Features of formation somatic pathologies under chronic exposure to hydrofluoride in the manufacture of titanic alloys

Introduction. Most studies on the morbidity of workers with fluorine compounds are devoted to occupational medicine at aluminium industry enterprises. The aim of the study is to identify the exposure, gender and evolutionary features of the formation of general somatic morbidity associated with chronic occupational exposure to hydrofluoride in the production of titanium alloys. Materials and methods. The analysis of the prevalence of chronic pathology according to the medical examination of 562 workers in contact with hydrofluoride and the incidence of temporary disability according to 29949 disability sheets in comparison with non-exposed persons of the same enterprise is given. Results. With an increase in the degree of harmfulness of working conditions, there was an augmentation increase in the risk of developing pathology of the respiratory organs, eyes, musculoskeletal system, arterial hypertension and hypercholesterolemia. In the working conditions of Class 3.1, an increased prevalence of diseases of the nervous and genitourinary systems with a moderate degree of occupational conditionality was revealed (relative risks (RR) 1.6 and 2.0, respectively, р < 0.05), class 3.2 - a high degree of professional conditionality of respiratory diseases (RR = 2.8). When working in harmful working conditions, there was an average degree of occupational conditionality of nervous system diseases in women (RR = 1.9) and a small degree of arterial hypertension in men (RR = 1.2). The prevalence of general somatic pathology in all age groups was higher than in non-exposed persons of the same age. Conclusion. Hydrofluoride in the production of titanium alloys was proved to be a trigger contributing to the formation of the pathology of the respiratory, circulatory, digestive, ear, eyes, skin, blood, musculoskeletal, nervous, endocrine, and genitourinary systems.

Towards Generalizable Predictions for the Effects of Mutations on G-Protein Coupled Receptor Expression

Missense mutations that compromise the plasma membrane expression (PME) of integral membrane proteins (MPs) are the root cause of numerous genetic diseases. Differentiation of this class of mutations from those that specifically modify the activity of the folded protein has proven useful for the development and targeting of precision therapeutics. Nevertheless, it remains challenging to predict the effects of mutations on the stability and/ or expression of MPs. In this work, we utilize deep mutational scanning data to train a series of artificial neural networks to predict the effects of mutations on the PME of the G-protein coupled receptor (GPCR) rhodopsin from structural and/ or evolutionary features. We show that our best performing network, which we term PMEpred, can differentiate pathogenic rhodopsin variants that induce misfolding from those that primarily compromise signaling. This network also generates statistically significant predictions for the effects of mutations on the PME of another GPCR (Beta-2 adrenergic receptor) but not for an unrelated voltage-gated potassium channel (KCNQ1). Notably, our analyses of these networks suggest structural features alone are generally sufficient to recapitulate the observed mutagenic trends. Moreover, our findings imply that networks trained in this manner may be generalizable to proteins that share a common fold. Implications of our findings for the design of mechanistically specific genetic predictors are discussed.

A comprehensive BIAPSS platform for the physicochemical featurization of phase separating proteins

The liquid-liquid phase separation (LLPS) of biological macromolecules has emerged as a foundational mechanism underlying the formation of a myriad of membraneless organelles (MLOs), such as stress granules, transcription factor condensates, and chromatin compartments. A molecular grammar of sequences, which would enable a quantitative prediction and understanding of protein phase separation from first principles is currently missing. A major challenge in the field is the sparsity of bioinformatics data and the lack of computational, data-driven tools for biophysical and statistical analysis of proteins capable of phase separation. Here we present the utility of web applications framed within a novel open-source platform for BioInformatic Analysis of liquid-liquid Phase-Separating protein Sequences, https://biapss.chem.iastate.edu/. BIAPSS combines high-throughput interactive data analytics of physicochemical and evolutionary features with a comprehensive repository of bioinformatic data for on-the-fly research of the sequence-dependent properties of proteins with known LLPS behavior. To facilitate exploration of the services and provide the interpretation guideline, we present two attention-getting case studies of FUS and hnRNPDL. This should help the LLPS community uncover the nature of interactions driving the formation of membraneless organelles.

Postmodern Tendencies in the Russian Poetry of the “Silver Age”

For the first time, the article analyses certain aspects of Russian poetry of the “Silver Age” in order to identify the rudiments or features which are characteristic of the postmodern creative paradigm. It is noted that a number of poets almost do not have any postmodernist tendencies. Despite the fact it is proved that postmodernism denies the personality-centric and aesthetically oriented concept of modernism, it nevertheless arose on the basis of modernism and has sharpened evolutionary features formulated in the first half of the 20th century. The article aims to prove a hypothesis that arises in the authors during a preliminary perceptual reading of the poets` works of the “Silver Age”: in the early 20th century. Sporadically and consistently in individual authors can be observed irony, play, reconstruction and performance as precursor of postmodernist creative thinking. Specialties of the Russian poetry of the “Silver Age”, which directly correlate with postmodernist tendencies of the second half of the 20th century is not a description itself, but the realization of reality, ambivalence, as well as following the linguistic and figurative, conceptual, motive levels of gradual transitions between the paradigms of “symbolism – modernism” and “modernism – postmodernism”. The international significance of the article is that the material of one of the Eastern European literatures has proved the existence of postmodern (quasi-postmodern) features in the first half of the 20th century for the first time, which can serve as a deeper research in the field of literary typology, continuity; culturology and anthropology.

Always the eBook of the Future

In their third decade, depending on one’s definition, eBooks are still in their incunabula moment. While eBooks began to emerge prior to the year 2000, they began to garner a more robust market after the launch of Amazon’s Kindle and Apple’s iPhone, both in 2007, and Apple’s iPad in 2010. At least by some measures, eBooks today are thriving, and are bound to continue to evolve, just as publishing itself has evolved over more than five centuries. This article examines the current state and potential future of digital publishing, including enhanced eBooks, hypertext, interactivity, artificial intelligence, augmented reality, data- and gesture-based manipulation, and other evolutionary features that transform the eBook into a fundamentally different, immersive experience in reading and engagement.

Predicting the Functional Impact of KCNQ1 Variants with Artificial Neural Networks

Predicting the functional impact of KCNQ1 variants of uncertain significance (VUS) can assist physicians in taking appropriate treatment decision for patients with genetic heart rhythm disorder. This work presents three artificial neural network (ANN)-based predictive models that classify four key functional parameters of KCNQ1 variants as normal or dysfunctional using evolutionary and/or biophysical descriptors. Recent advances in predicting protein structure and variant properties with artificial intelligence (AI) rely heavily on the availability of evolutionary features and thus fail to directly assess the biophysical underpinnings of a change in structure and/or function. The central goal of this work was to develop an ANN model based on structure and physiochemical properties of KCNQ1, that performs better or comparable with algorithms only on evolutionary features. These biophysical features highlight the structure-function relationships that govern protein stability, function, and regulation. The input sensitivity algorithm incorporates the roles of hydrophobicity, polarizability, and functional densities on key functional parameters of the KCNQ1 channel. Inclusion of the biophysical features outperforms exclusive use of evolutionary features in predicting variant activation voltage and deactivation time. As AI is increasing applied to problems in biology, biophysical understanding will be critical with respect to 'explainable AI', i.e., understanding the relation of sequence, structure, and function of proteins. Our model is available at www.kcnq1predict.org.

Potential Use of CRISPR/Cas13 Machinery in Understanding Virus–Host Interaction

Prokaryotes have evolutionarily acquired an immune system to fend off invading mobile genetic elements, including viral phages and plasmids. Through recognizing specific sequences of the invading nucleic acid, prokaryotes mediate a subsequent degradation process collectively referred to as the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)–CRISPR-associated (Cas) (CRISPR–Cas) system. The CRISPR–Cas systems are divided into two main classes depending on the structure of the effector Cas proteins. Class I systems have effector modules consisting of multiple proteins, while class II systems have a single multidomain effector. Additionally, the CRISPR–Cas systems can also be categorized into types depending on the spacer acquisition components and their evolutionary features, namely, types I–VI. Among CRISPR/Cas systems, Cas9 is one of the most common multidomain nucleases that identify, degrade, and modulate DNA. Importantly, variants of Cas proteins have recently been found to target RNA, especially the single-effector Cas13 nucleases. The Cas13 has revolutionized our ability to study and perturb RNAs in endogenous microenvironments. The Cas13 effectors offer an excellent candidate for developing novel research tools in virological and biotechnological fields. Herein, in this review, we aim to provide a comprehensive summary of the recent advances of Cas13s for targeting viral RNA for either RNA-mediated degradation or CRISPR–Cas13-based diagnostics. Additionally, we aim to provide an overview of the proposed applications that could revolutionize our understanding of viral–host interactions using Cas13-mediated approaches.

Genome-wide investigation of the AP2/ERF gene family in ginger: evolution and expression profiling during development and abiotic stresses

Background AP2/ERF transcription factors (TFs) constitute one of the largest TF families in plants, which play crucial roles in plant metabolism, growth, and development as well as biotic and abiotic stresses responses. Although the AP2/ERF family has been thoroughly identified in many plant species and several AP2/ERF TFs have been functionally characterized, little is known about this family in ginger (Zingiber officinale Roscoe), an important affinal drug and diet vegetable. Recent completion of the ginger genome sequencing provides an opportunity to investigate the expression profiles of AP2/ERF genes in ginger on a genome-wide basis. Results A total of 163 AP2/ERF genes were obtained in the Z.officinale genome and renamed according to the chromosomal distribution of the ZoAP2/ERF genes. Phylogenetic analysis divided them into three subfamilies, of which 35 belonged to the AP2 subfamily, 120 to ERF, three to RAV, and five to Sololist, respectively, which is in accordance with the number of conserved domains and gene structure analysis. A total of 10 motifs were detected in ZoAP2/ERF genes, and some of the unique motifs were found to be important for the function of ZoAP2/ERF genes. The chromosomal localization, gene structure, and conserved protein motif analyses, as well as the characterization of gene duplication events provided deep insight into the evolutionary features of these ZoAP2/ERF genes. The expression profiles derived from the RNA-seq data and quantitative reserve transcription (qRT-PCR) analysis of ZoAP2/ERFs during development and responses to abiotic stresses were investigated in ginger. Conclusion A comprehensive analysis of the AP2/ERF gene expression patterns in various tissues by RNA-seq and qRT-PCR showed that they played an important role in the growth and development of ginger, and genes that might regulate rhizome and flower development were preliminary identified. In additionally, the ZoAP2/ERF family genes that responded to abiotic stresses were also identified. This study is the first time to identify the ZoAP2/ERF family, which contributes to research on evolutionary characteristics and better understanding the molecular basis for development and abiotic stress response, as well as further functional characterization of ZoAP2/ERF genes with an aim of ginger crop improvement.

Genome-Wide Analysis of the Fatty Acid Desaturase Gene Family Reveals the Key Role of PfFAD3 in α-Linolenic Acid Biosynthesis in Perilla Seeds

Perilla (Perilla frutescens), a traditional medicinal and oilseed crop in Asia, contains extremely high levels of polyunsaturated α-linolenic acid (ALA) (up to 60.9%) in its seeds. ALA biosynthesis is a multistep process catalyzed by fatty acid desaturases (FADs), but the FAD gene family in perilla has not been systematically characterized. Here, we identified 42 PfFADs in the perilla genome and classified them into five subfamilies. Subfamily members of PfFADs had similar exon/intron structures, conserved domain sequences, subcellular localizations, and cis-regulatory elements in their promoter regions. PfFADs also possessed various expression patterns. PfFAD3.1 was highly expressed in the middle stage of seed development, whereas PfFAD7/8.3 and PfFAD7/8.5 were highly expressed in leaf and later stages of seed development, respectively. Phylogenetic analysis revealed that the evolutionary features coincided with the functionalization of different subfamilies of PUFA desaturase. Heterologous overexpression of PfFAD3.1 in Arabidopsis thaliana seeds increased ALA content by 17.68%–37.03%. These findings provided insights into the characteristics and functions of PfFAD genes in perilla.

Evolutionary features of a prolific subtype of avian influenza A virus in European waterfowl

Avian influenza A virus (AIV) is ubiquitous in waterfowl, and detected annually at high prevalence in waterfowl during the Northern Hemipshere autumn. Some AIV subtypes are globally common in waterfowl, such as H3N8, H4N6, and H6N2, and are detected in the same populations at high frequency, annually. In order to investigate genetic features associated to the long-term maintenance of common subtypes in migratory ducks, we sequenced 248 H4 viruses isolated across 8 years (2002-2009) from Mallards (Anas platyrhynchos) sampled in southeast Sweden. Phylogenetic analyses showed that both H4 and N6 sequences fell into in three distinct lineages, structured by year of isolation. Specifically, across the eight years of the study, we observed lineage replacement, whereby a different HA lineage circulated in the population each year. Analysis of deduced amino acid sequences of the HA lineages illustrated key differences in regions of the globular head of hemagglutinin that overlap with established antigentic sites in homologous hemagglutinin H3, suggesting the possibility of antigenic differences among these HA lineages. Beyond HA, lineage replacement was common to all segments, such that novel genome constellations were detected across years. A dominant genome constellation would rapidly amplify in the duck population, followed by unlinking of gene segments as a result of reassortment within 2-3 weeks following introduction. These data help reveal the evolutionary dynamics exhibited by AIV on both annual and decadal scales in an important reservoir host.