Search

The paper mulberry is one of the multifunctional tree species in agroforestry systems and is also commonly utilized in traditional medicine in China and other Asian countries. However, little is known about its molecular genetics, which hinders research on and exploitation of this valuable resource. To discern the correlation between gene expression and the essential properties of the paper mulberry, we performed a transcriptomics analysis, assembling a total of 37,725 unigenes from 54,638,676 reads generated by RNA-seq. Among these, 22,692 unigenes showed greater than 60% similarity with genes from other species. The lengths of 13,566 annotated unigenes were longer than 1,000 bp. Functional clustering analysis with COG (Cluster of Orthologous Groups) revealed that 17,184 unigenes are primarily involved in transcription, translation, signal transduction, carbohydrate metabolism, secondary metabolism, and energy metabolism. GO (Gene Ontology) annotation suggests enrichment of genes encoding antioxidant activity, transporter activity, biosynthesis, metabolism and stress response, with a total of 30,659 unigenes falling in these categories. KEGG (Kyoto Encyclopedia of Genes and Genomes) metabolic pathway analysis showed that 7,199 unigenes are associated with 119 metabolic pathways. In addition to the basic metabolism, these genes are enriched for plant pathogen interaction, flavonoid metabolism and other secondary metabolic processes. Furthermore, differences in the transcriptomes of leaf, stem and root tissues were analyzed and 7,233 specifically expressed unigenes were identified. This global expression analysis provided novel insights about the molecular mechanisms of the biosynthesis of flavonoid, lignin and cellulose, as well as on the response to biotic and abiotic stresses including the remediation of contaminated soil by the paper mulberry. [ABSTRACT FROM AUTHOR]

Determining the distribution of the Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis, YFP) in the Yangtze River has to date relied on traditional visual and counting methods, but such field surveys are time-consuming and expensive. Analyses using environmental DNA (eDNA) to investigate the presence and range of endangered aquatic species have proven to be more economical and effective detection methods, and are a non-invasive approach to sampling. A challenge of relying on eDNA for YFP monitoring is that the Yangtze River is characterized by high turbidity and a strong current. Here, we used an eDNA-based approach to estimate the presence of YFP at 18 sites in the Yangtze River in August 2017 and at an additional 11 sites in January 2018. At each sampling site, we filtered six 1 L water samples with 5 µm pore size filter paper and quantified the amount of YFP eDNA in each water sample using quantitative real-time polymerase chain reaction (qPCR). In addition, YFP eDNA was successfully detected in locations where we visually observed YFP, as well as in locations where YFP were not observed directly. We found that our eDNA-based method had higher detection rates than traditional field survey methods. Although YFP was visually observed in the Yangtze River in winter, water samples collected during the summer contained significantly higher YFP eDNA than winter water samples. Our results demonstrate the potential effectiveness of eDNA detection methods in determining the distribution of YFP in the Yangtze River. [ABSTRACT FROM AUTHOR]

In epidemiology, gerontology, human development and the social sciences, age-period-cohort (APC) models are used to study the variability in trajectories of change over time. A well-known issue exists in simultaneously identifying age, period and birth cohort effects, namely that the three characteristics comprise a perfectly collinear system. That is, since age = period−cohort, only two of these effects are estimable at a time. In this paper, we introduce an alternative framework for considering effects relating to age, period and birth cohort. In particular, instead of directly modeling age in the presence of period and cohort effects, we propose a risk modeling approach to characterize age-related risk (i.e., a hybrid of multiple biological and sociological influences to evaluate phenomena associated with growing older). The properties of this approach, termed risk-period-cohort (RPC), are described in this paper and studied by simulations. We show that, except for pathological circumstances where risk is uniquely determined by age, using such risk indices obviates the problem of collinearity. We also show that the size of the chronological age effect in the risk prediction model associates with the correlation between a risk index and chronological age and that the RPC approach can satisfactorily recover cohort and period effects in most cases. We illustrate the advantages of RPC compared to traditional APC analysis on 27496 individuals from NHANES survey data (2005–2016) to study the longitudinal variability in depression screening over time. Our RPC method has broad implications for examining processes of change over time in longitudinal studies. [ABSTRACT FROM AUTHOR]

Based on electrohysterogram, this paper designed a new method using wavelet-based nonlinear features and stacked sparse autoencoder for preterm birth detection. For each sample, three level wavelet decomposition of a time series was performed. Approximation coefficients at level 3 and detail coefficients at levels 1, 2 and 3 were extracted. Sample entropy of the detail coefficients at levels 1, 2, 3 and approximation coefficients at level 3 were computed as features. The classifier was constructed based on stacked sparse autoencoder. In addition, stacked sparse autoencoder was further compared with extreme learning machine and support vector machine in relation to their classification performance of electrohysterogram. The experiment results reveal that classifier based on stacked sparse autoencoder showed better performance than the other two classifiers with an accuracy of 90%, a sensitivity of 92%, a specificity of 88%. The results indicate that the method proposed in this paper could be effective for detecting preterm birth in electrohysterogram and the framework designed in this work presents higher discriminability than other techniques. [ABSTRACT FROM AUTHOR]

Human embryonic stem cells (hESC), derived from the blastocysts, provide unique cellular models for numerous potential applications. They have great promise in the treatment of diseases such as Parkinson’s, Huntington’s, diabetes mellitus, etc. hESC are a reliable developmental model for early embryonic growth because of their ability to divide indefinitely (pluripotency), and differentiate, or functionally change, into any adult cell type. Their adaptation to toxicological studies is particularly attractive as pluripotent stem cells can be used to model various stages of prenatal development. Automated detection and classification of human embryonic stem cell in videos is of great interest among biologists for quantified analysis of various states of hESC in experimental work. Currently video annotation is done by hand, a process which is very time consuming and exhaustive. To solve this problem, this paper introduces DeephESC 2.0 an automated machine learning approach consisting of two parts: (a) Generative Multi Adversarial Networks (GMAN) for generating synthetic images of hESC, (b) a hierarchical classification system consisting of Convolution Neural Networks (CNN) and Triplet CNNs to classify phase contrast hESC images into six different classes namely: Cell clusters, Debris, Unattached cells, Attached cells, Dynamically Blebbing cells and Apoptically Blebbing cells. The approach is totally non-invasive and does not require any chemical or staining of hESC. DeephESC 2.0 is able to classify hESC images with an accuracy of 93.23% out performing state-of-the-art approaches by at least 20%. Furthermore, DeephESC 2.0 is able to generate large number of synthetic images which can be used for augmenting the dataset. Experimental results show that training DeephESC 2.0 exclusively on a large amount of synthetic images helps to improve the performance of the classifier on original images from 93.23% to 94.46%. This paper also evaluates the quality of the generated synthetic images using the Structural SIMilarity (SSIM) index, Peak Signal to Noise ratio (PSNR) and statistical p-value metrics and compares them with state-of-the-art approaches for generating synthetic images. DeephESC 2.0 saves hundreds of hours of manual labor which would otherwise be spent on manually/semi-manually annotating more and more videos. [ABSTRACT FROM AUTHOR]

Samples of bleached kraft pine cellulosic pulp, either treated with an enzyme preparation (a Thermomyces lanuginosus xylanase, an Aspergillus sp. cellulase, and a multienzyme preparation NS-22086 containing both these activities) or untreated, were refined in a laboratory PFI mill. The treatment with cellulases contained in the last two preparations significantly improved the pulp’s susceptibility to refining (the target freeness value of 30°SR was achieved in a significantly shorter time), increased water retention value (WRV) and fines contents while the weighted average fiber length was significantly reduced. These changes of pulp parameters caused deterioration of paper strength properties. The treatment with the xylanase, which partially hydrolyzed xylan, small amounts of which are associated with cellulose fibers, only slightly loosened the structure of fibers. These subtle changes positively affected the susceptibility of the pulp to refining (refining energy was significantly reduced) and improved the static strength properties of paper. Thus, the treatment of kraft pulps with xylanases may lead to substantial savings of refining energy without negative effects on paper characteristics. [ABSTRACT FROM AUTHOR]

In clinical neuropsychology the cognitive abilities of neurological patients are commonly estimated using well-established paper-based tests. Typically, scores on some tests remain relatively well preserved, whilst others exhibit a significant and disproportionate decline. Scores on those tests that measure preserved cognitive functions (so-called ‘hold’ tests) may be used to estimate premorbid abilities, including scores in non-hold tests that would have been expected prior to the onset of cognitive impairment. Many hold tests entail word reading, with each word being graded as correctly or incorrectly pronounced. Inevitably, such tests are likely to contain words that provide little or no diagnostic power (i.e., can be eliminated without negatively affecting prediction accuracy). In this paper, a genetic algorithm is developed and demonstrated, using n = 92 neurologically healthy participants, to identify optimal word subsets from the National Adult Reading Test that minimize the mean error in predicting the most widely used clinical measure of IQ and cognitive ability, the Wechsler Adult Intelligence Scale Fourth Edition IQ. In addition to requiring only 17–20 of the original 50 words (suggesting that this test could be revised to be up to 66% shorter) and minimizing mean prediction error, the algorithm increases the proportion of the variance in the predicted variable explained in comparison to using all words (from r2 = 0.46 to r2 = 0.61). In a clinical setting this would improve estimates of premorbid cognitive function and, if an abbreviated revision to this test were to be adopted, reduce the arduousness of the test for patients. The proposed method is evaluated with jackknifing and leave one out cross validation. The general approach may be used to optimize the relationship between any two psychological tests by finding the question subset in one test that minimizes the prediction error in a second test by training the genetic algorithm using data collected from participants upon whom both tests have been administered. This approach may also be used to develop new predictive tests, since it provides a method to identify an optimal subset of a set of candidate questions (for which empirical data have been collected) that maximizes prediction accuracy and the proportion of variance in the predicted variable that can be explained. [ABSTRACT FROM AUTHOR]

High-fat diet is associated with hypercholesterolemia and seminal alterations in White New Zealand rabbits. We have previously reported disorders in the development of the manchette-acrosome complex during spermiogenesis and decreased testicular efficiency in hypercholesterolemic rabbits. On the other hand, olive oil incorporated into the diet improves cholesterolemia and semen parameters affected in hypercholesterolemic rabbits. In this paper, we report the recovery—with the addition of olive oil to diet—from the sub-cellular mechanisms involved in the shaping of the sperm cell and testicular efficiency altered in hypercholesterolemic rabbits. Using morphological (structural, ultra-structural and immuno-fluorescence techniques) and cell biology techniques, a reorganization of the manchette and related structures was observed when olive oil was added to the high-fat diet. Specifically, actin filaments, microtubules and lipid rafts—abnormally distributed in hypercholesterolemic rabbits—were recovered with dietary olive oil supplementation. The causes of the decline in sperm count were studied in the previous report and here in more detail. These were attributed to the decrease in the efficiency index and also to the increase in the apoptotic percentage in testis from animals under the high-fat diet. Surprisingly, the addition of olive oil to the diet avoided the sub-cellular, efficiency and apoptosis changes observed in hypercholesterolemic rabbits. This paper reports the positive effects of the olive oil addition to the diet in the recovery of testicular efficiency and normal sperm shaping, mechanisms altered by hypercholesterolemia. [ABSTRACT FROM AUTHOR]

Background: Body size, nutrition and socioeconomic position (SEP) in early life have been associated with a wide range of long-term health effects. Epigenetics is one possible mechanism through which these early life exposures can impact later life health. We conducted a systematic review examining the observational evidence for the impact of body size, nutrition and SEP in early life on the epigenome in humans. Methods: This systematic review is registered with the PROSPERO database (registration number: CRD42016050193). Three datasets were simultaneously searched using Ovid and the resulting studies were evaluated by at least two independent reviewers. Studies measuring epigenetic markers either at the same time as, or after, the early life exposure and have a measure of body size, nutrition or SEP in early life (up to 12 years), written in English and from a community-dwelling participants were included. Results: We identified 90 eligible studies. Seventeen of these papers examined more than one early life exposure of interest. Fifty six papers examined body size, 37 nutrition and 17 SEP. All of the included papers examined DNA methylation (DNAm) as the epigenetic marker. Overall there was no strong evidence for a consistent association between these early life variables in DNAm which may be due to the heterogeneous study designs, data collection methods and statistical analyses. Conclusions: Despite these inconclusive results, the hypothesis that the early life environment can impact DNAm, potentially persisting into adult life, was supported by some studies and warrants further investigation. We provide recommendations for future studies. [ABSTRACT FROM AUTHOR]

In this paper we compare systematically the most promising neuroevolutionary methods and two new original methods on the double-pole balancing problem with respect to: the ability to discover solutions that are robust to variations of the environment, the speed with which such solutions are found, and the ability to scale-up to more complex versions of the problem. The results indicate that the two original methods introduced in this paper and the Exponential Natural Evolutionary Strategy method largely outperform the other methods with respect to all considered criteria. The results collected in different experimental conditions also reveal the importance of regulating the selective pressure and the importance of exposing evolving agents to variable environmental conditions. The data collected and the results of the comparisons are used to identify the most effective methods and the most promising research directions. [ABSTRACT FROM AUTHOR]

Established cell lines are widely used in research, however an appealing question is the comparability of the cells between various laboratories, their characteristics and stability in time. Problematic is also the cell line misidentification, genetic and phenotypic shift or Mycoplasma contamination which are often forgotten in research papers. The monocyte/macrophage-like cell line RAW 264.7 has been one of the most commonly used myeloid cell line for more than 40 years. Despite its phenotypic and functional stability is often discussed in literature or at various scientific discussion panels, their stability during the consecutive passages has not been confirmed in any solid study. So far, only a few functional features of these cells have been studied, for example their ability to differentiate into osteoclasts. Therefore, in the present paper we have investigated the phenotype and functional stability of the RAW 264.7 cell line from passage no. 5 till passage no. 50. We found out that the phenotype (expression of particular macrophage-characteristic genes and surface markers) and functional characteristics (phagocytosis and NO production) of RAW 264.7 cell line remains stable through passages: from passage no. 10 up to passage no. 30. Overall, our results indicated that the RAW 264.7 cell line should not be used after the passage no. 30 otherwise it may influence the data reliability. [ABSTRACT FROM AUTHOR]

Kaempferol (kae) and its glycosides are widely distributed in nature and show multiple bioactivities, yet few reports have compared them. In this paper, we report the antitumor, antioxidant and anti-inflammatory activity differences of kae, kae-7-O-glucoside (kae-7-O-glu), kae-3-O-rhamnoside (kae-3-O-rha) and kae-3-O-rutinoside (kae-3-O-rut). Kae showed the highest antiproliferation effect on the human hepatoma cell line HepG2, mouse colon cancer cell line CT26 and mouse melanoma cell line B16F1. Kae also significantly inhibited AKT phosphorylation and cleaved caspase-9, caspase-7, caspase-3 and PARP in HepG2 cells. A kae-induced increase in DPPH and ABTS radical scavenging activity, inhibition of concanavalin A (Con A)-induced activation of T cell proliferation and NO or ROS production in LPS-induced RAW 264.7 macrophage cells were also seen. Kae glycosides were used to produce kae via environment-friendly enzymatic hydrolysis. Kae-7-O-glu and kae-3-O-rut were hydrolyzed to kae by β-glucosidase and/or α-L-rhamnosidase. This paper demonstrates the application of enzymatic catalysis to obtain highly biologically active kae. This work provides a novel and efficient preparation of high-value flavone-related products. [ABSTRACT FROM AUTHOR]

In this paper, we will investigate the effect of diffusion, which is ubiquitous in nature, on the immune system using a reaction-diffusion model in order to understand the dynamical behavior of complex patterns and control the dynamics of different patterns. Through control theory and linear stability analysis of local equilibrium, we obtain the optimal condition under which the system loses stability and a Turing pattern occurs. By combining mathematical analysis and numerical simulation, we show the possible patterns and how these patterns evolve. In addition, we establish a bridge between the complex patterns and the biological mechanism using the results from a previous study in Nature Cell Biology. The results in this paper can help us better understand the biological significance of the immune system. [ABSTRACT FROM AUTHOR]

The nodes and their connection relationships are the two main bodies for dynamic complex networks. In existing theoretical researches, the phenomena of stabilization and synchronization for complex dynamical networks are generally regarded as the dynamic characteristic behaviors of the nodes, which are mainly caused by coupling effect of connection relationships between nodes. However, the connection relationships between nodes are also one main body of a time-varying dynamic complex network, and thus they may evolve with time and maybe show certain characteristic phenomena. For example, the structural balance in the social networks and the synaptic facilitation in the biological neural networks. Therefore, it is important to investigate theoretically the reasons in dynamics for the occurrence. Especially, from the angle of large-scale systems, how the dynamic behaviors of nodes (such as the individuals, neurons) contribute to the connection relationships is one of worthy research directions. In this paper, according to the structural balance theory of triad proposed by F. Heider, we mainly focus on the connection relationships body, which is regarded as one of the two subsystems (another is the nodes body), and try to find the dynamic mechanism of the structural balance with the internal state behaviors of the nodes. By using the Riccati linear matrix differential equation as the dynamic model of connection relationships subsystem, it is proved under some mathematic conditions that the connection relationships subsystem is asymptotical structural balance via the effects of the coupling roles with the internal state of nodes. Finally, the simulation example is given to show the validity of the method in this paper. [ABSTRACT FROM AUTHOR]

This paper mainly studies the globally fixed-time synchronization of a class of coupled neutral-type neural networks with mixed time-varying delays via discontinuous feedback controllers. Compared with the traditional neutral-type neural network model, the model in this paper is more general. A class of general discontinuous feedback controllers are designed. With the help of the definition of fixed-time synchronization, the upper right-hand derivative and a defined simple Lyapunov function, some easily verifiable and extensible synchronization criteria are derived to guarantee the fixed-time synchronization between the drive and response systems. Finally, two numerical simulations are given to verify the correctness of the results. [ABSTRACT FROM AUTHOR]

This paper aims to optimize a desirable fare structure for the public transit service along a bus-subway corridor with the consideration of those factors related to equity in trip, including travel distance and comfort level. The travel distance factor is represented by the distance-based fare strategy, which is an existing differential strategy. The comfort level one is considered in the area-based fare strategy which is a new differential strategy defined in this paper. Both factors are referred to by the combined fare strategy which is composed of distance-based and area-based fare strategies. The flat fare strategy is applied to determine a reference level of social welfare and obtain the general passenger flow along transit lines, which is used to divide areas or zones along the corridor. This problem is formulated as a bi-level program, of which the upper level maximizes the social welfare and the lower level capturing traveler choice behavior is a variable-demand stochastic user equilibrium assignment model. A genetic algorithm is applied to solve the bi-level program while the method of successive averages is adopted to solve the lower-level model. A series of numerical experiments are carried out to illustrate the performance of the models and solution methods. Numerical results indicate that all three differential fare strategies play a better role in enhancing the social welfare than the flat fare strategy and that the fare structure under the combined fare strategy generates the highest social welfare and the largest resulting passenger demand, which implies that the more equity factors a differential fare strategy involves the more desirable fare structure the strategy has. [ABSTRACT FROM AUTHOR]

Frailty is a common condition in older age and is a public health concern which requires integrated care and involves different stakeholders. This meta-synthesis focuses on experiences, understanding, and attitudes towards screening, care, intervention and prevention for frailty across frail and healthy older persons, caregivers, health and social care practitioners. Studies published since 2001 were identified through search of electronic databases; 81 eligible papers were identified and read in full, and 45 papers were finally included and synthesized. The synthesis was conducted with a meta-ethnographic approach. We identified four key themes: Uncertainty about malleability of frailty; Strategies to prevent or to respond to frailty; Capacity to care and person and family-centred service provision; Power and choice. A bottom-up approach which emphasises and works in synchrony with frail older people's and their families' values, goals, resources and optimisation strategies is necessary. A greater employment of psychological skills, enhancing communication abilities and tools to overcome disempowering attitudes should inform care organisation, resulting in more efficient and satisfactory use of services. Public health communication about prevention and management of frailty should be founded on a paradigm of resilience, balanced acceptance, and coping. Addressing stakeholders’ views about the preventability of frailty was seen as a salient need. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of different components involved in the evaluation process. [ABSTRACT FROM AUTHOR]

To deal with the conflicts between left-turn and through traffic streams and increase the discharge capacity, this paper addresses the pre-signal which is implemented at a signalized intersection. Such an intersection with pre-signal is termed as a tandem intersection. For the tandem intersection, phase swap sorting strategy is deemed as the most effective phasing scheme in view of some exclusive merits, such as easier compliance of drivers, and shorter sorting area. However, a major limitation of the phase swap sorting strategy is not considered in previous studies: if one or more vehicle is left at the sorting area after the signal light turns to red, the capacity of the approach would be dramatically dropped. Besides, previous signal control studies deal with a fixed timing plan that is not adaptive with the fluctuation of traffic flows. Therefore, to cope with these two gaps, this paper firstly takes an in-depth analysis of the traffic flow operations at the tandem intersection. Secondly, three groups of loop detectors are placed to obtain the real-time vehicle information for adaptive signalization. The lane selection behavior in the sorting area is considered to set the green time for intersection signals. With the objective of minimizing the vehicle delay, the signal control parameters are then optimized based on a dynamic programming method. Finally, numerical experiments show that average vehicle delay and maximum queue length can be reduced under all scenarios. [ABSTRACT FROM AUTHOR]

Genomic signal processing (GSP) refers to the use of signal processing for the analysis of genomic data. GSP methods require the transformation or mapping of the genomic data to a numeric representation. To date, several DNA numeric representations (DNR) have been proposed; however, it is not clear what the properties of each DNR are and how the selection of one will affect the results when using a signal processing technique to analyze them. In this paper, we present an experimental study of the characteristics of nine of the most frequently-used DNR. The objective of this paper is to evaluate the behavior of each representation when used to measure the similarity of a given pair of DNA sequences. [ABSTRACT FROM AUTHOR]

Lignocellulosic materials from municipal solid waste emerge as attractive resources for anaerobic digestion biorefinery. To increase the knowledge required for establishing efficient bioprocesses, dynamics of batch fermentation by the cellulolytic bacterium Ruminiclostridium cellulolyticum were compared using three cellulosic materials, paper handkerchief, cotton discs and Whatman filter paper. Fermentation of paper handkerchief occurred the fastest and resulted in a specific metabolic profile: it resulted in the lowest acetate-to-lactate and acetate-to-ethanol ratios. By shotgun proteomic analyses of paper handkerchief and Whatman paper incubations, 151 proteins with significantly different levels were detected, including 20 of the 65 cellulosomal components, 8 non-cellulosomal CAZymes and 44 distinct extracytoplasmic proteins. Consistent with the specific metabolic profile observed, many enzymes from the central carbon catabolic pathways had higher levels in paper handkerchief incubations. Among the quantified CAZymes and cellulosomal components, 10 endoglucanases mainly from the GH9 families and 7 other cellulosomal subunits had lower levels in paper handkerchief incubations. An in-depth characterization of the materials used showed that the lower levels of endoglucanases in paper handkerchief incubations could hypothetically result from its lower crystallinity index (50%) and degree of polymerization (970). By contrast, the higher hemicellulose rate in paper handkerchief (13.87%) did not result in the enhanced expression of enzyme with xylanase as primary activity, including enzymes from the “xyl-doc” cluster. It suggests the absence, in this material, of molecular structures that specifically lead to xylanase induction. The integrated approach developed in this work shows that subtle differences among cellulosic materials regarding chemical and structural characteristics have significant effects on expressed bacterial functions, in particular the cellulolysis machinery, resulting in different metabolic patterns and degradation dynamics. [ABSTRACT FROM AUTHOR]

Lung cancer, primarily non-small-cell lung cancer (NSCLC), is the leading cause of cancer deaths in the United States and worldwide. While early detection significantly improves five-year survival, there are no reliable diagnostic tools for early detection. Several exosomal microRNAs (miRs) are overexpressed in NSCLC, and have been suggested as potential biomarkers for early detection. The present paper develops a mathematical model for early stage of NSCLC with emphasis on the role of the three highest overexpressed miRs, namely miR-21, miR-205 and miR-155. Simulations of the model provide quantitative relationships between the tumor volume and the total mass of each of the above miRs in the tumor. Because of the positive correlation between these miRs in the tumor tissue and in the blood, the results of the paper may be viewed as a first step toward establishing a combination of miRs 21, 205, 155 and possibly other miRs as serum biomarkers for early detection of NSCLC. [ABSTRACT FROM AUTHOR]

In nature, protozoa play a major role in controlling bacterial populations. This paper proposes a microfluidic device for the study of protozoa behaviors change due to their chemotactic response in the presence of bacterial cells. A three-channel microfluidic device was designed using a nitrocellulose membrane into which channels were cut using a laser cutter. The membrane was sandwiched between two glass slides; a Euglena suspension was then allowed to flow through the central channel. The two side channels were filled with either, 0.1% peptone as a negative control, or a Listeria suspension respectively. The membrane design prevented direct interaction but allowed Euglena cells to detect Listeria cells as secretions diffused through the nitrocellulose membrane. A significant number of Euglena cells migrated toward the chambers near the bacterial cells, indicating a positive chemotactic response of Euglena toward chemical cues released from Listeria cells. Filtrates collected from Listeria suspension with a series of molecular weight cutoffs (3k, 10k and 100k) were examined in Euglena chemotaxis tests. Euglena cells were attracted to all filtrates collected from the membrane filtration with different molecular weight cutoffs, suggesting small molecules from Listeria might be the chemical cues to attract protozoa. Headspace volatile organic compounds (VOC) released from Listeria were collected, spiked to 0.1% peptone and tested as the chemotactic effectors. It was discovered that the Euglena cells responded quickly to Listeria VOCs including decanal, 3,5- dimethylbenzaldehyde, ethyl acetate, indicating bacterial VOCs were used by Euglena to track the location of bacteria. [ABSTRACT FROM AUTHOR]

The gut microbial community structure of adult Thrips tabaci collected from 10 different agro-climatically diverse locations of India was characterized by using the Illumina MiSeq platform to amplify the V3 region of the 16S rRNA gene of bacteria present in the sampled insects. Analyses were performed to study the bacterial communities associated with Thrips tabaci in India. The complete bacterial metagenome of T. tabaci was comprised of 1662 OTUs of which 62.25% belong to known and 37.7% of unidentified/unknown bacteria. These OTUs constituted 21 bacterial phyla of 276 identified genera. Phylum Proteobacteria was predominant, followed by Actinobacteria, Firmicutes, Bacteroidetes and Cyanobacteria. Additionally, the occurrence of the reproductive endosymbiont, Wolbachia was detected at two locations (0.56%) of the total known OTUs. There is high variation in diversity and species richness among the different locations. Alpha-diversity metrics indicated the higher gut bacterial diversity at Bangalore and lowest at Rahuri whereas higher bacterial species richness at T. tabaci samples from Imphal and lowest at Jhalawar. Beta diversity analyses comparing bacterial communities between the samples showed distinct differences in bacterial community composition of T. tabaci samples from different locations. This paper also constitutes the first record of detailed bacterial communities associated with T. tabaci. The location-wise variation in microbial metagenome profile of T. tabaci suggests that bacterial diversity might be governed by its population genetic structure, environment and habitat. [ABSTRACT FROM AUTHOR]

The Epstein-Barr virus (EBV) induces B-cell proliferation with high efficiency through expression of latent proteins and microRNAs. This process takes place in vivo soon after infection, presumably to expand the virus reservoir, but can also induce pathologies, e.g. an infectious mononucleosis (IM) syndrome after primary infection or a B-cell lymphoproliferation in immunosuppressed individuals. In this paper, we investigated the growth characteristics of EBV-infected B-cells isolated from transplant recipients or patients with IM. We found that these cells grew and withstood apoptosis at highly variable rates, suggesting that the expansion rate of the infected B-cells widely varies between individuals, thereby influencing the size of the B-cell reservoir and the ability to form tumors in infected individuals. All viruses investigated were type 1 and genetically close to western strains. EBV-infected B-cells expressed the transforming EBV latent genes and microRNAs (miRNAs) at variable levels. We found that the B-cell growth rates positively correlated with the BHRF1 miRNA levels. Comparative studies showed that infected B-cells derived from transplant recipients with iEBVL on average expressed higher levels of EBV miR-BHRF1 miRNAs and grew more rapidly than B-cells from IM patients, suggesting infection by more transforming viruses. Altogether, these findings suggest that EBV infection has a highly variable impact on the B-cell compartment that probably reflects the genetic diversity of both the virus and the host. It also demonstrates the unexpected finding that B-cells from different individuals can grow at different speed under the influence of the same virus infection. [ABSTRACT FROM AUTHOR]

Due to the fast speed of data generation and collection from advanced equipment, the amount of data obviously overflows the limit of available memory space and causes difficulties achieving high learning accuracy. Several methods based on discard-after-learn concept have been proposed. Some methods were designed to cope with a single incoming datum but some were designed for a chunk of incoming data. Although the results of these approaches are rather impressive, most of them are based on temporally adding more neurons to learn new incoming data without any neuron merging process which can obviously increase the computational time and space complexities. Only online versatile elliptic basis function (VEBF) introduced neuron merging to reduce the space-time complexity of learning only a single incoming datum. This paper proposed a method for further enhancing the capability of discard-after-learn concept for streaming data-chunk environment in terms of low computational time and neural space complexities. A set of recursive functions for computing the relevant parameters of a new neuron, based on statistical confidence interval, was introduced. The newly proposed method, named streaming chunk incremental learning (SCIL), increases the plasticity and the adaptabilty of the network structure according to the distribution of incoming data and their classes. When being compared to the others in incremental-like manner, based on 11 benchmarked data sets of 150 to 581,012 samples with attributes ranging from 4 to 1,558 formed as streaming data, the proposed SCIL gave better accuracy and time in most data sets. [ABSTRACT FROM AUTHOR]

The neural computational model GrowthEstimate is introduced with focusing on new perspectives for the practical estimation of weight specific growth rate (SGR, % day–1). It is developed using recurrent neural networks of reservoir computing type, for estimating SGR based on the known data of three key biological factors relating to growth. These factors are: (1) weight (g) for specifying the age of the growth stage; (2) digestive efficiency through the pyloric caecal activity ratio of trypsin to chymotrypsin (T/C ratio) for specifying genetic differences in food utilization and growth potential, basically resulting from food consumption under variations in food quality and environmental conditions; and (3) protein growth efficiency through the condition factor (CF, 100 × g cm–3), as higher dietary protein level affecting higher skeletal growth (length) and resulting in lower CF. The computational model was trained using four datasets of different salmonids with size variations. It was evaluated with 15% of each dataset, resulting in an acceptable range of SGR outputs. Additional tests with different species indicated similarity between the estimated SGR outputs and the real SGR values, and the same ranking of wild population growth. The developed model GrowthEstimate is exceptionally useful for the precise and comparable growth estimation of living resources at individual levels, especially in natural ecosystems where the studied individuals, environmental conditions, food availability and consumption rates cannot be controlled. It is a revelation and will help to minimize uncertainty in wild stock assessment process. This will improve our knowledge in nutritional ecology, through the biochemical effects of climate change and environmental impact on the growth performance quality of aquatic living resources in the wild, as well as in aquaculture. The original GrowthEstimate software is available at GitHub repository (). All other relevant data are within the paper. It will be improved for generality for future use, and required co-operations of the biodata collections of different species from different climate zones. Therefore, a co-operation will be available. [ABSTRACT FROM AUTHOR]

The conclusion of our recent paper that performance of the STAN device in clinical practice is potentially limited by high false-negative and high false-positive STAN-event rates and loss of ST waveform assessment capacity during severe hypoxemia, evoked comments by Kjellmer, Lindecrantz and Rosén. These comments can be summarized as follows: 1) STAN analysis is based on a unipolar lead but the authors used a negative aVF lead, and they did not validate this methodology; 2) The fetuses used in the study were too young to display the signals that the authors were trying to detect. In response to these comments we now provide both a theoretical and an experimental underpinning of our approach. In an in vivo experiment in human we placed several electrodes over the head (simulating different places of a scalp electrode), simultaneously recorded Einthoven lead I and II, and constructed −aVF from these two frontal leads. Irrespective of scalp electrode placement, the correlation between any of unipolar scalp electrode-derived signals and constructed–aVF was excellent (≥ 0.92). In response to the second comment we refer to a study which demonstrated that umbilical cord occlusion resulted in rapid increase in T/QRS ratio that coincided with initial hypertension and bradycardia at all gestational ages which were tested from 0.6–0.8 gestation. The animals of our study were in this gestational range and, hence, our experimental setup can be used to assess STAN’s quality to detect fetal hypoxia. In conclusion, we have clearly demonstrated the appropriateness of using–aVF as a proxy for a scalp electrode-derived signal in STAN in these preterm lambs. Investigation why STAN could not detect relevant ST-changes and instead produced erroneous alarms in our experimental setup is hampered by the fact that the exact STAN algorithm (signal processing and analysis) is not in the public domain. [ABSTRACT FROM AUTHOR]

Single-point incremental forming (SPIF) is a technology that allows incremental manufacturing of complex parts from a flat sheet using simple tools; further, this technology is flexible and economical. Measuring the forming force using this technology helps in preventing failures, determining the optimal processes, and implementing on-line control. In this paper, an experimental study using SPIF is described. This study focuses on the influence of four different process parameters, namely, step size, tool diameter, sheet thickness, and feed rate, on the maximum forming force. For an efficient force predictive model based on an adaptive neuro-fuzzy inference system (ANFIS), an artificial neural network (ANN) and a regressions model were applied. The predicted forces exhibited relatively good agreement with the experimental results. The results indicate that the performance of the ANFIS model realizes the full potential of the ANN model. [ABSTRACT FROM AUTHOR]

The pepper weevil, Anthonomus eugenii, is a major pest on Capsicum species. Apart from natural spread, there is a risk of spread via international pepper trade. In the Netherlands, a pepper weevil outbreak occurred in 2012 and affected six greenhouses producing different sweet pepper varieties. The following year, a pepper weevil outbreak occurred in Italy. To trace the origin of the Dutch outbreak and to establish if the Dutch and Italian outbreaks were linked, we determined the mitogenomes of A. eugenii specimens collected at outbreak locations, and compared these with specimens from the native area, and other areas where the pest was introduced either by natural dispersal or via trade. The circular 17,257 bp A. eugenii mitogenome comprises thirteen mitochondrial genes typically found in insect species. Intra-species variation of these mitochondrial genes revealed four main mitochondrial lineages encompassing 41 haplotypes. The highest diversity was observed for specimens from its presumed native area (i.e. Mexico). The Dutch outbreak specimens represented three highly similar haplotypes, suggesting a single introduction of the pest. The major Dutch haplotype was also found in two specimens from New Jersey. As the Netherlands does not have pepper trade with New Jersey, it is likely that the specimens sampled in New Jersey and those sampled in the Netherlands originate from a shared source that was not included in this study. In addition, our analysis shows that the Italian and Dutch outbreaks were not linked. The mitochondrial genome is a useful tool to trace outbreak populations and the methodology presented in this paper could prove valuable for other invasive pest species, such as the African fruit moth Thaumatotibia leucotreta and emerald ash borer Agrilus planipennis. [ABSTRACT FROM AUTHOR]

Cells and organisms have developed homeostatic mechanisms which protect them against a changing environment. How growth and homeostasis interact is still not well understood, but of increasing interest to the molecular and synthetic biology community to recognize and design control circuits which can oppose the diluting effects of cell growth. In this paper we describe the performance of selected negative feedback controllers in response to different applied growth laws and time dependent outflow perturbations of a controlled variable. The approach taken here is based on deterministic mass action kinetics assuming that cell content is instantaneously mixed. All controllers behave ideal in the sense that they for step-wise perturbations in volume and a controlled compound A are able to drive A precisely back to the controllers’ theoretical set-points. The applied growth kinetics reflect experimentally observed growth laws, which range from surface to volume ratio growth to linear and exponential growth. Our results show that the kinetic implementation of integral control and the structure of the negative feedback loop are two properties which affect controller performance. Best performance is observed for controllers based on derepression kinetics and controllers with an autocatalytic implementation of integral control. Both are able to defend exponential growth and perturbations, although the autocatalytic controller shows an offset from its theoretical set-point. Controllers with activating signaling using zero-order or bimolecular (antithetic) kinetics for integral control behave very similar but less well. Their performance can be improved by implementing negative feedback structures having repression/derepression steps or by increasing controller aggressiveness. Our results provide a guide what type of feedback structures and integral control kinetics are suitable to oppose the dilution effects by different growth laws and time dependent perturbations on a deterministic level. [ABSTRACT FROM AUTHOR]

Plant cell walls development is an integrated process during which several components are deposited successively. In the cell walls in grass, the accessibility of structural polysaccharides is limited by the cell walls structure and composition mainly as a result of phenolic compounds. Here, we studied the patterns of cell walls establishment in the internode supporting the ear in three distinct maize genotypes. The developmental patterns observed in the internode cell walls in terms of its composition are reported with an emphasis on lignification, p-coumaroylation and feruloylation. We combined biochemical and histological approaches and revealed that internode cell walls development in maize before flowering is characterized by the rapid deposition of secondary cell walls components and robust lignification in both the pith and the rind. After flowering and until silage maturity, the slow deposition of secondary walls components occurs in the cortical region, and the deposited lignins are rich in β-O-4 bonds and are highly p-coumaroylated. We conclude the paper by proposing a revised spatiotemporal model based on that proposed by Terashima et al. (1993) for cell walls development in grass. [ABSTRACT FROM AUTHOR]

Freshwater sulfide springs have extreme environmental conditions that only few vertebrate species can tolerate. These species often develop a series of morphological and molecular adaptations to cope with the challenges of life under the toxic and hypoxic conditions of sulfide springs. In this paper, we described a new fish species of the genus Jenynsia, Anablepidae, from a sulfide spring in Northwestern Argentina, the first in the family known from such extreme environment. Jenynsia sulfurica n. sp. is diagnosable by the lack of scales on the pre-pelvic area or the presence of a single row of scales, continuous or not, from the isthmus to the bases of the pelvic fins. Additionally, it presents a series of morphological and molecular characteristics that appear convergent with those seen in other fish species (e.g., Poeciliids) inhabiting sulfide springs. Most notably, J. sulfurica has an enlarged head and postorbital area compared to other fish of the genus and a prognathous lower jaw with a hypertrophied lip, thought to facilitate respiration at the air-water interface. Analyses of cox1 sequence showed that J. sulfurica has two unique mutations resulting in amino acid substitutions convergent to those seen in Poeciliids from sulfide springs and known to provide a physiological mechanism related to living in sulfide environments. A phylogenetic analysis, including molecular and morphological characters, placed J. sulfurica as sister taxa to J. alternimaculata, a species found in nearby, non-sulfide habitats directly connected to the sulfide springs. Thus, it can be inferred that the selection imposed by the presence of H2S has resulted in the divergence between these two species and has potentially served as a barrier to gene flow. [ABSTRACT FROM AUTHOR]

The subset of pro-inflammatory B cells, called late memory, tissue-like or double negative (DN), accumulates in the blood of elderly individuals. Here we show that DN B cells do not proliferate and do not make antibodies to influenza antigens, but they secrete antibodies with autoimmune reactivity, in agreement with their membrane phenotype (CD95+CD21-CD11c+) and their spontaneous expression of the transcription factor T-bet. These cells also increase in the blood of individuals with obesity and autoimmune diseases, but causative mechanisms and signaling pathways involved are known only in part. In the present paper we compare frequencies and metabolic requirements of these cells in the blood of healthy individuals of different ages and in the blood and the subcutaneous adipose tissue (SAT) of individuals with obesity. Results show that DN B cells from young individuals have minimal metabolic requirements, DN B cells from elderly and obese individuals utilize higher amounts of glucose to perform autoimmune antibody production and enroll in aerobic glycolysis to support their function. DN B cells from the SAT have the highest metabolic requirements as they activate oxidative phosphorylation, aerobic glycolysis and fatty acid oxidation. DN B cells from the SAT also show the highest levels of ROS and the highest levels of phosphorylated AMPK (5’-AMP activated kinase) and Sestrin 1, both able to mitigate stress and cell death. This metabolic advantage drives DN B cell survival and function (secretion of autoimmune antibodies). [ABSTRACT FROM AUTHOR]

Endosomes are subcellular organelles which serve as important transport compartments in eukaryotic cells. Fluorescence microscopy is a widely applied technology to study endosomes at the subcellular level. In general, a microscopy image can contain a large number of organelles and endosomes in particular. Detecting and annotating endosomes in fluorescence microscopy images is a critical part in the study of subcellular trafficking processes. Such annotation is usually performed by human inspection, which is time-consuming and prone to inaccuracy if carried out by inexperienced analysts. This paper proposes a two-stage method for automated detection of ring-like endosomes. The method consists of a localization stage cascaded by an identification stage. Given a test microscopy image, the localization stage generates a voting-map by locally comparing the query endosome patches and the test image based on a bag-of-words model. Using the voting-map, a number of candidate patches of endosomes are determined. Subsequently, in the identification stage, a support vector machine (SVM) is trained using the endosome patches and the background pattern patches. Each of the candidate patches is classified by the SVM to rule out those patches of endosome-like background patterns. The performance of the proposed method is evaluated with real microscopy images of human myeloid endothelial cells. It is shown that the proposed method significantly outperforms several state-of-the-art competing methods using multiple performance metrics. [ABSTRACT FROM AUTHOR]

Microscopic examination of peripheral blood plays an important role in the field of diagnosis and control of major diseases. Peripheral leukocyte recognition by manual requires medical technicians to observe blood smears through light microscopy, using their experience and expertise to discriminate and analyze different cells, which is time-consuming, labor-intensive and subjective. The traditional systems based on feature engineering often need to ensure successful segmentation and then manually extract certain quantitative and qualitative features for recognition but still remaining a limitation of poor robustness. The classification pipeline based on convolutional neural network is of automatic feature extraction and free of segmentation but hard to deal with multiple object recognition. In this paper, we take leukocyte recognition as object detection task and apply two remarkable object detection approaches, Single Shot Multibox Detector and An Incremental Improvement Version of You Only Look Once. To improve recognition performance, some key factors involving these object detection approaches are explored and the detection models are generated using the train set of 14,700 annotated images. Finally, we evaluate these detection models on test sets consisting of 1,120 annotated images and 7,868 labeled single object images corresponding to 11 categories of peripheral leukocytes, respectively. A best mean average precision of 93.10% and mean accuracy of 90.09% are achieved while the inference time is 53 ms per image on a NVIDIA GTX1080Ti GPU. [ABSTRACT FROM AUTHOR]

Hydroxymethylcytosine (5hmC) methylation is a well-known epigenetic mark that is involved in gene regulation and may impact genome stability. To investigate a possible role of 5hmC in cancer development and progression, one must be able to detect and quantify its level first. In this paper, we address the issue of 5hmC detection at a single base resolution, starting with consideration of the well-established 5hmC measure Δβ and, in particular, with an analysis of its properties, both analytically and empirically. Then we propose several alternative hydroxymethylation measures and compare their properties with those of Δβ. In the absence of a gold standard, the (pairwise) resemblance of those 5hmC measures to Δβ is characterized by means of a similarity analysis and relative accuracy analysis. All results are illustrated on matched healthy and cancer tissue data sets as derived by means of bisulfite (BS) and oxidative bisulfite converting (oxBS) procedures. [ABSTRACT FROM AUTHOR]

Many computational theories have been developed to improve artificial phonetic classification performance from linguistic auditory streams. However, less attention has been given to psycholinguistic data and neurophysiological features recently found in cortical tissue. We focus on a context in which basic linguistic units–such as phonemes–are extracted and robustly classified by humans and other animals from complex acoustic streams in speech data. We are especially motivated by the fact that 8-month-old human infants can accomplish segmentation of words from fluent audio streams based exclusively on the statistical relationships between neighboring speech sounds without any kind of supervision. In this paper, we introduce a biologically inspired and fully unsupervised neurocomputational approach that incorporates key neurophysiological and anatomical cortical properties, including columnar organization, spontaneous micro-columnar formation, adaptation to contextual activations and Sparse Distributed Representations (SDRs) produced by means of partial N-Methyl-D-aspartic acid (NMDA) depolarization. Its feature abstraction capabilities show promising phonetic invariance and generalization attributes. Our model improves the performance of a Support Vector Machine (SVM) classifier for monosyllabic, disyllabic and trisyllabic word classification tasks in the presence of environmental disturbances such as white noise, reverberation, and pitch and voice variations. Furthermore, our approach emphasizes potential self-organizing cortical principles achieving improvement without any kind of optimization guidance which could minimize hypothetical loss functions by means of–for example–backpropagation. Thus, our computational model outperforms multiresolution spectro-temporal auditory feature representations using only the statistical sequential structure immerse in the phonotactic rules of the input stream. [ABSTRACT FROM AUTHOR]

Many mRNA-based vaccines have been investigated for their specific potential to activate dendritic cells (DCs), the highly-specialized antigen-presenting cells of the immune system that play a key role in inducing effective CD4+ and CD8+ T-cell responses. In this paper we report a new vaccine/gene delivery platform that demonstrates the benefits of using a self-amplifying (“replicon”) mRNA that is protected in a viral-protein capsid. Purified capsid protein from the plant virus Cowpea Chlorotic Mottle Virus (CCMV) is used to in vitro assemble monodisperse virus-like particles (VLPs) containing reporter proteins (e.g., Luciferase or eYFP) or the tandem-repeat model antigen SIINFEKL in RNA gene form, coupled to the RNA-dependent RNA polymerase from the Nodamura insect virus. Incubation of immature DCs with these VLPs results in increased activation of maturation markers – CD80, CD86 and MHC-II – and enhanced RNA replication levels, relative to incubation with unpackaged replicon mRNA. Higher RNA uptake/replication and enhanced DC activation were detected in a dose-dependent manner when the CCMV-VLPs were pre-incubated with anti-CCMV antibodies. In all experiments the expression of maturation markers correlates with the RNA levels of the DCs. Overall, these studies demonstrate that: VLP protection enhances mRNA uptake by DCs; coupling replicons to the gene of interest increases RNA and protein levels in the cell; and the presence of anti-VLP antibodies enhances mRNA levels and activation of DCs in vitro. Finally, preliminary in vivo experiments involving mouse vaccinations with SIINFEKL-replicon VLPs indicate a small but significant increase in antigen-specific T cells that are doubly positive for IFN and TFN induction. [ABSTRACT FROM AUTHOR]

A number of recent studies have shown that cell shape and cytoskeletal texture can be used as sensitive readouts of the physiological state of the cell. However, utilization of this information requires the development of quantitative measures that can describe relevant aspects of cell shape. In this paper we develop a toolbox, TISMorph, that calculates a set of quantitative measures to address this need. Some of the measures introduced here have been used previously, while others are new and have desirable properties for shape and texture quantification of cells. These measures, broadly classifiable into the categories of textural, irregularity and spreading measures, are tested by using them to discriminate between osteosarcoma cell lines treated with different cytoskeletal drugs. We find that even though specific classification tasks often rely on a few measures, these are not the same between all classification tasks, thus requiring the use of the entire suite of measures for classification and discrimination. We provide detailed descriptions of the measures, as well as the TISMorph package to implement them. Quantitative morphological measures that capture different aspects of cell morphology will help enhance large-scale image-based quantitative analysis, which is emerging as a new field of biological data. [ABSTRACT FROM AUTHOR]

Scaffold-based cancer cell culture techniques have been gaining prominence especially in the last two decades. These techniques can potentially overcome some of the limitations of current three-dimensional cell culture methods, such as uneven cell distribution, inadequate nutrient diffusion, and uncontrollable size of cell aggregates. Porous scaffolds can provide a convenient support for cell attachment, proliferation and migration, and also allows diffusion of oxygen, nutrients and waste. In this paper, a comparative study was done on porous poly (lactic-co-glycolic acid) (PLGA) microparticles prepared using three porogens—gelatin, sodium bicarbonate (SBC) or novel poly N-isopropylacrylamide [PNIPAAm] particles, as substrates for lung cancer cell culture. These fibronectin-coated, stable particles (19–42 μm) supported A549 cell attachment at an optimal cell seeding density of 250,000 cells/ mg of particles. PLGA-SBC porous particles had comparatively larger, more interconnected pores, and favored greater cell proliferation up to 9 days than their counterparts. This indicates that pore diameters and interconnectivity have direct implications on scaffold-based cell culture compared to substrates with minimally interconnected pores (PLGA-gelatin) or pores of uniform sizes (PLGA-PMPs). Therefore, PLGA-SBC-based tumor models were chosen for preliminary drug screening studies. The greater drug resistance observed in the lung cancer cells grown on porous particles compared to conventional cell monolayers agrees with previous literature, and indicates that the PLGA-SBC porous microparticle substrates are promising for in vitro tumor or tissue development. [ABSTRACT FROM AUTHOR]

Sudangrass, Sorghum sudanense (Piper) Stapf, is a vigorous forage crop that has also been used for biogas, paper, and electricity production. Due to the large biomass yields achieved by sudangrass and the large area of potential growth in Argentina seven sudangrass accessions from a collection of S. sudanense were analyzed to evaluate their potential as feedstocks for lignocellulosic bioethanol production, and to assess whether there is an association between the response to biotic and abiotic stresses and the composition of the biomass. The biomass composition was analyzed for major cell wall polymers, monosaccharides, and elemental composition. On average, 68% of stem lignocellulosic biomass was comprised of matrix polysaccharides and crystalline cellulose, representing a potential source of sugars for bioethanol production. Xylose was the predominant matrix polysaccharide monosaccharide comprising, on average, 45% of the total sugars, followed by arabinose, glucose, galactose, galacturonic acid, mannose, glucuronic acid, and fucose. Rhamnose was not detected in any of the biomasses analyzed. Silica was the most abundant element in sudangrass stem, followed by chloride, calcium, phosphorus and sulfur. We performed saccharification analyses after pretreatments. Alkaline pretreatment was more effective than water pretreatment. Sodium hydroxide pretreatment exposed different levels of recalcitrance among sudangrass accessions, whereas the water pretreatment did not. Phenological traits were also evaluated, showing significant variability among accessions. The comparison of major cell wall polymers and monosaccharide composition between tolerant and susceptible accessions to abiotic and biotic stresses suggests an association between the composition of the biomass and the response to stress. [ABSTRACT FROM AUTHOR]

Control problem in a biological system is the problem of finding an interventional policy for changing the state of the biological system from an undesirable state, e.g. disease, into a desirable healthy state. Boolean networks are utilized as a mathematical model for gene regulatory networks. This paper provides an algorithm to solve the control problem in Boolean networks. The proposed algorithm is implemented and applied on two biological systems: T-cell receptor network and Drosophila melanogaster network. Results show that the proposed algorithm works faster in solving the control problem over these networks, while having similar accuracy, in comparison to previous exact methods. Source code and a simple web service of the proposed algorithm is available at . [ABSTRACT FROM AUTHOR]

Providing complete mobility along with minimizing the poor quality of service (QoS) is one of the highest essential challenges in mobile wireless networks. Handover prediction can overcome these challenges. In this paper, two novel prediction schemes are proposed. The first, depends on scanning the quality of all signals among mobile station and all nearby stations in the surrounding area, while the second one is based on a multi-criteria prediction decision using both the signal-to-noise ratio SNR value and station’s bandwidth. Moreover, the prediction efficiency is improved by reducing the number of redundant/ unnecessary handovers. The proposed schemes are evaluated using different scenarios with several mobile stations’ numbers, different WLAN access points, LTE-base station number & location, and random mobile station movement manner. The proposed schemes achieved a success rate of 99% with the different scenarios using LTE-WLAN architecture. The performance of the proposed prediction schemes outperformed the performance of the existing prediction schemes in terms of the accuracy percentage. [ABSTRACT FROM AUTHOR]

In this paper we set the previously reported pressure-dependent, ordinary differential equation outflow model by Smith and Gardiner for the human eye, into a new three-dimensional (3D) porous media outflow model of the eye, and calibrate model parameters using data reported in the literature. Assuming normal outflow through anterior pathways, we test the ability of 3D flow model to predict the pressure elevation with a silicone oil tamponade. Then assuming outflow across the retinal pigment epithelium is normal, we test the ability of the 3D model to predict the pressure elevation in Schwartz-Matsuo syndrome. For the first time we find the flow model can successfully model both conditions, which helps to build confidence in the validity and accuracy of the 3D pressure-dependent outflow model proposed here. We employ this flow model to estimate the translaminar pressure gradient within the optic nerve head of a normal eye in both the upright and supine postures, and during the day and at night. Based on a ratio of estimated and measured pressure gradients, we define a factor of safety against acute interruption of axonal transport at the laminar cribrosa. Using a completely independent method, based on the behaviour of dynein molecular motors, we compute the factor of safety against stalling the dynein molecule motors, and so compromising retrograde axonal transport. We show these two independent methods for estimating factors of safety agree reasonably well and appear to be consistent. Taken together, the new 3D pressure-dependent outflow model proves itself to capable of providing a useful modeling platform for analyzing eye behaviour in a variety of physiological and clinically useful contexts, including IOP elevation in Schwartz-Matsuo syndrome and with silicone oil tamponade, and potentially for risk assessment for optic glaucomatous neuropathy. [ABSTRACT FROM AUTHOR]

Data analysis for flow-based in-vitro receptomics array, like a tongue-on-a-chip, is complicated by the relatively large variability within and between arrays, transfected DNA types, spots, and cells within spots. Simply averaging responses of spots of the same type would lead to high variances and low statistical power. This paper presents an approach based on linear mixed models, allowing a quantitative and robust comparison of complex samples and indicating which receptors are responsible for any differences. These models are easily extended to take into account additional effects such as the build-up of cell stress and to combine data from replicated experiments. The increased analytical power this brings to receptomics research is discussed. [ABSTRACT FROM AUTHOR]

This paper considers a novel dynamical behaviour of two microbial populations, competing in a chemostat over a single substrate, that is only possible through the use of population balance equations (PBEs). PBEs are partial integrodifferential equations that represent a distribution of cells according to some internal state, mass in our case. Using these equations, realistic parameter values and the assumption that one population can deploy an emergency mechanism, where it can change the mean mass of division and hence divide faster, we arrive at two different steady states, one oscillatory and one non-oscillatory both of which seem to be stable. A steady state of either form is normally either unstable or only attainable through external control (cycling the dilution rate). In our case no external control is used. Finally, in the oscillatory case we attempt to explain how oscillations appear in the biomass without any explicit dependence on the division rate (the function that oscillates) through the approximation of fractional moments as a combination of integer moments. That allows an implicit dependence of the biomass on the number of cells which in turn is directly dependent on the division rate function. [ABSTRACT FROM AUTHOR]

The genus Cyphostemma (Planch.) Alston (Vitaceae) includes about 150 species distributed in eastern and southern Africa and Madagascar. Some species are used in traditional medicine and their biological activities, including antiproliferative effects against cancer cell lines, have been demonstrated. To date no investigations on Cyphostemma essential oils have been carried out. Essential oils, which play important roles in plant defenses have been demonstrated to be active in the treatment of several human diseases and to enhance bioavability of other drugs. The aim of this paper was to identify the chemical composition of the essential oil of the leaves of Cyphostemma juttae (Dinter & Gilg) Desc. and to verify some biological activities on two triple negative breast cancer cell lines (MDA-MB-231, SUM 149), characterized by the over-expression of the transcription factor NF-κB. In the essential oil, obtained by hydrodistillation and analysed by gas chromatography-mass spectrometry, 39 compounds were detected and with phytol (30%) dominating the chemical composition. C. juttae essential oil reduced cell growth and showed a pro-oxidant activity in both cell lines. Moreover, C. juttae essential oil caused a substantial decrease of NF-κB activation and consequently a significant reduction of some NF-κB target genes. The present study shows for the first time the cytotoxic properties of C. juttae essential oil and highlight its availability to interfere with NF-κB pathway, suggesting a potential therapeutic use in triple negative breast cancers (TNBCs) of this essential oil. [ABSTRACT FROM AUTHOR]

The symbiosis between rhizobia and legumes is characterized by a complex molecular dialogue in which the bacterial NodD protein plays a major role due to its capacity to activate the expression of the nodulation genes in the presence of appropiate flavonoids. These genes are involved in the synthesis of molecules, the nodulation factors (NF), responsible for launching the nodulation process. Rhizobium tropici CIAT 899, a rhizobial strain that nodulates Phaseolus vulgaris, is characterized by its tolerance to multiple environmental stresses such as high temperatures, acidity or elevated osmolarity. This strain produces nodulation factors under saline stress and the same set of CIAT 899 nodulation genes activated by inducing flavonoids are also up-regulated in a process controlled by the NodD2 protein. In this paper, we have studied the effect of osmotic stress (high mannitol concentrations) on the R. tropici CIAT 899 transcriptomic response. In the same manner as with saline stress, the osmotic stress mediated NF production and export was controlled directly by NodD2. In contrast to previous reports, the nodA2FE operon and the nodA3 and nodD1 genes were up-regulated with mannitol, which correlated with an increase in the production of biologically active NF. Interestingly, in these conditions, this regulatory protein controlled not only the expression of nodulation genes but also the expression of other genes involved in protein folding and synthesis, motility, synthesis of polysaccharides and, surprinsingly, nitrogen fixation. Moreover, the non-metabolizable sugar dulcitol was also able to induce the NF production and the activation of nod genes in CIAT 899. [ABSTRACT FROM AUTHOR]

Multiscale signal processing techniques such as wavelet filtering have proved to be particularly successful in predicting exon sequences. Traditional wavelet predictor is domain filtering, and enforces exon features by weighting nucleotide values with coefficients. Such a measure performs linear filtering and is not suitable for preserving the short coding exons and the exon-intron boundaries. This paper describes a prediction framework that is capable of non-linearly processing DNA sequences while achieving high prediction rates. There are two key contributions. The first is the introduction of a genomic-inspired multiscale bilateral filtering (MSBF) which exploits both weighting coefficients in the spatial domain and nucleotide similarity in the range. Similarly to wavelet transform, the MSBF is also defined as a weighted sum of nucleotides. The difference is that the MSBF takes into account the variation of nucleotides at a specific codon position. The second contribution is the exploitation of inter-scale correlation in MSBF domain to find the inter-scale dependency on the differences between the exon signal and the background noise. This favourite property is used to sharp the important structures while weakening noise. Three benchmark data sets have been used in the evaluation of considered methods. By comparison with four existing techniques, the prediction results demonstrate that: the proposed method reveals at least improvement of 4.1%, 50.5%, 25.6%, 2.5%, 10.8%, 15.5%, 11.1%, 12.3%, 9.2% and 2.4% on the exons length of 1–24, 25–49, 50–74, 75–99, 100–124, 125–149, 150–174, 175–199, 200–299 and 300–300+, respectively. The MSBF of its nonlinear nature is good at energy compaction, which makes it capable of locating the sharp variations around short exons. The direct scale multiplication of coefficients at several adjacent scales obviously enhanced exon features while the noise contents were suppressed. We show that the non-linear nature and correlation-based property achieved in proposed predictor is greater than that for traditional filtering, which leads to better exon prediction performance. There are some possible applications of this predictor. Its good localization and protection of sharp variations will make the predictor be suitable to perform fault diagnosis of aero-engine. [ABSTRACT FROM AUTHOR]