Natural coagulates for wastewater treatment; a review for application and mechanism

The increase of water demand and wastewater generation is among the global concerns in the world. The less effective management of water sources leads to serious consequences, the direct disposal of untreated wastewater is associated with the environmental pollution, elimination of aquatic life and the spread of deadly epidemics. The flocculation process is one of the most important stages in water and wastewater treatment plants, wherein this phase the plankton, colloidal particles, and pollutants are precipitated and removed. Two major types of coagulants are used in the flocculation process included the chemical and natural coagulants. Many studies have been performed to optimize the flocculation process while most of these studies have confirmed the hazardous effects of chemical coagulants utilization on the ecosystem. This chapter reviews a summary of the coagulation/flocculation processes using natural coagulants as well as reviews one of the most effective natural methods of water and wastewater treatment

Hyaluronan Export through Plasma Membranes Depends on Concurrent K+ Efflux by Kir Channels

Hyaluronan is synthesized within the cytoplasm and exported into the extracellular matrix through the cell membrane of fibroblasts by the MRP5 transporter. In order to meet the law of electroneutrality, a cation is required to neutralize the emerging negative hyaluronan charges. As we previously observed an inhibiting of hyaluronan export by inhibitors of K+ channels, hyaluronan export was now analysed by simultaneously measuring membrane potential in the presence of drugs. This was done by both hyaluronan import into inside-out vesicles and by inhibition with antisense siRNA. Hyaluronan export from fibroblast was particularly inhibited by glibenclamide, ropivacain and BaCl2 which all belong to ATP-sensitive inwardly-rectifying Kir channel inhibitors. Import of hyaluronan into vesicles was activated by 150 mM KCl and this activation was abolished by ATP. siRNA for the K+ channels Kir3.4 and Kir6.2 inhibited hyaluronan export. Collectively, these results indicated that hyaluronan export depends on concurrent K+ efflux

Bacteria-inducing legume nodules involved in the improvement of plant growth, health and nutrition

Bacteria-inducing legume nodules are known as rhizobia and belong to the class Alphaproteobacteria and Betaproteobacteria. They promote the growth and nutrition of their respective legume hosts through atmospheric nitrogen fixation which takes place in the nodules induced in their roots or stems. In addition, rhizobia have other plant growth-promoting mechanisms, mainly solubilization of phosphate and production of indoleacetic acid, ACC deaminase and siderophores. Some of these mechanisms have been reported for strains of rhizobia which are also able to promote the growth of several nonlegumes, such as cereals, oilseeds and vegetables. Less studied are the mechanisms that have the rhizobia to promote the plant health; however, these bacteria are able to exert biocontrol of some phytopathogens and to induce the plant resistance. In this chapter, we revised the available data about the ability of the legume nodule-inducing bacteria for improving the plant growth, health and nutrition of both legumes and nonlegumes. These data showed that rhizobia meet all the requirements of sustainable agriculture to be used as bio-inoculants allowing the total or partial replacement of chemicals used for fertilization or protection of crops

From Mendel’s discovery on pea to today’s plant genetics and breeding

In 2015, we celebrated the 150th anniversary of the presentation of the seminal work of Gregor Johann Mendel. While Darwin’s theory of evolution was based on differential survival and differential reproductive success, Mendel’s theory of heredity relies on equality and stability throughout all stages of the life cycle. Darwin’s concepts were continuous variation and “soft” heredity; Mendel espoused discontinuous variation and “hard” heredity. Thus, the combination of Mendelian genetics with Darwin’s theory of natural selection was the process that resulted in the modern synthesis of evolutionary biology. Although biology, genetics, and genomics have been revolutionized in recent years, modern genetics will forever rely on simple principles founded on pea breeding using seven single gene characters. Purposeful use of mutants to study gene function is one of the essential tools of modern genetics. Today, over 100 plant species genomes have been sequenced. Mapping populations and their use in segregation of molecular markers and marker–trait association to map and isolate genes, were developed on the basis of Mendel's work. Genome-wide or genomic selection is a recent approach for the development of improved breeding lines. The analysis of complex traits has been enhanced by high-throughput phenotyping and developments in statistical and modeling methods for the analysis of phenotypic data. Introgression of novel alleles from landraces and wild relatives widens genetic diversity and improves traits; transgenic methodologies allow for the introduction of novel genes from diverse sources, and gene editing approaches offer possibilities to manipulate gene in a precise manner

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Towards creating a new triple store for literature-based discovery

Literature-based discovery (LBD) is a field of research aiming at discovering new knowledge by mining scientific literature. Knowledge bases are commonly used by LBD systems. SemMedDB, created with the use of SemRep information extraction system, is the most frequently used database in LBD. However, new applications of LBD are emerging that go beyond the scope of SemMedDB. In this work, we propose some new discovery patterns that lie in the domain of Natural Products and that are not covered by the existing databases and tools. Our goal thus is to create a new, extended knowledge base, addressing limitations of SemMedDB. Our proposed contribution is three-fold: 1) we add types of entities and relations that are of interest for LBD but are not covered by SemMedDB; 2) we plan to leverage full texts of scientific publications, instead of titles and abstracts only; 3) we envisage using the RDF model for our database, in accordance with Semantic Web standards. To create a new database, we plan to build a distantly supervised entity and relation extraction system, employing a neural networks/deep learning architecture. We describe the methods and tools we plan to employ