A design and implementation methodology for diagnostic systems

A methodology for design and implementation of diagnostic systems is presented. Also discussed are the advantages of embedding a diagnostic system in a host system environment. The methodology utilizes an architecture for diagnostic system development that is hierarchical and makes use of object-oriented representation techniques. Additionally, qualitative models are used to describe the host system components and their behavior. The methodology architecture includes a diagnostic engine that utilizes a combination of heuristic knowledge to control the sequence of diagnostic reasoning. The methodology provides an integrated approach to development of diagnostic system requirements that is more rigorous than standard systems engineering techniques. The advantages of using this methodology during various life cycle phases of the host systems (e.g., National Aerospace Plane (NASP)) include: the capability to analyze diagnostic instrumentation requirements during the host system design phase, a ready software architecture for implementation of diagnostics in the host system, and the opportunity to analyze instrumentation for failure coverage in safety critical host system operations

Diagnosis: Reasoning from first principles and experiential knowledge

Completeness, efficiency and autonomy are requirements for suture diagnostic reasoning systems. Methods for automating diagnostic reasoning systems include diagnosis from first principles (i.e., reasoning from a thorough description of structure and behavior) and diagnosis from experiential knowledge (i.e., reasoning from a set of examples obtained from experts). However, implementation of either as a single reasoning method fails to meet these requirements. The approach of combining reasoning from first principles and reasoning from experiential knowledge does address the requirements discussed above and can possibly ease some of the difficulties associated with knowledge acquisition by allowing developers to systematically enumerate a portion of the knowledge necessary to build the diagnosis program. The ability to enumerate knowledge systematically facilitates defining the program's scope, completeness, and competence and assists in bounding, controlling, and guiding the knowledge acquisition process

Polymorphisms of MUC16 (CA125) and MUC1 (CA15.3) in Relation to Ovarian Cancer Risk and Survival

Objective: To examine single nucleotide polymorphism (SNPs) in MUC16 (CA125) and MUC1 (CA15.3) in relation to ovarian cancer risk and survival. Methods: We genotyped germline variants of MUC16 (rs2547065, rs1559168, rs12984471, rs2121133) and MUC1 (rs2070803, rs4072037, rs1045253) using samples collected from 758 ovarian cancer cases and 788 controls enrolled in the New England Case-Control Study between 2003 and 2008. We calculated age-adjusted odds ratios (OR) and 95% confidence intervals (CIs) for disease risk using unconditional and polytomous logistic regression and hazard ratios (HR) for survival using Cox proportional hazard ratios. In a subset of cases, we compared log-normalized CA125 values by genotype using generalized linear models. Results: Cases homozygous for the variant allele of MUC16 SNP, rs12984471, had poorer overall survival (log-rank p = 0.03) and higher CA125 levels, especially cases over age 65 (p = 0.01). For MUC1 SNP, rs4072037, women homozygous for the G variant had a non-significantly decreased risk for serous invasive types but elevated risk for serous borderline tumors, mucinous borderline and invasive tumors, and endometrioid tumors. Women with the variant allele of MUC16 SNP, rs2547065, especially those who were homozygous had an elevated risk for ovarian cancer; but this association was not confirmed in an independent dataset. Conclusion: This targeted screen of seven polymorphisms of MUC16 and MUC1 genes failed to identify and confirm effects on ovarian cancer risk overall. However, there may be effects of MUC16 rs12984471 on survival and MUC1 rs4072037 on risk for histologic types of ovarian cancer other than invasive serous. Further study is warranted

Association of Prediabetes and Diabetes With Stroke Symptoms The REasons for Geographic And Racial Differences in Stroke (REGARDS) Study

OBJECTIVE Stroke symptoms among individuals reporting no physician diagnosis of stroke are associated with an increased risk of future stroke. Few studies have assessed whether individuals with diabetes or prediabetes, but no physician diagnosis of stroke, have an increased prevalence of stroke symptoms. RESEARCH DESIGN AND METHODS This study included 25,696 individuals aged ≥45 years from the REasons for Geographic And Racial Differences in Stroke (REGARDS) study who reported no history of stroke or transient ischemic attack at baseline (2003–2007). Glucose measurements, medication use, and self-reported physician diagnosis were used to categorize participants into diabetes, prediabetes, or normal glycemia groups. The presence of six stroke symptoms was assessed using a validated questionnaire. RESULTS The prevalence of any stroke symptom was higher among participants with diabetes (22.7%) compared with those with prediabetes (15.6%) or normal glycemia (14.9%). In multivariable models, diabetes was associated with any stroke symptom (prevalence odds ratio [POR] 1.28 [95% CI 1.18–1.39]) and two or more stroke symptoms (1.26 [1.12–1.43]) compared with normal glycemia. In analyses of individual stroke symptoms, diabetes was associated with numbness (1.15 [1.03–1.29]), vision loss (1.52 [1.31–1.76]), half-vision loss (1.54 [1.30–1.84]), and lost ability to understand people (1.34 [1.12–1.61]) after multivariable adjustment. No association was present between prediabetes and stroke symptoms. CONCLUSIONS In this population-based study, almost one in four individuals with diabetes reported stroke symptoms, which suggests that screening for stroke symptoms in diabetes may be warranted

Prospectus, September 23, 1991

https://spark.parkland.edu/prospectus_1991/1013/thumbnail.jp

Pennsylvania Folklife Vol. 41, No. 3

• Love, David • Studebaker and Stutz: The Evolution of Dunkard Entrepreneurs • Latches and Locks • H. L. Mencken and A Girl from Red Lion, PA • Mac E. Barrick (1933-1991): An Appreciation • Aldes un Neies (Old and New)https://digitalcommons.ursinus.edu/pafolklifemag/1134/thumbnail.jp

X-ray Structure of Gelatinase A Catalytic Domain Complexed with a Hydroxamate Inhibitor

Gelatinase A is a key enzyme in the family of matrix metalloproteinases (matrixins) that are involved in the degradation of the extracellular matrix. As this process is an integral part of tumour cell metastasis and angiogenesis, gelatinase is an important target for therapeutic intervention. The X-ray crystal structure of the gelatinase A catalytic domain (GaCD) complexed with batimastat (BB94), a hydroxamate inhibitor, shows an active site with a large S1\u27 specificity pocket. The structure is similar to previously solved structures of stromelysin catalytic domain (SCD) but with differences in VR1 and VR2, two surface-exposed loops on either side of the entrance to the active site. Comparison of GaCD with other members of the matrix metalloproteinase (MMP) family highlights the conservation of key secondary structural elements and the significant differences in the specificity pockets, knowledge of which should enhance our ability to design specific inhibitors for this important anticancer target

X-ray Structure of Gelatinase A Catalytic Domain Complexed with a Hydroxamate Inhibitor

Gelatinase A is a key enzyme in the family of matrix metalloproteinases (matrixins) that are involved in the degradation of the extracellular matrix. As this process is an integral part of tumour cell metastasis and angiogenesis, gelatinase is an important target for therapeutic intervention. The X-ray crystal structure of the gelatinase A catalytic domain (GaCD) complexed with batimastat (BB94), a hydroxamate inhibitor, shows an active site with a large S1\u27 specificity pocket. The structure is similar to previously solved structures of stromelysin catalytic domain (SCD) but with differences in VR1 and VR2, two surface-exposed loops on either side of the entrance to the active site. Comparison of GaCD with other members of the matrix metalloproteinase (MMP) family highlights the conservation of key secondary structural elements and the significant differences in the specificity pockets, knowledge of which should enhance our ability to design specific inhibitors for this important anticancer target

Measuring organisational readiness for patient engagement (MORE) : an international online Delphi consensus study

Date of Acceptance: 28/01/2015. © 2015 Oostendorp et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise statedWidespread implementation of patient engagement by organisations and clinical teams is not a reality yet. The aim of this study is to develop a measure of organisational readiness for patient engagement designed to monitor and facilitate a healthcare organisation’s willingness and ability to effectively implement patient engagement in healthcarePeer reviewedFinal Published versio