bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microbial diversity of extreme habitats in human homes
Authors: Savage Amy M. , Hills Justin , Driscoll Katherine , Fergus Daniel J , Grunden Amy M , Dunn Robert R 
Published: January 2018

Background: High throughput sequencing techniques have opened up the world of microbial diversity to scientists, and a flurry of studies in the most remote and extreme habitats on earth have begun to elucidate the key roles of microbes in ecosystems with extreme conditions. These same environmental extremes can also be found closer to humans; in fact, they can be found in our homes. Here, we used high throughput sequencing techniques to assess microbial diversity in the extreme environments inside human homes (e.g. dishwashers, hot water heaters, washing machine bleach reservoirs, etc.). We focused on habitats in the home with extreme temperature, pH and chemical environmental conditions.
Results: We found that although these habitats supported a lower diversity of microbes than less extreme habitats in the home, there were still diverse microbial assemblages in extreme home environments. Habitats with extreme temperatures alone appeared to be able to support a greater diversity of microbes than habitats with extreme pH or extreme chemical environments alone. Microbial diversity was lowest when habitats had both extreme temperature and one of these other extremes. This interactive effect was strongest when habitats had both extreme temperatures and extreme pH. Under these conditions, taxa with known associations with extreme conditions dominated.
Conclusions: Our findings highlight the importance of examining interactive effects of multiple environmental extremes on microbial communities. Inasmuch as taxa from extreme environments can be both pathogens and industrially useful, our findings also suggest future work to understand both the threats and opportunities posed by the life in these habitats.
Predictive analytics in practice: A novel simulation application for addressing patient flow challenges in today's emergency departments
Authors: Hurwitz Joshua E , Lopiano Kenneth K , Bohrmann Thomas F , Swan Wendy , Falgiani Michael , Tyndall J Adrian 
Published: January 2018

Objectives: To develop a flexible software application that uses predictive analytics to enable emergency department (ED) decision-makers in virtually any environment to predict the effects of operational interventions and enhance continual process improvement efforts. To demonstrate the ability of the application's core simulation model to recreate and predict site-specific patient flow in two very different EDs: a large academic center and a freestanding ED. To describe how the application was used by a freestanding ED medical director to match ED resources to patient demand.
Methods: The application was developed through a public-private partnership between University of Florida Health and Roundtable Analytics, Inc., supported by a National Science Foundation Small Business Technology Transfer (STTR) grant. The core simulation technology was designed to be quickly adaptable to any ED using data routinely collected by most electronic health record systems. To demonstrate model accuracy, Monte Carlo studies were performed to predict the effects of management interventions in two distinct ED settings. At one ED, the medical director conducted simulation studies to evaluate the sustainability of the current staffing strategy and inform his decision to implement specific interventions that better match ED resources to patient demand. After implementation of one intervention, the fidelity of the model's predictions was evaluated.
Results: A flexible, cloud-based software application enabling ED decision-makers to predict the effects of operational decisions was developed and deployed at two qualitatively distinct EDs. The application accurately recreated each ED's throughput and faithfully predicted the effects of specific management interventions. At one site, the application was used to identify when increasing arrivals will dictate that the current staffing strategy will be less effective than an alternative strategy. As actual arrivals approached this point, decision-makers used the application to simulate a variety different interventions; this directly informed their decision to implement a new strategy. The observed outcomes resulting from this intervention fell within the range of predictions from the model.
Conclusion: This application overcomes technical barriers that have made simulation modeling inaccessible to key decision-makers in emergency departments. Using this technology, ED managers with no programming experience can conduct customized simulation studies regardless of their ED's volume and complexity. In two very different case studies, the fidelity of the application was established and the application was shown to have a direct positive effect on patient flow. The effective use of simulation modeling promises to replace inefficient trial-and-error approaches and become a useful and accessible tool for hea
Does stature or wingspan length have a positive effect on competitor rankings or attainment of world title bouts in international and elite mixed martial arts?
Authors: Kirk Christopher 
Published: January 2018

Background: Whilst most anthropometrical research within sport has focussed on muscle and fat distribution, more studies are measuring the relationship between stature and wingspan, which has been found to be selective criteria in many sports.
Methods: In this study the stature, wingspan and stature-to-wingspan ratio (S:W) was recorded for N = 474 elite and international mixed martial arts (MMA) competitors who appeared in televised bouts over the course of one calendar year. Each weight division was split into three or four ranking groups (RG) depending on division size, as well as into groups depending on if the competitors had won a world title (Ch), competed for a world title (El) or had done neither (In).
Results: One-way ANOVA (≤0.05) found that shorter competitors are ranked higher in flyweight and in the middle in women’s straw weight. Independent t-tests (≤0.05) found that shorter competitors also have more chance of winning or competing for a world title in featherweight and flyweight. Independent t-tests (≤0.05) also found a significant difference between males and female for S:W. There was a weak, negative correlation and a moderate, negative correlation between stature and rank in lightweight and light heavyweight respectively and a moderate, negative correlation between S:W and rank in featherweight. There were no other significant differences found.
Discussion: Overall, whilst MMA competitors have a S:W of 1:1.024, due to the paucity of significant differences found, it was determined that anthropometrical measurements cannot be used to predict success in elite and international mixed martial arts.
Validation and development of COI metabarcoding primers for freshwater macroinvertebrate bioassessment
Authors: Elbrecht Vasco , Leese Florian 
Published: January 2018

A central challenge in the present era of biodiversity loss is to assess and manage human impacts on freshwater ecosystems. Macroinvertebrates are an important group for bioassessment as many taxa show specific responses to environmental conditions. However, generating accurate macroinvertebrate inventories based on larval morphology is difficult and error-prone. Here, DNA metabarcoding provides new opportunities. Its potential to accurately identify invertebrates in bulk samples to the species level, has been demonstrated in several case studies. However, DNA based identification is often limited by primer bias, potentially leading to taxa in the sample remaining undetected. Thus, the success of DNA metabarcoding as an emerging technique for bioassessment critically relies on carefully evaluating primers.
We used the R package PrimerMiner to obtain and process cytochrome c oxidase I (COI) sequence data for the 15 most globally relevant freshwater invertebrate groups for stream assessment. Using these sequence alignments, we developed four primer combinations optimized for freshwater macrozoobenthos. All primers were evaluated by sequencing ten mock community samples, each consisting of 52 freshwater invertebrate taxa. Additionally, popular metabarcoding primers from the literature and the developed primers were tested in silico against the 15 relevant invertebrate groups.
The developed primers varied in amplification efficiency and the number of detected taxa, yet all detected more taxa than standard ‘Folmer’ barcoding primers. Two new primer combinations showed more consistent amplification than a previously tested ribosomal marker (16S) and detected all 42 insect taxa present in the mock community samples. In silico evaluation revealed critical design flaws in some commonly used primers from the literature.
We demonstrate a reliable strategy to develop optimized primers using the tool PrimerMiner. The developed primers detected almost all taxa present in the mock samples, and we argue that high base degeneracy is necessary to decrease primer bias as confirmed by experimental results and in silico primer evaluation. We further demonstrate that some primers currently used in metabarcoding studies may not be suitable for amplification of freshwater macroinvertebrates. Therefore, careful primer evaluation and more region / ecosystem specific primers are needed before DNA metabarcoding can be used for routine bioassessment of freshwater ecosystems.
The potential of bacteriocin AS-48 in the control of Propionibacterium acnes
Authors: Cebrián Rubén , Arévalo Sergio , Ananou Samir , Arias-Santiago Salvador , Riazzo Cristina , Rojo Maria Dolores , Bermudez-Ruiz Maria Pilar , Valdivia Eva , Martinez-Bueno Manuel , Maqueda Mercedes 
Published: January 2018

Background Global reports show that the antimicrobial-resistance of Propionibacterium acnes isolated from patients with acne vulgaris is becoming a large problem, making it necessary to find new therapeutic drugs.
Methods In this study, 23 clinical isolates of P. acnes have been identified by MaldiToff and specific PCR. The susceptibility of theses strains to antibiotics (clindamicin, erytromycin and tetracicline) and to bacteriocin (AS-48) has been established, using the CECT 5684 strain as reference. Moreover, we have investigated the potential of several chemical compounds to bolster the activity of AS-48. Finally, the effectivity of four different formulations containing AS-48 and lysozyme have been evaluated on the surface of swine-ear skin previously inoculated with P. acnes CECT5684 strain.
Results. The results presented in this work probe that AS-48 has a significant bactericidal activity against the 23 clinical isolates of P. acnes, including isolates resistant to one or more common antibiotics used in the treatment of acne. Antibacterial synergy of AS-48 with other chemical compounds has been demonstrated, as was the effect of lysozyme and to a lesser extent with palmitic acid. Likewise, the use of a combination therapy into a cream formulation, resulted in large decrease in the number of viable P. acnes counts in an experiemental model.
Conclusion. Once more these studios support that compositions comprising bacteriocins displaying antibacterial activity, must be considered an approach for medical and pharmaceutical purposes. These applications are particularly promising in light of emerging antibiotic resistance across bacteria involved in treatment of dermatological disease as acne vulgaris.
Biofeedback based on mobile accelerometry to improve running in space – ideas and first results
Authors: Daumer Martin , Müller Karl , Mercader Alexandra , Lederer Christian 
Published: January 2018

Background – actibelt technology – a 3D accelerometer in a belt buckle and a package of algorithms, mainly used in international multi centre clinical trials – has also been evaluated for various applications in space, moon and mars in a series of studies and projects since roughly 10 years (2 parabola flight campaigns by ESA, 1 parabola flight campaign by NASA, mars 500).
Aim – To develop a training feedback application which compares the similarity of running parameters under artificial gravity conditions with natural running on earth.
Methods - We use an actibelt BLU2, a version of the actibelt with bluetooth transmission capability, an android tablet with internet access and R packages to visualize and quantify acceleration patterns. Data, including video documentation in some cases, was collected from various runners (marathon, mountain runs, B2run) and various running styles. Written informed consent was obtained.
Results: We have developed an application running on an android tablet. It displays an overview of the projections of the accelerometry pattern of the individual steps in the sagittal plane as well as a summary measure for the mean area per step. There are clear differences between extremes of running style (heel strike overstriding vs. forefoot) both in the area and the shape of the curve.
Discussion/Conclusion: We speculate that online-biofeedback of the acceleration patterns and extracted parameters could advise astronauts during their treadmill training how to best adapt their running style as to optimally avoid loss of bone mineral density. As with running on earth also footwear – with or without heel cushioning, minimal footwear, barefoot – may play an important role.
Structured unit testable templated code for efficient code review process
Authors: Patwardhan Amol S 
Published: January 2018

Background: Modern software development teams are distributed across onsite and off-shore locations. Each team has developers with varying experience levels and English communication skills. In such a diverse development environment it is important to maintain the software quality, coding standards, timely delivery of features and bug fixes. It is also important to reduce testing effort, minimize side effects such as change in functionality, user experience or application performance. Code reviews are intended to control code quality. Unfortunately, many projects lack enforcement of processes and standards because of approaching deadlines, live production issues and lack of resource availability.
Objective: This study examines a novel structured, unit testable templated code method to enforce code review standards with an intent to reduce coding effort, minimize revisions and eliminate functional and performance side effects on the system. The proposed method would also result in unit-testable code that can also be easily rolled back and increase team productivity.
Method: The baseline for traditional code review processes using metrics such as code review duration, bug regression rate, revision count was measured. These metrics were then compared with results from the proposed code review process that used structured unit testable templated code. The performance on 2 large enterprise level applications spanning over 2 years and 9 feature and maintenance release cycles was evaluated.
Results: The structured unit testable templated code method resulted in a decrease in total code review time, revision count and coding effort. It also decreased the number of live production issues caused by code churn or side effects of bug fix when compared to traditional code review process.
Conclusion: The study confirmed that the structured unit testable templated code results in improved code review efficiency. It also increased code quality and provided a robust tool to enforce coding standards in a cross-continent software maintenance team environment. It also relieved core resources from code review effort so that they could concentrate more on newer feature development.
Data Fusion for cleavage target prediction
Authors: Marini Simone , Demartini Andrea , Vitali Francesca , Bellazzi Riccardo , Akutsu Tatsuya 
Published: January 2018

Motivation: Protein cleavage is a pivotal process in cell metabolism. It is involved, among other processes, in cell differentiation and cycle control, stress and immune response, removal of abnormally folded proteins and cell death. Proteases (i.e. protein responsible for cleavage) account for ~2% of all gene products. As consequence, wrongly regulated proteolytic activity may result in diseases. The problem of predicting cleavage targets have been addressed by a number of algorithms. Traditional prediction models tackle the cleavage target machinery encoding directly related information to the outcome class (e.g. by extracting sequence patterns or frequency matrices). We are aware, however, that a huge amount of indirectly-related information is available in public data sets. Peptidases and targets are both proteins, and share similarities as well as non-cleavage interactions in knowledge bases; they are both encoded by genes, and gene interactions are also in databases. Our proposed Data Fusion algorithm leverages on these secondary information sources to infer novel peptidase targets.
Methods: Our approach is based on tri-factorization. The multiplicity of data are fused by inferring a joint model, and without altering their original structure, i.e. data are explicitly represented in the form of a relational block matrix R. Diagonal blocks of R are set to 0, while other blocks are sparse matrices, populated with the relations harvested from the various data sources. R elements are constrained into the range [0, 1], where 0s represent negative or unknown relationships, while 1s are interpreted as certain relationships. We considered three elements in our matrix, namely peptidases, targets and genes. From MEROPS we obtained 657 human peptidases affecting 3460 targets and forming 8931 pairs. From their mapping on Uniprot, 3833 genes coding for pepidases or targets were retained. This information was used to populate the peptidase-target, peptidase-gene and target-gene R blocks. During the data fusion process, each R block is decomposed into three sub-matrices, characterized by low dimensions (if compared to the original R block size). There is no clear consensus about a technique to define these dimensions, and we proceeded by choosing a rank for a given block based on the number of known interactions. Once the dimensions are set, the three sub-matrices are used to reconstruct a user-defined target block Rt. R decomposition is obtained through an iterative process, where constraint matrices play an important role. Constraint matrices are populated with the associations relating objects of the same type. In our application we utilized five constraints: one gene-gene interaction matrix from BIOGrid; two target-target and protease-protease interaction matrices from STRING (0.7 as combined score threshold); two target-target and protease-protease...
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Towards an integrated interactive database for the search of stratification biomarkers in Alkaptonuria
Authors: Cicaloni Vittoria , Zugarini Andrea , Rossi Alberto , Zazzeri Matteo , Santucci Annalisa , Bernini Andrea , Spiga Ottavia 
Published: January 2018

MOTIVATION Alkaptonuria (AKU) is a rare and genetic disease which causes discoloration of bone (a process called ‘ochronosis’) and induces early-onset osteoarthritis. AKU data have not been organized yet and the disease has no approved biomarkers. The ability to collect, integrate and analyze relevant data streams is the core for developing a “Precision Medicine Ecosystem” AKU-dedicated in which biological resources are shared between researchers, clinicians and patients. Computational modeling can be a useful guide to generate an exhaustive and dynamic picture of the individual and to identify the molecular interactions between biomarkers on which progressive diseases are based.
METHODS It has been built a new integrated interactive database thanks to MySQL, the most frequently chosen for use in web applications. In addition, data are statistically analyzed by R software (www.r-project.org) based on Pearson’s correlation coefficient andPvalue. For a biological interpretation of statistic results, Stitch (Kuhn M. et al, 2007) and KEGG (Kanehisa M. et al, 2000) are used.
RESULTS For Precision Medicine (PM) application to AKU, the collection of as much data as possible Alkaptonuria affected patients has been needed in order to organize them in an interactive and integrated database and to find a data-processing system for AKU biomarkers discovery. The database is an effective tool for registered researchers, clinicians and patients who could both easily access all the current information, as well as being able to insert new data, refreshing or replacing previous entries. Data are divided into different sections: genetic, proteic, biochemical, histopathologic and clinical. As far as data analysis is concerned, it has been developed an algorithm to build up a refreshable correlation matrix based on Pearson’s correlation coefficient andPvalue which allows the monitoring of renewable correlations between the most recent data inserted. Together with the mathematical and statistical interpretation, a biological explanation of the results is needed in order to investigate on AKU biomarkers. This dynamic tool could be useful for biomarkers investigation also in other osteoarticular diseases and it is a good starting point for the creation of data management and analysis model appropriate for PM. Through the use of AKU-dedicated database and this innovative analytic approach, it has been possible to become aware of the failure of biomarkers clinically used and to improve the detenction of more exploitable prognostic biomarkers for a more reliable AKU patients clinical monitoring.