Chain Clusters Research Articles

Traçage rétrospectif et gestion des clusters pendant l’épidémie de Covid-19 - Applications dans le canton de Vaud

Persons with SARS-CoV2 can be contagious with few or no symptoms. They can infect others in private, during education or work without knowing it. Few so-called super-propagators can thus initiate clusters of infections and chains of transmission. Isolation of new cases and quarantine of their contacts (forward contact tracing) often does not uncover such situations. Adding detailed backward investigations of events and places with elevated risk of transmission can increase the identification of potentially infected persons. These can then be quarantined, and chains of transmission be interrupted. We describe the principles and challenges of cluster investigation, epidemiological methods and IT tools that we deve loped at the Centre for contact tracing, Vaud. Knowledge of this method is useful in general clinical practice during a pandemic.

Bridging coordination of acenaphthylene to a Pd3 chain or a Pd4 sheet cluster

The coordination behaviour of multinuclear clusters to fused arene ligands is of continuous interest due to its relevance to metal catalysts supported by graphitic carbon materials. Herein, we report the bridging coordination behaviour of acenaphthylene to a Pd3 or a Pd4 cluster. A bis-acenaphthylene Pd3 chain cluster and an acenaphthylene-COT Pd4 sheet cluster were isolated, and the μ3-π-coordination mode or the μ4-oxidative π-addition mode of the acenaphthylene ligand in each cluster was elucidated by X-ray structure analysis.

Enhancing Persistent Luminescence of Cellulose by Dehydration for Label-Free Time-Resolved Imaging

Organic persistent luminescence is usually emitted from synthesized materials containing π units (aromatic rings, double bonds, etc.). It is challenging but desirable to develop organic materials from renewable resources with tunable persistent luminescence to reduce environmental impact. Herein, we proposed an effective method to enhance the luminescence of cellulose, the most abundant natural renewable material free of π units. It was found that removing the crystal water in cellulose would increase the compactness of molecular packing and stabilize the hydroxyl clusters of polysaccharide chains, consequently leading to significant enhancement of phosphorescence with lifetime up to subseconds. This dehydration induced luminescence enhancement was found in not only purified cellulose but also cellulose-contained substances such as papers, cottons, and many other plant tissues. This indicated easier access to cellulose-based luminescence materials without chemical purification. In addition, label-free time-resolved luminescence imaging of plant tissues was achieved on a smartphone-based apparatus, since endogenous cellulose is distributed extensively in plants. Compared with synthetical luminophores, cellulose is a renewable and biodegradable source abundant in nature, not only readily available but also environmentally friendly. We believe this method may be used to develop other sustainable organic luminescence materials with a lack of π units for various optical applications.

The Impact of an Anchoring Layer on the Formation of Tethered Bilayer Lipid Membranes on Silver Substrates.

Tethered bilayer lipid membranes (tBLMs) have been known as stable and versatile experimental platforms for protein–membrane interaction studies. In this work, the assembly of functional tBLMs on silver substrates and the effect of the molecular chain-length of backfiller molecules on their properties were investigated. The following backfillers 3-mercapto-1-propanol (3M1P), 4-mercapto-1-butanol (4M1B), 6-mercapto-1-hexanol (6M1H), and 9-mercapto-1-nonanol (9M1N) mixed with the molecular anchor WC14 (20-tetradecyloxy-3,6,9,12,15,18,22 heptaoxahexatricontane-1-thiol) were used to form self-assembled monolayers (SAMs) on silver, which influenced a fusion of multilamellar vesicles and the formation of tBLMs. Spectroscopic analysis by SERS and RAIRS has shown that by using different-length backfiller molecules, it is possible to control WC14 anchor molecules orientation on the surface. An introduction of increasingly longer surface backfillers in the mixed SAM may be related to the increasing SAMs molecular order and more vertical orientation of WC14 at both the hydrophilic ethylenoxide segment and the hydrophobic lipid bilayer anchoring alkane chains. Since no clustering of WC14 alkane chains, which is deleterious for tBLM integrity, was observed on dry samples, the suitability of mixed-component SAMs for subsequent tBLM formation was further interrogated by electrochemical impedance spectroscopy (EIS). EIS showed the arrangement of well-insulating tBLMs if 3M1P was used as a backfiller. An increase in the length of the backfiller led to increased defectiveness of tBLMs. Despite variable defectiveness, all tBLMs responded to the pore-forming cholesterol-dependent cytolysin, vaginolysin in a manner consistent with the functional reconstitution of the toxin into phospholipid bilayer. This experiment demonstrates the biological relevance of tBLMs assembled on silver surfaces and indicates their utility as biosensing elements for the detection of pore-forming toxins in liquid samples.

The chain length of anisotropic paramagnetic particles in a rotating field

In this article the maximal length of a chain of paramagnetic particles with magnetic anisotropy in a rotating magnetic field is studied. The theory of paramagnetic particle chains usually assumes that the particles are magnetically isotropic and do not rotate in a rotating field. In experiments it is seen that spherical paramagnetic particles rotate, which can be explained by small magnetic anisotropy. In this article, the maximal chain length is calculated for paramagnetic particles with magnetic anisotropy in a rotating magnetic field. Results show that the maximal chain length as a function of field frequency has the same trend for isotropic magnetic particles and particles with magnetic anisotropy if the field frequency is much higher or much lower than the critical frequency of an individual particle. Initially randomly distributed particles will form chains that will collide and exchange with particles till they obtain a typical chain length. The typical chain length of a small cluster is shorter than the maximal chain length of an isolated chain for the same field frequency. The distribution of chain lengths in a small cluster of chains is narrower for particles with higher magnetic anisotropy. Due to the narrower distribution of chain lengths, particles with magnetic anisotropy can suit better for mass-production. This article will show how magnetic anisotropy parameters of paramagnetic particles influence chain length of chains which form in a rotating magnetic field.

Revealing the High-Modulus Mechanism of Polyimide Films Prepared with 3,4'-ODA.

To prepare PIs (polyimides) with desirable thermal and mechanical properties is highly demanded due to their widespread applications in flexible optoelectronic devices and printed circuit boards. Here, the PI films of BPDA/4,4′-ODA, BPDA/3,4′-ODA, PMDA/4,4′-ODA, PMDA/3,4′-ODA systems were prepared, and it was found that the PIs with 3,4′-ODA always exhibit a high modulus compared with the PIs with 4,4′-ODA. To disclose the mechanism of high-modulus PI films with 3,4′-ODA, amorphous PI models and uniaxial drawing PI models were established and calculated based on MD simulation. The PI structural deformations at different length scales, i.e., molecular chain cluster scale and repeat unit scale, under the same stress were detailed and analyzed, including the variation of chain conformation, bond length, bond angle, internal rotation energy, and torsion angle. The results indicate that PIs with 3,4-ODA have higher internal rotation energy and smaller deformation with the same stress, consistent with the high modulus.

Landscape of the Dark Transcriptome Revealed Through Re-mining Massive RNA-Seq Data.

The “dark transcriptome” can be considered the multitude of sequences that are transcribed but not annotated as genes. We evaluated expression of 6,692 annotated genes and 29,354 unannotated open reading frames (ORFs) in the Saccharomyces cerevisiae genome across diverse environmental, genetic and developmental conditions (3,457 RNA-Seq samples). Over 30% of the highly transcribed ORFs have translation evidence. Phylostratigraphic analysis infers most of these transcribed ORFs would encode species-specific proteins (“orphan-ORFs”); hundreds have mean expression comparable to annotated genes. These data reveal unannotated ORFs most likely to be protein-coding genes. We partitioned a co-expression matrix by Markov Chain Clustering; the resultant clusters contain 2,468 orphan-ORFs. We provide the aggregated RNA-Seq yeast data with extensive metadata as a project in MetaOmGraph (MOG), a tool designed for interactive analysis and visualization. This approach enables reuse of public RNA-Seq data for exploratory discovery, providing a rich context for experimentalists to make novel, experimentally testable hypotheses about candidate genes.

Consumer behavior clustering of food retail chains by machine learning algorithms

Analysis of the behavior of an economic agent is one of the central themes of microeconomics. Right now, with the comprehensive increase in the amount of data and the expansion of the computing capabilities of personal computers, there is a need to implement methods of behavioral economics in the study of human behavior. In the course of this study, a survey was created aimed at identification of patterns of behavior of the modern consumer according to his selection criteria stores and reactions to questions based on Behavioral Economics theorems. Clustering the obtained results were performed using machine learning algorithms, after which the Random Forest classification algorithm was trained. According to the results of Silhouette analysis, K-means clusters were selected as the main ones for further modeling. T-SNE algorithms, hierarchical and spectral analysis were used for additional visual representation. This study offers a tool for classifying customer preferences and analyzing current industry trends. A tool has been created to classify consumers of food retail chains in order to improve their buyer's journey and better understand their needs. The created tool for clustering and classification by machine learning methods can be used in business processes. To improve the result, it is necessary to choose a more representative sample, because used in this study consists of an average rationally thinking and knowledgeable individuals, which cannot be said of the average consumer not only among the older generation but also among the younger. Therefore, the next directions in the study may be to identify new ones behavioral trends in other industries; deepening understanding of food retail; use of geodata to improve analysis, etc. Potentially attractive the direction may be to add an assessment of the impact of network advertising on behavior consumers through semantics analysis and image recognition..

The association between supply chain structure and transparency: A large‐scale empirical study

AbstractAn emerging body of work acknowledges the challenges focal firms face in gathering material information about their extended supply chains and begins to point to the role of supply chain structure in influencing supply chain transparency. Still, large‐scale empirical evidence on this complex association remains elusive, especially at the supply chain level of analysis. We begin to bridge this empirical gap by examining whether supply chain structure systematically associates to supply chain transparency in the context of the collective public environmental, social, and governance (ESG) disclosures made by a focal firm's customers, suppliers, and subsuppliers. To shed light on this underexplored empirical phenomenon, we gather Bloomberg SPLC data and Bloomberg ESG data about 4803 firms and 20,504 contractual ties organized in 187 extended supply chains. We find that supply chain density positively associates with supply chain transparency, whereas supply chain clustering holds a negative association. We also find that supply chain geographical heterogeneity positively associates with supply chain transparency. Our results significantly expand the literature on supply chain transparency and are relevant to supply chain professionals because they emphasize the central role of supply chain structure in enabling or constraining supply chain transparency.

A facile method for coal to graphene oxide and its application to a biosensor

The classic methods of synthesis of graphene oxide derived from graphite require harsh oxidation with excessive chemicals (H2SO4, H3PO4, KMnO4, etc.) and multiple processes. In this paper, we present a facile one-pot process using HNO3 to obtain graphene oxide from coal (Coal-GO). Coal has a unique molecular structure comprising of small regions or clusters of graphene-like and aliphatic side chains, for which our process is successfully able to exclude aliphatic compounds while preserving graphene domains during oxidization and subsequent exfoliation. The Coal-GO was converted to reduced graphene oxide (Coal-rGO) by conventional method to produce a few-layered graphene nanosheets in lateral size of 300–700 nm. The surface characteristics of the Coal-GO indicate the persistence of N from the raw coal as well as that introduced in the process. Notably, the Coal-GO shows a considerable amount of COOH compared to the other oxygen groups. Our data indicates that the process is effective in oxidative scissoring of the edges of coal, with minimal effect on swelling of coal towards the c-direction. Lastly, we demonstrate that compared to Graphite-GO, the Coal-GO has superior interaction with single stranded DNA aptamer, which could result in higher sensitivity chemiluminescence resonance energy transfer-based biosensors.

A generalizable strategy toward highly tough and heat-resistant stereocomplex-type polylactide/elastomer blends with substantially enhanced melt processability

Sustainable stereocomplex-type polylactide (SC-PLA) has been recognized as a potential substitute for some traditional engineering plastics, however its widespread application still faces several hurdles primarily related to poor melt processability (i.e., the unfavorable melt memory effect in SC crystallization as well as the low melt strength) and insufficient fracture toughness. To overcome these hurdles, an equimolar poly(l-lactide)/poly(d-lactide) (PLLA/PDLA) blend toughened with poly(ethylene-co-vinyl acetate) (EVA) has been chosen as a model system and a facile strategy has been devised by incorporating trace amounts (i.e., 0.5 wt%) of epoxy-functionalized oligo(styrene-acrylic) (ESA) into the PLLA/PDLA/elastomer blends through direct melt-blending at 200 °C. Such a one-pot blending not only facilitates the stereocomplexation between PLLA and PDLA chains but also permits the highly efficient reaction between terminal hydroxyl groups of some enantiomeric PLAs and epoxy groups of ESA before their stereocomplexation. This results in the in situ generation of large amounts of long-chain-branched PLA-graft-ESA copolymer in the SC-PLA matrix. Very impressively, the generation of this PLA-graft-ESA copolymer gives rise to a substantial improvement in the melt memory effect of the SC-PLA matrix. This copolymer behaves as a compatibilizer to stabilize regular PLLA/PDLA chain clusters in blend melts and hence to stimulate the exclusive formation of SC crystallites in melt-processed blend products. In addition, long PLA branches endow the matrix with a considerably enhanced melt viscosity owing to the increased interchain entanglement density. Consequently, highly stereocomplexed SC-PLA/EVA products with exceptional impact toughness and heat resistance as well as robust mechanical strength have been prepared by injection molding. More notably, this strategy can be generalized to various SC-PLA-based blends, irrespective of whether the elastomers have reactive groups. Overall, these exciting findings illustrate a promising avenue toward the design and applications of high-performance SC-PLA-based materials with excellent melt-processability via the generation of unique graft copolymers having long PLLA and PDLA branches.

DEFINING THE NOTIONS OF MANAGEMENT OF SUPPLY CHAINS, VALUE CHAINS AND CLUSTERS IN AGRICULTURE

Supply chain management as a new business philosophy in today’s competitive conditions is a source of numerous advantages for those enterprises that apply it. Due to its dynamic structure, it is a much wider term than that of logistics management, because it encompasses the process of conceiving, developing, optimizing and managing internal and external components of acquisition, transformation of material and distribution of finished products or services in accordance with the business strategic goals. The aim of the supply chain management is the creation of as great a value as possible for all value chain participants, especially for the final consumer, as he is at the end of the system of value creation and he validates the quality of supply chain via his purchase. When all enterprises –participants in the supply chain – do their business separately and act on their own separate business strategies, the sum of their expenses surpasses the expenses generated by integrated business of these enterprises within the supply chain. It is precisely because of this fact that, when an enterprise creates a unique system of goods and information flow with other members of the chain, it in fact enhances the efficiency of managing the entire chain. In that way, the value of the whole system increases for the consumer and competitive advantage of the chain is created. Since the clusters occur by connecting enterprises or chains of new value creation, the rest of this paper explains the meeting points between cluster concept and supply chain concept respectively, with special emphasis on agricultural clusters. The basic idea was that agricultural clusters are a geographical concentration of mutually connected SMEs, specialized suppliers and service providers, companies in related businesses, scientific and educational institutions, and government bodies and agencies in the sectors of agriculture and rural development. Therefore, the network of interdependent enterprises (individual agricultural farmsteads), within agricultural clusters and related institutions, confirms that within every cluster there are numerous supply chains, that is, that the supply chain management is an integral part and an indispensable factor of a cluster. At the same time, there is a complementarity and symbiosis between the concept of supply chain management and cluster concept, that is, their combination can effectively advance the competitive advantage both of the enterprises (individual agricultural farmsteads) and consequently regional and national economic competitiveness. The geographical proximity of cluster participants enables a more efficient access to specialized resources, information, human resources, institutions, and trainings; facilitates the coordination of activities within enterprises (individual agricultural farmsteads) as well as among cluster members; creates larger possibilities for innovation; stimulates permanent comparison of performances and of creating more successful business models, so-called best practices; and contributes to the commercialization of products and services and entering the new markets, as well as creating of new enterprises (individual agricultural farmsteads). More specifically, doing business in a cluster environment stimulates the competitiveness of enterprises (individual agricultural farmsteads) and affects the promotion of supply chain management within enterprises (individual agricultural farmsteads).

Simulation of the influence of spatial obstacles on evacuation pedestrian flow in walking facilities

In order to research the influence mechanism of spatial obstacles on evacuation pedestrian flow, simulations of pedestrian evacuation are carried out by using the improved dynamic parameter model based on cellular automata. A retardation coefficient is introduced to describe the effect of obstacles slowing down pedestrian movement. A special technique is adopted to calculate the shortest estimated distance (SED) from cell site to exit considering obstacle layout and retardation coefficient. The repulsion and isolation effect of obstacles on pedestrian flow is manifested by the clusters of evacuation path chains. The movement probability is considered to narrow the gap between the normal speed and simulated evacuation speed caused by spatial discretization. The effectiveness of movement probability is verified by theoretical analysis and simulation results. It is found that in evacuation from a walkway, the influence of retardation coefficient on evacuation time will be gradually weakened and stabilized with walkway width rising. The influence of obstacle layout on the selection of evacuation path will be observed in the classroom. It also shows in the evacuation through an exit with a prepositive obstacle that the evacuation time is determined by the narrowest one in the series-connected bottlenecks. Moreover, the phenomena such as “pedestrians keeping a certain spatial distance from the boundaries of walkway”, “pedestrians preferring to choose a wider movement aisle in classroom” and “evacuation time being dominated by the narrowest one of series-connected bottlenecks” can also be observed during pedestrian evacuation in the simulation.

Developing a Sustainable and Circular Bio-Based Economy in EU: By Partnering Across Sectors, Upscaling and Using New Knowledge Faster, and For the Benefit of Climate, Environment & Biodiversity, and People & Business.

This paper gives an overview of development of the EU-bioeconomy, 2014–2020. The Vision of the new Circular Bio-based Economy, CBE is presented: Unlocking the full potential of all types of sustainably sourced biomass, crop residues, industrial side-streams, and wastes by transforming it into value-added products. The resulting product portfolio consists of a wide spectrum of value-added products, addressing societal and consumer needs. Food and feed, bio-based chemicals, materials, health-promoting products; and bio-based fuels. The pillars of CBE are described, including biotechnology, microbial production, enzyme technology, green chemistry, integrated physical/chemical processing, policies, conducive framework conditions and public private partnerships. Drivers of CBE are analyzed: Biomass supply, biorefineries, value chain clusters, rural development, farmers, foresters and mariners; urgent need for climate change mitigation and adaptation, and stopping biodiversity loss. Improved framework conditions can be drivers but also obstacles if not updated to the era of circularity. Key figures, across the entire BBI-JU project portfolio (2014–2020) are provided, including expansion into biomass feedstocks, terrestrial and aquatic, and an impressive broadening of bio-based product portfolio, including higher-value, health-promoting products for man, animal, plants and soil. Parallel to this, diversification of industrial segments and types of funding instruments developed, reflecting industrial needs and academic research involvement. Impact assessment is highlighted. A number of specific recommendations are given; e.g., including international win/win CBE-collaborations, as e.g., expanding African EU collaboration into CBE. In contrast to fossil resources biological resources are found worldwide. In its outset, circular bio-based economy, can be implemented all over, in a just manner, not the least stimulating rural development.

The Role of SMEs in Strengthening the UK-USA Partnership

UK-U.S. Partnership has a historical legacy in the political, cultural, and economic matters concerning both countries mutually. Trade has played a significant role in boosting economic relationships between both countries. This study aims to study SMEs’ role (Small and Medium Enterprises) in the post-COVID trade policy with an emphasis on technological transformation and economic recovery. Data shows that SMEs have risen to prominence in the last decade in both countries; SMEs consists of more than 95% of businesses and are employing close to 50% or more in both countries. SME traders from the U.K. mutually identify the U.S. as a significant destination for imports and exports in the next three years. COVID-19 has disrupted businesses worldwide, forcing businesses to rethink their business strategies, especially the SMEs. We aim to look at how global pandemic, trade, business policy blend together under the context of changing technology and supply chains around the world. We suggest the need for rigorous and integrated approach to trade policy going forward which will play a major role in the business ecosystems for the two countries. This study points to the research noting the importance of SME entrepreneurial employers’ presence in the last economic recovery. The key is to achieve a cluster of SME supply chains collaborating and inter-linked with inherent entrepreneurial leadership and innovation within specific markets. In the present scenario, it is not the size but the quality of business relationships that can accelerate core competencies and tie companies to each other across the supply chain. SMEs’ flexibility is a vital tool to gain efficiencies, and bilateral free trade agreements can prove to be a useful tool to gain greater flexibility due to better trust and trade connectedness, as observed in the literature.

An Enriched RPCO-BCNN Mechanisms for Attack Detection and Classification in SCADA Systems

Providing security to the Supervisory Control and Data Acquisition (SCADA) systems is one of the demanding and crucial tasks in recent days, due to the different types of attacks on the network. For this purpose, there are different types of attack detection and classification methodologies have been developed in the conventional works. But it limits with the issues like high complexity in design, misclassification results, increased error rate, and reduced detection efficiency. In order to solve these issues, this paper aims to develop an advanced machine learning models for improving the SCADA security. This work comprises the stages of preprocessing, clustering, feature selection, and classification. At first, the Markov Chain Clustering (MCC) model is implemented to cluster the network data by normalizing the feature values. Then, the Rapid Probabilistic Correlated Optimization (RPCO) mechanism is employed to select the optimal features by computing the matching score and likelihood of particles. Finally, the Block Correlated Neural Network (BCNN) technique is employed to classify the predicted label, where the relevancy score is computed by using the kernel function with the feature points. During experimentation, there are different performance indicators have been used to validate the results of proposed attack detection mechanisms. Also, the obtained results are compared with the RPCO-BCNN mechanism for proving the superiority of the proposed attack detection system.

Unique and generic structural features of cholinium amino acid-based biocompatible ionic liquids.

Cholinium amino acid-based (Ch-AA) biocompatible ionic liquids (bio-ILs) are synthesized from renewable components and are efficiently used for biomass processing. However, their microscopic structural features that lead to their application as biomass solvents remain undetermined. Herein, we use atomistic simulations to investigate the structures of six different Ch-AA bio-ILs up to the nanometer length scale and demonstrate that, depending on the anion side chain structure, the respective IL exhibits structural ordering at different length scales. All the six Ch-AA bio-ILs investigated here show a generic feature of having a strong hydrogen bonding network between the hydroxyl group of the cholinium cation and the carboxyl group of the amino acid anions. We illustrate that each of these bio-ILs also displays a unique feature. Distinctive intermediate range structural ordering leads to heterogeneity in methioninate- and phenylalaninate-based ILs caused by the anion side chain segregation. Intermediate range ordering is not observed in glutaminate- and glutamate-based ILs because significant anion side chain and backbone interactions hinder the formation of side chain clusters. Interestingly, for the cysteinate-based IL, the side chains do not interact with the backbones and the intermediate range ordering is not observed because of a shorter anionic side chain.

Qualitative meta-analysis of the socioeconomic impacts of offshore wind farms

Climate change and an increased interest in renewable energy have resulted in a burgeoning wind energy sector. However, in the recent past, wind farms have faced resistance in acquiring permits due to concerns about their long-term effects on the local community. To understand the extent of these externalities, this study qualitatively meta-analyses four socio-economic impacts of interest, namely: house prices, tourism, catalytic effects of supply chain clustering, and social change. Geographically, the analysed reports include Europe, Canada and the US, and deductions are made for the EU. In order to bridge the gap of unavailability of primary data on the wind sector, relevant conclusions are drawn from other comparable sectors. Based on a rigorous review of primary qualitative research, this study concludes that offshore wind farms should be located more than 40 km away from the coast to eliminate risks of housing price devaluation and tourist activity reduction, which would directly affect the economic value of the region. In addition, the study found limited evidence to acknowledge the employment benefits in the local economy and social change in the community due to offshore wind farms. Monitoring mechanisms should be set up to prove or disprove the creation of local employment, crime and substance abuse. Furthermore, the study finds that adequate planning and management can ensure better socioeconomic outcomes in the community. Further research is recommended for the specific impact of overhead transmission lines and substations on property values and tourism.

Crystalline Peroxosolvates: Nature of the Coformer, Hydrogen-Bonded Networks and Clusters, Intermolecular Interactions.

Despite the technological importance of urea perhydrate (percarbamide) and sodium percarbonate, and the growing technological attention to solid forms of peroxide, fewer than 45 peroxosolvates were known by 2000. However, recent advances in X-ray diffractometers more than tripled the number of structurally characterized peroxosolvates over the last 20 years, and even more so, allowed energetic interpretation and gleaning deeper insight into peroxosolvate stability. To date, 134 crystalline peroxosolvates have been structurally resolved providing sufficient insight to justify a first review article on the subject. In the first chapter of the review, a comprehensive analysis of the structural databases is carried out revealing the nature of the co-former in crystalline peroxosolvates. In the majority of cases, the coformers can be classified into three groups: (1) salts of inorganic and carboxylic acids; (2) amino acids, peptides, and related zwitterions; and (3) molecular compounds with a lone electron pair on nitrogen and/or oxygen atoms. The second chapter of the review is devoted to H-bonding in peroxosolvates. The database search and energy statistics revealed the importance of intermolecular hydrogen bonds (H-bonds) which play a structure-directing role in the considered crystals. H2O2 always forms two H-bonds as a proton donor, the energy of which is higher than the energy of analogous H-bonds existing in isostructural crystalline hydrates. This phenomenon is due to the higher acidity of H2O2 compared to water and the conformational mobility of H2O2. The dihedral angle H-O-O-H varies from 20 to 180° in crystalline peroxosolvates. As a result, infinite H-bonded 1D chain clusters are formed, consisting of H2O2 molecules, H2O2 and water molecules, and H2O2 and halogen anions. H2O2 can form up to four H-bonds as a proton acceptor. The third chapter of the review is devoted to energetic computations and in particular density functional theory with periodic boundary conditions. The approaches are considered in detail, allowing one to obtain the H-bond energies in crystals. DFT computations provide deeper insight into the stability of peroxosolvates and explain why percarbamide and sodium percarbonate are stable to H2O2/H2O isomorphic transformations. The review ends with a description of the main modern trends in the synthesis of crystalline peroxosolvates, in particular, the production of peroxosolvates of high-energy compounds and mixed pharmaceutical forms with antiseptic and analgesic effects.

Muscle progenitor specification and myogenic differentiation are associated with changes in chromatin topology

Using Hi-C, promoter-capture Hi-C (pCHi-C), and other genome-wide approaches in skeletal muscle progenitors that inducibly express a master transcription factor, Pax7, we systematically characterize at high-resolution the spatio-temporal re-organization of compartments and promoter-anchored interactions as a consequence of myogenic commitment and differentiation. We identify key promoter-enhancer interaction motifs, namely, cliques and networks, and interactions that are dependent on Pax7 binding. Remarkably, Pax7 binds to a majority of super-enhancers, and together with a cadre of interacting transcription factors, assembles feed-forward regulatory loops. During differentiation, epigenetic memory and persistent looping are maintained at a subset of Pax7 enhancers in the absence of Pax7. We also identify and functionally validate a previously uncharacterized Pax7-bound enhancer hub that regulates the essential myosin heavy chain cluster during skeletal muscle cell differentiation. Our studies lay the groundwork for understanding the role of Pax7 in orchestrating changes in the three-dimensional chromatin conformation in muscle progenitors.