Species composition and abundance of fishes in Amirkelayeh Wetland

In order to determine the species composition and abundance of fishes in Amirkelayeh International wetland a series of seasonal survey were carried out in 2001-2002. The samples were collected by different methods of gillnet, beach seine, castnet, electroshocker and dipnet. After catching the fishes, they were transfered to the laboratory for further species indentification. A total of 1639 specimens were collected that belong to 7 orders, 9 families, 15 species and subspecies. The identification orders were: Cypriniformes, Salmoniformes, Syngnathiformes, Cyprinodontoformes, Siluriformes, Perciformes and Gasterosteiformes. Among different orders, the order of Cypriniformes and Gasterosteiformes and among different families, the Cyprinidae and Cobitidae and among different species, Perca jluviatilis and Scardinius erythrophthalmus had the most and the least abundance, respectively. The stock of Tinca tina and Esox lucius were so high. It should be noticed that three species of Cyprinus carpio, Scardinius erythrophthalmus and Cobitis taenia were found for the first time in this wetland

An untargeted lipidomic approach for qualitative determination of latent fingermark glycerides using UPLC-IMS-QToF-MSE

More detailed fundamental information is required about latent fingermark composition in order to better understand fingermark properties and their impact on detection efficiency, and the physical and chemical changes that occur with time following deposition. The composition of the glyceride fraction of latent fingermark lipids in particular is relatively under-investigated due in part to their high structural variability and the limitations of the analytical methods most frequently utilised to investigate fingermark composition. Here, we present an ultra performance liquid chromatography-ion mobility spectroscopy-quadrupole time-of-flight mass spectrometry (UPLC-IMS-QToF-MSE) method to characterise glycerides in charged latent fingermarks using data-independent acquisition. Di- and triglycerides were identified in fingermark samples from a population of 10 donors, through a combination of in silico fragmentation and monitoring for fatty acid neutral losses. 23 diglycerides and 85 families of triglycerides were identified, with significant diversity in chain length and unsaturation. 21 of the most abundant triglyceride families were found to be common to most or all donors, presenting potential targets for further studies to monitor chemical and physical changes in latent fingermarks over time. Differences in relative peak intensities may be indicative of inter- and intra-donor variability. While this study represents a promising step to obtaining more in-depth information about fingermark composition, it also highlights the complex nature of these traces

Generalized high-order classes for solving nonlinear systems and their applications

[EN] A generalized high-order class for approximating the solution of nonlinear systems of equations is introduced. First, from a fourth-order iterative family for solving nonlinear equations, we propose an extension to nonlinear systems of equations holding the same order of convergence but replacing the Jacobian by a divided difference in the weight functions for systems. The proposed GH family of methods is designed from this fourth-order family using both the composition and the weight functions technique. The resulting family has order of convergence 9. The performance of a particular iterative method of both families is analyzed for solving different test systems and also for the Fisher's problem, showing the good performance of the new methods.This research was partially supported by both Ministerio de Ciencia, Innovacion y Universidades and Generalitat Valenciana, under grants PGC2018-095896-B-C22 (MCIU/AEI/FEDER/UE) and PROMETEO/2016/089, respectively.Chicharro, FI.; Cordero Barbero, A.; Garrido-Saez, N.; Torregrosa Sánchez, JR. (2019). Generalized high-order classes for solving nonlinear systems and their applications. Mathematics. 7(12):1-14. https://doi.org/10.3390/math7121194S114712Petković, M. S., Neta, B., Petković, L. D., & Džunić, J. (2014). Multipoint methods for solving nonlinear equations: A survey. Applied Mathematics and Computation, 226, 635-660. doi:10.1016/j.amc.2013.10.072Kung, H. T., & Traub, J. F. (1974). Optimal Order of One-Point and Multipoint Iteration. Journal of the ACM, 21(4), 643-651. doi:10.1145/321850.321860Cordero, A., Gómez, E., & Torregrosa, J. R. (2017). Efficient High-Order Iterative Methods for Solving Nonlinear Systems and Their Application on Heat Conduction Problems. Complexity, 2017, 1-11. doi:10.1155/2017/6457532Sharma, J. R., & Arora, H. (2016). Improved Newton-like methods for solving systems of nonlinear equations. SeMA Journal, 74(2), 147-163. doi:10.1007/s40324-016-0085-xAmiri, A., Cordero, A., Taghi Darvishi, M., & Torregrosa, J. R. (2018). Stability analysis of a parametric family of seventh-order iterative methods for solving nonlinear systems. Applied Mathematics and Computation, 323, 43-57. doi:10.1016/j.amc.2017.11.040Cordero, A., Hueso, J. L., Martínez, E., & Torregrosa, J. R. (2009). A modified Newton-Jarratt’s composition. Numerical Algorithms, 55(1), 87-99. doi:10.1007/s11075-009-9359-zChicharro, F. I., Cordero, A., Garrido, N., & Torregrosa, J. R. (2019). Wide stability in a new family of optimal fourth‐order iterative methods. Computational and Mathematical Methods, 1(2), e1023. doi:10.1002/cmm4.1023FISHER, R. A. (1937). THE WAVE OF ADVANCE OF ADVANTAGEOUS GENES. Annals of Eugenics, 7(4), 355-369. doi:10.1111/j.1469-1809.1937.tb02153.xSharma, J. R., Guha, R. K., & Sharma, R. (2012). An efficient fourth order weighted-Newton method for systems of nonlinear equations. Numerical Algorithms, 62(2), 307-323. doi:10.1007/s11075-012-9585-7Soleymani, F., Lotfi, T., & Bakhtiari, P. (2013). A multi-step class of iterative methods for nonlinear systems. Optimization Letters, 8(3), 1001-1015. doi:10.1007/s11590-013-0617-6Cordero, A., & Torregrosa, J. R. (2007). Variants of Newton’s Method using fifth-order quadrature formulas. Applied Mathematics and Computation, 190(1), 686-698. doi:10.1016/j.amc.2007.01.06

Functional classification of G-Protein coupled receptors, based on their specific ligand coupling patterns

Functional identification of G-Protein Coupled Receptors (GPCRs) is one of the current focus areas of pharmaceutical research. Although thousands of GPCR sequences are known, many of them re- main as orphan sequences (the activating ligand is unknown). Therefore, classification methods for automated characterization of orphan GPCRs are imperative. In this study, for predicting Level 2 subfamilies of Amine GPCRs, a novel method for obtaining fixed-length feature vectors, based on the existence of activating ligand specific patterns, has been developed and utilized for a Support Vector Machine (SVM)-based classification. Exploiting the fact that there is a non-promiscuous relationship between the specific binding of GPCRs into their ligands and their functional classification, our method classifies Level 2 subfamilies of Amine GPCRs with a high predictive accuracy of 97.02% in a ten-fold cross validation test. The presented machine learning approach, bridges the gulf between the excess amount of GPCR sequence data and their poor functional characterization

The impact of sequencing depth on the inferred taxonomic composition and AMR gene content of metagenomic samples

Shotgun metagenomics is increasingly used to characterise microbial communities, particularly for the investigation of antimicrobial resistance (AMR) in different animal and environmental contexts. There are many different approaches for inferring the taxonomic composition and AMR gene content of complex community samples from shotgun metagenomic data, but there has been little work establishing the optimum sequencing depth, data processing and analysis methods for these samples. In this study we used shotgun metagenomics and sequencing of cultured isolates from the same samples to address these issues. We sampled three potential environmental AMR gene reservoirs (pig caeca, river sediment, effluent) and sequenced samples with shotgun metagenomics at high depth (~ 200 million reads per sample). Alongside this, we cultured single-colony isolates of Enterobacteriaceae from the same samples and used hybrid sequencing (short- and long-reads) to create high- quality assemblies for comparison to the metagenomic data. To automate data processing, we developed an open- source software pipeline, ‘ResPipe’

An analysis of the Sargasso Sea resource and the consequences for database composition

Background: The environmental sequencing of the Sargasso Sea has introduced a huge new resource of genomic information. Unlike the protein sequences held in the current searchable databases, the Sargasso Sea sequences originate from a single marine environment and have been sequenced from species that are not easily obtainable by laboratory cultivation. The resource also contains very many fragments of whole protein sequences, a side effect of the shotgun sequencing method.These sequences form a significant addendum to the current searchable databases but also present us with some intrinsic difficulties. While it is important to know whether it is possible to assign function to these sequences with the current methods and whether they will increase our capacity to explore sequence space, it is also interesting to know how current bioinformatics techniques will deal with the new sequences in the resource.Results: The Sargasso Sea sequences seem to introduce a bias that decreases the potential of current methods to propose structure and function for new proteins. In particular the high proportion of sequence fragments in the resource seems to result in poor quality multiple alignments.Conclusion: These observations suggest that the new sequences should be used with care, especially if the information is to be used in large scale analyses. On a positive note, the results may just spark improvements in computational and experimental methods to take into account the fragments generated by environmental sequencing techniques

Splitting and composition methods in the numerical integration of differential equations

We provide a comprehensive survey of splitting and composition methods for the numerical integration of ordinary differential equations (ODEs). Splitting methods constitute an appropriate choice when the vector field associated with the ODE can be decomposed into several pieces and each of them is integrable. This class of integrators are explicit, simple to implement and preserve structural properties of the system. In consequence, they are specially useful in geometric numerical integration. In addition, the numerical solution obtained by splitting schemes can be seen as the exact solution to a perturbed system of ODEs possessing the same geometric properties as the original system. This backward error interpretation has direct implications for the qualitative behavior of the numerical solution as well as for the error propagation along time. Closely connected with splitting integrators are composition methods. We analyze the order conditions required by a method to achieve a given order and summarize the different families of schemes one can find in the literature. Finally, we illustrate the main features of splitting and composition methods on several numerical examples arising from applications.Comment: Review paper; 56 pages, 6 figures, 8 table

Patent Landscape of Influenza A Virus Prophylactic Vaccines and Related Technologies

Executive Summary: This report focuses on patent landscape analysis of technologies related to prophylactic vaccines targeting pandemic strains of influenza. These technologies include methods of formulating vaccine, methods of producing of viruses or viral subunits, the composition of complete vaccines, and other technologies that have the potential to aid in a global response to this pathogen. The purpose of this patent landscape study was to search, identify, and categorize patent documents that are relevant to the development of vaccines that can efficiently promote the development of protective immunity against pandemic influenza virus strains. The search strategy used keywords which the team felt would be general enough to capture (or “recall”) the majority of patent documents which were directed toward vaccines against influenza A virus. After extensive searching of patent literature databases, approximately 33,500 publications were identified and collapsed to about 3,800 INPADOC families. Relevant documents, almost half of the total, were then identified and sorted into the major categories of vaccine compositions (about 570 families), technologies which support the development of vaccines (about 750 families), and general platform technologies that could be useful but are not specific to the problems presented by pandemic influenza strains (about 560 families). The first two categories, vaccines and supporting technologies, were further divided into particular subcategories to allow an interested reader to rapidly select documents relevant to the particular technology in which he or she is focused. This sorting process increased the precision of the result set. The two major categories (vaccines and supporting technologies) were subjected to a range of analytics in order to extract as much information as possible from the dataset. First, patent landscape maps were generated to assess the accuracy of the sorting procedure and to reveal the relationships between the various technologies that are involved in creating an effective vaccine. Then, filings trends are analyzed for the datasets. The country of origin for the technologies was determined, and the range of distribution to other jurisdictions was assessed. Filings were also analyzed by year, by assignee, and by inventor. Finally, the various patent classification systems were mapped to find which particular classes tend to hold influenza vaccine-related technologies. Besides the keywords developed during the searches and the landscape map generation, the classifications represent an alternate way for further researchers to identify emerging influenza technologies. The analysis included creation of a map of keywords, as shown above, describing the relationship of the various technologies involved in the development of prophylactic influenza A vaccines. The map has regions corresponding to live attenuated virus vaccines, subunit vaccines composed of split viruses or isolated viral polypeptides, and plasmids used in DNA vaccines. Important technologies listed on the map include the use of reverse genetics to create reassortant viruses, the growth of viruses in modified cell lines as opposed to the traditional methods using eggs, the production of recombinant viral antigens in various host cells, and the use of genetically-modified plants to produce virus-like particles. Another major finding was that the number of patent documents related to influenza being published has been steadily increasing in the last decade, as shown in the figure below. Until the mid-1990s, there were only a few influenza patent documents being published each year. The number of publications increased noticeably when TRIPS took effect, resulting in publication of patent applications. However, since 2006 the number of vaccine publications has exploded. In each of 2011 and 2012, about 100 references disclosing influenza vaccine technologies were published. Thus, interest in developing new and more efficacious influenza vaccines has been growing in recent years. This interest is probably being driven by recent influenza outbreaks, such as the H5N1 (bird flu) epidemic that began in the late 1990s and the 2009 H1N1 (swine flu) pandemic. The origins of the vaccine-related inventions were also analyzed. The team determined the country in which the priority application was filed, which was taken as an indication of the country where the invention was made or where the inventors intended to practice the invention. By far, most of the relevant families originated with patent applications filed in the United States. Other prominent priority countries were the China and United Kingdom, followed by Japan, Russia, and South Korea. France was a significant priority country only for supporting technologies, not for vaccines. Top assignees for these families were mostly large pharmaceutical companies, with the majority of patent families coming from Novartis, followed by GlaxoSmithKline, Pfizer, U.S. Merck (Merck, Sharpe, & Dohme), Sanofi, and AstraZeneca. Governmental and nonprofit institutes in China, Japan, Russia, South Korea and the United States also are contributing heavily to influenza vaccine research. Lastly, the jurisdictions were inventors have sought protection for their vaccine technologies were determined, and the number of patent families filing in a given country is plotted on the world map shown on page seven. The United States, Canada, Australia, Japan, South Korea and China have the highest level of filings, followed by Germany, Brazil, India, Mexico and New Zealand. However, although there are a significant number of filings in Brazil, the remainder of Central and South America has only sparse filings. Of concern, with the exception of South Africa, few other African nations have a significant number of filings. In summary, the goal of this report is to provide a knowledge resource for making informed policy decisions and for creating strategic plans concerning the assembly of efficacious vaccines against a rapidly-spreading, highly virulent influenza strain. The team has defined the current state of the art of technologies involved in the manufacture of influenza vaccines, and the important assignees, inventors, and countries have been identified. This document should reveal both the strengths and weaknesses of the current level of preparedness for responding to an emerging pandemic influenza strain. The effects of H5N1 and H1N1 epidemics have been felt across the globe in the last decade, and future epidemics are very probable in the near future, so preparations are necessary to meet this global health threat