Wind tunnel site analysis of Dow Chemical Facility at Rocky Flats, Colorado, part II

Prepared for Research and Ecology, Rocky Flats Division, Dow Chemical Company.CER72-73RNM-JAP-TGH-16.March 1973.Includes bibliographical references.This report deals with two separate problems occurring at the Dow Chemical Company Plutonium Recovery Facility, Rocky Flats Division, namely the dispersion of potential effluents and the protection of parking areas from the destructive action of high velocity west winds by the use of shelterbelts. The dispersion study is a continuation of a previous study and consisted of modeling the geography, wind and turbulence profiles and effluent releases in a wind tunnel study. Dispersion and trajectory behavior was determined by the use of Krypton-85 as a tracer gas. The results reinforce the conclusion advanced in the previous study that Pasquill-Gifford prediction methods apply well to the site. The shelterbelt study consisted of evaluating the effects of porosity, barrier height and length, geometric configuration of barriers, parking lot orientation and wind approach angle upon the protection of parking areas from high velocity wind action in assaulting vehicles with abrasive particles. Tests were accomplished by observing the effectiveness of the wind in transporting a zinc oxide-mineral oil suspension. This effectiveness was correlated to velocity reduction and wind profile modification effectiveness of shelterbelts. It was found that the most effective use of shelterbelts could be accomplished if the parking lot were reoriented with the long side running in a north-south direction

Azole Drugs Are Imported By Facilitated Diffusion in Candida albicans and Other Pathogenic Fungi

Despite the wealth of knowledge regarding the mechanisms of action and the mechanisms of resistance to azole antifungals, very little is known about how the azoles are imported into pathogenic fungal cells. Here the in-vitro accumulation and import of Fluconazole (FLC) was examined in the pathogenic fungus, Candida albicans. In energized cells, FLC accumulation correlates inversely with expression of ATP-dependent efflux pumps. In de-energized cells, all strains accumulate FLC, suggesting that FLC import is not ATP-dependent. The kinetics of import in de-energized cells displays saturation kinetics with a Km of 0.64 uM and Vmax of 0.0056 pmol/min/108 cells, demonstrating that FLC import proceeds via facilitated diffusion through a transporter rather than passive diffusion. Other azoles inhibit FLC import on a mole/mole basis, suggesting that all azoles utilize the same facilitated diffusion mechanism. An analysis of related compounds indicates that competition for azole import depends on an aromatic ring and an imidazole or triazole ring together in one molecule. Import of FLC by facilitated diffusion is observed in other fungi, including Cryptococcus neoformans, Saccharomyces cerevisiae, and Candida krusei, indicating that the mechanism of transport is conserved among fungal species. FLC import was shown to vary among Candida albicans resistant clinical isolates, suggesting that altered facilitated diffusion may be a previously uncharacterized mechanism of resistance to azole drugs

Artificial Intelligence and Liver Transplant:Predicting Survival of Individual Grafts

The demand for liver transplantation far outstrips the supply of deceased donor organs, and so, listing and allocation decisions aim to maximize utility. Most existing methods for predicting transplant outcomes use basic methods, such as regression modeling, but newer artificial intelligence (AI) techniques have the potential to improve predictive accuracy. The aim was to perform a systematic review of studies predicting graft outcomes following deceased donor liver transplantation using AI techniques and to compare these findings to linear regression and standard predictive modeling: donor risk index (DRI), Model for End‐Stage Liver Disease (MELD), and Survival Outcome Following Liver Transplantation (SOFT). After reviewing available article databases, a total of 52 articles were reviewed for inclusion. Of these articles, 9 met the inclusion criteria, which reported outcomes from 18,771 liver transplants. Artificial neural networks (ANNs) were the most commonly used methodology, being reported in 7 studies. Only 2 studies directly compared machine learning (ML) techniques to liver scoring modalities (i.e., DRI, SOFT, and balance of risk [BAR]). Both studies showed better prediction of individual organ survival with the optimal ANN model, reporting an area under the receiver operating characteristic curve (AUROC) 0.82 compared with BAR (0.62) and SOFT (0.57), and the other ANN model gave an AUC ROC of 0.84 compared with a DRI (0.68) and SOFT (0.64). AI techniques can provide high accuracy in predicting graft survival based on donors and recipient variables. When compared with the standard techniques, AI methods are dynamic and are able to be trained and validated within every population. However, the high accuracy of AI may come at a cost of losing explainability (to patients and clinicians) on how the technology works

Applying multi-phase DES approach for modelling the patient journey through accident and emergency departments

Accident and Emergency departments (A&ED) are in charge of providing access to patients requiring urgent acute care. A&ED are difficult to model due to the presence of interactions, different pathways and the multiple outcomes that patients may undertake depending on their health status. In addition, public concern has focused on the presence of overcrowding, long waiting times, patient dissatisfaction and cost overruns associated with A&ED. There is then a need for tackling these problems through developing integrated and explicit models supporting healthcare planning. However, the studies directly concentrating on modelling the A&EDs are largely limited. Therefore, this paper presents the use of a multi-phase DES framework for modelling the A&ED and facilitating the assessment of potential improvement strategies. Initially, the main components, critical variables and different states of the A&ED are identified to correctly model the entire patient journey. In this step, it is also necessary to characterize the demand in order to categorize the patients into pipelines. After this, a discrete-event simulation (DES) model is developed. Then, validation is conducted through the 2-sample t test to demonstrate whether the model is statistically comparable with the real-world A&ED department. This is followed by the use of Markov phase-type models for calculating the total costs of the whole system. Finally, various scenarios are explored to assess their potential impact on multiple outcomes of interest. A case study of a mixed-patient environment in a private A&E department is provided to validate the effectiveness of the multi-phase DES approach

IL-4 Deficiency Is Associated with Mechanical Hypersensitivity in Mice

Interleukin-4 (IL-4) is an anti-inflammatory and analgesic cytokine that induces opioid receptor transcription. We investigated IL-4 knockout (ko) mice to characterize their pain behavior before and after chronic constriction injury (CCI) of the sciatic nerve as a model for neuropathic pain. We investigated opioid responsivity and measured cytokine and opioid receptor gene expression in the peripheral and central nervous system (PNS, CNS) of IL-4 ko mice in comparison with wildtype (wt) mice. Naïve IL-4 ko mice displayed tactile allodynia (wt: 0.45 g; ko: 0.18 g; p<0.001), while responses to heat and cold stimuli and to muscle pressure were not different. No compensatory changes in the gene expression of tumor necrosis factor-alpha (TNF), IL-1β, IL-10, and IL-13 were found in the PNS and CNS of naïve IL-4 ko mice. However, IL-1β gene expression was stronger in the sciatic nerve of IL-4 ko mice (p<0.001) 28 days after CCI and only IL-4 ko mice had elevated IL-10 gene expression (p = 0.014). Remarkably, CCI induced TNF (p<0.01), IL-1β (p<0.05), IL-10 (p<0.05), and IL-13 (p<0.001) gene expression exclusively in the ipsilateral spinal cord of IL-4 ko mice. The compensatory overexpression of the anti-inflammatory and analgesic cytokines IL-10 and IL-13 in the spinal cord of IL-4 ko mice may explain the lack of genotype differences for pain behavior after CCI. Additionally, CCI induced gene expression of μ, κ, and δ opioid receptors in the contralateral cortex and thalamus of IL-4 ko mice, paralleled by fast onset of morphine analgesia, but not in wt mice. We conclude that a lack of IL-4 leads to mechanical sensitivity; the compensatory hyperexpression of analgesic cytokines and opioid receptors after CCI, in turn, protects IL-4 ko mice from enhanced pain behavior after nerve lesion

The Impact of Inpatient Boarding on ED Efficiency: A Discrete-Event Simulation Study

In this study, a discrete-event simulation approach was used to model Emergency Department’s (ED) patient flow to investigate the effect of inpatient boarding on the ED efficiency in terms of the National Emergency Department Crowding Scale (NEDOCS) score and the rate of patients who leave without being seen (LWBS). The decision variable in this model was the boarder-released-ratio defined as the ratio of admitted patients whose boarding time is zero to all admitted patients. Our analysis shows that the Overcrowded+ (a NEDOCS score over 100) ratio decreased from 88.4% to 50.4%, and the rate of LWBS patients decreased from 10.8% to 8.4% when the boarder-released-ratio changed from 0% to 100%. These results show that inpatient boarding significantly impacts both the NEDOCS score and the rate of LWBS patient and this analysis provides a quantification of the impact of boarding on emergency department patient crowding

Integrin α3β1–dependent β-catenin phosphorylation links epithelial Smad signaling to cell contacts

Injury-initiated epithelial to mesenchymal transition (EMT) depends on contextual signals from the extracellular matrix, suggesting a role for integrin signaling. Primary epithelial cells deficient in their prominent laminin receptor, α3β1, were found to have a markedly blunted EMT response to TGF-β1. A mechanism for this defect was explored in α3-null cells reconstituted with wild-type (wt) α3 or point mutants unable to engage laminin 5 (G163A) or epithelial cadherin (E-cadherin; H245A). After TGF-β1 stimulation, wt epithelial cells but not cells expressing the H245A mutant internalize complexes of E-cadherin and TGF-β1 receptors, generate phospho-Smad2 (p-Smad2)–pY654–β-catenin complexes, and up-regulate mesenchymal target genes. Although Smad2 phosphorylation is normal, p-Smad2–pY654–β-catenin complexes do not form in the absence of α3 or when α3β1 is mainly engaged on laminin 5 or E-cadherin in adherens junctions, leading to attenuated EMT. These findings demonstrate that α3β1 coordinates cross talk between β-catenin and Smad signaling pathways as a function of extracellular contact cues and thereby regulates responses to TGF-β1 activation

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

The putative Tumor Suppressor VILIP-1 Counteracts Epidermal Growth Factor-Induced Epidermal-Mesenchymal Transition in Squamous Carcinoma Cells

Epithelial-mesenchymal transition (EMT) is a crucial step for the acquisition of invasive properties of carcinoma cells during tumor progression. Epidermal growth factor (EGF)-treatment of squamous cell carcinoma (SCC) cells provokes changes in the expression of lineage markers, morphological changes, and a higher invasive and metastatic potential. Here we show that chronic stimulation with EGF induces EMT in skin-derived SCC cell lines along with the down-regulation of the epithelial marker E-cadherin, and of the putative tumor suppressor VILIP-1 (visinin-like protein 1). In esophageal squamous cell carcinoma and non-small cell lung carcinoma the loss of VILIP-1 correlates with clinicopathological features related to enhanced invasiveness. VILIP-1 has previously been shown to suppress tumor cell invasion via enhancing cAMP-signaling in a murine SCC model. In mouse skin SCC cell lines the VILIP-1-negative tumor cells have low cAMP levels, whereas VILIP-1-positive SCCs possess high cAMP levels, but low invasive properties. We show that in VILIP-1-negative SCCs, Snail1, a transcriptional repressor involved in EMT, is up-regulated. Snail1 expression is reduced by ectopic VILIP-1-expression in VILIP-1-negative SCC cells, and application of the general adenylyl cyclase inhibitor 2′,3′-dideoxyadenosine attenuated this effect. Conversely, EGF-stimulation of VILIP-1-positive SCC cells leads to the down-regulation of VILIP-1 and the induction of Snail1 expression. The induction of Snail is inhibited by elevated cAMP levels. The role of cAMP in EMT was further highlighted by its suppressive effect on the EGF-induced enhancement of migration in VILIP-1-positive SCC cells. These findings indicate that VILIP-1 is involved in EMT of SCC by regulating the transcription factor Snail1 in a cAMP-dependent manner