Endometrial Cancer Presenting as Acute Urinary Retention: a Case Report and Review of the Literature

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Endometrial Cancer Presenting as Acute Urinary Retention : a Case Report and Review of The Literature

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Evolution of associative learning in chemical networks

Organisms that can learn about their environment and modify their behaviour appropriately during their lifetime are more likely to survive and reproduce than organisms that do not. While associative learning – the ability to detect correlated features of the environment – has been studied extensively in nervous systems, where the underlying mechanisms are reasonably well understood, mechanisms within single cells that could allow associative learning have received little attention. Here, using in silico evolution of chemical networks, we show that there exists a diversity of remarkably simple and plausible chemical solutions to the associative learning problem, the simplest of which uses only one core chemical reaction. We then asked to what extent a linear combination of chemical concentrations in the network could approximate the ideal Bayesian posterior of an environment given the stimulus history so far? This Bayesian analysis revealed the ’memory traces’ of the chemical network. The implication of this paper is that there is little reason to believe that a lack of suitable phenotypic variation would prevent associative learning from evolving in cell signalling, metabolic, gene regulatory, or a mixture of these networks in cells

Designing an automated clinical decision support system to match clinical practice guidelines for opioid therapy for chronic pain

Abstract Background Opioid prescribing for chronic pain is common and controversial, but recommended clinical practices are followed inconsistently in many clinical settings. Strategies for increasing adherence to clinical practice guideline recommendations are needed to increase effectiveness and reduce negative consequences of opioid prescribing in chronic pain patients. Methods Here we describe the process and outcomes of a project to operationalize the 2003 VA/DOD Clinical Practice Guideline for Opioid Therapy for Chronic Non-Cancer Pain into a computerized decision support system (DSS) to encourage good opioid prescribing practices during primary care visits. We based the DSS on the existing ATHENA-DSS. We used an iterative process of design, testing, and revision of the DSS by a diverse team including guideline authors, medical informatics experts, clinical content experts, and end-users to convert the written clinical practice guideline into a computable algorithm to generate patient-specific recommendations for care based upon existing information in the electronic medical record (EMR), and a set of clinical tools. Results The iterative revision process identified numerous and varied problems with the initially designed system despite diverse expert participation in the design process. The process of operationalizing the guideline identified areas in which the guideline was vague, left decisions to clinical judgment, or required clarification of detail to insure safe clinical implementation. The revisions led to workable solutions to problems, defined the limits of the DSS and its utility in clinical practice, improved integration into clinical workflow, and improved the clarity and accuracy of system recommendations and tools. Conclusions Use of this iterative process led to development of a multifunctional DSS that met the approval of the clinical practice guideline authors, content experts, and clinicians involved in testing. The process and experiences described provide a model for development of other DSSs that translate written guidelines into actionable, real-time clinical recommendations.http://deepblue.lib.umich.edu/bitstream/2027.42/78267/1/1748-5908-5-26.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/2/1748-5908-5-26.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/3/1748-5908-5-26-S3.TIFFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/4/1748-5908-5-26-S2.TIFFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/5/1748-5908-5-26-S1.TIFFPeer Reviewe

On the nonequilibrium entropy of large and small systems

Thermodynamics makes definite predictions about the thermal behavior of macroscopic systems in and out of equilibrium. Statistical mechanics aims to derive this behavior from the dynamics and statistics of the atoms and molecules making up these systems. A key element in this derivation is the large number of microscopic degrees of freedom of macroscopic systems. Therefore, the extension of thermodynamic concepts, such as entropy, to small (nano) systems raises many questions. Here we shall reexamine various definitions of entropy for nonequilibrium systems, large and small. These include thermodynamic (hydrodynamic), Boltzmann, and Gibbs-Shannon entropies. We shall argue that, despite its common use, the last is not an appropriate physical entropy for such systems, either isolated or in contact with thermal reservoirs: physical entropies should depend on the microstate of the system, not on a subjective probability distribution. To square this point of view with experimental results of Bechhoefer we shall argue that the Gibbs-Shannon entropy of a nano particle in a thermal fluid should be interpreted as the Boltzmann entropy of a dilute gas of Brownian particles in the fluid

Surveillance for endometrial cancer with transvaginal ultrasonography of breast cancer patients under tamoxifen treatment

The association of endometrial thickness with the risk of developing endometrial cancer (EC) within 2 years was investigated in a consecutive cohort of 1205 breast cancer patients under tamoxifen treatment, undergoing transvaginal ultrasonography (TVUS) for follow-up purpose (asymptomatic, 1068) or for abnormal uterine bleeding (AUB, 137). Linkage with tumour registry allowed for the follow-up of 3184.3 person-years. According to underlying incidence, 1.85 EC cases were expected in the study cohort while 12 were observed (observed/expected ratio=6.49, 95% CI 3.35–11.33; asymptomatic=4.09, 95% CI 1.65–8.43, symptomatic=35.71, 95% CI 11.59–83.34). No EC was observed with thickness (half layer) <3 mm. Raising this threshold increased specificity with a substantial loss of sensitivity (⩾3, ⩾4, ⩾6, ⩾9 mm; spec.=25.8, 44.5, 76.1, 91.5%, sens.=100, 91.6, 75.0, 66.6%). The presence of AUB was rather specific (88.94%) but poorly sensitive (41.67%). A combination of AUB presence/absence and thickness allowed the best accuracy (AUB + thickness ⩾3, ⩾4 or ⩾5; sens.=100, 81.6 or 91.6%; spec.=22.8, 40.4, or 56.7%). Breast cancer patients under tamoxifen might be selected for further invasive assessment on the basis of AUB and endometrial thickness assessed at TVUS

Use of an Anaerobic Chamber Environment for the Assay of Endogenous Cellular Protein-Tyrosine Phosphatase Activities

Protein-tyrosine phosphatases (PTPases) have a catalytic cysteine residue whose reduced state is integral to the reaction mechanism. Since exposure to air can artifactually oxidize this highly reactive thiol, PTPase assays have typically used potent reducing agents to reactivate the enzymes present; however, this approach does not allow for the measurement of the endogenous PTPase activity directly isolated from the in vivo cellular environment. Here we provide a method for using an anaerobic chamber to preserve the activity of the total PTPase complement in a tissue lysate or of an immunoprecipitated PTPase homolog to characterize their endogenous activation state. Comparison with a sample treated with biochemical reducing agents allows the determination of the activatable (reducible) fraction of the endogenous PTPase pool