, including juvenile IIM. They generally perform better than existing criteria.