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Biosensors have emerged as a valuable tool with high specificity and sensitivity for fast and reliable detection of hazardous substances in drinking water. Numerous substances have been addressed using synthetic biology approaches. However, many proposed biosensors are based on living, genetically modified organisms and are therefore limited in shelf life, usability and biosafety. We addressed these issues by the construction of an extensible, cell-free biosensor. Storage is possible through freeze drying on paper. Following the addition of an aqueous sample, a highly efficient cell-free protein synthesis (CFPS) reaction is initiated. Specific allosteric transcription factors modulate the expression of ‘superfolder’ green fluorescent protein (sfGFP) depending on the presence of the substance of interest. The resulting fluorescence intensities are analyzed with a conventional smartphone accompanied by simple and cheap light filters. An ordinary differential equitation (ODE) model of the biosensors was developed, which enabled prediction and optimization of performance. With an optimized cell-free biosensor based on the Shigella flexneri MerR transcriptional activator, detection of 6 μg/L Hg(II) ions in water was achieved. Furthermore, a completely new biosensor for the detection of gamma-hydroxybutyrate (GHB), a substance used as date-rape drug, was established by employing the naturally occurring transcriptional repressor BlcR from Agrobacterium tumefaciens. [ABSTRACT FROM AUTHOR]

Type 1 diabetes (T1D) is increasing in incidence and predictable with measurement of serum islet autoantibodies (iAb) years prior to clinical disease onset. Identifying iAb positive individuals reduces diabetic ketoacidosis and identifies individuals for T1D prevention trials. However, large scale screening for iAb remains challenging as assays have varying sensitivities and specificities, insulin autoantibodies remain difficult to measure and venipuncture is generally required to obtain serum. We developed an approach to reliably measure all four major iAb, including insulin autoantibodies, from dried blood spots (DBS) on filter-paper. By spiking iAb positive serum into iAb negative whole blood in a dose titration, we optimized the conditions for autoantibody elution from filter paper as measured by fluid phase radioimmunoassays. After assessing stability of measuring iAb from DBS over time, we then screened iAb from DBS and the corresponding serum in new-onset T1D (n = 52), and controls (n = 72) which included first-degree relatives of T1D patients. iAb measured from eluted DBS in new-onset T1D strongly correlated with serum measurements (R2 = 0.96 for mIAA, GADA = 0.94, IA-2A = 0.85, ZnT8A = 0.82, p<0.01 for each autoantibody). There were no false positives in control subjects, and 5/6 with previously unknown iAb positivity in sera were detected using DBS. With further validation, measuring iAb from DBS can be a reliable method to screen for T1D risk. [ABSTRACT FROM AUTHOR]

Many results have been obtained when studying scientific papers citations databases in a network perspective. Articles can be ranked according to their current in-degree and their future popularity or citation counts can even be predicted. The dynamical properties of such networks and the observation of the time evolution of their nodes started more recently. This work adopts an evolutionary perspective and proposes an original algorithm for the construction of genealogical trees of scientific papers on the basis of their citation count evolution in time. The fitness of a paper now amounts to its in-degree growing trend and a “dying” paper will suddenly see this trend declining in time. It will give birth and be taken over by some of its most prevalent citing “offspring”. Practically, this might be used to trace the successive published milestones of a research field. [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]

Fast-moving, competitive fields often inadvertently duplicate research. In a research environment that values being first over being robust, this results in one manuscript “scooping” ongoing research from other groups. Opportunities to demonstrate the solidity of a result through coincidental reproduction are thus lost. Here, two group leaders, one the scooper and one the scoopee, discuss their experiences under PLOS Biology’s new “complementary research” policy. In this case, submission of the second article followed publication of the first by mere days. Scooper and scoopee discuss how complementary research is good for everyone by expanding the scientific reach of studies that are overlapping but not identical, demonstrating the robustness of related results, increasing readership for both authors, and making “replication” studies cost effective by creatively using resources that have already been spent. [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]

Engineering faster cellulose deconstruction is difficult because it is a complex, cooperative, multi-enzyme process. Here we use experimental evolution to select for populations of Trichoderma citrinoviride that deconstruct up to five-fold more cellulose. Ten replicate populations of T. citrinoviride were selected for growth on filter paper by serial culture. After 125 periods of growth and transfer to fresh media, the filter paper deconstruction increased an average of 2.5 fold. Two populations were examined in more detail. The activity of the secreted cellulase mixtures increased more than two-fold relative to the ancestor and the largest increase was in the extracellular β-glucosidase activity. qPCR showed at least 16-fold more transcribed RNA for egl4 (endoglucanase IV gene), cbh1 (cellobiohydrolase I gene) and bgl1 (extracellular β-glucosidase I gene) in selected populations as compared to the ancestor, and earlier peak expressions of these genes. Deep sequencing shows that the regulatory strategies used to alter cellulase secretion differ in the two strains. The improvements in cellulose deconstruction come from earlier expression of all cellulases and increased relative amount of β-glucosidase, but with small increases in the total secreted protein and therefore little increase in metabolic cost. [ABSTRACT FROM AUTHOR]

In their comment, Chen and Chuang [] pointed out several weak points of our recent paper []. Here we respond in detail to clarify the dataset we used in our work. We also discuss the three confounding factors they listed in their comment. [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]

Protein carbonylation is one of the most pervasive oxidative stress-induced post-translational modifications (PTMs), which plays a significant role in the etiology and progression of several human diseases. It has been regarded as a biomarker of oxidative stress due to its relatively early formation and stability compared with other oxidative PTMs. Only a subset of proteins is prone to carbonylation and most carbonyl groups are formed from lysine (K), arginine (R), threonine (T) and proline (P) residues. Recent advancements in analysis of the PTM by mass spectrometry provided new insights into the mechanisms of protein carbonylation, such as protein susceptibility and exact modification sites. However, the experimental approaches to identifying carbonylation sites are costly, time-consuming and capable of processing a limited number of proteins, and there is no bioinformatics method or tool devoted to predicting carbonylation sites of human proteins so far. In the paper, a computational method is proposed to identify carbonylation sites of human proteins. The method extracted four kinds of features and combined the minimum Redundancy Maximum Relevance (mRMR) feature selection criterion with weighted support vector machine (WSVM) to achieve total accuracies of 85.72%, 85.95%, 83.92% and 85.72% for K, R, T and P carbonylation site predictions respectively using 10-fold cross-validation. The final optimal feature sets were analysed, the position-specific composition and hydrophobicity environment of flanking residues of modification sites were discussed. In addition, a software tool named CarSPred has been developed to facilitate the application of the method. Datasets and the software involved in the paper are available at . [ABSTRACT FROM AUTHOR]

Type 2 diabetes leads to premature death and reduced quality of life for 8% of Americans. Nutrition management is critical to maintaining glycemic control, yet it is difficult to achieve due to the high individual differences in glycemic response to nutrition. Anticipating glycemic impact of different meals can be challenging not only for individuals with diabetes, but also for expert diabetes educators. Personalized computational models that can accurately forecast an impact of a given meal on an individual’s blood glucose levels can serve as the engine for a new generation of decision support tools for individuals with diabetes. However, to be useful in practice, these computational engines need to generate accurate forecasts based on limited datasets consistent with typical self-monitoring practices of individuals with type 2 diabetes. This paper uses three forecasting machines: (i) data assimilation, a technique borrowed from atmospheric physics and engineering that uses Bayesian modeling to infuse data with human knowledge represented in a mechanistic model, to generate real-time, personalized, adaptable glucose forecasts; (ii) model averaging of data assimilation output; and (iii) dynamical Gaussian process model regression. The proposed data assimilation machine, the primary focus of the paper, uses a modified dual unscented Kalman filter to estimate states and parameters, personalizing the mechanistic models. Model selection is used to make a personalized model selection for the individual and their measurement characteristics. The data assimilation forecasts are empirically evaluated against actual postprandial glucose measurements captured by individuals with type 2 diabetes, and against predictions generated by experienced diabetes educators after reviewing a set of historical nutritional records and glucose measurements for the same individual. The evaluation suggests that the data assimilation forecasts compare well with specific glucose measurements and match or exceed in accuracy expert forecasts. We conclude by examining ways to present predictions as forecast-derived range quantities and evaluate the comparative advantages of these ranges. [ABSTRACT FROM AUTHOR]

Methods have been developed for Mendelian randomization that can obtain consistent causal estimates under weaker assumptions than the standard instrumental variable assumptions. The median-based estimator and MR-Egger are examples of such methods. However, these methods can be sensitive to genetic variants with heterogeneous causal estimates. Such heterogeneity may arise from over-dispersion in the causal estimates, or specific variants with outlying causal estimates. In this paper, we develop three extensions to robust methods for Mendelian randomization with summarized data: 1) robust regression (MM-estimation); 2) penalized weights; and 3) Lasso penalization. Methods using these approaches are considered in two applied examples: one where there is evidence of over-dispersion in the causal estimates (the causal effect of body mass index on schizophrenia risk), and the other containing outliers (the causal effect of low-density lipoprotein cholesterol on Alzheimer’s disease risk). Through an extensive simulation study, we demonstrate that robust regression applied to the inverse-variance weighted method with penalized weights is a worthwhile additional sensitivity analysis for Mendelian randomization to provide robustness to variants with outlying causal estimates. The results from the applied examples and simulation study highlight the importance of using methods that make different assumptions to assess the robustness of findings from Mendelian randomization investigations with multiple genetic variants. [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]

Introduction: The system of clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated proteins (cas) is a new technology that allows easier manipulation of the genome. Its potential to edit genes opened a new door in treatment development for incurable neurological monogenic diseases (NMGDs). The aim of this systematic review was to summarise the findings on the current development of CRISPR-cas for therapeutic purposes in the most frequent NMGDs and provide critical assessment. Methods and data acquisition: We searched the MEDLINE and EMBASE databases, looking for original studies on the use of CRISPR-cas to edit pathogenic variants in models of the most frequent NMGDs, until end of 2017. We included all the studies that met the following criteria: 1. Peer-reviewed study report with explicitly described experimental designs; 2. In vitro, ex vivo, or in vivo study using human or other animal biological systems (including cells, tissues, organs, organisms); 3. focusing on CRISPR as the gene-editing method of choice; and 5. featured at least one NMGD. Results: We obtained 404 papers from MEDLINE and 513 from EMBASE. After removing the duplicates, we screened 490 papers by title and abstract and assessed them for eligibility. After reading 50 full-text papers, we finally selected 42 for the review. Discussion: Here we give a systematic summary on the preclinical development of CRISPR-cas for therapeutic purposes in NMGDs. Furthermore, we address the clinical interpretability of the findings, giving a comprehensive overview of the current state of the art. Duchenne’s muscular dystrophy (DMD) paves the way forward, with 26 out of 42 studies reporting different strategies on DMD gene editing in different models of the disease. Most of the strategies aimed for permanent exon skipping by deletion with CRISPR-cas. Successful silencing of the mHTT gene with CRISPR-cas led to successful reversal of the neurotoxic effects in the striatum of mouse models of Huntington’s disease. Many other strategies have been explored, including epigenetic regulation of gene expression, in cellular and animal models of: myotonic dystrophy, Fraxile X syndrome, ataxias, and other less frequent dystrophies. Still, before even considering the clinical application of CRISPR-cas, three major bottlenecks need to be addressed: efficacy, safety, and delivery of the systems. This requires a collaborative approach in the research community, while having ethical considerations in mind. [ABSTRACT FROM AUTHOR]

Understanding expression levels of proteins and their interactions is a key factor to diagnose and explain the Down syndrome which can be considered as the most prevalent reason of intellectual disability in human beings. In the previous studies, the expression levels of 77 proteins obtained from normal genotype control mice and from trisomic Ts65Dn mice have been analyzed after training in contextual fear conditioning with and without injection of the memantine drug using statistical methods and machine learning techniques. Recent studies have also pointed out that there may be a linkage between the Down syndrome and the immune system. Thus, the research presented in this paper aim at in silico identification of proteins which are significant to the learning process and the immune system and to derive the most accurate model for classification of mice. In this paper, the features are selected by implementing forward feature selection method after preprocessing step of the dataset. Later, deep neural network, gradient boosting tree, support vector machine and random forest classification methods are implemented to identify the accuracy. It is observed that the selected feature subsets not only yield higher accuracy classification results but also are composed of protein responses which are important for the learning and memory process and the immune system. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this cross-sectional observational study was to compare the prevalence of different oral Candida spp. in patients with Type 2 Diabetes and chronic periodontitis in two oral sites: dorsal surface of the tongue and subgingival area. In order to determine subgingival areas as potential reservoirs of yeasts, this study aimed to find differences in the yeasts’ detection between the dorsum of the tongue, as the oral site most commonly inhabited with microorganisms, and subgingival samples. Additionally, potential predictors for the yeasts prevalence were determined. Material and methods: Subjects (N = 146) were divided into four groups: group A- healthy individuals without periodontitis, group B- healthy individuals with chronic periodontitis, group C- Type 2 Diabetes patients with good glycoregulation and Chronic periodontitis and group D- Type 2 Diabetes patients with poor glycoregulation and Chronic periodontitis. Samples were obtained from the tongue by swabbing. Subgingival plaque samples were taken by paper points and periodontal curette. Isolation and identification of different Candida spp. was done using ChromAgar medium. In addition, germ-tube production and carbohydrate assimilation tests were performed. Results: The prevalence of Candida spp. was higher in diabetics with poor glycoregulation. The most frequently isolated species was Candida albicans followed by Candida glabrata and Candida tropicalis. In 15.6% of cases, Candida spp. was present in the subgingival area while absent on the tongue. Multivariate regression model showed that HbA1c was Candida spp. predictor for both locations. Conclusions: Our results confirmed that there are Candida spp. carriers among subjects with clinically healthy oral mucosa. Also, this study identified subgingival areas as potential reservoirs of these pathogenic species. Glycoregulation has been recognized as a positive predictor factor of Candida spp. [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]

This paper is concerned with the potential multistability of protein concentrations in the cell. That is, situations where one, or a family of, proteins may sit at one of two or more different steady state concentrations in otherwise identical cells, and in spite of them being in the same environment. For models of multisite protein phosphorylation for example, in the presence of excess substrate, it has been shown that the achievable number of stable steady states can increase linearly with the number of phosphosites available. In this paper, we analyse the consequences of adding enzyme docking to these and similar models, with the resultant sequestration of phosphatase and kinase by the fully unphosphorylated and by the fully phosphorylated substrates respectively. In the large molecule numbers limit, where deterministic analysis is applicable, we prove that there are always values for these rates of sequestration which, when exceeded, limit the extent of multistability. For the models considered here, these numbers are much smaller than the affinity of the enzymes to the substrate when it is in a modifiable state. As substrate enzyme-sequestration is increased, we further prove that the number of steady states will inevitably be reduced to one. For smaller molecule numbers a stochastic analysis is more appropriate, where multistability in the large molecule numbers limit can manifest itself as multimodality of the probability distribution; the system spending periods of time in the vicinity of one mode before jumping to another. Here, we find that substrate enzyme sequestration can induce bimodality even in systems where only a single steady state can exist at large numbers. To facilitate this analysis, we develop a weakly chained diagonally dominant M-matrix formulation of the Chemical Master Equation, allowing greater insights in the way particular mechanisms, like enzyme sequestration, can shape probability distributions and therefore exhibit different behaviour across different regimes. [ABSTRACT FROM AUTHOR]

A significant approach for the discovery of biological regulatory rules of genes, protein and their inheritance relationships is the extraction of meaningful patterns from biological sequence data. The existing algorithms of sequence pattern discovery, like MSPM and FBSB, suffice their low efficiency and accuracy. In order to deal with this issue, this paper presents a new algorithm for biological sequence pattern mining abbreviated MpBsmi based on the data index structure. The MpBsmi algorithm employs a sequence position table abbreviated ST and a sequence database index structure named DB-Index for data storing, mining and pattern expansion. The ST and DB-Index of single items are firstly obtained through scanning sequence database once. Then a new algorithm for fast support counting is developed to mine the table ST to identify the frequent single items. Based on a connection strategy, the frequent patterns are expanded and the expanded table ST is updated by scanning the DB-Index. The fast support counting algorithm is used for obtaining the frequent expansion patterns. Finally, a new pruning technique is developed for extended pattern to avoid the generation of unnecessarily large number of candidate patterns. The experiments results on multiple classical protein sequences from the Pfam database validate the performance of the proposed algorithm including the accuracy, stability and scalability. It is showed that the proposed algorithm has achieved the better space efficiency, stability and scalability comparing with MSPM, FBSB which are the two main algorithms for biological sequence mining. [ABSTRACT FROM AUTHOR]

In a previous paper we showed that the yeast Pichia pastoris X-33 grown in parboiled rice effluent supplemented with glycerol byproduct from the biodiesel industry improved the quality of the effluent. In this paper we show the validation of this yeast (PPE) as probiotic for broilers. Its effect on feed efficiency and immunomodulation was compared with the same yeast grown in yeast peptone dextrose medium (PPY), with Saccharomyces boulardii (SBY) and with the controls fed unsupplemented feed (CON). One-day-old female chicks were vaccinated against infectious bursal disease (IBD) and the titers of anti-IBD antibodies were measured by ELISA. PPE group had the highest mean titres on days 14 and 28 (p<0,05), and at 28 days, 64% of the animals showed seroconvertion. The PPE group also showed the best weight gains at 42 days of age, that, on days 7, 14 and 21 were 19%, 15%, and 8.7% higher, respectively, than the control group. The best feed conversion, 8.2% higher than the control group, was obtained by PPY at 42 days. Histopathological studies did not detect any undesirable effects in the supplemented animals. We concluded that Pichia pastoris X-33 when grown in effluents of the rice parboiling industry supplemented with glycerol byproduct from the biodiesel has probiotic properties for poultry. [ABSTRACT FROM AUTHOR]

The high-affinity interaction between biotin and streptavidin has opened avenues for using recombinant proteins with site-specific biotinylation to achieve efficient and directional immobilization. The site-specific biotinylation of proteins carrying a 15 amino acid long Biotin Acceptor Peptide tag (BAP; also known as AviTag) is effected on a specific lysine either by co-expressing the E. coli BirA enzyme in vivo or by using purified recombinant E. coli BirA enzyme in the presence of ATP and biotin in vitro. In this paper, we have designed a T7 promoter-lac operator-based expression vector for rapid and efficient cloning, and high-level cytosolic expression of proteins carrying a C-terminal BAP tag in E. coli with TEV protease cleavable N-terminal deca-histidine tag, useful for initial purification. Furthermore, a robust three-step purification pipeline integrated with well-optimized protocols for TEV protease-based H10 tag removal, and recombinant BirA enzyme-based site-specific in vitro biotinylation is described to obtain highly pure biotinylated proteins. Most importantly, the paper demonstrates superior sensitivities in indirect ELISA with directional and efficient immobilization of biotin-tagged proteins on streptavidin-coated surfaces in comparison to passive immobilization. The use of biotin-tagged proteins through specific immobilization also allows more efficient selection of binders from a phage-displayed naïve antibody library. In addition, for both these applications, specific immobilization requires much less amount of protein as compared to passive immobilization and can be easily multiplexed. The simplified strategy described here for the production of highly pure biotin-tagged proteins will find use in numerous applications, including those, which may require immobilization of multiple proteins simultaneously on a solid surface. [ABSTRACT FROM AUTHOR]

The most frequent disorder of glycosylation, PMM2-CDG, is caused by a deficiency of phosphomannomutase activity. In humans two paralogous enzymes exist, both of them require mannose 1,6-bis-phosphate or glucose 1,6-bis-phosphate as activators, but only phospho-mannomutase1 hydrolyzes bis-phosphate hexoses. Mutations in the gene encoding phosphomannomutase2 are responsible for PMM2-CDG. Although not directly causative of the disease, the role of the paralogous enzyme in the disease should be clarified. Phosphomannomutase1 could have a beneficial effect, contributing to mannose 6-phosphate isomerization, or a detrimental effect, hydrolyzing the bis-phosphate hexose activator. A pivotal role in regulating mannose-1phosphate production and ultimately protein glycosylation might be played by inosine monophosphate that enhances the phosphatase activity of phosphomannomutase1. In this paper we analyzed human phosphomannomutases by conventional enzymatic assays as well as by novel techniques such as 31P-NMR and thermal shift assay. We characterized a triple mutant of phospomannomutase1 that retains mutase and phosphatase activity, but is unable to bind inosine monophosphate. [ABSTRACT FROM AUTHOR]

Background and aims: Persistent intestinal damage is associated with higher complication rates in celiac disease. We aimed to assess the potential modifiers of mucosal recovery. Materials and methods: We screened databases (PubMed, Embase, Cochrane Trials, and Web of Science) for papers on celiac disease. Papers discussing (1) celiac patients (2) follow-up biopsy and (3) mucosal recovery after commencement of a gluten-free diet were included. The primary outcome was to produce a comprehensive analysis of complete mucosal recovery (i.e., Marsh 0 on follow-up). We compared children’s recovery ratios to those of adults. Patients following a strict gluten-free dietary regimen were included in a subgroup. Summary point estimates, 95% confidence intervals (CIs), and 95% predictive intervals (PIs) were calculated. Heterogeneity was tested with I2-statistic. The PROSPERO registration number is CRD42016053482. Results: The overall complete mucosal recovery ratio, calculated from 37 observational studies, was 0.36 (CI: 0.28–0.44, PI: -0.12–0.84; I2: 98.4%, p<0.01). Children showed higher complete mucosal recovery ratio than adults (p<0.01): 0.65 (CI: 0.44–0.85, PI: -0.10–1.39; I2: 96.5%, p<0.01) as opposed to 0.24 (CI: 0.15–0.33, PI: -0.19–1.08; I2: 96.3%, p<0.01). In the strict dietary adherence subgroup, complete mucosal recovery ratio was 0.47 (CI: 0.24–0.70, PI: -0.47–1.41; I2: 98.8%, p<0.001). On meta-regression, diagnostic villous atrophy (Marsh 3) ratio (-8.97, p<0.01) and male ratio (+6.04, p<0.01) proved to be a significant determinant of complete mucosal recovery, unlike duration of gluten-free diet (+0.01, p = 0.62). The correlation between complete mucosal recovery ratio and age on diagnosis is of borderline significance (-0.03, p = 0.05). Conclusions: There is considerable heterogeneity across studies concerning complete mucosal recovery ratios achieved by a gluten-free diet in celiac disease. Several celiac patients fail to achieve complete mucosal recovery even if a strict dietary regimen is followed. Younger age on diagnosis, less severe initial histologic damage and male gender predispose for achieving mucosal recovery. [ABSTRACT FROM AUTHOR]

Organismal complexity broadly relates to the number of different cell types within an organism and generally increases across a phylogeny. Whilst gene expression will underpin organismal complexity, it has long been clear that a simple count of gene number is not a sufficient explanation. In this paper, we use open-access information from the Ensembl databases to quantify the functional diversity of human genes that are broadly involved in transcription. Functional diversity is described in terms of the numbers of paralogues, protein isoforms and structural domains for each gene. The change in functional diversity is then calculated for up to nine orthologues from the nematode worm to human and correlated to the change in cell-type number. Those with the highest correlation are subject to gene ontology term enrichment and interaction analyses. We found that a range of genes that encode proteins associated with dynamic changes to chromatin are good candidates to contribute to organismal complexity. [ABSTRACT FROM AUTHOR]

Customized buses (CBs) are a new mode of public transportation and an important part of diversified public transportation, providing advanced, attractive and user-led service. The operational activity of a CB is planned by aggregating space–time demand and similar passenger travel demands. Based on an analysis of domestic and international research and the current development of CBs in China and considering passenger travel data, this paper studies the problems associated with the operation of CBs, such as stop selection, line planning and timetables, and establishes a model for the stop planning and timetables of CBs. The improved immune genetic algorithm (IIGA) is used to solve the model with regard to the following: 1) multiple population design and transport operator design, 2) memory library design, 3) mutation probability design and crossover probability design, and 4) the fitness calculation of the gene segment. Finally, a real-world example in Beijing is calculated, and the model and solution results are verified and analyzed. The results illustrate that the IIGA solves the model and is superior to the basic genetic algorithm in terms of the number of passengers, travel time, average passenger travel time, average passenger arrival time ahead of schedule and total line revenue. This study covers the key issues involving operational systems of CBs, combines theoretical research and empirical analysis, and provides a theoretical foundation for the planning and operation of CBs. [ABSTRACT FROM AUTHOR]

Background: To allow early diagnosis and monitoring of disease progression, there is a need for biomarkers in amyotrophic lateral sclerosis (ALS). Neurofilaments (NF) are emerging protein biomarkers in other neurological diseases, and are of possible use in ALS. Objective: The aim of this study is to evaluate the utility of NF levels as blood or cerebrospinal fluid (CSF) biomarker in patients with ALS. Methods: A systematic search of Pubmed, Embase and Scopus was performed. Methodological quality assessment was applied to refine the final search results. Meta-analysis of the data was performed. Results: Level of NF heavy chain and light chains were significantly elevated in the CSF of ALS patients compared to healthy controls/controls without parenchymal central nervous system (CNS) involvement and ALS mimic disease patients. NF light chain level in CSF was higher in ALS patients than in neurological patients with CNS involvement (SMD = 1.352, P = 0.01). NF light chain concentration in blood was higher in ALS patients than healthy controls/controls without CNS involvement (SMD = 1.448, P<0.0001). NF heavy chain levels in CSF were negatively correlated disease duration and ALSFRS-R ((r = -0.447, P<0.0001; r = -0.486, P<0.0001). NF light chain levels in CSF were negatively correlated with disease duration (r = -0.273, P = 0.011). Conclusion: NF heavy and light chain levels have potential use as a marker of neural degeneration in ALS, but are not specific for the disease, and are more likely to be used as measures of disease progression. [ABSTRACT FROM AUTHOR]

The origins of agriculture in Southwest Asia over 10,000 years ago and its subsequent spread into Europe during the Neolithic have been the focus of much archaeological research over the past several decades. Increasingly more sophisticated analytical techniques have allowed for better understanding of the complex interactions that occurred amongst humans, animals, and their environments during this transition. The Aegean Islands are critically situated where Anatolia and the mainland Greece meet, making the region pivotal for understanding the movement of the Neolithic into Europe. Located on the largest Turkish Aegean island of Gökçeada, the site of Uğurlu Höyük dates to the early Neolithic and has been the subject of ongoing excavations and research integrating a rigorous dating program with comprehensive zooarchaeological research. This paper focuses on the combination of bone collagen and tooth enamel stable isotope data with existing archaeological data to develop a fine-resolution picture of the spread of the Neolithic, particularly the importation and management of domestic fauna on Gökçeada, with broader relevance for understanding Aegean-Anatolian interactions. The stable isotope values from the fauna at Uğurlu have been used for both diachronic intrasite analyses and intersite comparisons between contemporaneous mainland sites. Integrating stable isotope and zooarchaeological datasets makes Uğurlu one of the first island sites to provide a comprehensive understanding of the geographic origin of Neolithic livestock populations and the timing of their spread from Anatolia into Europe during the process of Neolithization. [ABSTRACT FROM AUTHOR]

SCCmec elements are very important mobile genetic elements in Staphylococci that carry beta-lactam resistance genes mecA/mecC, recombinase genes and a variety of accessory genes. Twelve main types and a couple of variants have yet been described. In addition, there are also other SCC elements harbouring other markers. In order to subtype strains of methicillin-resistant S. aureus (MRSA) based on variations within their SCCmec elements, 86 markers were selected from published SCC sequences for an assay based on multiplexed primer extension reactions followed by hybridisation to the specific probes. These included mecA/mecC, fusC, regulatory genes, recombinase genes, genes from ACME and heavy metal resistance loci as well as several genes of unknown function. Hybridisation patterns for published genome or SCC sequences were theoretically predicted. For validation of the microarray based assay and for stringent hybridisation protocol optimization, real hybridization experiments with fully sequenced reference strains were performed modifying protocols until yielded the results were in concordance to the theoretical predictions. Subsequently, 226 clinical isolates from two hospitals in the city of Dresden, Germany, were characterised in detail. Beside previously described types and subtypes, a wide variety of additional SCC types or subtypes and pseudoSCC elements were observed as well as numerous composite elements. Within the study collection, 61 different such elements have been identified. Since hybridisation cannot recognise the localisation of target genes, gene duplications or inversions, this is a rather conservative estimate. Interestingly, some widespread epidemic strains engulf distinct variants with different SCCmec subtypes. Notable examples are ST239-MRSA-III, CC5-, CC22-, CC30-, and CC45-MRSA-IV or CC398-MRSA-V. Conversely, identical SCC elements were observed in different strains with SCCmec IVa being spread among the highest number of Clonal Complexes. The proposed microarray can help to distinguish isolates that appear similar or identical by other typing methods and it can be used as high-throughput screening tool for the detection of putative new SCC types or variants that warrant further investigation and sequencing. The high degree of diversity of SCC elements even within so-called strains could be helpful for epidemiological typing. It also raises the question on scale and speed of the evolution of SCC elements. [ABSTRACT FROM AUTHOR]

Background: Identifying conserved regions in protein sequences is a fundamental operation, occurring in numerous sequence-driven analysis pipelines. It is used as a way to decode domain-rich regions within proteins, to compute protein clusters, to annotate sequence function, and to compute evolutionary relationships among protein sequences. A number of approaches exist for identifying and characterizing protein families based on their domains, and because domains represent conserved portions of a protein sequence, the primary computation involved in protein family characterization is identification of such conserved regions. However, identifying conserved regions from large collections (millions) of protein sequences presents significant challenges. Methods: In this paper we present a new, alignment-free method for detecting conserved regions in protein sequences called NADDA (No-Alignment Domain Detection Algorithm). Our method exploits the abundance of exact matching short subsequences (k-mers) to quickly detect conserved regions, and the power of machine learning is used to improve the prediction accuracy of detection. We present a parallel implementation of NADDA using the MapReduce framework and show that our method is highly scalable. Results: We have compared NADDA with Pfam and InterPro databases. For known domains annotated by Pfam, accuracy is 83%, sensitivity 96%, and specificity 44%. For sequences with new domains not present in the training set an average accuracy of 63% is achieved when compared to Pfam. A boost in results in comparison with InterPro demonstrates the ability of NADDA to capture conserved regions beyond those present in Pfam. We have also compared NADDA with ADDA and MKDOM2, assuming Pfam as ground-truth. On average NADDA shows comparable accuracy, more balanced sensitivity and specificity, and being alignment-free, is significantly faster. Excluding the one-time cost of training, runtimes on a single processor were 49s, 10,566s, and 456s for NADDA, ADDA, and MKDOM2, respectively, for a data set comprised of approximately 2500 sequences. [ABSTRACT FROM AUTHOR]

Recombinant expression of proteins has become an indispensable tool in modern day research. The large yields of recombinantly expressed proteins accelerate the structural and functional characterization of proteins. Nevertheless, there are literature reported that the recombinant proteins show some differences in structure and function as compared with the native ones. Now there have been more than 100,000 structures (from both recombinant and native sources) publicly available in the Protein Data Bank (PDB) archive, which makes it possible to investigate if there exist any proteins in the RCSB PDB archive that have identical sequence but have some difference in structures. In this paper, we present the results of a systematic comparative study of the 3D structures of identical naturally purified versus recombinantly expressed proteins. The structural data and sequence information of the proteins were mined from the RCSB PDB archive. The combinatorial extension (CE), FATCAT-flexible and TM-Align methods were employed to align the protein structures. The root-mean-square distance (RMSD), TM-score, P-value, Z-score, secondary structural elements and hydrogen bonds were used to assess the structure similarity. A thorough analysis of the PDB archive generated five-hundred-seventeen pairs of native and recombinant proteins that have identical sequence. There were no pairs of proteins that had the same sequence and significantly different structural fold, which support the hypothesis that expression in a heterologous host usually could fold correctly into their native forms. [ABSTRACT FROM AUTHOR]

In this paper we apply machine learning methods for predicting protein interactions in fungal secretion pathways. We assume an inter-species transfer setting, where training data is obtained from a single species and the objective is to predict protein interactions in other, related species. In our methodology, we combine several state of the art machine learning approaches, namely, multiple kernel learning (MKL), pairwise kernels and kernelized structured output prediction in the supervised graph inference framework. For MKL, we apply recently proposed centered kernel alignment and p-norm path following approaches to integrate several feature sets describing the proteins, demonstrating improved performance. For graph inference, we apply input-output kernel regression (IOKR) in supervised and semi-supervised modes as well as output kernel trees (OK3). In our experiments simulating increasing genetic distance, Input-Output Kernel Regression proved to be the most robust prediction approach. We also show that the MKL approaches improve the predictions compared to uniform combination of the kernels. We evaluate the methods on the task of predicting protein-protein-interactions in the secretion pathways in fungi, S.cerevisiae, baker’s yeast, being the source, T. reesei being the target of the inter-species transfer learning. We identify completely novel candidate secretion proteins conserved in filamentous fungi. These proteins could contribute to their unique secretion capabilities. [ABSTRACT FROM AUTHOR]

Background: There is no point of care diagnostic test for infection with M. Leprae or for leprosy, although ELISA anti PGL-1 has been considered and sometimes used as a means to identify infection. Methods: A systematic review of all cohort studies, which classified healthy leprosy contacts, at entry, according to anti-PGL1 positivity, and had at least one year follow up. The outcome was clinical diagnosis of leprosy by an experienced physician. The meta-analysis used a fixed model to estimated OR for the association of PGL-1 positivity and clinical leprosy. A fixed model also estimated the sensibility of PGL-1 positivity and positive predictive value. Results: Contacts who were anti PGL-1 positive at baseline were 3 times as likely to develop leprosy; the proportion of cases of leprosy that were PGL-1 positive at baseline varied but was always under 50%. Conclusions: Although there is a clear and consistent association between positivity to anti PGL-1 and development of leprosy in healthy contacts, selection of contacts for prophylaxis based on anti PGL1 response would miss more than half future leprosy cases. Should chemoprophylaxis of controls be incorporated into leprosy control programmes, PGL1 appears not to be a useful test in the decision of which contacts should receive chemoprophylaxis. [ABSTRACT FROM AUTHOR]

The aim of this paper is to provide a Bayesian formulation of the so-called magnitude-based inference approach to quantifying and interpreting effects, and in a case study example provide accurate probabilistic statements that correspond to the intended magnitude-based inferences. The model is described in the context of a published small-scale athlete study which employed a magnitude-based inference approach to compare the effect of two altitude training regimens (live high-train low (LHTL), and intermittent hypoxic exposure (IHE)) on running performance and blood measurements of elite triathletes. The posterior distributions, and corresponding point and interval estimates, for the parameters and associated effects and comparisons of interest, were estimated using Markov chain Monte Carlo simulations. The Bayesian analysis was shown to provide more direct probabilistic comparisons of treatments and able to identify small effects of interest. The approach avoided asymptotic assumptions and overcame issues such as multiple testing. Bayesian analysis of unscaled effects showed a probability of 0.96 that LHTL yields a substantially greater increase in hemoglobin mass than IHE, a 0.93 probability of a substantially greater improvement in running economy and a greater than 0.96 probability that both IHE and LHTL yield a substantially greater improvement in maximum blood lactate concentration compared to a Placebo. The conclusions are consistent with those obtained using a ‘magnitude-based inference’ approach that has been promoted in the field. The paper demonstrates that a fully Bayesian analysis is a simple and effective way of analysing small effects, providing a rich set of results that are straightforward to interpret in terms of probabilistic statements. [ABSTRACT FROM AUTHOR]

Information transmission in cells occurs quite accurately even when concentration changes are “read” by individual binding sites. In this paper we study ligand number and site occupancy fluctuations when ligands diffuse and react going beyond the analyses that focus on their asymptotic decay. In this way we show that, for immobile binding sites, fluctuations in the number of bound molecules decay on a relatively fast scale before the asymptotic behavior kicks in. This result can explain the observed co-existence of highly fluctuating instantaneous transcriptional activities with accumulated mRNA concentrations that have relatively small noise levels. We also show that the initial stages of the decay in the bound molecule number fluctuations have one or two characteristic timescales depending on the concentration of free molecules. This transition can explain the changes in enzyme activity observed at the single molecule level. [ABSTRACT FROM AUTHOR]

Fungal laccases are enzymes that have been studied because of their ability to decolorize and detoxify effluents; they are also used in paper bleaching, synthesis of polymers, bioremediation, etc. In this work we were able to express a laccase from Trametes (Pycnoporus) sanguineus in the filamentous fungus Trichoderma atroviride. For this purpose, a transformation vector was designed to integrate the gene of interest in an intergenic locus near the blu17 terminator region. Although monosporic selection was still necessary, stable integration at the desired locus was achieved. The native signal peptide from T. sanguineus laccase was successful to secrete the recombinant protein into the culture medium. The purified, heterologously expressed laccase maintained similar properties to those observed in the native enzyme (Km and kcat and kcat/km values for ABTS, thermostability, substrate range, pH optimum, etc). To determine the bioremediation potential of this modified strain, the laccase-overexpressing Trichoderma strain was used to remove xenobiotic compounds. Phenolic compounds present in industrial wastewater and bisphenol A (an endocrine disruptor) from the culture medium were more efficiently removed by this modified strain than with the wild type. In addition, the heterologously expressed laccase was able to decolorize different dyes as well as remove benzo[α]pyrene and phenanthrene in vitro, showing its potential for xenobiotic compound degradation. [ABSTRACT FROM AUTHOR]

Nucleases are enzymes that can degrade genomic DNA and RNA that decrease the accuracy of quantitative measures of those nucleic acids. Here, we study conventional heating, standard microwave irradiation, and Lyse-It, a microwave-based lysing technology, for the potential to fragment and inactivate DNA and RNA endonucleases. Lyse-It employs the use of highly focused microwave irradiation to the sample ultimately fragmenting and inactivating RNase A, RNase B, and DNase I. Nuclease size and fragmentation were determined visually and quantitatively by SDS polyacrylamide gel electrophoresis and the mini-gel Agilent 2100 Bioanalyzer system, with a weighted size calculated to depict the wide range of nuclease fragmentation. Enzyme activity assays were conducted, and the rates were calculated to determine the effect of various lysing conditions on each of the nucleases. The results shown in this paper clearly demonstrate that Lyse-It is a rapid and highly efficient way to degrade and inactivate nucleases so that nucleic acids can be retained for down-stream detection. [ABSTRACT FROM AUTHOR]

Objective: Systematic Review was used to evaluate the efficacy and safety of Dalfampridine (DAP) in the treatment of Mobility Disability (MS) in patients with Multiple Sclerosis. Methods: Clinical randomized controlled studies about DAP and placebo in the treatment of Mobility Disability in patients with Multiple Sclerosis until March 2019 were explored by searching Embase, PubMed, Cochrane, Web of Knowledge, and ClinicalTrials.gov. Literature screening, data extraction, quality assessment, and statistical analysis were performed by using Stata 14.0. Results: 10 papers were included in the meta-analysis, and the number of patients was 2100. In conclusion, the application of DAP in clinical can significantly improve the Mobility Disability of patients [OR = 2.73, 95%CI (1.66, 4.50), P<0.001, I2 = 74.1%] and boost the mobility speed of patients in Timing 24 Minute Walk Test (T24FW) [SMD = 3,08, 95%CI(1,58, 4.58), P<0.001, I2 = 98.7%]. There are no significant differences of the incidence of adverse events [RR = 1.06, 95%CI (0.99, 1.14), P = 0.928, I2 = 0.0%] and urinary tract infection [RR = 1.21, 95%CI(0.91, 1.60), P = 0.145, I2 = 37.2%] between the DAP test group (Doses≤10 mg) and the placebo control group, and the incidence of adverse events [RR = 1.14, 95%CI(1.02, 1.28), P = 0.793, I2 = 0.0%] and urinary tract infection[RR = 3.05, 95%CI(1.04, 8.99), P = 0.680, I2 = 0.0%] for the DAP test group (Doses>10 mg) is a litter higher than the placebo control group. Conclusion: DAP can effectively improve Mobility Disability in patients with Multiple Sclerosis, which is safe and reliable in specific DAP usage doses. [ABSTRACT FROM AUTHOR]