Robust model predictive control for dynamics compensation in real-time hybrid simulation

Hybrid simulation is an efficient method to obtain the response of an emulated system subjected to dynamic excitation by combining loading-rate-sensitive numerical and physical substructures. In such simulations, the interfaces between physical and numerical substructures are usually implemented using transfer systems, i.e., an arrangement of actuators. To guarantee high fidelity of the simulation outcome, conducting hybrid simulation in hard real-time is required. Albeit attractive, real-time hybrid simulation comes with numerous challenges, such as the inherent dynamics of the transfer system used, along with communication interrupts between numerical and physical substructures, that introduce time delays to the overall hybrid model altering the dynamic response of the system under consideration. Hence, implementation of adequate control techniques to compensate for such delays is necessary. In this study, a novel control strategy is proposed for time delay compensation of actuator dynamics in hard real-time hybrid simulation applications. The method is based on designing a transfer system controller consisting of a robust model predictive controller along with a polynomial extrapolation algorithm and a Kalman filter. This paper presents a proposed tracking controller first, followed by two virtual real-time hybrid simulation parametric case studies, which serve to validate the performance and robustness of the novel control strategy. Real-time hybrid simulation using the proposed control scheme is demonstrated to be effective for structural performance assessment

Creation and Implementation of a Pediatric Advanced Practice Nurse Critical Care Fellowship Program

Advanced practice registered nurses (APRNs) who begin their careers in the pediatric intensive care unit (PICU) may be challenged in this practice environment. Inadequate prior experience as a staff nurse, limited opportunities for clinical placements in the PICU during graduate education, and being in a fast-paced, high-acuity practice environment without prior exposure to critically ill children are practice challenges in the PICU setting. The goal of postgraduate education training programs (fellowship programs) for the acute care pediatric nurse practitioner (ACPNP) is to prepare students to become beginner practitioners who can function effectively in the acute care setting within a few months of being hired, much like that of their physician counterparts who complete a fellowship. The health care environment continues to be influenced by trends in national health care reform, shifts in the models for physician training, and the Accreditation Council for Graduate Medical Education resident duty hour restrictions. These emerging trends have given health care organizations the opportunity to evaluate their current care delivery and training models. It is expected that the demand for APRNs with specialty training will increase. The aim of this article is to describe our experience in the creation and implementation of a critical care pediatric nurse practitioner (CCPNP) fellowship training program at a large midwestern U.S. tertiary care center. It is expected that the demand for APRNs with specialty training will increase. When this fellowship was created, there were no known fellowships available for pediatric nurse practitioners (PNPs) interested in pediatric critical care. To meet the needs of these providers, a focused training program is required to provide specific preparation and competencies to practice to the full extent of the provider\u27s license. A recent recommendation is for health care administrators to consider implementing fellowship training programs to assist nurse practitioners transitioning into specialty roles (Kells, Dunn, Melchiono, & Burke, 2015). We used several online search engines to identify pediatric health care institutions with active advanced practice provider postgraduate fellowships. Our search in June 2017 identified fellowship programs in primary care, pediatric hematology/oncology, palliative care, neuro-critical care, and urgent care/emergency department. To our knowledge, this fellowship program was the first of its kind and seeks to provide postgraduate specialty training and education focused on the unique requirements of critically ill children and their families to help fill a knowledge gap when entering practice in this highly specialized practice environment

Differential expression of colon cancer associated transcript1 (CCAT1) along the colonic adenoma-carcinoma sequence

Cataloged from PDF version of article.Background: The transition from normal epithelium to adenoma and, to invasive carcinoma in the human colon is associated with acquired molecular events taking 5-10 years for malignant transformation. We discovered CCAT1, a non-coding RNA over-expressed in colon cancer (CC), but not in normal tissues, thereby making it a potential disease-specific biomarker. We aimed to define and validate CCAT1 as a CC-specific biomarker, and to study CCAT1 expression across the adenoma- carcinoma sequence of CC tumorigenesis. Methods: Tissue samples were obtained from patients undergoing resection for colonic adenoma(s) or carcinoma. Normal colonic tissue (n = 10), adenomatous polyps (n = 18), primary tumor tissue (n = 22), normal mucosa adjacent to primary tumor (n = 16), and lymph node(s) (n = 20), liver (n = 8), and peritoneal metastases (n = 19) were studied. RNA was extracted from all tissue samples, and CCAT1 expression was analyzed using quantitative real time-PCR (qRT-PCR) with confirmatory in-situ hybridization (ISH). Results: Borderline expression of CCAT1 was identified in normal tissue obtained from patients with benign conditions [mean Relative Quantity (RQ) = 5.9]. Significant relative CCAT1 up-regulation was observed in adenomatous polyps (RQ = 178.6 +/- 157.0; p = 0.0012); primary tumor tissue (RQ = 64.9 +/- 56.9; p = 0.0048); normal mucosa adjacent to primary tumor (RQ = 17.7 +/- 21.5; p = 0.09); lymph node, liver and peritoneal metastases (RQ = 11,414.5 +/- 12,672.9; 119.2 +/- 138.9; 816.3 +/- 2,736.1; p = 0.0001, respectively). qRT-PCR results were confirmed by ISH, demonstrating significant correlation between CCAT1 up-regulation measured using these two methods. Conclusion: CCAT1 is up-regulated across the colon adenoma-carcinoma sequence. This up-regulation is evident in pre-malignant conditions and through all disease stages, including advanced metastatic disease suggesting a role in both tumorigenesis and the metastatic process

Evaluation of the collaborative network of highly correlating skin proteins and its change following treatment with glucocorticoids

<p>Abstract</p> <p>Background</p> <p>Glucocorticoids (GC) represent the core treatment modality for many inflammatory diseases. Its mode of action is difficult to grasp, not least because it includes direct modulation of many components of the extracellular matrix as well as complex anti-inflammatory effects. Protein expression profile of skin proteins is being changed with topical application of GC, however, the knowledge about singular markers in this regard is only patchy and collaboration is ill defined.</p> <p>Material/Methods</p> <p>Scar formation was observed under different doses of GC, which were locally applied on the back skin of mice (1 to 3 weeks). After euthanasia we analyzed protein expression of collagen I and III (picrosirius) in scar tissue together with 16 additional protein markers, which are involved in wound healing, with immunhistochemistry. For assessing GC's effect on co-expression we compared our results with a model of random figures to estimate how many significant correlations should be expected by chance.</p> <p>Results</p> <p>GC altered collagen and protein expression with distinct results in different areas of investigation. Most often we observed a reduced expression after application of low dose GC. In the scar infiltrate a multivariate analysis confirmed the significant impact of both GC concentrations. Calculation of Spearman's correlation coefficient similarly resulted in a significant impact of GC, and furthermore, offered the possibility to grasp the entire interactive profile in between all variables studied. The biological markers, which were connected by significant correlations could be arranged in a highly cross-linked network that involved most of the markers measured. A marker highly cross-linked with more than 3 significant correlations was indicated by a higher variation of all its correlations to the other variables, resulting in a standard deviation of > 0.2.</p> <p>Conclusion</p> <p>In addition to immunohistochemical analysis of single protein markers multivariate analysis of co-expressions by use of correlation coefficients reveals the complexity of biological relationships and identifies complex biological effects of GC on skin scarring. Depiction of collaborative clusters will help to understand functional pathways. The functional importance of highly cross-linked proteins will have to be proven in subsequent studies.</p

Role of deregulated microRNAs in breast cancer progression Using FFPE tissue

MicroRNAs (miRNAs) contribute to cancer initiation and progression by silencing the expression of their target genes, causing either mRNA molecule degradation or translational inhibition. Intraductal epithelial proliferations of the breast are histologically and clinically classified into normal, atypical ductal hyperplasia (ADH), ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC). To better understand the progression of ductal breast cancer development, we attempt to identify deregulated miRNAs in this process using Formalin-Fixed, Paraffin-Embedded (FFPE) tissues from breast cancer patients. Following tissue microdissection, we obtained 8 normal, 4 ADH, 6 DCIS and 7 IDC samples, which were subject to RNA isolation and miRNA expression profiling analysis. We found that miR-21, miR-200b/c, miR-141, and miR-183 were consistently up-regulated in ADH, DCIS and IDC compared to normal, while miR-557 was uniquely down-regulated in DCIS. Interestingly, the most significant miRNA deregulations occurred during the transition from normal to ADH. However, the data did not reveal a step-wise miRNA alteration among discrete steps along tumor progression, which is in accordance with previous reports of mRNA profiling of different stages of breast cancer. Furthermore, the expression of MSH2 and SMAD7, two important molecules involving TGF-β pathway, was restored following miR-21 knockdown in both MCF-7 and Hs578T breast cancer cells. In this study, we have not only identified a number of potential candidate miRNAs for breast cancer, but also found that deregulation of miRNA expression during breast tumorigenesis might be an early event since it occurred significantly during normal to ADH transition. Consequently, we have demonstrated the feasibility of miRNA expression profiling analysis using archived FFPE tissues, typically with rich clinical information, as a means of miRNA biomarker discovery

Clinical decision modeling system

<p>Abstract</p> <p>Background</p> <p>Decision analysis techniques can be applied in complex situations involving uncertainty and the consideration of multiple objectives. Classical decision modeling techniques require elicitation of too many parameter estimates and their conditional (joint) probabilities, and have not therefore been applied to the problem of identifying high-performance, cost-effective combinations of clinical options for diagnosis or treatments where many of the objectives are unknown or even unspecified.</p> <p>Methods</p> <p>We designed a Java-based software resource, the Clinical Decision Modeling System (CDMS), to implement Naïve Decision Modeling, and provide a use case based on published performance evaluation measures of various strategies for breast and lung cancer detection. Because cost estimates for many of the newer methods are not yet available, we assume equal cost. Our use case reveals numerous potentially high-performance combinations of clinical options for the detection of breast and lung cancer.</p> <p>Results</p> <p>Naïve Decision Modeling is a highly practical applied strategy which guides investigators through the process of establishing evidence-based integrative translational clinical research priorities. CDMS is not designed for clinical decision support. Inputs include performance evaluation measures and costs of various clinical options. The software finds trees with expected emergent performance characteristics and average cost per patient that meet stated filtering criteria. Key to the utility of the software is sophisticated graphical elements, including a tree browser, a receiver-operator characteristic surface plot, and a histogram of expected average cost per patient. The analysis pinpoints the potentially most relevant pairs of clinical options ('critical pairs') for which empirical estimates of conditional dependence may be critical. The assumption of independence can be tested with retrospective studies prior to the initiation of clinical trials designed to estimate clinical impact. High-performance combinations of clinical options may exist for breast and lung cancer detection.</p> <p>Conclusion</p> <p>The software could be found useful in simplifying the objective-driven planning of complex integrative clinical studies without requiring a multi-attribute utility function, and it could lead to efficient integrative translational clinical study designs that move beyond simple pair wise competitive studies. Collaborators, who traditionally might compete to prioritize their own individual clinical options, can use the software as a common framework and guide to work together to produce increased understanding on the benefits of using alternative clinical combinations to affect strategic and cost-effective clinical workflows.</p

Development of a clinical decision model for thyroid nodules

<p>Abstract</p> <p>Background</p> <p>Thyroid nodules represent a common problem brought to medical attention. Four to seven percent of the United States adult population (10–18 million people) has a palpable thyroid nodule, however the majority (>95%) of thyroid nodules are benign. While, fine needle aspiration remains the most cost effective and accurate diagnostic tool for thyroid nodules in current practice, over 20% of patients undergoing FNA of a thyroid nodule have indeterminate cytology (follicular neoplasm) with associated malignancy risk prevalence of 20–30%. These patients require thyroid lobectomy/isthmusectomy purely for the purpose of attaining a definitive diagnosis. Given that the majority (70–80%) of these patients have benign surgical pathology, thyroidectomy in these patients is conducted principally with diagnostic intent. Clinical models predictive of malignancy risk are needed to support treatment decisions in patients with thyroid nodules in order to reduce morbidity associated with unnecessary diagnostic surgery.</p> <p>Methods</p> <p>Data were analyzed from a completed prospective cohort trial conducted over a 4-year period involving 216 patients with thyroid nodules undergoing ultrasound (US), electrical impedance scanning (EIS) and fine needle aspiration cytology (FNA) prior to thyroidectomy. A Bayesian model was designed to predict malignancy in thyroid nodules based on multivariate dependence relationships between independent covariates. Ten-fold cross-validation was performed to estimate classifier error wherein the data set was randomized into ten separate and unique train and test sets consisting of a training set (90% of records) and a test set (10% of records). A receiver-operating-characteristics (ROC) curve of these predictions and area under the curve (AUC) were calculated to determine model robustness for predicting malignancy in thyroid nodules.</p> <p>Results</p> <p>Thyroid nodule size, FNA cytology, US and EIS characteristics were highly predictive of malignancy. Cross validation of the model created with Bayesian Network Analysis effectively predicted malignancy [AUC = 0.88 (95%CI: 0.82–0.94)] in thyroid nodules. The positive and negative predictive values of the model are 83% (95%CI: 76%–91%) and 79% (95%CI: 72%–86%), respectively.</p> <p>Conclusion</p> <p>An integrated predictive decision model using Bayesian inference incorporating readily obtainable thyroid nodule measures is clinically relevant, as it effectively predicts malignancy in thyroid nodules. This model warrants further validation testing in prospective clinical trials.</p

Thyrotropin-releasing hormone (TRH) promotes wound re-epithelialisation in frog and human skin

There remains a critical need for new therapeutics that promote wound healing in patients suffering from chronic skin wounds. This is, in part, due to a shortage of simple, physiologically and clinically relevant test systems for investigating candidate agents. The skin of amphibians possesses a remarkable regenerative capacity, which remains insufficiently explored for clinical purposes. Combining comparative biology with a translational medicine approach, we report the development and application of a simple ex vivo frog (Xenopus tropicalis) skin organ culture system that permits exploration of the effects of amphibian skin-derived agents on re-epithelialisation in both frog and human skin. Using this amphibian model, we identify thyrotropin-releasing hormone (TRH) as a novel stimulant of epidermal regeneration. Moving to a complementary human ex vivo wounded skin assay, we demonstrate that the effects of TRH are conserved across the amphibian-mammalian divide: TRH stimulates wound closure and formation of neo-epidermis in organ-cultured human skin, accompanied by increased keratinocyte proliferation and wound healing-associated differentiation (cytokeratin 6 expression). Thus, TRH represents a novel, clinically relevant neuroendocrine wound repair promoter that deserves further exploration. These complementary frog and human skin ex vivo assays encourage a comparative biology approach in future wound healing research so as to facilitate the rapid identification and preclinical testing of novel, evolutionarily conserved, and clinically relevant wound healing promoters