Distributed Object Medical Imaging Model

Abstract- Digital medical informatics and images are commonly used in hospitals today,. Because of the interrelatedness of the radiology department and other departments, especially the intensive care unit and emergency department, the transmission and sharing of medical images has become a critical issue. Our research group has developed a Java-based Distributed Object Medical Imaging Model(DOMIM) to facilitate the rapid development and deployment of medical imaging applications in a distributed environment that can be shared and used by related departments and mobile physiciansDOMIM is a unique suite of multimedia telemedicine applications developed for the use by medical related organizations. The applications support realtime patients’ data, image files, audio and video diagnosis annotation exchanges. The DOMIM enables joint collaboration between radiologists and physicians while they are at distant geographical locations. The DOMIM environment consists of heterogeneous, autonomous, and legacy resources. The Common Object Request Broker Architecture (CORBA), Java Database Connectivity (JDBC), and Java language provide the capability to combine the DOMIM resources into an integrated, interoperable, and scalable system. The underneath technology, including IDL ORB, Event Service, IIOP JDBC/ODBC, legacy system wrapping and Java implementation are explored. This paper explores a distributed collaborative CORBA/JDBC based framework that will enhance medical information management requirements and development. It encompasses a new paradigm for the delivery of health services that requires process reengineering, cultural changes, as well as organizational changes

A Primer on Social Neuroscience

{Excerpt} Human history is not only social history but also neurobiological history. Throughout most of the 20th century, social and biological explanations were widely viewed as incompatible. However, from the 1990s, the emergence of social neuroscience vindicates Aristotle’s pioneering deductions. The young science accepts that the brain is a single, pivotal component of an undeniably social species and that it is orderly in its complexity. It treats the human brain as a social organ, whose physiological and neurological reactions are directly and profoundly shaped by social interaction. (To a mammal, being socially connected to caregivers is indispensablefor survival: this, incidentally, suggests that Abraham Maslow’s hierarchy of needs might need to be revised to ascribe more weight to social needs, e.g., love and belonging, and esteem, in relation to self-actualization.) Nondualistic and nonreductionistic, social neuroscience, through a multilevel and integrative approach, aims to understand the role of the central nervous system in the formation and maintenance of social behaviors and processes. Spanning the social and biological domains, e.g., molecular, cellular, system, person, relational, collective, and societal, it exploits biological concepts and neurobiological techniques such as functional magnetic resonance imaging—which measures patterns of blood oxygenation responses in the brain as a subject engages in a particular task, to inform and refine theories of social behavior. In short, it focuses on how the brain mediates social interaction. (Brain scans captured through functional magnetic resonance imaging show that the same areas are associated with distress, be that caused by social rejection or by physical pain.) Arguably, the potential benefits of social neuroscience are that it can inform debates in social psychology, provide tools for measuring brain–body activity directly and unobtrusively and provide information that would be impossible to assess using other techniques, and permit the examination of social processes by pointing to the importance of social variables (from context to culture) in altering processes within the brain and body

Outcomes Assessment and Health Care Reform

Argues for the use of outcomes assessment in measuring cost-effectiveness and quality to capture the overall impact of multi-dimensional treatment strategies and to identify healthcare systems that both adopt appropriate technologies and perform well

The value of remote sensing techniques in supporting effective extrapolation across multiple marine spatial scales

The reporting of ecological phenomena and environmental status routinely required point observations, collected with traditional sampling approaches to be extrapolated to larger reporting scales. This process encompasses difficulties that can quickly entrain significant errors. Remote sensing techniques offer insights and exceptional spatial coverage for observing the marine environment. This review provides guidance on (i) the structures and discontinuities inherent within the extrapolative process, (ii) how to extrapolate effectively across multiple spatial scales, and (iii) remote sensing techniques and data sets that can facilitate this process. This evaluation illustrates that remote sensing techniques are a critical component in extrapolation and likely to underpin the production of high-quality assessments of ecological phenomena and the regional reporting of environmental status. Ultimately, is it hoped that this guidance will aid the production of robust and consistent extrapolations that also make full use of the techniques and data sets that expedite this process

Equine or porcine synovial fluid as a novel ex vivo model for the study of bacterial free-floating biofilms that form in human joint infections

Bacterial invasion of synovial joints, as in infectious or septic arthritis, can be difficult to treat in both veterinary and human clinical practice. Biofilms, in the form of free-floating clumps or aggregates, are involved with the pathogenesis of infectious arthritis and periprosthetic joint infection (PJI). Infection of a joint containing an orthopedic implant can additionally complicate these infections due to the presence of adherent biofilms. Because of these biofilm phenotypes, bacteria within these infected joints show increased antimicrobial tolerance even at high antibiotic concentrations. To date, animal models of PJI or infectious arthritis have been limited to small animals such as rodents or rabbits. Small animal models, however, yield limited quantities of synovial fluid making them impractical for in vitro research. Herein, we describe the use of ex vivo equine and porcine models for the study of synovial fluid induced biofilm aggregate formation and antimicrobial tolerance. We observed Staphylococcus aureus and other bacterial pathogens adapt the same biofilm aggregate phenotype with significant antimicrobial tolerance in both equine and porcine synovial fluid, analogous to human synovial fluid. We also demonstrate that enzymatic dispersal of synovial fluid aggregates restores the activity of antimicrobials. Future studies investigating the interaction of bacterial cell surface proteins with host synovial fluid proteins can be readily carried out in equine or porcine ex vivo models to identify novel drug targets for treatment of prevention of these difficult to treat infectious diseases

Advances in computational modelling for personalised medicine after myocardial infarction

Myocardial infarction (MI) is a leading cause of premature morbidity and mortality worldwide. Determining which patients will experience heart failure and sudden cardiac death after an acute MI is notoriously difficult for clinicians. The extent of heart damage after an acute MI is informed by cardiac imaging, typically using echocardiography or sometimes, cardiac magnetic resonance (CMR). These scans provide complex data sets that are only partially exploited by clinicians in daily practice, implying potential for improved risk assessment. Computational modelling of left ventricular (LV) function can bridge the gap towards personalised medicine using cardiac imaging in patients with post-MI. Several novel biomechanical parameters have theoretical prognostic value and may be useful to reflect the biomechanical effects of novel preventive therapy for adverse remodelling post-MI. These parameters include myocardial contractility (regional and global), stiffness and stress. Further, the parameters can be delineated spatially to correspond with infarct pathology and the remote zone. While these parameters hold promise, there are challenges for translating MI modelling into clinical practice, including model uncertainty, validation and verification, as well as time-efficient processing. More research is needed to (1) simplify imaging with CMR in patients with post-MI, while preserving diagnostic accuracy and patient tolerance (2) to assess and validate novel biomechanical parameters against established prognostic biomarkers, such as LV ejection fraction and infarct size. Accessible software packages with minimal user interaction are also needed. Translating benefits to patients will be achieved through a multidisciplinary approach including clinicians, mathematicians, statisticians and industry partners

Summary of the Active Microwave Workshop, chapter 1

An overview is given of the utility, feasibility, and advantages of active microwave sensors for a broad range of applications, including aerospace. In many instances, the material provides an in-depth examination of the applicability and/or the technology of microwave remote sensing, and considerable documentation is presented in support of these techniques. An assessment of the relative strengths and weaknesses of active microwave sensor data indicates that satisfactory data are obtainable for several significant applications