bluuebunny/crossref_metadata_2025 huggingface dataset:
A School-Based Neuromuscular Training Program and Sport-Related Injury Incidence: A Prospective Randomized Controlled Clinical Trial
Authors: Foss Kim D. Barber , Thomas Staci , Khoury Jane C. , Myer Gregory D. , Hewett Timothy E.
Published: January 2018

Context: 

An estimated 40 million school-aged children (age range = 5−18 years) participate annually in sports in the United States, generating approximately 4 million sport-related injuries and requiring 2.6 million emergency department visits at a cost of nearly $2 billion.

Objective: 

To determine the effects of a school-based neuromuscular training (NMT) program on sport-related injury incidence across 3 sports at the high school and middle school levels, focusing particularly on knee and ankle injuries.

Design: 

Randomized controlled clinical trial.

Setting: 

A total of 5 middle schools and 4 high schools in a single-county public school district.

Patients or Other Participants: 

A total of 474 girls (222 middle school, 252 high school; age = 14.0 ± 1.7 years, height = 161.0 ± 8.1 cm, mass = 55.4 ± 12.2 kg) were cluster randomized to an NMT (CORE; n = 259 athletes) or sham (SHAM; n = 215 athletes) intervention group by team within each sport (basketball, soccer, and volleyball).

Intervention(s): 

The CORE intervention consisted of exercises focused on the trunk and lower extremity, whereas the SHAM protocol consisted of resisted running using elastic bands. Each intervention was implemented at the start of the season and continued until the last competition. An athletic trainer evaluated athletes weekly for sport-related injuries. The coach recorded each athlete-exposure (AE), which was defined as 1 athlete participating in 1 coach-directed session (game or practice).

Main Outcome Measure(s): 

Injury rates were calculated overall, by sport, and by competition level. We also calculated rates of specific knee and ankle injuries. A mixed-model approach was used to account for multiple injuries per athlete.

Results: 

Overall, the CORE group reported 107 injuries (rate = 5.34 injuries/1000 AEs), and the SHAM group reported 134 injuries (rate = 8.54 injuries/1000 AEs; F1,578 = 18.65, P < .001). Basketball (rate = 4.99 injuries/1000 AEs) and volleyball (rate = 5.74 injuries/1000 AEs) athletes in the CORE group demonstrated lower injury incidences than basketball (rate = 7.72 injuries/1000 AEs) and volleyball (rate = 11.63 injuries/1000 AEs; F1,275 = 9.46, P = .002 and F1,149 = 11.36, P = .001, respectively) athletes in the SHAM group. The CORE intervention appeared to have a greater protective effect on knee injuries at the middle school level (knee-injury incidence rate = 4.16 injuries/1000 AEs) than the SHAM intervention (knee-injury incidence rate = 7.04 injuries/1000 AEs; F1,261 = 5.36, P = .02). We did not observe differences between groups for ankle injuries (F1,578 = 1.02, P = .31).

Conclusions: 

Participation in an NMT intervention program resulted in a reduced injury incidence relative to participation in a SHAM intervention. This protective benefit of NMT was demonstrated at both the high school and middle school levels.
Balance Regularity Among Former High School Football Players With or Without a History of Concussion
Authors: Schmidt Julianne D. , Terry Douglas P. , Ko Jihyun , Newell Karl M. , Miller L. Stephen
Published: January 2018

Context: 

Subclinical postural-control changes may persist beyond the point when athletes are considered clinically recovered postconcussion.

Objective: 

To compare postural-control performance between former high school football players with or without a history of concussion using linear and nonlinear metrics.

Design: 

Case-control study.

Setting: 

Clinical research laboratory.

Patients or Other Participants: 

A total of 11 former high school football players (age range, 45–60 years) with 2 or more concussions and 11 age- and height-matched former high school football players without a history of concussion. No participant had college or professional football experience.

Main Outcome Measure(s): 

Participants completed the Sensory Organization Test. We compared postural control (linear: equilibrium scores; nonlinear: sample and multiscale entropy) between groups using a 2 × 3 analysis of variance across conditions 4 to 6 (4: eyes open, sway-referenced platform; 5: eyes closed, sway-referenced platform; 6: eyes open, sway-referenced surround and platform).

Results: 

We observed a group-by-condition interaction effect for medial-lateral sample entropy (F2,40 = 3.26, P = .049, ηp2 = 0.140). Participants with a history of concussion presented with more regular medial-lateral sample entropy values (0.90 ± 0.41) for condition 5 than participants without a history of concussion (1.30 ± 0.35; mean difference = −0.40; 95% confidence interval [CI] = −0.74, −0.06; t20 = −2.48, P = .02), but conditions 4 (mean difference = −0.11; 95% CI: −0.37, 0.15; t20 = −0.86, P = .40) and 6 (mean difference = −0.25; 95% CI: −0.55, 0.06; t20 = −1.66, P = .11) did not differ between groups.

Conclusions: 

Postconcussion deficits, detected using nonlinear metrics, may persist long after injury resolution. Subclinical concussion deficits may persist for years beyond clinical concussion recovery.
THERMOREVERSIBLE CROSS-LINKING OF RUBBER COMPOUNDS: FROM PROOF-OF-CONCEPT TOWARD AN INDUSTRIAL PROCESS
Authors: Polgar L. M. , Keizer J. , Blom R. , Niemeijer B. , de With T. , Picchioni F. , van Duin M.
Published: January 2018

It is demonstrated that the concept of thermoreversible cross-linking of functionalized maleic anhydride grafted ethylene–propylene (EPM-g-MA) rubber using Diels–Alder chemistry is limited neither to laboratory scale using a solvent route nor to gum rubber. The use of an internal mixer is the first step toward an industrial process, since it greatly reduces the processing time and allows for a solventless process for the furan-functionalization and subsequent bismaleimide cross-linking of EPM rubber. Practical rubber compounds were prepared by mixing thermoreversibly cross-linked EPM with carbon black and mineral oil in the same batch mixer. This resulted in reinforcement of the rubber without affecting the thermoreversible character of the cross-linking. The pendant furan groups of the (non)cross-linked EPM-g-furan interact with the carbon black filler. Finally, crystalline EPM rubber compounds were prepared, which show excellent material properties and property retention over multiple reprocessing cycles.
Detection of Anaplastic Lymphoma Kinase (ALK) gene in Non-Small Cell lung Cancer (NSCLC) By CISH Technique
Authors: AlBayyaa Mohanad Ali , Abdulmajeed Ban A.
Published: January 2018

Background/Aim: Anaplastic Lymphoma Kinase (ALK) rearrangement has evaluated activity of NSCLC compared with other molecular subtypes (EGFR, KRAS). Many studies demonstrated that patients with ALK rearrangement positive NSCLC have improved with a good response rates and progression (free survival) when treated with either monotherapy or by a combination therapy compared with EGFR-mutated, KRAS/EGFR/ALK wild type or KRAS-mutated. The aim of this study was to detect and study the signal pattern of normal ALK and compare it to that of mutated ALK with gene rearrangement in cases of non-small cell lung cancer and Inflammatory conditions by implementing the CISH technique. In addition to correlate ALK signal pattern with the histopathological type and grade as well as the age and sex of the patients.Materials & Methods: Forty patients with NSCLC and Inflammatory diseases were enrolled in a comparative cross sectional study. The tissue blocks were sectioned on non-charged slides for the preparation of routine H&E staining. Positively charged slides were used for tissue sections prepared for chromogenic in situ hybridization procedure to detect ALK gene.Results: ALK gene signal break apart was detected in (18/20, 90%) of malignant cases; (0/20, 0%) of non-neoplastic lung lesions. There was a significant statistical difference in their distribution, p < 0.05. While There was no significant association between any disease status and sex P value = 1.000NS. The CISH test was 100% sensitive using negative score as a cutoff point and 90.9% specific. The score was divided into three levels that categorized the cases, so there were six cases in score one (1-32%), nine cases in score two (33-67%) and three cases in score three (68-100%).Conclusion: Detection of ALK rearrangement in the early diagnosis of NSCLC is highly sensitive and can save a lot of efforts in planning chemotherapy regimens. Results were very promising in identifying this mutation by a sensitive and highly specific test. The ALK gene rearrangement could be an early mutation and it is needed as an initiating step for the carcinogenesis process. The presence of a double gene mutation, however, could be the cause of a higher-grade cancer.
Mouse xenograft models for elucidating drug resistance mechanisms
Authors: Ng Wenfa
Published: January 2018

Chemotherapy is the mainstay in cancer treatment. Nevertheless, divergence of treatment responses exists across patients, often with underlying mechanisms unknown. More disturbingly, certain patients exhibit worsened outcome upon treatment. Genomic approaches hold promise for fundamentally altering the cancer treatment landscape. Nevertheless, the goal of formulating effective personalized treatment by profiling the mutational landscape of primary tumour remains elusive, due to current deficiencies in predicting drug sensitivity from genotype. Xenografts, both indirect (via cell line) and direct (from primary tumours), are better physiologic models of human cancers relative to cell lines and transgenic animals. Their utility in informing cancer treatment, however, is constrained by high cost of generating and maintaining animal models, and the paucity of tissue sample available from biopsies, the latter affecting the site of tissue implantation and, by extension, model relevance. Recent advent of high throughput profiling techniques finally afford the tools for decoding the expansive molecular fingerprints that encode observed phenotypes in xenografts; thus, providing a holistic set of biological information that justifies their use. This abstract-only preprint describes a short essay that introduces the scientific and clinical possibilities offered by xenografts for understanding drug resistance mechanisms, and validating functional roles of putative mutations as either oncogenes or tumour suppressors. More important, possibility and workflow of generating a predictive platform for informing drug treatment options based on non-invasive blood biomarkers would be discussed. Known as an integrated genomic classifier, combination of physiological response of direct xenografts to drug treatment and bioinformatics-enabled correlation of blood biomarkers with observed phenotype, at cellular and organismal levels, provides the biological basis for predicting patients’ prognosis without invasive biopsy of solid tumours. Elucidation of drug resistance mechanisms via xenograft models entails: (i) recapitulating in vivo tumour behavior using primary tissue derived cell lines; (ii) identifying mutations and longitudinal profiling of phenotypic responses; and (iii) validating mutations and phenotype via both knockout mice and direct allogenic xenografts. Biological models seek to recapitulate human physiology at specific levels of abstraction for answering targeted questions, but some incongruence is inevitable. Nevertheless, xenografts remain powerful tools for addressing basic, clinical and treatment-related questions using a close functional replica of patient physiology in an animal model. Residual incompatibility between model and observed patient response would require the expertise and clinical experience of oncologists for fine-tuning model suggested drug regimen to particular patient.
Mouse xenograft models for elucidating drug resistance mechanisms
Authors: Ng Wenfa
Published: January 2018

Divergence of treatment responses to chemotherapy exists across patients (often with unknown underlying mechanisms), with some patients exhibiting worsened outcome upon treatment. Genomic approaches (such as microarray profiling and whole genome sequencing) hold promise for transforming cancer treatment, particularly, in tailoring drug regimen to specific patients. Nevertheless, formulating effective personalized treatment via surveying the mutational landscape remains difficult, due to current deficiencies in predicting drug sensitivity from genotype. Xenografts, both indirect (via cell line) and direct (from primary tumours), are good physiologic models of cancers. Their utility in informing cancer treatment, however, is constrained by high cost of generating and maintaining genetically modified animals, and the paucity of tissue samples from biopsies. Advent of high throughput biomolecular profiling tools finally enable reading out the expansive molecular fingerprints that encode observed phenotypes in xenografts. Using pheochromocytoma (an adrenal medulla cancer) as example, this short essay provides a broad overview of the scientific and clinical possibilities offered by xenograft models for understanding resistance mechanisms to particular chemotherapeutic regimens, and upon identification of the putative mutations, confirms their functional roles as either oncogenes or tumour suppressors. Additionally, workflow involved in generating a predictive platform, based on non-invasive blood biomarkers, for informing drug treatment options is discussed. Known as an integrated genomic classifier, combination of physiological response of direct xenografts to drug treatment and bioinformatics enabled correlation of blood biomarkers to observed phenotype at cellular and animal levels, and provides the biological basis for predicting patients’ prognosis without invasive biopsy of solid tumours. Elucidation of drug resistance mechanisms entails: (i) recapitulating in vivo tumour behaviour using cell lines derived from primary tumour; (ii) identification of aetiological mutations and longitudinal profiling of phenotypic response; and (iii) validation of mutations and phenotype via both knockout mice and direct allogenic xenografts. Biological models seek to recapitulate human physiology at specific levels of abstraction for answering designated questions, but incongruence in phenotype is inevitable. Nevertheless, xenografts (especially those derived from patients, PDTX), are powerful tools for addressing basic science, clinical and treatment related questions using close functional replicas of patient physiology in an animal model. Residual incompatibility between model and patient response would require the expertise and clinical experience of oncologists for fine tuning model suggested drug regimen to particular patients.
Sensitivity and specificity of information criteria
Authors: Dziak John J. , Coffman Donna L. , Lanza Stephanie T. , Li Runze
Published: January 2018

Choosing a model with too few parameters can involve making unrealistically simple assumptions and lead to high bias, poor prediction, and missed opportunities for insight. Such models are not flexible enough to describe the sample or the population well. A model with too many parameters can fit the observed data very well, but be too closely tailored to it. Such models may generalize poorly. Penalized-likelihood information criteria, such as Akaike's Information Criterion (AIC), the Bayesian Information Criterion (BIC), the Consistent AIC, and the Adjusted BIC, are widely used for model selection. However, different criteria sometimes support different models, leading to uncertainty about which criterion is the most trustworthy. In some simple cases the comparison of two models using information criteria can be viewed as equivalent to a likelihood ratio test, with the different models representing different alpha levels (i.e., different emphases on sensitivity or specificity; Lin & Dayton 1997). This perspective may lead to insights about how to interpret the criteria in less simple situations. For example, AIC or BIC could be preferable, depending on sample size and on the relative importance one assigns to sensitivity versus specificity. Understanding the differences among the criteria may make it easier to compare their results and to use them to make informed decisions.
Ammonium interference reduced copper uptake by formaldehyde-crosslinked Sargassum sp. seaweed
Authors: Ng Wenfa
Published: January 2018

Sargassum sp., a marine brown macroalgae, is an efficient sorbent for various heavy metals at high concentrations. Nevertheless, the efficiency at which seaweed removes heavy metals from dilute solutions and the effect of ammonium on metal removal is not well understood; an issue of importance given the ubiquity of nitrogenous compounds in the environment arising from various surface run-offs. Herein, the effect of ammonium on copper removal (at trace to low concentration) by formaldehyde crosslinked Sargassum sp. (treated SW) was studied. Due to high copper background, equilibrium sorption experiments was inconclusive concerning treated SW’s ability in removing copper (<1000 ppb), but rapid copper sorption observed in kinetic experiments suggested potential feasibility of the process. Within initial copper concentration of 4 to 20 ppm and pH 2 to 5, experiments revealed that, above a threshold concentration of [NH4+-N] of 50 ppm, ammonium impeded copper uptake on treated SW in a concentration-dependent manner. Specifically, sorption kinetics slowed and uptake capacity decreased with increase in [NH4+-N] from 0 to 2500 ppm. Collectively, beyond demonstrating that treated SW could remove copper from dilute solutions, revelations that ammonium reduced copper sorption highlighted the importance of accounting for the effect in data interpretation and modelling.
What is the Truck Factor of popular GitHub applications? A first assessment
Authors: Avelino Guilherme , Valente Marco Tulio , Hora Andre
Published: January 2018

The Truck Factor designates the minimal number of developers that have to be hit by a truck (or quit) before a project is incapacitated. It can be seen as a measurement of the concentration of information in individual team members. We calculate the Truck Factor for 133 popular GitHub applications, in six languages. To infer the authors of a file we use the Degree-of-Authorship (DOA) metric, which is computed using version history data, and to estimate the Truck Factor, we use a greedy heuristic. Results show that most systems have a small truck factor (46% have Truck Factor=1 and 28% have Truck Factor=2).
A survey of secure middleware for the Internet of Things
Authors: Fremantle Paul , Scott Philip
Published: January 2018

The rapid growth of small Internet connected devices, known as the Internet of Things (IoT), is creating a new set of challenges to create secure, private infrastructures. This paper reviews the current literature on the challenges and approaches to security and privacy in the Internet of Things, with a strong focus on how these aspects are handled in IoT middleware. We focus on IoT middleware because many systems are built from existing middleware and these inherit the underlying security properties of the middleware framework. The paper is composed of three main sections. Firstly, we propose a matrix of security and privacy threats for IoT. This matrix is used as the basis of a widespread literature review aimed at identifying requirements on IoT platforms and middleware. Secondly, we present a structured literature review of the available middleware and how security is handled in these middleware approaches. We utilise the requirements from the first phase to evaluate. Finally, we draw a set of conclusions and identify further work in this area.
Problems in using text-mining and p-curve analysis to detect rate of p-hacking
Authors: Bishop Dorothy V , Thompson Paul A
Published: January 2018

Background: The p-curve is a plot of the distribution of p-values below .05 reported in a set of scientific studies. It has been used to identify bias in the selection of variables and analyses for publication, p-hacking. A recent study by Head et al. (2015) combined this approach with automated text-mining of p-values from a large corpus of published papers and concluded that although there was evidence of p-hacking, its effect was weak in relation to real effect sizes, and not likely to cause serious distortions in the literature. We argue that the methods used by these authors do not support this inference. Methods: P-hacking can take various forms. For the current paper, we developed R code to simulate the use of ghost variables, where an experimenter gathers data on numerous variables but reports only those with statistically significant effects. We also examined the text-mined dataset used by Head et al. to assess its suitability for investigating p-hacking. Results: For uncorrelated variables, simulated p-hacked data do not give the "p-hacking bump" that is evidence of p-hacking. The p-curve develops a positive slope when simulated variables are highly intercorrelated, but does not show the excess of p-values in the p-curve just below .05 that has been regarded as indicative of extreme p-hacking. A right-skewed p-curve is obtained, as expected, when there is a true difference between groups, but it was also obtained in p-hacked datasets containing a high proportion of cases with a true null effect. The results of Head et al are further compromised because their automated text mining detected any p-value mentioned in the Results or Abstract of a paper, including those reported in the course of validation of materials or methods, or confirmation of well-established facts, as opposed to hypothesis-testing. There was no information on the statistical power of studies, nor on the statistical test conducted. Conclusions: We find two problems with the analysis by Head et al. First, though a significant bump in the p-curve just below .05 is good evidence of p-hacking, lack of a bump is not indicative of lack of p-hacking. Furthermore, while studies with evidential value will generate a right-skewed p-curve, we cannot treat a right-skewed p-curve as an indicator of the extent of evidential value. This is particularly the case when there is no control over the type of p-values entered into the analysis. The analysis presented here suggests that the potential for systematic bias is substantial. We conclude that the study by Head et al. provides evidence of p-hacking in the scientific literature, but it cannot be used to estimate the extent and consequences of p-hacking. Analysis of meta-analysed datasets avoids some of these problems, but will still miss an important type of p-hacking.
The universal non-neuronal nature of Parkinson's disease: A theory
Authors: Valente André , Adilbayeva Altynay , Tokay Tursonjan , Rizvanov Albert
Published: January 2018

Parkinson's disease (PD) is one of the most common neurodegenerative disorders, yet the etiology of themajority of its cases remains unknown. In here, relevant published evidence is interpreted and integrated into a comprehensive hypothesis on the nature, origin and inter-cellular mode of propagation of sporadic PD. We propose to characterize sporadic PD as a pathological deviation in the global gene expression program of a cell: the PD expression-state, or PD-state for short.A universal cell-generic state, the PD-state deviation would be particularly damaging in a neuronal context, ultimately leading to neuron death and the ensuing observed clinical signs. We review why age accumulated damage caused by oxidative stress in mitochondria could be the trigger for a primordial cell to shift to the PD-state. We put forward hematopoietic cells could be the first to acquire the PD-state, at hematopoiesis, from the disruption in reactive oxygen species (ROS) homeostasis that arises with age in the hematopoietic stem-cell niche. We argue why, nonetheless, a cell ageing process is unlikely to explain the shift to the PD-state of all the subsequently affected cells in a patient, thus indicating the existence of a distinct mechanism of cellular propagation of the PD-state. We highlight recent findings on the intercellular exchange of mitochondrial DNA and the ability of mitochondrial DNA to modulate the cellular global gene expression state and propose this could form the basis for the intercellular propagation of the PD-state.
Unit testing, model validation, and biological simulation
Authors: Sarma Gopal , Jacobs Travis W , Watts Mark D , Ghayoomi Vahid , Gerkin Richard C , Larson Stephen D
Published: January 2018

The growth of the software industry has gone hand in hand with the development of tools and cultural practices for ensuring the reliability of complex pieces of software. These tools and practices are now acknowledged to be essential to the management of modern software. As computational models and methods have become increasingly common in the biological sciences, it is important to examine how these practices can accelerate biological software development and improve research quality. In this article, we give a focused case study of our experience with the practices of unit testing and test-driven development in OpenWorm, an open-science project aimed at modeling Caenorhabditis elegans. We identify and discuss the challenges of incorporating test-driven development into a heterogeneous, data-driven project, as well as the role of model validation tests, a category of tests unique to software which expresses scientific models.
Actively restored ecosystems as a refuge for biological diversity: evidence from a marine foundational species
Authors: Lefcheck Jonathan , Marion Scott R , Orth Robert J
Published: January 2018

As nearshore ecosystems are increasingly degraded by human activities, active restoration is a critical strategy in ensuring the continued provision of goods and services by coastal habitats. After being absent for nearly six decades, over 1800 ha of the foundational species eelgrass (Zostera marina L.) has been successfully reestablished in the coastal bays of the mid-western Atlantic, USA, but nothing is known about the recovery of associated animal communities. Here, we determine the patterns and drivers of functional recovery in epifaunal invertebrates associated with the restored eelgrass habitat from 2001-2013. After less than a decade, the invertebrate community in the restored bed was richer, more even, and exhibited greater variation in functional traits than a nearby reference bed. Analysis of a suite of environmental and physical variables using random forests revealed these differences were primarily due to the increasing area and density of eelgrass directly attributable to ongoing restoration efforts. Based on analysis of functional traits, we propose that the rapid life histories of constituent organisms may have played a key role in their successful recovery. We also suggest that the diverse epifaunal communities observed may have positive consequences for continued restoration success through the removal of fouling epiphytes from eelgrass blades. Given that restored eelgrass now make up 32% of total seagrass cover in the mid-Atlantic coastal bays, this restoration may foster regional biodiversity by providing new and pristine habitat, particularly given the general decline of existing eelgrass in this region, and globally.
Development of a semi-defined medium for high cell density cultivation of Escherichia coli in shake flask culture system
Authors: Ng Wenfa , Ting Yen-Peng
Published: January 2018

Microbes in environmental studies should be cultured in growth media with characteristics as close to their original habitat as possible, and which also allows a high cell density to be attained for providing enough cells in subsequent experiments. This in-progress report describes the formulation of a medium with an environmentally-relevant composition, and which also affords aerobic high cell density cultivation of Escherichia coli DH5α in shake flasks. The formulated medium comprises four components: a buffer system (K2HPO4: 12.54 g/L and KH2PO4: 2.31 g/L), vitamins (yeast extract: 12.0 g/L), salts (NaCl: 5.0 g/L and MgSO4: 0.24 g/L), and carbon and nitrogen sources (D-Glucose: 6.0 g/L and NH4Cl: 1.5 g/L). Notable characteristics of this medium were: high capacity phosphate buffer system (89 mM phosphate); 1:1 molar ratio between D-Glucose and NH4Cl; and yeast extract providing trace elements and a secondary carbon and nitrogen source. Growth experiments revealed that an OD600nm of 9 was attained after 24 hours of cultivation at 37 oC. This phase of growth was largely fuelled by glucose and NH4Cl. After 48 hours, the OD600nm reached 11, which was fuelled by the mixture of carbohydrates, lipids and proteins in yeast extract. Broth’s pH varied between 5.5 and 7.8 during cultivation, which was in the range conducive for growth of E. coli. In comparison, the OD600nm of E. coli reached 1.4, 3.2, and 9.2 for three commonly used complex media; Nutrient Broth, LB Lennox, and Tryptic Soy Broth, respectively, over 48 hours under identical culture conditions. In addition, the formulated medium was able to maintain a large viable cell population for a longer period of time (three days) relative to Tryptic Soy Broth. Thus, preliminary data suggested that the formulated medium holds potential for use as a high cell density aerobic growth medium for Gram-negative bacteria.
Formulation of a semi-defined medium for high cell density cultivation of Escherichia coli in shake flasks
Authors: Ng Wenfa , Ting Yen-Peng
Published: January 2018

Microbes for environmental research should be cultured in growth media with characteristics (e.g., pH, ionic strength, and organic and ionic composition) as close to their original habitat as possible. In addition, the medium should also enable high cell density to be obtained - needed for providing sufficient cells in subsequent experiments. This in-progress report describes the formulation of a medium with an environmentally-relevant composition (i.e., lack of complex organics), and that allows aerobic high cell density cultivation of Escherichia coli DH5α (ATCC 53868) in shake flasks. The formulated medium comprises four components: a buffer system (K2HPO4: 12.54 g/L and KH2PO4: 2.31 g/L), vitamins (yeast extract: 12.0 g/L), salts (NaCl: 5.0 g/L and MgSO4: 0.24 g/L), and carbon and nitrogen sources (D-Glucose: 6.0 g/L and NH4Cl: 1.5 g/L). Notable characteristics of this medium were: high capacity phosphate buffer system (89 mM phosphate); 1:1 molar ratio between D-Glucose and NH4Cl; and yeast extract providing trace elements and a secondary carbon and nitrogen source. Growth experiments revealed that an OD600nm of 9 was obtained after 24 hours of cultivation at 37 oC. Glucose and NH4Cl served as primary carbon and nitrogen sources for this phase of growth. After 48 hours, the OD600nm reached 11, where carbohydrates, lipids and proteins in yeast extract provided the nutrients for biomass formation. Broth’s pH varied between 5.5 and 7.8 during cultivation, which was in the range conducive for E. coli growth. In comparison, the OD600nm of E. coli reached 1.4, 3.2, and 9.2 in three commonly used complex media; Nutrient Broth, LB Lennox, and Tryptic Soy Broth, respectively, over 48 hours under identical culture conditions. In addition, the formulated medium was able to maintain a large viable cell population for a longer period of time (three days) compared to Tryptic Soy Broth. Thus, preliminary data suggested that the formulated medium holds potential for use as a high cell density aerobic growth medium for Gram-negative bacteria.
Simplex: An individual-based platform for ecological modeling
Authors: Locey Kenneth J
Published: January 2018

A popular approach in ecological modeling explicitly simulates the biology and ecology of individual organisms. Individual-based models (IBM) allow ecological patterns and dynamics to be studied as they emerge from the individual level according to simulated principles and theories. IBMs also allow virtually any aspect of a simulated system to be tracked and recorded for later analysis. I developed a novel IBM platform (i.e, simplex) to explicitly simulate physiology, life history, resource-limited growth, fluctuating environmental dynamics, and community assembly and structure in both fluid and non-fluid environments. simplex accomplishes three primary tasks in keeping with its namesake (i.e., a generalized notion of a triangle to arbitrary dimensions). First, simplex assembles and runs stochastic ecological models from random combinations of over 20 state variables. Second, simplex stores the output of models and generates and stores animations. Third, simplex provides R Markdown files for analyzing simulated data. The simplex source code is freely available, includes the standard ODD description protocol, is open to community-based revision, includes unit testing and time testing, and has been developed to run on modest hardware.
Green software engineering: the curse of methodology
Authors: Hindle Abram
Published: January 2018

Computer Science often seems distant from its natural science cousins, especially software engineering which feels closer to sociology and psychology than to physics. Physical measurements are often rare in software engineering, except in a few niches. One such important niche is that of software energy consumption, green mining, green IT, and sustainable computing, which all fall under the umbrella of green software engineering. With the physical measurement of energy consumption comes all of the limitations of measurement and experimentation that exist in the natural sciences and engineering. Issues abound, from attribution of energy use, isolation of components, to replicable experiments. These get further complicated by cloud computing whereby systems are virtualized and attribution of resource usage is a serious issue. Thus in this work we discuss the current state of software energy consumption, and where will it go.
ANGSD-wrapper
Authors: Durvasula Arun , Kent Tyler V , Hoffman Paul J , Liu Chaochih , Kono Thomas J Y , Morrell Peter L , Ross-Ibarra Jeffrey
Published: January 2018

High throughput sequencing has changed many aspects of population genetics, molecular ecology, and related fields, affecting both experimental design and data analysis. The software package ANGSD allows users to perform a number of population genetic analyses on high-throughput sequencing data. The package is specifically designed to produce more accurate results for samples with low sequencing depth, but it handles a wide array of sampling and experimental designs and makes use of full genome data. Here we present ANGSD-wrapper, a user-friendly interface to ANGSD. ANGSD-wrapper includes a number of ’wrapper’ scripts that facilitate configuration and execution of multi-step analyses. ANGSD- wrapper also provides interactive graphing of ANGSD results, thus enhancing data exploration. We demonstrate the usefulness of ANGSD-wrapper by analyzing resequencing data from populations of wild and domesticated Oryza. ANGSD-wrapper is freely available from https://github.com/ arundurvasula/angsd- wrapper.
ANGSD-wrapper: utilities for analyzing next generation sequencing data
Authors: Durvasula Arun , Hoffman Paul J , Kent Tyler V , Liu Chaochih , Kono Thomas J Y , Morrell Peter L , Ross-Ibarra Jeffrey
Published: January 2018

High throughput sequencing has changed many aspects of population genetics, molecular ecology, and related fields, affecting both experimental design and data analysis. The software package ANGSD allows users to perform a number of population genetic analyses on high-throughput sequencing data. ANGSD uses probabilistic approaches to calculate genome-wide descriptive statistics. The package makes use of genotype likelihood estimates rather than SNP calls and is specifically designed to produce more accurate results for samples with low sequencing depth. ANGSD makes use of full genome data while handling a wide array of sampling and experimental designs. Here we present ANGSD-wrapper, a set of wrapper scripts that provide a user-friendly interface for running ANGSD and visualizing results. ANGSD-wrapper supports multiple types of analyses including esti- mates of nucleotide sequence diversity and performing neutrality tests, principal component analysis, estimation of admixture proportions for individuals samples, and calculation of statistics that quantify recent introgression. ANGSD-wrapper also provides interactive graphing of ANGSD results to enhance data exploration. We demonstrate the usefulness of ANGSD-wrapper by analyzing resequencing data from populations of wild and domesticated Zea. ANGSD-wrapper is freely available from https://github.com/mojaveazure/angsd-wrapper.
Finding patterns in biochemical reaction networks
Authors: Henkel Ron , Lambusch Fabienne , Wolkenhauer Olaf , Sandkuhl Kurt , Rosenke Christian , Waltemath Dagmar
Published: January 2018

Computational models in biology encode molecular and cell biological processes. Many of them can be represented as biochemical reaction networks. Studying such networks, one is often interested in systems that share similar reactions and mechanisms. Typical goals are to understand the parts of a model, to identify reoccurring patterns, and to find biologically relevant motifs. The large number of models are available for such a search, but also the large size of models require automated methods.Specifically the generic problem of finding patterns in large networks is computationally hard. As a consequence, only partial solutions for a structural analysis of models exist. Here we introduce a tool chain that identifies reoccurring patterns in biochemical reaction networks. We started this work with an evaluation of algorithms for the identification of frequent subgraphs. Then, we created graph representations of existing SBML models and ran the most suitable algorithm on the data. The result was a list of reaction patterns together with statistics about the occurrence of each pattern in the data set. The approach was validated with 575 SBML models from the curated branch of BioModels. We analysed how the resulting patterns confirm with expectations from the literature and from previous model statistics. In the future, the identified patterns can serve as a tool to measure the similarity of models.
Post-graduate scholars can publish Literature-Guides on the Web by using Compending-Forum Software to create Knowledge-Step Compendia
Authors: Jewett Don L
Published: January 2018

"Publication forms the core structure supporting the development and transmission of scientific knowledge" (Galbraith2015). Yet, with the WorldWideWeb a dominant part of many activities, internet "publication" is still paper-based in its style and methods, even when it uses a digital medium. Such a paper-based publishing "model" is not adequate for a Web-based world!

In 2006, an estimated 3,700 peer-reviewed articles were published per day (Bjork2009)! As will become apparent, the methods and features described here are needed now, and will be absolutely necessary in the future, when even more articles are published.

A New Knowledge-Tool is proposed that is in addition to those already available. The new Knowledge-Tool is a new Literature-Guide called a "Knowledge-Step Compendium" which will be on a very-narrow topic, will be organized in a new MultiLevel-Format, and will be created in a Compending-Forum on the Internet.

This New Knowledge-Tool will, in turn, be the basis for a change in academic careers of the timing of when a scholar "Compends" Knowledge. A "Knowledge-Compendor" need not be a senior faculty member (as is the case in traditional literature-reviews), but can be a Post-Graduate Student new to a field. Because a Knowledge-Step Compendium is based on a very-narrow topic and created with the aid of an Internet Forum, for a Graduate Student Compendor this activity will be a means to self-organize groups of like-minded scholars that can be the basis for reviews of new data, discovering new ideas, and finding jobs.
Multilayered model of speech
Authors: Chistyakov Andrey
Published: January 2018

Today there are no grammar systems, which allow the creation of a fundamentally new word and concept. All existing grammar systems only work by referring to previously chosen terms, on the bases of which all definitions are created. Implementation of operation on grammar systems are introduced for creation of new terms. The main prerequisite of the research was the rejection of finding a universal solution, which is true for any person. Instead of this, all people were divided into groups according MBTI classification. Each group was expected to have uniform perception of new knowledge. Assessment has been conducted to each group. A mathematical model was created as result of the communication. The scheme of dividing words and sentences into components are shown in the first section of the article. The second section shows a notation construction from the components and the notation packing in memory. The third section shows the ability for conscious memory access (self-action and self-image). As a result, the model of human speech was structured, in where it is possible to create new terms from new knowledge independently.
In silico homology modelling and identification of Tousled-like kinase 1 inhibitors for glioblastoma therapy via high throughput virtual screening protein-ligand docking
Authors: Ibrahim Kamariah , Danjuma Abubakar , Ng Chyan Leong , Abdul Murad Nor Azian , Harun Roslan , Mokhtar Norfilza , Wan Ngah Wan Zurinah , Jamal Rahman
Published: January 2018

Background: Glioblastoma multiforme (GBM) is a grade IV brain tumor that arises from star-shaped glial cells supporting neural cells called astrocytes. The survival of GBM patients remains poor despite many specific molecular targets have been developed. Tousled-like kinase 1 (TLK1), a serine-threonine kinase, was identified to be overexpressed in cancer such as GBM. TLK1 plays an important role in controlling chromosomal aggregation, cell survival and proliferation. In vitro studies suggested that TLK1 is a potential target for some cancers. Hence, identification of suitable molecular inhibitors for TLK1 is warranted as new therapeutic agents in GBM. To date, there is no direct structural information available from X-ray crystallography and NMR studies for TLK1. In this study, we aimed to create a homology model of TLK1 and to identify suitable molecular inhibitors or compounds that are likely to bind and inhibit TLK1 activity via in silico high-throughput virtual screening (HTVS) protein-ligand docking. Methods: 3D homology models of TLK1 were derived from various servers including HOmology ModellER, i-Tasser, Psipred and Swiss Model. All models were evaluated using Swiss-Model Q-Mean server. Only one model was selected for further analysis. Further validation was performed using PDBsum, 3d2go, ProSA, Procheck analysis and ERRAT. Energy minimization was performed using YASARA energy minimization server. Subsequently, HTVS was performed using Molegro Virtual Docker 6.0 and candidate ligands from ligand.info database. Ligand-docking procedures were analyzed at the catalytic site of TLK1. Drug-like molecules were filtered using FAFDrugs3 ADME-Tox filter. Results and conclusion: High quality homology models were obtained from the 4B8M Aurora B kinase derived from Xenopus levias structure that share 33% sequence identity to TLK1. From the HTVS ligand-docking, two compounds were identified to be the potential inhibitors as it did not violate the Lipinski rule of five and CNS-based filter as a potential drug-like molecule for GBM.
Differential response to stress in Ostrea lurida (Carpenter 1864) as measured by gene expression
Authors: Heare J. Emerson , White Samuel J. , Roberts Steven B.
Published: January 2018

Olympia oysters are the only native oyster to the west coast of North America. The population within Puget Sound, WA has been decreasing significantly since the early 1900’s. Current restoration efforts are focused on supplementing local populations with hatchery bred oysters. A recent study by Heare et al. (2015) has shown that there appears to be differences in stress response in oysters from different locations in Puget Sound. However, nothing is known about the underlying mechanisms associated with these observed differences. In this study, expression of genes associated with growth, immune function, and gene regulatory activity in oysters from Oyster Bay, Dabob Bay, and Fidalgo Bay were characterized following temperature and mechanical stress. We found that heat stress and mechanical stress significantly changed expression in molecular regulatory activity and immune response, respectively. We also found that oysters from Oyster Bay had the most dramatic response to stress at the gene expression level. These data provide important baseline information on the physiological response of Ostrea lurida to stress and provide clues to underlying performance differences in the three populations examined.
Differential response to stress in Ostrea lurida as measured by gene expression
Authors: Heare J. Emerson , White Samuel J. , Vadopalas Brent , Roberts Steven B.
Published: January 2018

Olympia oysters are the only oyster native to the west coast of North America. The population within Puget Sound, WA has been decreasing significantly since the early 1900’s. Current restoration efforts are focused on supplementing local populations with hatchery bred oysters. A recent study by Heare et al. (2015) has shown differences in stress response in oysters from different locations in Puget Sound however, nothing is known about the underlying mechanisms associated with these observed differences. In this study, expression of genes associated with growth, immune function, and gene regulatory activity in oysters from Oyster Bay, Dabob Bay, and Fidalgo Bay were characterized following temperature and mechanical stress. We found that heat stress and mechanical stress significantly changed expression in molecular regulatory activity and immune response, respectively. We also found that oysters from Oyster Bay had the most dramatic response to stress at the gene expression level. These data provide important baseline information on the physiological response of Ostrea lurida to stress and provide clues to underlying performance differences in the three populations examined.