Immunocytochemical localization of the neural-specific regulatory subunit of the type II cyclic AMP-dependent protein kinase to postsynaptic structures in the rat brain.

The cellular and subcellular distribution of a major cyclic AMP binding protein in the central nervous system, the neural-specific regulatory subunit of the type II cyclic AMP-dependent protein kinase (RII-B), was analyzed in rat brains with light and electron microscopic immunocytochemical methods. The distribution of the non-neural isoform of the regulatory subunit of the enzyme (RII-H) was also analyzed. It was found that RII-B immunoreactivity was predominantly localized to neurons whereas glial and endothelial cells were unlabeled. In the neurons the RII-B immunoreactivity occurred in the perikaryal cytoplasm and in the dendrites; there was no significant accumulation of immunoreaction product in nuclei, myelinated axons and axon terminals. Although immunoreactivity was never detected in axon terminals, it was characteristically associated with the postsynaptic densities and the surrounding non-synaptic sites in somata, dendrites and dendritic spines. The localization of RII-B antigenic sites did not show specificity to any type of neuron or synapse, but the amount of immunoreactivity varied. The distribution of RII-H immunoreactivity was similar to that of RII-B except that RII-H immunoreaction product was also observed in glial cells and occurred more frequently in myelinated axons. Our data confirm that RII-B is one of the major cyclic AMP binding proteins in neurons, and provide morphological support for the involvement of the type II cyclic AMP-dependent protein kinase in postsynaptic neural functions

The Emergence of Precision Urologic Oncology: A Collaborative Review on Biomarker-driven Therapeutics

CONTEXT: Biomarker-driven cancer therapy, also referred to as precision oncology, has received increasing attention for its promise of improving patient outcomes by defining subsets of patients more likely to respond to various therapies. OBJECTIVES: In this collaborative review article, we examine recent literature regarding biomarker-driven therapeutics in urologic oncology, to better define the state of the field, explore the current evidence supporting utility of this approach, and gauge potential for the future. EVIDENCE ACQUISITION: We reviewed relevant literature, with a particular focus on recent studies about targeted therapy, predictors of response, and biomarker development. EVIDENCE SYNTHESIS: The recent advances in molecular profiling have led to a rapid expansion of potential biomarkers and predictive information for patients with urologic malignancies. Across disease states, distinct molecular subtypes of cancers have been identified, with the potential to inform choices of management strategy. Biomarkers predicting response to standard therapies (such as platinum-based chemotherapy) are emerging. In several malignancies (particularly renal cell carcinoma and castration-resistant prostate cancer), targeted therapy against commonly altered signaling pathways has emerged as standard of care. Finally, targeted therapy against alterations present in rare patients (less than 2%) across diseases has the potential to drastically alter patterns of care and choices of therapeutic options. CONCLUSIONS: Precision medicine has the highest potential to impact the care of patients. Prospective studies in the setting of clinical trials and standard of care therapy will help define reliable predictive biomarkers and new therapeutic targets leading to real improvement in patient outcomes. PATIENT SUMMARY: Precision oncology uses molecular information (DNA and RNA) from the individual and the tumor to match the right patient with the right treatment. Tremendous strides have been made in defining the molecular underpinnings of urologic malignancies and understanding how these predict response to treatment—this represents the future of urologic oncology

A Bioengineered Implant for a Predetermined Bone Cellular Response to Loading Forces. A Literature Review and Case Report

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142048/1/jper1276.pd

On defining rules for cancer data fabrication

Funding: This research is partially funded by the Data Lab, and the EU H2020 project Serums: Securing Medical Data in Smart Patient-Centric Healthcare Systems (grant 826278).Data is essential for machine learning projects, and data accuracy is crucial for being able to trust the results obtained from the associated machine learning models. Previously, we have developed machine learning models for predicting the treatment outcome for breast cancer patients that have undergone chemotherapy, and developed a monitoring system for their treatment timeline showing interactively the options and associated predictions. Available cancer datasets, such as the one used earlier, are often too small to obtain significant results, and make it difficult to explore ways to improve the predictive capability of the models further. In this paper, we explore an alternative to enhance our datasets through synthetic data generation. From our original dataset, we extract rules to generate fabricated data that capture the different characteristics inherent in the dataset. Additional rules can be used to capture general medical knowledge. We show how to formulate rules for our cancer treatment data, and use the IBM solver to obtain a corresponding synthetic dataset. We discuss challenges for future work.Postprin

Micro-morphologic changes around biophysically-stimulated titanium implants in ovariectomized rats

<p>Abstract</p> <p>Background</p> <p>Osteoporosis may present a risk factor in achievement of osseointegration because of its impact on bone remodeling properties of skeletal phsiology. The purpose of this study was to evaluate micro-morphological changes in bone around titanium implants exposed to mechanical and electrical-energy in osteoporotic rats.</p> <p>Methods</p> <p>Fifteen 12-week old sprague-dowley rats were ovariectomized to develop osteoporosis. After 8 weeks of healing period, two titanium implants were bilaterally placed in the proximal metaphyses of tibia. The animals were randomly divided into a control group and biophysically-stimulated two test groups with five animals in each group. In the first test group, a pulsed electromagnetic field (PEMF) stimulation was administrated at a 0.2 mT 4 h/day, whereas the second group received low-magnitude high-frequency mechanical vibration (MECHVIB) at 50 Hz 14 min/day. Following completion of two week treatment period, all animals were sacrificed. Bone sites including implants were sectioned, removed <it>en bloc </it>and analyzed using a microCT unit. Relative bone volume and bone micro-structural parameters were evaluated for 144 μm wide peri-implant volume of interest (VOI).</p> <p>Results</p> <p>Mean relative bone volume in the peri-implant VOI around implants PEMF and MECHVIB was significantly higher than of those in control (<it>P </it>< .05). Differences in trabecular-thickness and -separation around implants in all groups were similar (<it>P </it>> .05) while the difference in trabecular-number among test and control groups was significant in all VOIs (<it>P </it>< .05).</p> <p>Conclusion</p> <p>Biophysical stimulation remarkably enhances bone volume around titanium implants placed in osteoporotic rats. Low-magnitude high-frequency MECHVIB is more effective than PEMF on bone healing in terms of relative bone volume.</p

Protégé: A Tool for Managing and Using Terminology in Radiology Applications

The development of standard terminologies such as RadLex is becoming important in radiology applications, such as structured reporting, teaching file authoring, report indexing, and text mining. The development and maintenance of these terminologies are challenging, however, because there are few specialized tools to help developers to browse, visualize, and edit large taxonomies. Protégé (http://protege.stanford.edu) is an open-source tool that allows developers to create and to manage terminologies and ontologies. It is more than a terminology-editing tool, as it also provides a platform for developers to use the terminologies in end-user applications. There are more than 70,000 registered users of Protégé who are using the system to manage terminologies and ontologies in many different domains. The RadLex project has recently adopted Protégé for managing its radiology terminology. Protégé provides several features particularly useful to managing radiology terminologies: an intuitive graphical user interface for navigating large taxonomies, visualization components for viewing complex term relationships, and a programming interface so developers can create terminology-driven radiology applications. In addition, Protégé has an extensible plug-in architecture, and its large user community has contributed a rich library of components and extensions that provide much additional useful functionalities. In this report, we describe Protégé’s features and its particular advantages in the radiology domain in the creation, maintenance, and use of radiology terminology

Microarray Method for the Rapid Detection of Glycosaminoglycan–Protein Interactions

Glycosaminoglycans (GAGs) perform numerous vital functions within the body. As major components of the extracellular matrix, these polysaccharides participate in a diverse array of cell-signaling events. We have developed a simple microarray assay for the evaluation of protein binding to various GAG subclasses. In a single experiment, the binding to all members of the GAG family can be rapidly determined, giving insight into the relative specificity of the interactions and the importance of specific sulfation motifs. The arrays are facile to prepare from commercially available materials

Shedding light on the elusive role of endothelial cells in cytomegalovirus dissemination.

Cytomegalovirus (CMV) is frequently transmitted by solid organ transplantation and is associated with graft failure. By forming the boundary between circulation and organ parenchyma, endothelial cells (EC) are suited for bidirectional virus spread from and to the transplant. We applied Cre/loxP-mediated green-fluorescence-tagging of EC-derived murine CMV (MCMV) to quantify the role of infected EC in transplantation-associated CMV dissemination in the mouse model. Both EC- and non-EC-derived virus originating from infected Tie2-cre(+) heart and kidney transplants were readily transmitted to MCMV-naïve recipients by primary viremia. In contrast, when a Tie2-cre(+) transplant was infected by primary viremia in an infected recipient, the recombined EC-derived virus poorly spread to recipient tissues. Similarly, in reverse direction, EC-derived virus from infected Tie2-cre(+) recipient tissues poorly spread to the transplant. These data contradict any privileged role of EC in CMV dissemination and challenge an indiscriminate applicability of the primary and secondary viremia concept of virus dissemination

Multiple imputation for estimation of an occurrence rate in cohorts with attrition and discrete follow-up time points: a simulation study

<p>Abstract</p> <p>Background</p> <p>In longitudinal cohort studies, subjects may be lost to follow-up at any time during the study. This leads to attrition and thus to a risk of inaccurate and biased estimations. The purpose of this paper is to show how multiple imputation can take advantage of all the information collected during follow-up in order to estimate the cumulative probability <it>P(E) </it>of an event <it>E</it>, when the first occurrence of this event is observed at <it>t </it>successive time points of a longitudinal study with attrition.</p> <p>Methods</p> <p>We compared the performance of multiple imputation with that of Kaplan-Meier estimation in several simulated attrition scenarios.</p> <p>Results</p> <p>In missing-completely-at-random scenarios, the multiple imputation and Kaplan-Meier methods performed well in terms of bias (less than 1%) and coverage rate (range = [94.4%; 95.8%]). In missing-at-random scenarios, the Kaplan-Meier method was associated with a bias ranging from -5.1% to 7.0% and with a very poor coverage rate (as low as 0.2%). Multiple imputation performed much better in this situation (bias <2%, coverage rate >83.4%).</p> <p>Conclusions</p> <p>Multiple imputation shows promise for estimation of an occurrence rate in cohorts with attrition. This study is a first step towards defining appropriate use of multiple imputation in longitudinal studies.</p

Predicting developmental dysplasia of the hip in at-risk newborns.

BACKGROUND: The development of developmental dysplasia of the hip can be attributed to several risk factors and often in combination with each other. When predicting the likelihood of developing this condition, clinicians tend to over and underestimate its likelihood of occurring. Therefore, the study aim is to determine among at-risk newborns how to best predict developmental dysplasia of the hip (DDH) within 8 weeks post-partum. METHODS: Prospective cohort study in secondary care. Patient population included newborns at-risk for DDH - we assessed 13,276 consecutive newborns for the presence of DDH risk factors. Only newborns with at least one of the predefined risk factors and those showing an abnormal examination of the hip were enrolled (n = 2191). For the development of a risk prediction model we considered 9 candidate predictors and other variables readily available at childbirth. The main outcome measure was ultrasonography at a median age of 8 weeks using consensus diagnostic criteria; outcome assessors were blinded. RESULTS: The risk model includes four predictors: female sex (OR = 5.6; 95% CI: 2.9-10.9; P  4000 g (OR = 1.6; 95% CI: 0.6-4.2; P = 0.34), and abnormal examination of hip (OR = 58.8; 95% CI: 31.9, 108.5; P <  0.001). This model demonstrated excellent discrimination (C statistic = 0.9) and calibration of observed and predicted risk (P = 0.35). A model without the variable 'hip examination' demonstrated similar performance. CONCLUSION: The risk model quantifies absolute risk of DDH within 8 weeks postpartum in at-risk newborns. Based on clinical variables readily available at the point of childbirth, the model will enhance parental counselling and could serve as the basis for real time decisions prior to discharge from maternity wards