Knockdown of Midgut Genes by dsRNA-Transgenic Plant-Mediated RNA Interference in the Hemipteran Insect Nilaparvata lugens

BACKGROUND: RNA interference (RNAi) is a powerful technique for functional genomics research in insects. Transgenic plants producing double-stranded RNA (dsRNA) directed against insect genes have been reported for lepidopteran and coleopteran insects, showing potential for field-level control of insect pests, but this has not been reported for other insect orders. METHODOLOGY/PRINCIPAL FINDINGS: The Hemipteran insect brown planthopper (Nilaparvata lugens Stål) is a typical phloem sap feeder specific to rice (Oryza sativa L.). To analyze the potential of exploiting RNAi-mediated effects in this insect, we identified genes (Nlsid-1 and Nlaub) encoding proteins that might be involved in the RNAi pathway in N. lugens. Both genes are expressed ubiquitously in nymphs and adult insects. Three genes (the hexose transporter gene NlHT1, the carboxypeptidase gene Nlcar and the trypsin-like serine protease gene Nltry) that are highly expressed in the N. lugens midgut were isolated and used to develop dsRNA constructs for transforming rice. RNA blot analysis showed that the dsRNAs were transcribed and some of them were processed to siRNAs in the transgenic lines. When nymphs were fed on rice plants expressing dsRNA, levels of transcripts of the targeted genes in the midgut were reduced; however, lethal phenotypic effects after dsRNA feeding were not observed. CONCLUSIONS: Our study shows that genes for the RNAi pathway (Nlsid-1 and Nlaub) are present in N. lugens. When insects were fed on rice plant materials expressing dsRNAs, RNA interference was triggered and the target genes transcript levels were suppressed. The gene knockdown technique described here may prove to be a valuable tool for further investigations in N. lugens. The results demonstrate the potential of dsRNA-mediated RNAi for field-level control of planthoppers, but appropriate target genes must be selected when designing the dsRNA-transgenic plants

Surgical Techniques to Optimize Early Urinary Continence Recovery Post Robot Assisted Radical Prostatectomy for Prostate Cancer.

PURPOSE OF REVIEW: A variety of different surgical techniques are thought to impact on urinary continence (UC) recovery in patients undergoing robot assisted radical prostatectomy (RARP) for prostate cancer. Herein, we review current evidence and propose a composite evidence-based technique to optimize UC recovery after RARP. RECENT FINDINGS: A literature search on studies reporting on surgical techniques to improve early continence recovery post robotic prostatectomy was conducted on PubMed and EMBASE. The available data from studies ranging from randomized control trials to retrospective cohort studies suggest that minimizing damage to the internal and external urinary sphincters and their neural supply, maximal sparing of urethral length, creating a secure vesicourethral anastomosis, and providing anterior and posterior myo- fascio-ligamentous support to the anastomosis can improve early UC recovery post RARP. A composite evidence-based surgical technique incorporating the above principles could optimize early UC recovery post RARP. Evidence from randomized studies is required to prove benefit

Deoxygedunin, a Natural Product with Potent Neurotrophic Activity in Mice

Gedunin, a family of natural products from the Indian neem tree, possess a variety of biological activities. Here we report the discovery of deoxygedunin, which activates the mouse TrkB receptor and its downstream signaling cascades. Deoxygedunin is orally available and activates TrkB in mouse brain in a BDNF-independent way. Strikingly, it prevents the degeneration of vestibular ganglion in BDNF −/− pups. Moreover, deoxygedunin robustly protects rat neurons from cell death in a TrkB-dependent manner. Further, administration of deoxygedunin into mice displays potent neuroprotective, anti-depressant and learning enhancement effects, all of which are mediated by the TrkB receptor. Hence, deoxygedunin imitates BDNF's biological activities through activating TrkB, providing a powerful therapeutic tool for treatment of various neurological diseases

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

The CHEMDNER corpus of chemicals and drugs and its annotation principles

The automatic extraction of chemical information from text requires the recognition of chemical entity mentions as one of its key steps. When developing supervised named entity recognition (NER) systems, the availability of a large, manually annotated text corpus is desirable. Furthermore, large corpora permit the robust evaluation and comparison of different approaches that detect chemicals in documents. We present the CHEMDNER corpus, a collection of 10,000 PubMed abstracts that contain a total of 84,355 chemical entity mentions labeled manually by expert chemistry literature curators, following annotation guidelines specifically defined for this task. The abstracts of the CHEMDNER corpus were selected to be representative for all major chemical disciplines. Each of the chemical entity mentions was manually labeled according to its structure-associated chemical entity mention (SACEM) class: abbreviation, family, formula, identifier, multiple, systematic and trivial. The difficulty and consistency of tagging chemicals in text was measured using an agreement study between annotators, obtaining a percentage agreement of 91. For a subset of the CHEMDNER corpus (the test set of 3,000 abstracts) we provide not only the Gold Standard manual annotations, but also mentions automatically detected by the 26 teams that participated in the BioCreative IV CHEMDNER chemical mention recognition task. In addition, we release the CHEMDNER silver standard corpus of automatically extracted mentions from 17,000 randomly selected PubMed abstracts. A version of the CHEMDNER corpus in the BioC format has been generated as well. We propose a standard for required minimum information about entity annotations for the construction of domain specific corpora on chemical and drug entities. The CHEMDNER corpus and annotation guidelines are available at: http://www.biocreative.org/resources/biocreative-iv/chemdner-corpus

Together in the Fight against Arthropod-Borne Diseases: A One Health Perspective

Arthropod-borne diseases represent a major risk for humans, livestock, pets and wildlife worldwide [...]

Abundance and distribution of recent benthic foraminifera from the southwestern part of the Bay of Bengal

Foraminifers are ubiquitous and abundant organisms in the marine environment, sensitive to different environmental variables such as pH, dissolved oxygen, salinity, temperature, organic matter and substrate. In the present study, environmental variables and benthic foraminiferal assemblages from 32 surface sediment samples belonging to different water depths were studied to understand the shelf and slope environment of the southwestern Bay of Bengal. Statistical methods such as cluster and principal component analysis (PCA) were used to infer the relationship existing among various foraminiferal assemblages, bathymetry, sediment and bottom water characteristics. Statistical analysis yielded four assemblages, of which assemblage-I is dominated by Nonion faba, Rotalidium annectens, Asterorotalia pulchella, Elphidium crispum, and Amphistegina radiata, and is confined to the shallowest inner shelf region (5 to 35 m water depth) with sandy sediments indicating high-energy condition. Assemblage-II is marked by the abundance of Cibicidoides wuellerstorfi, Hanzawaia concentrica, Quinqueloculina agglutinans, Quinqueloculina seminula, Quinqueloculina lamarckiana, Ammonia beccarri, and Ammonia tepida which are associated with the middle shelf region (water depth 35 to 70 m) with sandy to slightly muddy sand sediments. Assemblage-III is dominated by Asterorotalia dentata, Quinqueloculina venusta, Cancris communis, Cassidulina laevigata, and N. costiferum which occur at a depth of 70 to 170 m in the outer shelf, and are highly associated with slightly muddy sand to muddy sand. Whereas, assemblage -IV includes Uvigerina mediterranea, Bolivina dilatata, Bolivina robusta, and Bulimina marginata foraminiferal species that are abundant in the upper slope (170–244 m water depth) and are confined to muddy sand and sandy mud with low dissolved oxygen in the bottom water. The above assemblages depict that the abundance and distribution of foraminifera are largely controlled by substrate, energy conditions and environmental variables such as temperature, salinity, organic matter and dissolved oxygen