Analysis of ANRIL gene polymorphism rs4977574 association with kidney cancer development in Ukrainian population.

ANRIL (Antisense Non-coding RNA in the INK4 Locus, also known as CDKN2B-AS1) – 3.8-kb long non-coding RNA transcribed from the antisense strand of INK4b-ARF-INK4a gene cluster. It is known that ANRIL overexpression is associated with development of oncological pathologies of different localization. In addition, there are a number of studies devoted to role of ANRIL genetic polymorphism in emergence and progression of tumors, including tumors of genitourinary system. The aim of the study was to check the possible association between ANRIL gene polymorphism rs4977574 and kidney cancer development in representatives of Ukrainian population. Whole venous blood of 101 patients with clear cell renal cell carcinoma (CCRCC) (42 women and 59 men) and 100 patients without oncology history (34 women and 66 men) was used in the study. DNA from blood white cells was extracted using GeneJET Whole Blood Genomic DNA Purification Mini Kit (Thermo Fisher Scientific, USA). Genotyping of rs4977574 ANRIL gene polymorphic locus was performed using real-time polymerase chain reaction (real-time PCR) method in the presence of TaqMan assay C_31720978_30. The mathematical data were processed using the SPSS software package (version 17.0). P values <0.05 were considered as statistically significant. It was found that difference in rs4977574-genotype distribution between patients with CCRCC and control persons was absent in general group (P=0.216). At the same time, the statistical analysis stratified by gender showed that both in female and male subjects rs4977574-genotypes frequency also did not differ significantly between comparison groups (P=0.526 and P=0.160, respectively). However, after adjusting for age, body mass index, and smoking habits statistically significant association between rs4977574 ANRIL gene polymorphism and risk of kidney cancer development was detected in male subjects under superdominant inheritance model (P=0.049). It was revealed that heterozygotes (AG-genotype) have 2.17-fold  higher risk of CCRCC development (95% CI=1.005-4.695) compared to patients with AA- and GG-genotypes. In summary, this is the first report about ANRIL gene polymorphisms association with kidney cancer. Obtained results revealed that rs4977574 is related to kidney cancer risk only in Ukrainian men. Male individuals with AG-genotype have higher risk of CCRCC development compared to AA- and GG-genotypes carriers

Fasciclin II signals new synapse formation through amyloid precursor protein and the scaffolding protein dX11/Mint

Cell adhesion molecules (CAMs) have been universally recognized for their essential roles during synapse remodeling. However, the downstream pathways activated by CAMs have remained mostly unknown. Here, we used the Drosophila larval neuromuscular junction to investigate the pathways activated by Fasciclin II (FasII), a transmembrane CAM of the Ig superfamily, during synapse remodeling. We show that the ability of FasII to stimulate or to prevent synapse formation depends on the symmetry of transmembrane FasII levels in the presynaptic and postsynaptic cell and requires the presence of the fly homolog of amyloid precursor protein (APPL). In turn, APPL is regulated by direct interactions with the PDZ (postsynaptic density-95/Discs large/zona occludens-1)-containing protein dX11/Mint/Lin-10, which also regulates synapse expansion downstream of FasII. These results provide a novel mechanism by which cell adhesion molecules are regulated and provide fresh insights into the normal operation of APP during synapse development

Calmodulin’s Interaction with α- Synuclein, a Protein Implicated in Parkinson’s Disease

60,000 people in one year diagnosed, 1 million in the United States, and over 10 million worldwide have Parkinson’s disease (PD), which is the 2nd most common neurodegenerative disease. PD is prevalent in males and is typically seen in patients in their 60s. The most notable symptom of PD is the degeneration of neuronal control, especially in the hands. Over $156 million is spent on researching this disease and about$25 billion is spent for diagnosed patients each year. Aside from managing the financial burdens of PD, patients also have physical burdens. Most patients develop tremors and have difficulties writing, eating, and can degenerate quickly. The PD has previously been attributed to the lack of the neurotransmitter, dopamine, in the patient’s brain; however recent biochemical studies have surfaced other biomolecular mechanisms that attribute to PD, such as the interaction between Calmodulin and α-Synuclein. Calmodulin (CaM) is a protein found in the brain of healthy patients and is an intermediate calcium (Ca2+) binding messenger with over 100 different targets in eukaryotic cells. α- Synuclein (α-Syn) is a protein found at the ends of neurons in the presynaptic terminals in healthy patients, suggesting involvement with neurotransmitter signaling, however the exact function of α- Syn is still under investigation. Recent studies show that α- Syn and CaM interact resulting in protein aggregation. The α- Syn aggregation is the main structural component of Lewy bodies which is enhanced in the presence of Ca2+. Lewy bodies are known to develop in cranial nerve cells of PD patients and interrupts neuronal function. Little is known about how Lewy bodies attribute to abnormalities in PD patients, but there are connections to low levels of acetylcholine and dopamine, in addition to an interruption of signals between nerve cells. By using fluorescence spectroscopy, we studied the interaction between α- Syn and CaM and explore Ca2+’s role in the interaction that promotes the degenerateness of PD patients

On the Importance of Word Boundaries in Character-level Neural Machine Translation

Neural Machine Translation (NMT) models generally perform translation using a fixed-size lexical vocabulary, which is an important bottleneck on their generalization capability and overall translation quality. The standard approach to overcome this limitation is to segment words into subword units, typically using some external tools with arbitrary heuristics, resulting in vocabulary units not optimized for the translation task. Recent studies have shown that the same approach can be extended to perform NMT directly at the level of characters, which can deliver translation accuracy on-par with subword-based models, on the other hand, this requires relatively deeper networks. In this paper, we propose a more computationally-efficient solution for character-level NMT which implements a hierarchical decoding architecture where translations are subsequently generated at the level of words and characters. We evaluate different methods for open-vocabulary NMT in the machine translation task from English into five languages with distinct morphological typology, and show that the hierarchical decoding model can reach higher translation accuracy than the subword-level NMT model using significantly fewer parameters, while demonstrating better capacity in learning longer-distance contextual and grammatical dependencies than the standard character-level NMT model

Quantum communication networks with optical vortices

Quantum communications bring a paradigm change in internet security by using quantum resources to establish secure keys between parties. Present-day quantum communications networks are mainly point-to-point and use trusted nodes and key management systems to relay the keys. Future quantum networks, including the quantum internet, will have complex topologies in which groups of users are connected and communicate with each-other. Here we investigate several architectures for quantum communication networks. We show that photonic orbital angular momentum (OAM) can be used to route quantum information between different nodes. Starting from a simple, point-to-point network, we will gradually develop more complex architectures: point-to-multipoint, fully-connected and entanglement-distribution networks. As a particularly important result, we show that an $n$-node, fully-connected network can be constructed with a single OAM sorter and $n-1$ OAM values. Our results pave the way to construct complex quantum communication networks with minimal resources.Comment: 10 pages, 9 figure

Glia and Muscle Sculpt Neuromuscular Arbors by Engulfing Destabilized Synaptic Boutons and Shed Presynaptic Debris

As synapses grow at the Drosophila neuromuscular junction, they shed membrane material in an activity-dependent manner. Glia and postsynaptic muscle cells are required to engulf this debris to ensure new synaptic growth

Synergism between the N-acetyltransferase 2 gene and oxidant exposure increases the risk of idiopathic male infertility

N-acetyltransferase (NAT2) is a phase-II xenobiotic-metabolizing enzyme participating in the detoxification of toxic arylamines, aromatic amines and hydrazines. The present study was designed to investigate whether two common single-nucleotide polymorphisms (SNP) of the NAT2 gene (481C>T, rs1799929; 590G>A, rs1799930) are associated with susceptibility to idiopathic male infertility and to assess if the risk is modified by oxidant and antioxidant exposures. A total 430 DNA samples (203 infertile patients and 227 fertile men) were genotyped for the polymorphisms by PCR and restriction fragment length polymorphism. No association was found between the NAT2 polymorphisms and idiopathic male infertilit

Compositional Source Word Representations for Neural Machine Translation

The requirement for neural machine translation (NMT) models to use fixed-size input and output vocabularies plays an important role for their accuracy and generalization capability. The conventional approach to cope with this limitation is performing translation based on a vocabulary of sub-word units that are predicted using statistical word segmentation methods. However, these methods have recently shown to be prone to morphological errors, which lead to inaccurate translations. In this paper, we extend the source-language embedding layer of the NMT model with a bi-directional recurrent neural network that generates compositional representations of the source words from embeddings of character n-grams. Our model consistently outperforms conventional NMT with sub-word units on four translation directions with varying degrees of morphological complexity and data sparseness on the source side

FBK’s Neural Machine Translation Systems for IWSLT 2016

In this paper, we describe FBK’s neural machine translation (NMT) systems submitted at the International Workshop on Spoken Language Translation (IWSLT) 2016. The systems are based on the state-of-the-art NMT architecture that is equipped with a bi-directional encoder and an attention mechanism in the decoder. They leverage linguistic information such as lemmas and part-of-speech tags of the source words in the form of additional factors along with the words. We compare performances of word and subword NMT systems along with different optimizers. Further, we explore different ensemble techniques to leverage multiple models within the same and across different networks. Several reranking methods are also explored. Our submissions cover all directions of the MSLT task, as well as en-{de, fr} and {de, fr}-en directions of TED. Compared to previously published best results on the TED 2014 test set, our models achieve comparable results on en-de and surpass them on en-fr (+2 BLEU) and fr-en (+7.7 BLEU) language pairs