Effect of ovariectomy on the progression of chronic kidney disease-mineral bone disorder (CKD-MBD) in female Cy/+ rats

Male Cy/+ rats have shown a relatively consistent pattern of progressive kidney disease development that displays multiple key features of late stage chronic kidney disease-mineral bone disorder (CKD-MBD), specifically the development of cortical bone porosity. However, progression of disease in female Cy/+ rats, assessed in limited studies, is more heterogeneous and to date has failed to show development of the CKD-MBD phenotype, thus limiting their use as a practical model of progressive CKD-MBD. Animal and human studies suggest that estrogen may be protective against kidney disease in addition to its established protective effect on bone. Therefore, in this study, we aimed to determine the effect of ovariectomy (OVX) on the biochemical and skeletal manifestations of CKD-MBD in Cy/+ female rats. We hypothesized that OVX would accelerate development of the biochemical and skeletal features of CKD-MBD in female Cy/+ rats, similar to those seen in male Cy/+ rats. Female Cy/+ rats underwent OVX (n = 8) or Sham (n = 8) surgery at 15 weeks of age. Blood was collected every 5 weeks post-surgery until 35 weeks of age, when the rats underwent a 4-day metabolic balance, and the tibia and final blood were collected at the time of sacrifice. OVX produced the expected changes in trabecular and cortical parameters consistent with post-menopausal disease, and negative phosphorus balance compared with Sham. However, indicators of CKD-MBD were similar between OVX and Sham (similar kidney weight, plasma blood urea nitrogen, creatinine, creatinine clearance, phosphorus, calcium, parathyroid hormone, and no cortical porosity). Contrary to our hypothesis, OVX did not produce evidence of development of the CKD-MBD phenotype in female Cy/+ rats

Design and Data Management System

The Design and Data Management System (DDMS) was developed to automate the NASA Engineering Order (EO) and Engineering Change Request (ECR) processes at the Propulsion Test Facilities at Stennis Space Center for efficient and effective Configuration Management (CM). Prior to the development of DDMS, the CM system was a manual, paper-based system that required an EO or ECR submitter to walk the changes through the acceptance process to obtain necessary approval signatures. This approval process could take up to two weeks, and was subject to a variety of human errors. The process also requires that the CM office make copies and distribute them to the Configuration Control Board members for review prior to meetings. At any point, there was a potential for an error or loss of the change records, meaning the configuration of record was not accurate. The new Web-based DDMS eliminates unnecessary copies, reduces the time needed to distribute the paperwork, reduces time to gain the necessary signatures, and prevents the variety of errors inherent in the previous manual system. After implementation of the DDMS, all EOs and ECRs can be automatically checked prior to submittal to ensure that the documentation is complete and accurate. Much of the configuration information can be documented in the DDMS through pull-down forms to ensure consistent entries by the engineers and technicians in the field. The software also can electronically route the documents through the signature process to obtain the necessary approvals needed for work authorization. The workflow of the system allows for backups and timestamps that determine the correct routing and completion of all required authorizations in a more timely manner, as well as assuring the quality and accuracy of the configuration documents

Top-Ranked Priority Research Questions for Soil Science in the 21st Century

Soils provide critical support essential for life on earth, regulate processes across diverse terrestrial and aquatic ecosystems, and interact with the atmosphere. However, soil science is constrained by a variety of challenges including decreasing funding prospects and a declining number of new students and young professionals. Hence, there is a crucial need to revitalize the impact, relevance, and recognition of soil science as well as promote collaboration beyond traditionally defined soil science research disciplines. Such revitalization and collaboration may be fostered by a shift from discipline-focused soil science research to cross-disciplinary research approaches and issue-driven research. In this paper, we present the outcomes of an initiative to identify priority research questions as a tool for guiding future soil science research. The collaborative approach involved four stages including (i) survey-based solicitation of questions; (ii) criteria-based screening of submitted candidate questions, (iii) criteria-based ranking of screened questions, and (iv) final revision of top ranked questions. The 25 top ranked research questions emerged from 140 submitted candidate questions within five predetermined thematic areas that represent current and emerging research areas. We expect that the identified questions will inspire both existing and prospective researchers, enhance multi-disciplinary collaboration both within and outside soil science, draw the attention of grant-awarding bodies, and guide soil science research to address pressing societal, agricultural, and environmental challenges. Furthermore, we hope that the approach and findings presented in this paper will advance soil sciences by fostering improved collaboration among soil science practitioners and researchers, as well as with other sciences, policy experts, and emerging professionals (including students) to meet societal needs

Finding Aid to the Collection of Elizabeth Akers Allen Materials

This collection includes correspondence, manuscripts, and first publications of Maine writer, Elizabeth Akers Allen. The bulk of the collection consists of manuscripts and published writings written by Allen between 1846 and 1906. The collection also contains correspondence, an Autograph book, clippings, and a few photographic prints. Elizabeth Akers Allen grew up in Farmington, Maine, and first published a volume of poems under the pen name Florence Percy. She traveled through Europe as a journalist reporting for the Portland Transcript and Boston Evening Gazette, and was later a regular contributor to Atlantic Monthly

Statistical learning with phylogenetic network invariants

Phylogenetic networks provide a means of describing the evolutionary history of sets of species believed to have undergone hybridization or gene flow during their evolution. The mutation process for a set of such species can be modeled as a Markov process on a phylogenetic network. Previous work has shown that a site-pattern probability distributions from a Jukes-Cantor phylogenetic network model must satisfy certain algebraic invariants. As a corollary, aspects of the phylogenetic network are theoretically identifiable from site-pattern frequencies. In practice, because of the probabilistic nature of sequence evolution, the phylogenetic network invariants will rarely be satisfied, even for data generated under the model. Thus, using network invariants for inferring phylogenetic networks requires some means of interpreting the residuals, or deviations from zero, when observed site-pattern frequencies are substituted into the invariants. In this work, we propose a method of utilizing invariant residuals and support vector machines to infer 4-leaf level-one phylogenetic networks, from which larger networks can be reconstructed. Given data for a set of species, the support vector machine is first trained on model data to learn the patterns of residuals corresponding to different network structures to classify the network that produced the data. We demonstrate the performance of our method on simulated data from the specified model and primate data.Comment: 27 pages, 8 figure