Using Community Based Participatory Action Research as Service-learning for Tribal College Students

This work reports the methodological approach used in a Community Based Participatory Research (CBPR) project that incorporated Northern Plains tribal college students from four different communities as data gatherers and co-researchers in their communities. We report preliminary findings of perceptions of service learning among the participating tribal college students based on reflective interviews

A stochastic mixed effects model to assess treatment effects and fluctuations in home-measured peak expiratory flow and the association with exacerbation risk in asthma

Home-based measures of lung function, inflammation, symptoms, and medication use are frequently collected in respiratory clinical trials. However, new statistical approaches are needed to make better use of the information contained in these data-rich variables. In this work, we use data from two phase III asthma clinical trials demonstrating the benefit of benralizumab treatment to develop a novel longitudinal mixed effects model of peak expiratory flow (PEF), a lung function measure easily captured at home using a hand-held device. The model is based on an extension of the mixed effects modeling framework to incorporate stochastic differential equations and allows for quantification of several statistical properties of a patient\u27s PEF data: the longitudinal trend, long-term fluctuations, and day-to-day variability. These properties are compared between treatment groups and related to a patient\u27s exacerbation risk using a repeated time-to-event model. The mixed effects model adequately described the observed data from the two clinical trials, and model parameters were accurately estimated. Benralizumab treatment was shown to improve a patient\u27s average PEF level and reduce long-term fluctuations. Both of these effects were shown to be associated with a lower exacerbation risk. The day-to-day variability was neither significantly affected by treatment nor associated with exacerbation risk. Our work shows the potential of a stochastic model-based analysis of home-based lung function measures to support better estimation and understanding of treatment effects and disease stability. The proposed analysis can serve as a complement to descriptive statistics of home-based measures in the reporting of respiratory clinical trials

Bacterial artificial chromosomes improve recombinant protein production in mammalian cells

<p>Abstract</p> <p>Background</p> <p>The development of appropriate expression vectors for large scale protein production constitutes a critical step in recombinant protein production. The use of conventional expression vectors to obtain cell lines is a cumbersome procedure. Often, stable cell lines produce low protein yields and production is not stable over the time. These problems are due to silencing of randomly integrated expression vectors by the surrounding chromatin. To overcome these chromatin effects, we have employed a Bacterial Artificial Chromosome (BAC) as expression vector to obtain stable cell lines suitable for protein production.</p> <p>Results</p> <p>In this work, we explore the efficacy of a Bacterial Artificial Chromosome based vector applied to production of the constant region of the human IgG1. Direct comparison of bulk HEK 293 cell cultures generated with a "conventional" vector or with a BAC-based vector showed that the BAC-based vector improved the protein yield by a factor of 10. Further analysis of stable cell clones harboring the BAC-based vector showed that the protein production was directly proportional to the number of integrated BAC copies and that the protein production was stable for at least 30 passages.</p> <p>Conclusion</p> <p>Generation of stable cell clones for protein production using Bacterial Artificial Chromosomes offers a clear advantage over the use of conventional vectors. First, protein production is increased by a factor of 10; second, protein production is stable overtime and third, generation of BAC-based expression vectors does not imply a significant amount of work compare to a conventional vector. Therefore, BAC-based vectors may become an attractive tool for protein production.</p

Environmental determinants of perch (Perca fluviatilis) growth in gravel pit lakes and the relative performance of simple versus complex ecological predictors

Growth of fish is an important contributor to individual fitness as well as fish production. Explaining and predicting growth variation across populations is thus important from fundamental and applied perspectives, which requires knowledge about the ecological factors involved in shaping growth. To that end, we estimated environment-dependent von Bertalanffy growth models for 13 gravel pit lake populations of Eurasian perch (Perca fluviatilis) from north-western Germany. To identify the main drivers of perch growth, we evaluated the performance of 16 different biotic or abiotic lake variables in explaining growth variation among lakes. In addition, we compared growth predictions from the best-performing model incorporating “complex” variables that require intensive sampling effort, with a model using only “simple”, easily measurable lake variables (e.g. shoreline development factor). The derivation of a simple model aimed at future applications in typically data-poor inland fisheries, predicting expected growth potential from easily measurable lake variables. A model combining metabolic biomass of predators, maximum depth and shoreline development factor performed best in predicting perch growth variation across gravel pits. All three parameters in this model were positively related to perch growth. The best-performing simple model consisted only of the shoreline development factor. Length-at-age predictions from both models were largely identical, highlighting the utility of shoreline development factor in approximating growth potential of perch in gravel pits similar to our study lakes. Our results can be used to inform fisheries management and restoration efforts at existing or newly excavated gravel pit lakes.Bundesamt für Naturschutz http://dx.doi.org/10.13039/501100010415Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347Spanish Ministry of Economy, Industry and Competitiveness http://dx.doi.org/10.13039/501100010198Peer Reviewe

Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations

While the evaluation of explanations is an important step towards trustworthy models, it needs to be done carefully, and the employed metrics need to be well-understood. Specifically model randomization testing is often overestimated and regarded as a sole criterion for selecting or discarding certain explanation methods. To address shortcomings of this test, we start by observing an experimental gap in the ranking of explanation methods between randomization-based sanity checks [1] and model output faithfulness measures (e.g. [25]). We identify limitations of model-randomization-based sanity checks for the purpose of evaluating explanations. Firstly, we show that uninformative attribution maps created with zero pixel-wise covariance easily achieve high scores in this type of checks. Secondly, we show that top-down model randomization preserves scales of forward pass activations with high probability. That is, channels with large activations have a high probility to contribute strongly to the output, even after randomization of the network on top of them. Hence, explanations after randomization can only be expected to differ to a certain extent. This explains the observed experimental gap. In summary, these results demonstrate the inadequacy of model-randomization-based sanity checks as a criterion to rank attribution methods.Comment: 23 page

Evaluation of an epigenetic assay for predicting repeat prostate biopsy outcome in African American men

OBJECTIVE: To evaluate an epigenetic assay performed on tissue from negative prostate biopsies in a group of African American (AA) men undergoing repeat biopsy, and to compare accuracy for predicting repeat biopsy outcome to prior studies conducted in predominantly Caucasian populations. MATERIALS AND METHODS: The study population consisted of 211 AA men from 7 urology centers across the United States; all of whom were undergoing 12-core transrectal ultrasound-guided repeat biopsy within 30 months from a negative index biopsy. All biopsy cores from the negative index biopsy were profiled for the epigenetic biomarkers GSTP1, APC, and RASSF1 using ConfirmMDx for Prostate Cancer (MDxHealth, Irvine, CA). RESULTS: Upon repeat biopsy, 130 of 211 subjects (62%) had no prostate cancer (PCa) detected and 81 of 211 (38%) were diagnosed with PCa. Of the subjects with PCa, 54 (67%) were diagnosed with Gleason score (GS) = 7 disease. For detection of PCa at repeat biopsy, ConfirmMDx sensitivity was 74.1% and specificity was 60.0%, equivalent to prior studies (P = .235 and .697, respectively). For detection of GS >= 7 PCa, sensitivity was 78% and specificity was 53%. The negative predictive values for detection of all PCa and GS >= 7 PCa were 78.8% and 94.2%, respectively. CONCLUSION: In this group of AA men, we successfully validated an epigenetic assay to assess the need for repeat biopsy. Results were consistent with previous studies from predominantly Caucasian populations. Therefore, the ConfirmMDx assay is a useful tool for risk stratification of AA men who had an initial negative biopsy

Surgical Treatment of Periimplantitis With Augmentative Techniques.

OBJECTIVES To address the focused question: "In patients with osseointegrated implants diagnosed with periimplantitis, what are the clinical and radiographic outcomes of augmentative surgical interventions compared with nonaugmentative surgical measures"? MATERIAL AND METHODS Literature screening was performed in MEDLINE through the PubMed database, for articles published until January 1, 2018. Human studies reporting on the clinical (ie, bleeding on probing [BOP] and probing depth [PD] changes) and/or radiographic (ie, periimplant defect reduction and/or fill) treatment outcomes after surgical augmentative periimplantitis therapy, and/or comparing augmentative and nonaugmentative surgical approaches were searched. RESULTS Thirteen comparative and 11 observational clinical studies were included. Surgical augmentative periimplantitis therapy resulted in mean BOP and PD reduction ranging from 26% to 91%, and 0.74 to 5.4 mm, respectively. The reported mean radiographic fill of intrabony defects ranged between 57% and 93.3%, and defect vertical reduction varied from 0.2 to 3.77 mm. Three randomized controlled clinical studies failed to demonstrate the superiority of augmentative therapy compared with nonaugmentative approach in terms of PD and BOP reduction. CONCLUSIONS The available evidence to support superiority of augmentative surgical techniques for periimplantitis management on the treatment outcomes over nonaugmentative methods is limited

Sector Expansion and Elliptical Modeling of Blue-Gray Ovoids for Basal Cell Carcinoma Discrimination in Dermoscopy Images

Background: Blue-gray ovoids (B-GOs), a critical dermoscopic structure for basal cell carcinoma (BCC), offer an opportunity for automatic detection of BCC. Due to variation in size and color, B-GOs can be easily mistaken for similar structures in benign lesions. Analysis of these structures could afford accurate characterization and automatic recognition of B-GOs, furthering the goal of automatic BCC detection. This study utilizes a novel segmentation method to discriminate B-GOs from their benign mimics. Methods: Contact dermoscopy images of 68 confirmed BCCs with B-GOs were obtained. Another set of 131 contact dermoscopic images of benign lesions possessing B-GO mimics provided a benign competitive set. A total of 22 B-GO features were analyzed for all structures: 21 color features and one size feature. Regarding segmentation, this study utilized a novel sector-based, non-recursive segmentation method to expand the masks applied to the B-GOs and mimicking structures. Results: Logistic regression analysis determined that blue chromaticity was the best feature for discriminating true B-GOs in BCC from benign, mimicking structures. Discrimination of malignant structures was optimal when the final B-GO border was approximated by a best-fit ellipse. Using this optimal configuration, logistic regression analysis discriminated the expanded and fitted malignant structures from similar benign structures with a classification rate as high as 96.5%. Conclusions: Experimental results show that color features allow accurate expansion and localization of structures from seed areas. Modeling these structures as ellipses allows high discrimination of B-GOs in BCCs from similar structures in benign images

The Lantern Vol. 18, No. 1, Fall 1949

• Want, an Old Freedom Unused • Is History Bunk? • How Things Grow • A Real Gone Poem • Hish Proves Himself • Death? Not Yet! • On the Neglect of Victorian Literature • The Tradition Lives On • To the Other Side • Autumn\u27s Panorama • Autumn Treasure • A Walk • Leaves • The Moment • Dawn • Sentiments • Dustinghttps://digitalcommons.ursinus.edu/lantern/1049/thumbnail.jp

The Lantern Vol. 18, No. 1, Fall 1949

• Want, an Old Freedom Unused • Is History Bunk? • How Things Grow • A Real Gone Poem • Hish Proves Himself • Death? Not Yet! • On the Neglect of Victorian Literature • The Tradition Lives On • To the Other Side • Autumn\u27s Panorama • Autumn Treasure • A Walk • Leaves • The Moment • Dawn • Sentiments • Dustinghttps://digitalcommons.ursinus.edu/lantern/1049/thumbnail.jp