From Fischer projections to quantum mechanics of tetrahedral molecules: new perspectives in chirality

The algebraic structure of central molecular chirality can be achieved starting from the geometrical representation of bonds of tetrahedral molecules, as complex numbers in polar form, and the empirical Fischer projections used in organic chemistry. A general orthogonal O(4) algebra is derived from which we obtain a chirality index related to the classification of a molecule as achiral, diastereoisomer or enantiomer. Consequently, the chiral features of tetrahedral chains can be predicted by means of a molecular Aufbau. Moreover, a consistent Schroedinger equation is developed, whose solutions are the bonds of tetrahedral molecules in complex number representation. Starting from this result, the O(4) algebra can be considered as a quantum chiral algebra. It is shown that the operators of such an algebra preserve the parity of the whole system.Comment: 33 pages, to appear in Adv. Quantum Che

Giant benzenoid hydrocarbons Superphenalene resonance energy

We calculated molecular resonance energy for "superphenalene", a recently reported giant benzenoid which can be viewed as obtained from three fused "superbenzenes" Chexa-peri-hexabenzocoronenes). Using the Method of Conjugated Circuits we derived quantitative characterization of Clar's qualitative description of the considered benzenoids as composed from disjoint "pi -sextets". The calculations show the degree of differentiation between neighboring rings which decreases as we move more towards the central part of the molecule

Giant benzenoid hydrocarbons Superphenalene resonance energy

We have calculated the molecular resonance energy for "superphenalene," a recently reported giant benzenoid that can be viewed as obtained from three fused "superbenzenes" (hexa-peri-hexabenzocoronenes). Using the method of conjugated circuits we derived quantitative characterization of Clar's qualitative description of the considered benzenoids as composed from disjoint "pi-sextets." The calculations show the degree of differentiation between neighboring rings, which decreases as we progressively move towards the center of the molecule

A Device-Based Process Signal Design of Electric Power Plants

Automation and computerized control of processes in electric power plants were intensively started at the end of seventies and at the beginning of eighties during the introduction of microprocessor–based computer systems. The first generation of the information processing equipment has in most cases already become disused. From that time, visibility of controlled process has been increased by installing new and modern devices which enable better informing about all relevant events. The increased quantity of information by which processes can be described implies that new and more efficient techniques for information modeling should be developed. In this paper a device-based approach to process information modeling is proposed. Such modeling approach is more efficient than function-based approach we used before. The efficiency lies in the fact that device-based approach is in the very essence an object-oriented modeling approach. Therefore, device-based information models can be easily mapped to object-oriented models. Both function-based and device-based modeling approaches are described in the paper and differences between two modeling paradigms are emphasized. In the last Chapter of the paper analogy between device-based and object-oriented models is described. This analogy represents basis for the model mapping

A multi-omics integrative approach unravels novel genes and pathways associated with senescence escape after targeted therapy in NRAS mutant melanoma

Therapy Induced Senescence (TIS) leads to sustained growth arrest of cancer cells. The associated cytostasis has been shown to be reversible and cells escaping senescence further enhance the aggressiveness of cancers. Chemicals specifically targeting senescent cells, so-called senolytics, constitute a promising avenue for improved cancer treatment in combination with targeted therapies. Understanding how cancer cells evade senescence is needed to optimise the clinical benefits of this therapeutic approach. Here we characterised the response of three different NRAS mutant melanoma cell lines to a combination of CDK4/6 and MEK inhibitors over 33 days. Transcriptomic data show that all cell lines trigger a senescence programme coupled with strong induction of interferons. Kinome profiling revealed the activation of Receptor Tyrosine Kinases (RTKs) and enriched downstream signaling of neurotrophin, ErbB and insulin pathways. Characterisation of the miRNA interactome associates miR-211-5p with resistant phenotypes. Finally, iCell-based integration of bulk and single-cell RNA-seq data identifies biological processes perturbed during senescence and predicts 90 new genes involved in its escape. Overall, our data associate insulin signaling with persistence of a senescent phenotype and suggest a new role for interferon gamma in senescence escape through the induction of EMT and the activation of ERK5 signaling.VG is supported by the Luxembourg National Research Fond (FNR) PRIDE DTU CanBIO [grant reference: 21/16763386]. TR is supported by the FNR PRIDE DTU CriTiCS [grant reference: 10907093]. Project-related work performed by VG, HH, CM, DP, MTN, MB, AG, FT and SK were also supported by the University of Luxembourg and the Fondation Cancer, Luxembourg (grant “SecMelPro”). KM and NP are supported by funding from the European Union’s EU Framework Programme for Research and Innovation Horizon 2020, Innovative Training Networks (MSCA-ITN-2019), funded under EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions, Grant Agreement No 860895. KM, NMD, GC and NP are supported by funding from the European Research Council (ERC) Consolidator Grant 770827. NP is also supported by funding from the Spanish State Research Agency AEI 10.13039/501100011033 grant number PID2019-105500GB-I00.Peer ReviewedArticle signat per 22 autors/es: Vincent Gureghian 1, Hailee Herbst 1, Ines Kozar 2, Katarina Mihajlovic 3, Noël Malod-Dognin 3, Gaia Ceddia 3, Cristian Angeli 1, Christiane Margue 1, Tijana Randic 1, Demetra Philippidou 1, Milène Tetsi Nomigni 1, Ahmed Hemedan 4, Leon-Charles Tranchevent 4, Joseph Longworth 5, Mark Bauer 1, Apurva Badkas 1, Anthoula Gaigneaux 1, Arnaud Muller 6, Marek Ostaszewski 4, Fabrice Tolle 1, Nataša Pržulj 3, 7, 8 and Stephanie Kreis 1 // 1 Department of Life Sciences and Medicine, University of Luxembourg, 6, Avenue du Swing, L-4367 Belvaux, Luxembourg; 2 Laboratoire National de Santé, Dudelange, Luxembourg; 3 Barcelona Supercomputing Center, 08034 Barcelona, Spain; 4 Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; 5 Experimental and Molecular Immunology, Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg; 6 LuxGen, TMOH and Bioinformatics platform, Data Integration and Analysis unit, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg; 7 Department of Computer Science, University College London, London WC1E 6BT, UK; 8 ICREA, Pg. Lluís Companys 23, 08010 Barcelona, SpainPostprint (published version

Higher order assortativity in complex networks

Assortativity was first introduced by Newman and has been extensively studied and applied to many real world networked systems since then. Assortativity is a graph metrics and describes the tendency of high degree nodes to be directly connected to high degree nodes and low degree nodes to low degree nodes. It can be interpreted as a first order measure of the connection between nodes, i.e. the first autocorrelation of the degree-degree vector. Even though assortativity has been used so extensively, to the author's knowledge, no attempt has been made to extend it theoretically. This is the scope of our paper. We will introduce higher order assortativity by extending the Newman index based on a suitable choice of the matrix driving the connections. Higher order assortativity will be defined for paths, shortest paths, random walks of a given time length, connecting any couple of nodes. The Newman assortativity is achieved for each of these measures when the matrix is the adjacency matrix, or, in other words, the correlation is of order 1. Our higher order assortativity indexes can be used for describing a variety of real networks, help discriminating networks having the same Newman index and may reveal new topological network features.Comment: 24 pages, 16 figure

Estimating the Octanol/Water Partition Coefficient for Aliphatic Organic Compounds Using Semi-Empirical Electrotopological Index

A new possibility for estimating the octanol/water coefficient (log P) was investigated using only one descriptor, the semi-empirical electrotopological index (ISET). The predictability of four octanol/water partition coefficient (log P) calculation models was compared using a set of 131 aliphatic organic compounds from five different classes. Log P values were calculated employing atomic-contribution methods, as in the Ghose/Crippen approach and its later refinement, AlogP; using fragmental methods through the ClogP method; and employing an approach considering the whole molecule using topological indices with the MlogP method. The efficiency and the applicability of the ISET in terms of calculating log P were demonstrated through good statistical quality (r > 0.99; s < 0.18), high internal stability and good predictive ability for an external group of compounds in the same order as the widely used models based on the fragmental method, ClogP, and the atomic contribution method, AlogP, which are among the most used methods of predicting log P

Neuronal circuitry for pain processing in the dorsal horn

Neurons in the spinal dorsal horn process sensory information, which is then transmitted to several brain regions, including those responsible for pain perception. The dorsal horn provides numerous potential targets for the development of novel analgesics and is thought to undergo changes that contribute to the exaggerated pain felt after nerve injury and inflammation. Despite its obvious importance, we still know little about the neuronal circuits that process sensory information, mainly because of the heterogeneity of the various neuronal components that make up these circuits. Recent studies have begun to shed light on the neuronal organization and circuitry of this complex region