Genetically Encoded Crosslinking Enables Identification of Multivalent Ubiquitin-Deubiquitylating Enzyme Interactions

Ubiquitin (Ub) proteoforms control nearly every aspect of eukaryotic cell biology through their diversity. Inspired by the widely used Ub C-terminal electrophiles (Ub−E), here we report the identification of multivalent binding of Ub with deubiquitylating enzymes (Dubs) using genetic code expansion (GCE) and crosslinking mass spectrometry. While the Ub−Es only gather structural information with the S1 Dub sites, we demonstrate that GCE of Ub with p-benzoyl-L-phenylalanine enables identification of interaction modes beyond the S1 site with a panel of Dubs of both eukaryotic and prokaryotic origin. Collectively, this represents the next generation of Ub-based affinity probes with a unique ability to unravel Ub interaction landscapes beyond what is afforded by cysteine-based chemistries.     

Drug Usage Safety from Drug Reviews with Hybrid Machine Learning Approach

With the increasing usage of drugs to remedy different diseases, drug safety has become crucial over the past few years. Often medicine from several companies is offered for a single disease that involves the same/similar substances with slightly different formulae. Such diversification is both helpful and dangerous as such medicine proves to be more effective or shows side effects to different patients. Despite clinical trials, side effects are reported when the medicine is used by the mass public, of which several such experiences are shared on social media platforms. A system capable of analyzing such reviews could be very helpful to assist healthcare professionals and companies for evaluating the safety of drugs after it has been marketed. Sentiment analysis of drug reviews has a large potential for providing valuable insights into these cases. Therefore, this study proposes an approach to perform analysis on the drug safety reviews using lexicon-based and deep learning techniques. A dataset acquired from the ‘Drugs.Com’ containing reviews of drug-related side effects and reactions, is used for experiments. A lexicon-based approach, Textblob is used to extract the positive, negative or neutral sentiment from the review text. Review classification is achieved using a novel hybrid deep learning model of convolutional neural networks and long short-term memory (CNN-LSTM) network. The CNN is used at the first level to extract the appropriate features while LSTM is used at the second level. Several well-known machine learning models including logistic regression, random forest, decision tree, and AdaBoost are evaluated using term frequency-inverse document frequency (TF-IDF), a bag of words (BoW), feature union of (TF-IDF + BoW), and lexicon-based methods. Performance analysis with machine learning models, long short term memory and convolutional neural network models, and state-of-the-art approaches indicate that the proposed CNN-LSTM model shows superior performance with an 0.96 accuracy. We also performed a statistical significance T-test to show the significance of the proposed CNN-LSTM model in comparison with other approaches.     

Search for ionisation density effects in the radiation absorption stage in LiF:Mg,Ti

Optical absorption (OA) dose-response of LiF:Mg,Ti (TLD-100) is studied as a function of electron energy (ionisation density) and irradiation dose. Contrary to the situation in thermoluminescence dose-response where the supralinearity is strongly energy-dependent, no dependence of the OA dose filling constants on energy is observed. This result is interpreted as indicating a lack of competitive process in the radiation absorption stage. The lack of an energy dependence of the dose filling constant also suggests that the charge carrier migration distances are sufficiently large to smear out the differences in the non-uniform distribution of ionisation events created by the impinging gamma/electron radiation of various energies.     

Color evolution during a coating process of pharmaceutical tablet cores by random spraying

Placebo white tablet cores (lactose anhydrous [47.6%], corn starch [23.8%], microcrystalline cellulose [19.1%], polyvinylpyrrolidone [7.9%], magnesium stearate [0.8%], and talcum powder [0.8%]) were coated with a colorant (hydroxypropyl methylcellulose [8% w/v], titanium dioxide [0.2% w/v], FD&C yellow No. 6 with aluminum lacquer [0.8% w/v], polyethylene glycol 4000 [0.4% w/v], and purified water [q.s.p. 100 mL]) using a random spraying method during 130 minutes. During the coating process, batches of 21 samples were extracted every 10 minutes and measured with a DigiEye imaging system. The initial cores showed very similar and uniform colors (Mean Color Difference from the Mean [MCDM] of 0.8 CIELAB units), but partially coated tablets showed lower uniformity (MCDM below 2.0 CIELAB units). There was a high color variability (MCDM about 4.0 CIELAB units) among tablets of the same batch in the period between 10 and 30 minutes, which decreased as the coating process progressed, until achieving a final acceptable value (MCDM below 2.0 CIELAB units). During the coating process, L^* decreased, C^*_ab strongly increased, and h _ab remained nearly constant (disregarding results at 0 and 10 minutes). CIELAB and CIEDE2000 color differences (mainly chroma differences) with respect to the initial color of the tablets were modeled as a function of time by exponential functions with three coefficients. The color change in the interval from 90 to 130 minutes (4.3 CIELAB units, or 2.6 CIEDE2000 units), may be considered negligible bearing in mind the color variability in the batches of 21 samples and typical values of visual color thresholds.     

The product of the cph oncogene is a truncated, nucleotide-binding protein that enhances cellular survival to stress

Cph was isolated from neoplastic Syrian hamster embryo fibroblasts initiated by 3-methylcholanthrene (MCA), and was shown to be a single copy gene in the hamster genome, conserved from yeast to human cells, expressed in fetal cells and most adult tissues, and acting synergistically with H-ras in the transformation of murine NIH3T3 fibroblasts. We have now isolated Syrian hamster full-length cDNAs for the cph oncogene and proto-oncogene. Nucleotide sequence analysis revealed that cph was activated in MCA-treated cells by a point-mutational deletion at codon 214, which caused a shift in the normal open reading frame (ORF) and brought a translation termination codon 33 amino acids downstream. While proto-cph encodes a protein (pcph) of 469 amino acids, cph encodes a truncated protein (cph) of 246 amino acids with a new, hydrophobic C-terminus. Similar mechanisms activated cph in other MCA-treated Syrian hamster cells. The cph and proto-cph proteins have partial sequence homology with two protein families: GDP/GTP exchange factors and nucleotide phosphohydrolases. In vitro translated, gel-purified cph proteins did not catalyze nucleotide exchange for H-ras, but were able to bind nucleotide phosphates, in particular ribonucleotide diphosphates such as UDP and GDP. Steady-state levels of cph mRNA increased 6.7-fold in hamster neoplastic cells, relative to a 2.2-fold increase in normal cells, when they were subjected to a nutritional stress such as serum deprivation. Moreover, cph-transformed NIH3T3 cells showed increased survival to various forms of stress (serum starvation, hyperthermia, ionizing radiation), strongly suggesting that cph participates in cellular mechanisms of response to stress.     

DC conductivity study of polyaniline and poly(acrylonitrile-butadiene-styrene) blends

In this study, conducting blends of poly(acrylonitrile-butadiene-styrene) and polyaniline doped with dodecylbenzene sulfonic acid were prepared by solution blending. In order to understand the electrical conduction mechanism of the samples, DC electrical conductivity measurements of the blends were carried out in the temperature range of 80–320 K. The experimental results fit well with Mott's model of three-dimensional variable range hopping conduction. The values of Mott's temperature, density of states at the Fermi energy, average hopping distance and barrier height for the composites were calculated and presented.     

The local spatial autocorrelation and the kernel method for identifying black zones: A comparative approach

This article aims to determine the location and the length of road sections characterized by a concentration of accidents (black zones). Two methods are compared: one based on a local decomposition of a global autocorrelation index, the other on kernel estimation. After explanation, both methods are applied and compared in terms of operational results, respective advantages and shortcomings, as well as underlying conceptual elements. The operationality of both methods is illustrated by an application to one Belgian road.