Antleroma in a free-ranging white-tailed deer (Odocoileus virginianus).

A 2-year-old male free-ranging white-tailed deer (Odocoileus virginianus) was diagnosed with bilateral expansile tumors of antler origin. The deer was found dead by a landowner in High Springs, Florida. Two roughly spherical, multilobular, broad-based, bony, velvet-covered masses originated from each antler pedicle. These masses replaced or displaced many of the bones and soft tissues of the skull and extended through the left cribriform plate and the right petrous temporal bone, compressing portions of the brain. Microscopically, the masses closely resembled normal-growing antler, containing all the elements thereof but with areas of necrosis and hemorrhage suggestive of ischemi or trauma. Tumorlike outgrowths termed antleromas have been described in free-ranging and captive cervids and typically are associated with disruptions in the seasonal rise and fall of circulating testosterone necessary for normal antler growth, casting, and regeneration.

Ozanimod (RPC1063) is a potent sphingosine-1-phosphate receptor-1 (S1P1 ) and receptor-5 (S1P5 ) agonist with autoimmune disease-modifying activity.

BACKGROUND AND PURPOSE: Sphingosine1-phosphate (S1P) receptors mediate multiple events including lymphocyte trafficking, cardiac function, and endothelial barrier integrity. Stimulation of S1P1 receptors sequesters lymphocyte subsets in peripheral lymphoid organs, preventing their trafficking to inflamed tissue sites, modulating immunity. Targeting S1P receptors for treating autoimmune disease has been established in clinical studies with the non-selective S1P modulator, FTY720 (fingolimod, Gilenya™). The purpose of this study was to assess RPC1063 for its therapeutic utility in autoimmune diseases. EXPERIMENTAL APPROACH: The specificity and potency of RPC1063 (ozanimod) was evaluated for all five S1P receptors, and its effect on cell surface S1P1 receptor expression, was characterized in vitro. The oral pharmacokinetic (PK) parameters and pharmacodynamic effects were established in rodents, and its activity in three models of autoimmune disease (experimental autoimmune encephalitis, 2,4,6-trinitrobenzenesulfonic acid colitis and CD4(+) CD45RB(hi) T cell adoptive transfer colitis) was assessed. KEY RESULTS: RPC1063 was specific for S1P1 and S1P5 receptors, induced S1P1 receptor internalization and induced a reversible reduction in circulating B and CCR7(+) T lymphocytes in vivo. RPC1063 showed high oral bioavailability and volume of distribution, and a circulatory half-life that supports once daily dosing. Oral RPC1063 reduced inflammation and disease parameters in all three autoimmune disease models. CONCLUSIONS AND IMPLICATIONS: S1P receptor selectivity, favourable PK properties and efficacy in three distinct disease models supports the clinical development of RPC1063 for the treatment of relapsing multiple sclerosis and inflammatory bowel disease, differentiates RPC1063 from other S1P receptor agonists, and could result in improved safety outcomes in the clinic.

The first modern operating room in America.

The modern OR was a vital addition to aseptic technique and essential to the development of invasive surgery, and many people do not realize that it needed to be "invented." Gustav Neuber, William S. Halsted, Charles McBurney, and others pioneered the necessary changes in practices and the environment to protect the patient from infection. This article presents the history behind the evolvement of the modern OR and discusses changes in the structures of some facilities as awareness increased about the principles of asepsis.

A natural language parsing system for encoding admitting diagnoses.

Free-text or natural language documents make up an increasing part of the computerized medical record. While they do provide accessible clinical information to health care personnel, they fail to support processes that require clinical data coded according to a shared lexicon and data structure. We have developed a natural language parser that converts free-text admitting diagnoses into a coded form. This application has proven acceptably accurate in the experimental laboratory to warrant a test in the target clinical environment. Here we describe an approach to moving this research application into a production environment where it can contribute to the efforts of the Health Information Services Department. This transition is essential if the products of natural language understanding research are to contribute to patient care in a routine and sustainable way.

Development and evaluation of a computerized admission diagnoses encoding system.

Hospital information systems designed to support the needs of health care professionals include patient data entered using both freetext and precoded storage schemes. A major disadvantage of freetext storage schemes is that data captured in this format can only be presented as is to the user for review tasks. In the view of many health care scientists, natural language understanding systems capable of identifying, extracting, and encoding information contained in freetext data may provide the necessary tools to overcome this weakness. This paper describes the development and evaluation of a such a system designed to encode freetext admission diagnoses. This system combines both semantic and syntactic linguistic analysis techniques. Evaluation results demonstrate the overall performance of this system to be reasonable, accurately encoding approximately 76% of admission diagnoses. Inefficiencies are primarily due to the inability of this system to generate encodings in roughly 15% of test cases. When encodings are produced, however, accuracy equals that of the current manual coding method. With further modification, this application can partially automate the coding process.