F-Actin Organization and Epidermal Cell Morphogenesis in the Brown Alga Sargassum vulgare.

The ordinary epidermal cells of various vascular plants are characterized by wavy anticlinal wall contours. This feature has not yet been reported in multicellular algal species. Here, we found that, in the leaf-like blades of the brown alga Sargassum vulgare, epidermal cells exhibit prominent waviness. Initially, the small meristodermal cells exhibit straight anticlinal contour, which during their growth becomes wavy, in a pattern highly reminiscent of that found in land plants. Waviness is restricted close to the external periclinal wall, while at inner levels the anticlinal walls become thick and even. The mechanism behind this shape relies on cortical F-actin organization. Bundles of actin filaments are organized, extending under the external periclinal wall and connecting its junctions with the anticlinal walls, constituting an interconnected network. These bundles define the sites of local thickening deposition at the anticlinal/periclinal wall junctions. These thickenings are interconnected by cellulose microfibril extensions under the external periclinal wall. Apart from the wavy anticlinal contour, outward protrusions also arise on the external periclinal wall, thus the whole epidermis exhibits a quilted appearance. Apart from highlighting a new role for F-actin in cell shaping, the comparison of this morphogenetic mechanism to that of vascular plants reveals a case of evolutionary convergence among photosynthetic organisms.

SCINOBO: a novel system classifying scholarly communication in a dynamically constructed hierarchical Field-of-Science taxonomy.

Classifying scientific publications according to Field-of-Science taxonomies is of crucial importance, powering a wealth of relevant applications including Search Engines, Tools for Scientific Literature, Recommendation Systems, and Science Monitoring. Furthermore, it allows funders, publishers, scholars, companies, and other stakeholders to organize scientific literature more effectively, calculate impact indicators along Science Impact pathways and identify emerging topics that can also facilitate Science, Technology, and Innovation policy-making. As a result, existing classification schemes for scientific publications underpin a large area of research evaluation with several classification schemes currently in use. However, many existing schemes are domain-specific, comprised of few levels of granularity, and require continuous manual work, making it hard to follow the rapidly evolving landscape of science as new research topics emerge. Based on our previous work of scinobo, which incorporates metadata and graph-based publication bibliometric information to assign Field-of-Science fields to scientific publications, we propose a novel hybrid approach by further employing Neural Topic Modeling and Community Detection techniques to dynamically construct a Field-of-Science taxonomy used as the backbone in automatic publication-level Field-of-Science classifiers. Our proposed Field-of-Science taxonomy is based on the OECD fields of research and development (FORD) classification, developed in the framework of the Frascati Manual containing knowledge domains in broad (first level(L1), one-digit) and narrower (second level(L2), two-digit) levels. We create a 3-level hierarchical taxonomy by manually linking Field-of-Science fields of the sciencemetrix Journal classification to the OECD/FORD level-2 fields. To facilitate a more fine-grained analysis, we extend the aforementioned Field-of-Science taxonomy to level-4 and level-5 fields by employing a pipeline of AI techniques. We evaluate the coherence and the coverage of the Field-of-Science fields for the two additional levels based on synthesis scientific publications in two case studies, in the knowledge domains of Energy and Artificial Intelligence. Our results showcase that the proposed automatically generated Field-of-Science taxonomy captures the dynamics of the two research areas encompassing the underlying structure and the emerging scientific developments.

Histone Acetyltransferase GCN5 Affects Auxin Transport during Root Growth by Modulating Histone Acetylation and Gene Expression of PINs.

General Control Non-Derepressible 5 (GCN5) is a histone acetyltransferase that targets multiple genes and is essential for the acetylation of Lysine residues in the N-terminal tail of histone H3 in Arabidopsis. GCN5 interacts with the transcriptional coactivator Alteration/Deficiency in Activation 2b (ADA2b), which enhances its activity functioning in multiprotein complexes, such as the Spt-Ada-Gcn5-Acetyltransferase complex (SAGA). Mutations in GCN5 and ADA2b result in pleiotropic phenotypes, including alterations in the growth of roots. Auxin is known to regulate root development by modulating gene expression patterns. Auxin moves polarly during plant growth via the Pin-formed (PIN) auxin efflux transport proteins. The effect of GCN5 and ADA2b on auxin distribution at different stages of early root growth (4 to 7 days post-germination) was studied using the reporter lines DR5rev::GFP and PIN1::PIN1-GFP. In wild-type plants, auxin efflux transporter PIN1 expression increases from the fourth to the seventh day of root growth. The PIN1 expression was reduced in the roots of gcn5-1 and ada2b-1 compared to the wild type. The expression of PIN1 in ada2b-1 mutants is confined only to the meristematic zone, specifically in the stele cells, whereas it is almost abolished in the elongation zone. Gene expression analysis showed that genes associated with auxin transport, PIN1, PIN3 and PIN4, are downregulated in gcn5-1 and ada2b-1 mutants relative to the wild type. As a result, auxin accumulation was also reduced in gcn5-1 and ada2b-1 compared to wild-type roots. Furthermore, acetylation of Lysine 14 of histone H3 (H3K14) was also affected in the promoter and coding region of PIN1, PIN3 and PIN4 genes during root growth of Arabidopsis in gcn5 mutants. In conclusion, GCN5 acts as a positive regulator of auxin distribution in early root growth by modulating histone H3 acetylation and the expression of auxin efflux transport genes.

Microcystin-LR and cyanobacterial extracts alter the distribution of cell wall matrix components in rice root cells.

Cyanobacterial toxins (known as cyanotoxins) disrupt the plant cytoskeleton (i.e. microtubules and F-actin), which is implicated in the regulation of cell wall architecture. Therefore, cyanotoxins are also expected to affect cell wall structure and composition. However, the effects of cyanobacterial toxicity on plant cell wall have not been yet thoroughly studied. Accordingly, the alterations of cell wall matrix after treatments with pure microcystin-LR (MC-LR), or cell extracts of one MC-producing and one non-MC-producing Microcystis strain were studied in differentiated Oryza sativa (rice) root cells. Semi-thin transverse sections of variously treated LR-White-embedded roots underwent immunostaining for various cell wall epitopes, including homogalacturonans (HGs), arabinogalactan-proteins (AGPs), and hemicelluloses. Homogalacturonan and arabinan distribution patterns were altered in the affected roots, while a pectin methylesterase (PME) activity assay revealed that PMEs were also affected. Elevated intracellular Ca2+ levels, along with increased callose and mixed linkage glucans (MLGs) deposition, were also observed after treatment. Xyloglucans appeared unaffected and lignification was not observed. The exact mechanism of cyanobacterial toxicity against the cell wall is to be further investigated.

A novel tool that allows interactive screening of PubMed citations showed promise for the semi-automation of identification of Biomedical Literature.

BACKGROUND AND OBJECTIVES: Systematic reviews form the basis of evidence-based medicine, but are expensive and time-consuming to produce. To address this burden, we have developed a literature identification system (Pythia) that combines the query formulation and citation screening steps. METHODS: Pythia incorporates a set of natural-language questions with machine-learning algorithms to rank all PubMed citations based on relevance, returning the 100 top-ranked citations for human screening. The tagged citations are iteratively exploited by Pythia to refine the search and re-rank the citations. RESULTS: Across seven systematic reviews, the ability of Pythia to identify the relevant citations (sensitivity) ranged from 0.09 to 0.58. The number of abstracts reviewed per relevant abstract number needed to read (NNR) was lower than in the manually screened project in four reviews, higher in two, and had mixed results in one. The reviews that had greater overall sensitivity retrieved more relevant citations in early batches, but retrieval was generally unaffected by other aspects, such as study design, study size, and specific key question. CONCLUSION: Due to its low sensitivity, Pythia is not ready for widespread use. Future research should explore ways to encode domain knowledge in query formulation to better enrich the questions used in the search.

Cytokinesis in fra2 Arabidopsis thaliana p60-Katanin Mutant: Defects in Cell Plate/Daughter Wall Formation.

Cytokinesis is accomplished in higher plants by the phragmoplast, creating and conducting the cell plate to separate daughter nuclei by a new cell wall. The microtubule-severing enzyme p60-katanin plays an important role in the centrifugal expansion and timely disappearance of phragmoplast microtubules. Consequently, aberrant structure and delayed expansion rate of the phragmoplast have been reported to occur in p60-katanin mutants. Here, the consequences of p60-katanin malfunction in cell plate/daughter wall formation were investigated by transmission electron microscopy (TEM), in root cells of the fra2 Arabidopsis thaliana loss-of-function mutant. In addition, deviations in the chemical composition of cell plate/new cell wall were identified by immunolabeling and confocal microscopy. It was found that, apart from defective phragmoplast microtubule organization, cell plates/new cell walls also appeared faulty in structure, being unevenly thick and perforated by large gaps. In addition, demethylesterified homogalacturonans were prematurely present in fra2 cell plates, while callose content was significantly lower than in the wild type. Furthermore, KNOLLE syntaxin disappeared from newly formed cell walls in fra2 earlier than in the wild type. Taken together, these observations indicate that delayed cytokinesis, due to faulty phragmoplast organization and expansion, results in a loss of synchronization between cell plate growth and its chemical maturation.

Beyond Microcystins: Cyanobacterial Extracts Induce Cytoskeletal Alterations in Rice Root Cells.

Microcystins (MCs) are cyanobacterial toxins and potent inhibitors of protein phosphatases 1 (PP1) and 2A (PP2A), which are involved in plant cytoskeleton (microtubules and F-actin) organization. Therefore, studies on the toxicity of cyanobacterial products on plant cells have so far been focused on MCs. In this study, we investigated the effects of extracts from 16 (4 MC-producing and 12 non-MC-producing) cyanobacterial strains from several habitats, on various enzymes (PP1, trypsin, elastase), on the plant cytoskeleton and H2O2 levels in Oryza sativa (rice) root cells. Seedling roots were treated for various time periods (1, 12, and 24 h) with aqueous cyanobacterial extracts and underwent either immunostaining for α-tubulin or staining of F-actin with fluorescent phalloidin. 2,7-dichlorofluorescein diacetate (DCF-DA) staining was performed for H2O2 imaging. The enzyme assays confirmed the bioactivity of the extracts of not only MC-rich (MC+), but also MC-devoid (MC-) extracts, which induced major time-dependent alterations on both components of the plant cytoskeleton. These findings suggest that a broad spectrum of bioactive cyanobacterial compounds, apart from MCs or other known cyanotoxins (such as cylindrospermopsin), can affect plants by disrupting the cytoskeleton.

Comparative study of aggression - Dangerousness on patients with paranoid schizophrenia: Focus on demographic data, PANSS, drug use and aggressiveness.

This cross sectional study aimed to compare the differences in psychopathology of Greek homicide and homicide attempters, patients with schizophrenia, with non violent individuals, suffering from schizophrenia. The study compared three Groups of 220 men, diagnosed with schizophrenia: (a) Group Α (Schizophrenia - No violence, (b) Group Β (Schizophrenia - with violence or violent crime), (c) Group C (Schizophrenia - not guilty by reason of insanity - violent crime). Several psychometric tools were used, such as M.I.N·I (Mini-International Neuropsychiatric Interview), PANSS scale (Positive and Negative Symptoms Scale). Most subjects suffered from paranoid schizophrenia. On factors such as demographic characteristics (i.e. current occupational status, living status), statistically significant findings were shown for Groups B and C vs Group A. Predisposing psychosocial factors, such as family conflicts and aggressiveness against family, were found to be statistically significant in differentiating violent versus nonviolent individuals with psychosis. They differed significantly in factors like history of juvenile delinquency, but also in the type of aggressiveness in general. These differences were confirmed on PANSS scale. In conclusion, the longer the history of aggressiveness is presented, the greater the chances are of individuals falling into Group C and it is possible to spend several years from the onset of the disease until the moment of crime.

Hierarchical bi-directional attention-based RNNs for supporting document classification on protein-protein interactions affected by genetic mutations.

In this paper, we describe a hierarchical bi-directional attention-based Re-current Neural Network (RNN) as a reusable sequence encoder architecture, which is used as sentence and document encoder for document classification. The sequence encoder is composed of two bi-directional RNN equipped with an attention mechanism that identifies and captures the most important elements, words or sentences, in a document followed by a dense layer for the classification task. Our approach utilizes the hierarchical nature of documents which are composed of sequences of sentences and sentences are composed of sequences of words. In our model, we use word embeddings to project the words to a low-dimensional vector space. We leverage word embeddings trained on PubMed for initializing the embedding layer of our network. We apply this model to biomedical literature specifically, on paper abstracts published in PubMed. We argue that the title of the paper itself usually contains important information more salient than a typical sentence in the abstract. For this reason, we propose a shortcut connection that integrates the title vector representation directly to the final feature representation of the document. We concatenate the sentence vector that represents the title and the vectors of the abstract to the document feature vector used as input to the task classifier. With this system we participated in the Document Triage Task of the BioCreative VI Precision Medicine Track and we achieved 0.6289 Precision, 0.7656 Recall and 0.6906 F1-score with the Precision and F1-score be the highest ranking first among the other systems.Database URL: https://github.com/afergadis/BC6PM-HRNN.