New Imaging Modalities in Bone

The digital era has witnessed an exponential growth in bone imaging as new modalities and analytic techniques improve the potential for noninvasive study of bone anatomy, physiology, and pathophysiology. Bone imaging very much lends itself to input across medical and engineering disciplines. It is in part a reflection of this multidisciplinary input that developments in the field of bone imaging over the past 30 years have in some respects outshone those in many other fields of medicine. These developments have resulted in much deeper knowledge of bone macrostructure and microstructure in osteoporosis and a much better understanding of the subtle changes that occur with age, concurrent disease, and treatment. This new knowledge is already being translated into improved day-to day clinical care with better recognition, treatment, and monitoring of the osteoporotic process. As “the more you know, the more you know you don’t know” certainly holds true with osteoporosis and bone disease, there is little doubt that further advances in bone imaging and analytical techniques will continue to hold center stage in osteoporosis and related research

DGIdb 5.0: Rebuilding the Drug-Gene Interaction Database for precision medicine and drug discovery platforms

The Drug-Gene Interaction Database (DGIdb, https://dgidb.org) is a publicly accessible resource that aggregates genes or gene products, drugs and drug-gene interaction records to drive hypothesis generation and discovery for clinicians and researchers. DGIdb 5.0 is the latest release and includes substantial architectural and functional updates to support integration into clinical and drug discovery pipelines. The DGIdb service architecture has been split into separate client and server applications, enabling consistent data access for users of both the application programming interface (API) and web interface. The new interface was developed in ReactJS, and includes dynamic visualizations and consistency in the display of user interface elements. A GraphQL API has been added to support customizable queries for all drugs, genes, annotations and associated data. Updated documentation provides users with example queries and detailed usage instructions for these new features. In addition, six sources have been added and many existing sources have been updated. Newly added sources include ChemIDplus, HemOnc, NCIt (National Cancer Institute Thesaurus), Drugs@FDA, HGNC (HUGO Gene Nomenclature Committee) and RxNorm. These new sources have been incorporated into DGIdb to provide additional records and enhance annotations of regulatory approval status for therapeutics. Methods for grouping drugs and genes have been expanded upon and developed as independent modular normalizers during import. The updates to these sources and grouping methods have resulted in an improvement in FAIR (findability, accessibility, interoperability and reusability) data representation in DGIdb

FIRE Spectroscopy of Five Late-type T Dwarfs Discovered with the Wide-field Infrared Survey Explorer

We present the discovery of five late-type T dwarfs identified with the Wide-field Infrared Survey Explorer (WISE). Low-resolution near-infrared spectroscopy obtained with the Magellan Folded-port InfraRed Echellette (FIRE) reveal strong water and methane absorption in all five sources, and spectral indices and comparison to spectral templates indicate classifications ranging from T5.5 to T8.5:. The spectrum of the latest-type source, WISE J1812+2721, is an excellent match to that of the T8.5 companion brown dwarf Wolf 940B. WISE-based spectrophotometric distance estimates place these T dwarfs at 12-13 pc from the Sun, assuming they are single. Preliminary fits of the spectral data to the atmosphere models of Saumon & Marley indicate effective temperatures ranging from 600 K to 930 K, both cloudy and cloud-free atmospheres, and a broad range of ages and masses. In particular, two sources show evidence of both low surface gravity and cloudy atmospheres, tentatively supporting a trend noted in other young brown dwarfs and exoplanets. In contrast, the high proper motion T dwarf WISE J2018-7423 exhibits a suppressed K-band peak and blue spectrophotometric J-K colors indicative of an old, massive brown dwarf; however, it lacks the broadened Y-band peak seen in metal-poor counterparts. These results illustrate the broad diversity of low-temperature brown dwarfs that will be uncovered with WISE.Comment: 19 pages, 13 figures; accepted for publication to Ap

Ecoregions and Subregions of Iowa: A Framework for Water Quality Assessment and Management

Ecoregion frameworks are valuable tools for inventorying and assessing environmental resources, for setting resource management goals, and for developing biological criteria and water quality standards. In a collaborative project between the Iowa Department of Natural Resources (DNR) and the U.S. Environmental Protection Agency (EPA), we have refined boundaries of the EPA\u27s five ecological regions of Iowa and defined six subregions of the Western Corn Belt Plains ecoregion within the state. Lists of candidate stream reference sites have been developed to date for the seven largest regions, and the sites were visited and evaluated by Iowa DNR and U.S. EPA personnel to determine their suitability for sampling aquatic biota. The Iowa DNR plans to use the ecoregions and reference sites to better understand regional variations in stream quality, to help define best-attainable conditions, to develop biological criteria, and as a framework to report on water quality

Unsupervised Domain Adaptation for Automated Knee Osteoarthritis Phenotype Classification

Purpose: The aim of this study was to demonstrate the utility of unsupervised domain adaptation (UDA) in automated knee osteoarthritis (OA) phenotype classification using a small dataset (n=50). Materials and Methods: For this retrospective study, we collected 3,166 three-dimensional (3D) double-echo steady-state magnetic resonance (MR) images from the Osteoarthritis Initiative dataset and 50 3D turbo/fast spin-echo MR images from our institute (in 2020 and 2021) as the source and target datasets, respectively. For each patient, the degree of knee OA was initially graded according to the MRI Osteoarthritis Knee Score (MOAKS) before being converted to binary OA phenotype labels. The proposed UDA pipeline included (a) pre-processing, which involved automatic segmentation and region-of-interest cropping; (b) source classifier training, which involved pre-training phenotype classifiers on the source dataset; (c) target encoder adaptation, which involved unsupervised adaption of the source encoder to the target encoder and (d) target classifier validation, which involved statistical analysis of the target classification performance evaluated by the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity and accuracy. Additionally, a classifier was trained without UDA for comparison. Results: The target classifier trained with UDA achieved improved AUROC, sensitivity, specificity and accuracy for both knee OA phenotypes compared with the classifier trained without UDA. Conclusion: The proposed UDA approach improves the performance of automated knee OA phenotype classification for small target datasets by utilising a large, high-quality source dataset for training. The results successfully demonstrated the advantages of the UDA approach in classification on small datasets.Comment: Junru Zhong and Yongcheng Yao share the same contribution. 17 pages, 4 figures, 4 table

DGIdb 2.0: Mining clinically relevant drug-gene interactions

The Drug–Gene Interaction Database (DGIdb, www. dgidb.org) is a web resource that consolidates dis-parate data sources describing drug–gene interac-tions and gene druggability. It provides an intuitive graphical user interface and a documented applica-tion programming interface (API) for querying these data. DGIdb was assembled through an extensive manual curation effort, reflecting the combined in-formation of twenty-seven sources. For DGIdb 2.0, substantial updates have been made to increase content and improve its usefulness as a resource for mining clinically actionable drug targets. Specif-ically, nine new sources of drug–gene interactions have been added, including seven resources specifi-cally focused on interactions linked to clinical trials. These additions have more than doubled the over-all count of drug–gene interactions. The total num-ber of druggable gene claims has also increased by 30%. Importantly, a majority of the unrestricted, publicly-accessible sources used in DGIdb are now automatically updated on a weekly basis, providing the most current information for these sources. Fi-nally, a new web view and API have been developed to allow searching for interactions by drug identifiers to complement existing gene-based search function-ality. With these updates, DGIdb represents a com-prehensive and user friendly tool for mining the druggable genome for precision medicine hypothe-sis generation

Combination vinorelbine and capecitabine for metastatic breast cancer using a non-body surface area dosing scheme

Purpose : This study sought to determine the maximum tolerated dose of flat-dosed vinorelbine in combination with capecitabine in patients with metastatic breast cancer. At the time of study initiation, it was anticipated that vinorelbine would be developed as an oral capsule. A flat dosing scheme of both drugs was used to facilitate development of the oral regimen, and because neither drug’s clearance is associated with body surface area (BSA), pharmacokinetic and pharmacogenetic endpoints were explored. Experimental Design : Capecitabine was administered orally at 3,000 mg/day on days 1–14. The starting dose of vinorelbine was 20 mg intravenously on days 1 and 8 of a 21-day cycle. The vinorelbine dose was escalated until dose limiting toxicity (DLT). Vinorelbine pharmacokinetics were measured after the first dose. Patients underwent genotype analysis for polymorphisms in the CYP3A5 gene, and the erythromycin breath test (ERMBT), a phenotypic test of CYP3A enzyme activity. Results : Twenty five eligible patients were enrolled. Hematologic DLT was seen at the 50 and 45 mg vinorelbine doses; thus the recommended dose is 40 mg on days 1 and 8. Response rate was 30%, and disease stabilization rate was 64% (all dose levels included). Vinorelbine clearance was not associated with ERMBT, BSA, or age. CYP3A5 genotype in this small sample did not have an obvious relationship to clearance or toxicity. Conclusions : A non-BSA based dosing scheme of capecitabine and vinorelbine is safe and efficacious. BSA did not affect vinorelbine clearance. We recommend future studies with capecitabine and/or vinorelbine to compare the safety and efficacy of flat dosed versus BSA-dosed treatment.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46933/1/280_2005_Article_132.pd

1987: Abilene Christian College Bible Lectures - Full Text

THE MIND OF CHRIST Being the Abilene Christian University Annual Bible Lectures 1987 Published by A.C.U. Press 1634 Campus Court Abilene, Texas 7960

Advanced Magnetic Resonance Imaging and Molecular Imaging of the Painful Knee

Chronic knee pain is a common condition. Causes of knee pain include trauma, inflammation, and degeneration, but in many patients the pathophysiology remains unknown. Recent developments in advanced magnetic resonance imaging (MRI) techniques and molecular imaging facilitate more in-depth research focused on the pathophysiology of chronic musculoskeletal pain and more specifically inflammation. The forthcoming new insights can help develop better targeted treatment, and some imaging techniques may even serve as imaging biomarkers for predicting and assessing treatment response in the future. This review highlights the latest developments in perfusion MRI, diffusion MRI, and molecular imaging with positron emission tomography/MRI and their application in the painful knee. The primary focus is synovial inflammation, also known as synovitis. Bone perfusion and bone metabolism are also addressed.</p