LEADER 02678nam0 22003971i 450 001 SUN0022864 005 20061206120000.0 100 $a20040907d1995 |0itac50 ba 101 $aita$aENG 102 $aIT 105 $a|||| ||||| 200 1 $aTokyo Harbin Seoul$esistemi urbani dell'Est-Asia$ecooperazione innovazione ambiente mobilitą$fAlberto Notarangelo$gsaggio introduttivo di Corrado Beguinot$gcon scritti di Annalaura Casolaro e Francesca Paola Cilento 210 $aNapoli$cUniversitą degli studi, Dipartimento di pianificazione e scienza del territorio$d[1995] 215 $a191 p.$cill.$d25 cm. 606 $aCittą$xAsia orientale$xSec. 20.$2FI$3SUNC010781 620 $dNapoli$3SUNL000005 676 $a711.4095$v21 700 1$aNotarangelo$b, Alberto$3SUNV019055$031908 702 1$aCasolaro$b, Annalaura$3SUNV019056 702 1$aCilento$b, Francesca P.$3SUNV019057 712 $aUniversitą degli studi di Napoli Federico 2.$3SUNV000343$4650 790 1$aCilento, Francesca Paola$zCilento, Francesca P.$3SUNV066998 801 $aIT$bSOL$c20181109$gRICA 912 $aSUN0022864 950 $aBIBLIOTECA DEL DIPARTIMENTO DI ARCHITETTURA E DISEGNO INDUSTRIALE$d01 PREST IIEa39 $e01 28564 950 $aBIBLIOTECA DEL DIPARTIMENTO DI ARCHITETTURA E DISEGNO INDUSTRIALE$d01 PREST IIEa40 $e01 28565 950 $aBIBLIOTECA DEL DIPARTIMENTO DI ARCHITETTURA E DISEGNO INDUSTRIALE$d01 PREST IIEa41 $e01 28566 950 $aBIBLIOTECA DEL DIPARTIMENTO DI ARCHITETTURA E DISEGNO INDUSTRIALE$d01 PREST IIEa42 $e01 28567 950 $aBIBLIOTECA DEL DIPARTIMENTO DI ARCHITETTURA E DISEGNO INDUSTRIALE$d01 CONS BPETR(91) $e01 48127 995 $aBIBLIOTECA DEL DIPARTIMENTO DI ARCHITETTURA E DISEGNO INDUSTRIALE$bIT-CE0107$h28564$kPREST IIEa39$op$qa 995 $aBIBLIOTECA DEL DIPARTIMENTO DI ARCHITETTURA E DISEGNO INDUSTRIALE$bIT-CE0107$h28565$kPREST IIEa40$op$qa 995 $aBIBLIOTECA DEL DIPARTIMENTO DI ARCHITETTURA E DISEGNO INDUSTRIALE$bIT-CE0107$h28566$kPREST IIEa41$op$qa 995 $aBIBLIOTECA DEL DIPARTIMENTO DI ARCHITETTURA E DISEGNO INDUSTRIALE$bIT-CE0107$h28567$kPREST IIEa42$op$qa 995 $aBIBLIOTECA DEL DIPARTIMENTO DI ARCHITETTURA E DISEGNO INDUSTRIALE$bIT-CE0107$h48127$kCONS BPETR(91)$op$qa 996 $aTokyo Harbin Seoul$91432435 997 $aUNICAMPANIA LEADER 03127nam 2200445z- 450 001 9910220049403321 005 20210211 035 $a(CKB)3800000000216283 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/56244 035 $a(oapen)doab56244 035 $a(EXLCZ)993800000000216283 100 $a20202102d2016 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aThe Physiology and Pharmacology of Leucine-rich Repeat GPCRs 210 $cFrontiers Media SA$d2016 215 $a1 online resource (115 p.) 225 1 $aFrontiers Research Topics 311 08$a2-88919-958-4 330 $aG protein-coupled receptors (GPCRs) represent a large and physiologically important class of cell surface receptors. There are approximately 750 known GPCRs present in the human genome that can be subdivided into general classes based upon sequence homology within their transmembrane domains. Therapeutically, GPCRs represent a fertile source for the development of therapies as they are a significant percentage of our current pharmacopeia. Among the three subclasses of GPCRs, the Class A (rhodopsin-like) receptors are by far the most prevalent and extensively studied. However, within the Class A receptors, sub-families of receptors can be distinguished based upon common sequence motifs within the transmembrane domains as well as extracellular and intracellular domains. One such family of Class A receptors is characterized by multiple leucine- rich repeats within their amino- terminal domains (the Leucine-rich Repeat family (LRR)). This family of GPCRs are best represented by the glycoprotein hormone receptors (LHR, FSHR and TSHR) which have been studied extensively but also includes receptors for the peptide hormone relaxin (RXFP1 and RXFP2 (RXFP2 also binds insulin-like peptide 3)) and three other receptors (LGR4, LGR5 and LGR6). LGR4-6 were, until recently, considered orphan receptors. However, emerging data have revealed that these proteins are the receptors for a family of growth factors called R-spondins. Over the last 20 years much has been learned about LRR receptors, including the development of synthetic agonists and antagonists, new insights into signaling (including signaling bias) and the physiological role these receptors play in regulating the function of many tissues. This topic will focus on what is known concerning the regulation of these receptors, their signaling pathways, functional consequences of activation and pharmacology. 606 $aMedicine and Nursing$2bicssc 610 $aFSH 610 $aGPCR 610 $aLeucine- rich repeat 610 $aLH 610 $aLRR 610 $aPharmacology 610 $aR-spondin 610 $aRelaxin 610 $aTSH 615 7$aMedicine and Nursing 700 $aBrian J. Arey$4auth$01329502 702 $aJames A. Dias$4auth 906 $aBOOK 912 $a9910220049403321 996 $aThe Physiology and Pharmacology of Leucine-rich Repeat GPCRs$93039523 997 $aUNINA LEADER 04146nam 22007095 450 001 9910874693603321 005 20251225195043.0 010 $a9783031637353 024 7 $a10.1007/978-3-031-63735-3 035 $a(CKB)33388411800041 035 $a(MiAaPQ)EBC31552554 035 $a(Au-PeEL)EBL31552554 035 $a(DE-He213)978-3-031-63735-3 035 $a(EXLCZ)9933388411800041 100 $a20240723d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligence and Image Analysis $e18th International Symposium on Artificial Intelligence and Mathematics, ISAIM 2024, and 22nd International Workshop on Combinatorial Image Analysis, IWCIA 2024, Fort Lauderdale, FL, USA, January 8?10, 2024, Revised Selected Papers /$fedited by Reneta P. Barneva, Valentin E. Brimkov, Claudio Gentile, Aldo Pacchiano 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (269 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v14494 311 08$a9783031637346 327 $a -- A Model for Optimizing Recalculation Schedules to Minimize Regret. -- A Theory of Learning with Competing Objectives and User Feedback. -- Trick Costs for $\alpha\mu$ and New Relatives. -- A Differential Approach for Several NP-hard Optimization Problems. -- On the Computational Complexities of Finding Selected Refutations of Linear Programs. -- Extending the Tractability of the Clique Problem via Graph Classes Generalizing Treewidth. -- Principled Approaches for Learning to Defer with Multiple Experts. -- On Sample Reuse Methods for Answering $k$-wise Statistical Queries. -- Neural Diffusion Graph Convolutional Network for Predicting Heat Transfer in Selective Laser Melting. -- New Proportion Measures of Discrimination Based on Natural Direct and Indirect Effects. -- Addressing Discretization Artifacts in Tomography by Accessing and Balancing Pixel Coverage of Projections. -- Finding the Straight Skeleton for 3D Orthogonal Polyhedrons: A Combinatorial Approach. -- Towards a Unifying View on Monotone Constructive Definitions. -- Partial Boolean Functions for QBF Semantics. 330 $aThis book constitutes the refereed joint proceedings of the 18th International Symposium on Artificial Intelligence and Mathematics, ISAIM 2024, and the 22nd International Workshop on Combinatorial Image Analysis, IWCIA 2024, held in Fort Lauderdale, FL, USA, during January 8?10, 2024. The 14 full papers presented were carefully reviewed and selected from 25 submissions. The papers cover topics from AI, theoretical computer science, mathematics, medicine, robotics, defense, and security. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v14494 606 $aComputer vision 606 $aImage processing 606 $aComputer science$xMathematics 606 $aDiscrete mathematics 606 $aArtificial intelligence 606 $aComputer networks 606 $aComputer Vision 606 $aImage Processing 606 $aDiscrete Mathematics in Computer Science 606 $aArtificial Intelligence 606 $aComputer Communication Networks 615 0$aComputer vision. 615 0$aImage processing. 615 0$aComputer science$xMathematics. 615 0$aDiscrete mathematics. 615 0$aArtificial intelligence. 615 0$aComputer networks. 615 14$aComputer Vision. 615 24$aImage Processing. 615 24$aDiscrete Mathematics in Computer Science. 615 24$aArtificial Intelligence. 615 24$aComputer Communication Networks. 676 $a006.37 700 $aBarneva$b Reneta P$01749780 701 $aBrimkov$b Valentin E$01749781 701 $aGentile$b Claudio$0616158 701 $aPacchiano$b Aldo$01749782 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910874693603321 996 $aArtificial Intelligence and Image Analysis$94184141 997 $aUNINA