University of Münster
UniversityMünster, North Rhine-Westphalia, Germany
Research output, citation impact, and the most-cited recent papers from University of Münster (Germany). Aggregated across the NobleBlocks index of 300M+ scholarly works.
Top-cited papers from University of Münster
The method of dispersion correction as an add-on to standard Kohn-Sham density functional theory (DFT-D) has been refined regarding higher accuracy, broader range of applicability, and less empiricism. The main new ingredients are atom-pairwise specific dispersion coefficients and cutoff radii that are both computed from first principles. The coefficients for new eighth-order dispersion terms are computed using established recursion relations. System (geometry) dependent information is used for the first time in a DFT-D type approach by employing the new concept of fractional coordination numbers (CN). They are used to interpolate between dispersion coefficients of atoms in different chemical environments. The method only requires adjustment of two global parameters for each density functional, is asymptotically exact for a gas of weakly interacting neutral atoms, and easily allows the computation of atomic forces. Three-body nonadditivity terms are considered. The method has been assessed on standard benchmark sets for inter- and intramolecular noncovalent interactions with a particular emphasis on a consistent description of light and heavy element systems. The mean absolute deviations for the S22 benchmark set of noncovalent interactions for 11 standard density functionals decrease by 15%-40% compared to the previous (already accurate) DFT-D version. Spectacular improvements are found for a tripeptide-folding model and all tested metallic systems. The rectification of the long-range behavior and the use of more accurate C(6) coefficients also lead to a much better description of large (infinite) systems as shown for graphene sheets and the adsorption of benzene on an Ag(111) surface. For graphene it is found that the inclusion of three-body terms substantially (by about 10%) weakens the interlayer binding. We propose the revised DFT-D method as a general tool for the computation of the dispersion energy in molecules and solids of any kind with DFT and related (low-cost) electronic structure methods for large systems.
A new density functional (DF) of the generalized gradient approximation (GGA) type for general chemistry applications termed B97-D is proposed. It is based on Becke's power-series ansatz from 1997 and is explicitly parameterized by including damped atom-pairwise dispersion corrections of the form C(6) x R(-6). A general computational scheme for the parameters used in this correction has been established and parameters for elements up to xenon and a scaling factor for the dispersion part for several common density functionals (BLYP, PBE, TPSS, B3LYP) are reported. The new functional is tested in comparison with other GGAs and the B3LYP hybrid functional on standard thermochemical benchmark sets, for 40 noncovalently bound complexes, including large stacked aromatic molecules and group II element clusters, and for the computation of molecular geometries. Further cross-validation tests were performed for organometallic reactions and other difficult problems for standard functionals. In summary, it is found that B97-D belongs to one of the most accurate general purpose GGAs, reaching, for example for the G97/2 set of heat of formations, a mean absolute deviation of only 3.8 kcal mol(-1). The performance for noncovalently bound systems including many pure van der Waals complexes is exceptionally good, reaching on the average CCSD(T) accuracy. The basic strategy in the development to restrict the density functional description to shorter electron correlation lengths scales and to describe situations with medium to large interatomic distances by damped C(6) x R(-6) terms seems to be very successful, as demonstrated for some notoriously difficult reactions. As an example, for the isomerization of larger branched to linear alkanes, B97-D is the only DF available that yields the right sign for the energy difference. From a practical point of view, the new functional seems to be quite robust and it is thus suggested as an efficient and accurate quantum chemical method for large systems where dispersion forces are of general importance.
It is shown by an extensive benchmark on molecular energy data that the mathematical form of the damping function in DFT-D methods has only a minor impact on the quality of the results. For 12 different functionals, a standard "zero-damping" formula and rational damping to finite values for small interatomic distances according to Becke and Johnson (BJ-damping) has been tested. The same (DFT-D3) scheme for the computation of the dispersion coefficients is used. The BJ-damping requires one fit parameter more for each functional (three instead of two) but has the advantage of avoiding repulsive interatomic forces at shorter distances. With BJ-damping better results for nonbonded distances and more clear effects of intramolecular dispersion in four representative molecular structures are found. For the noncovalently-bonded structures in the S22 set, both schemes lead to very similar intermolecular distances. For noncovalent interaction energies BJ-damping performs slightly better but both variants can be recommended in general. The exception to this is Hartree-Fock that can be recommended only in the BJ-variant and which is then close to the accuracy of corrected GGAs for non-covalent interactions. According to the thermodynamic benchmarks BJ-damping is more accurate especially for medium-range electron correlation problems and only small and practically insignificant double-counting effects are observed. It seems to provide a physically correct short-range behavior of correlation/dispersion even with unmodified standard functionals. In any case, the differences between the two methods are much smaller than the overall dispersion effect and often also smaller than the influence of the underlying density functional.
BACKGROUND: The use of warfarin reduces the rate of ischemic stroke in patients with atrial fibrillation but requires frequent monitoring and dose adjustment. Rivaroxaban, an oral factor Xa inhibitor, may provide more consistent and predictable anticoagulation than warfarin. METHODS: In a double-blind trial, we randomly assigned 14,264 patients with nonvalvular atrial fibrillation who were at increased risk for stroke to receive either rivaroxaban (at a daily dose of 20 mg) or dose-adjusted warfarin. The per-protocol, as-treated primary analysis was designed to determine whether rivaroxaban was noninferior to warfarin for the primary end point of stroke or systemic embolism. RESULTS: In the primary analysis, the primary end point occurred in 188 patients in the rivaroxaban group (1.7% per year) and in 241 in the warfarin group (2.2% per year) (hazard ratio in the rivaroxaban group, 0.79; 95% confidence interval [CI], 0.66 to 0.96; P<0.001 for noninferiority). In the intention-to-treat analysis, the primary end point occurred in 269 patients in the rivaroxaban group (2.1% per year) and in 306 patients in the warfarin group (2.4% per year) (hazard ratio, 0.88; 95% CI, 0.74 to 1.03; P<0.001 for noninferiority; P=0.12 for superiority). Major and nonmajor clinically relevant bleeding occurred in 1475 patients in the rivaroxaban group (14.9% per year) and in 1449 in the warfarin group (14.5% per year) (hazard ratio, 1.03; 95% CI, 0.96 to 1.11; P=0.44), with significant reductions in intracranial hemorrhage (0.5% vs. 0.7%, P=0.02) and fatal bleeding (0.2% vs. 0.5%, P=0.003) in the rivaroxaban group. CONCLUSIONS: In patients with atrial fibrillation, rivaroxaban was noninferior to warfarin for the prevention of stroke or systemic embolism. There was no significant between-group difference in the risk of major bleeding, although intracranial and fatal bleeding occurred less frequently in the rivaroxaban group. (Funded by Johnson & Johnson and Bayer; ROCKET AF ClinicalTrials.gov number, NCT00403767.).
The brms package implements Bayesian multilevel models in R using the probabilistic programming language Stan. A wide range of distributions and link functions are supported, allowing users to fit - among others - linear, robust linear, binomial, Poisson, survival, ordinal, zero-inflated, hurdle, and even non-linear models all in a multilevel context. Further modeling options include autocorrelation of the response variable, user defined covariance structures, censored data, as well as meta-analytic standard errors. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their beliefs. In addition, model fit can easily be assessed and compared with the Watanabe-Akaike information criterion and leave-one-out cross-validation.
AUTORES: Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425, \nAbraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981, \nPeter J Adhihetty1625, Sharon G Adler700, Galila Agam67, Rajesh Agarwal1587, Manish K Aghi1537, Maria Agnello1826, \nPatrizia Agostinis664, Patricia V Aguilar1960, Julio Aguirre-Ghiso784,786, Edoardo M Airoldi89,422, Slimane Ait-Si-Ali1376, \nTakahiko Akematsu2010, Emmanuel T Akporiaye1097, Mohamed Al-Rubeai1394, Guillermo M Albaiceta1294, \nChris Albanese363, Diego Albani561, Matthew L Albert517, Jesus Aldudo128, Hana Alg€ul1164, Mehrdad Alirezaei1198, \nIraide Alloza642,888, Alexandru Almasan206, Maylin Almonte-Beceril524, Emad S Alnemri1212, Covadonga Alonso544, \nNihal Altan-Bonnet848, Dario C Altieri1205, Silvia Alvarez1497, Lydia Alvarez-Erviti1395, Sandro Alves107, \nGiuseppina Amadoro860, Atsuo Amano930, Consuelo Amantini1554, Santiago Ambrosio1458, Ivano Amelio756, \nAmal O Amer918, Mohamed Amessou2089, Angelika Amon726, Zhenyi An1538, Frank A Anania291, Stig U Andersen6, \nUsha P Andley2079, Catherine K Andreadi1690, Nathalie Andrieu-Abadie502, Alberto Anel2027, David K Ann58, \nShailendra Anoopkumar-Dukie388, Manuela Antonioli832,858, Hiroshi Aoki1791, Nadezda Apostolova2007, \nSaveria Aquila1500, Katia Aquilano1876, Koichi Araki292, Eli Arama2098, Agustin Aranda456, Jun Araya591, \nAlexandre Arcaro1472, Esperanza Arias26, Hirokazu Arimoto1225, Aileen R Ariosa1749, Jane L Armstrong1930, \nThierry Arnould1773, Ivica Arsov2120, Katsuhiko Asanuma675, Valerie Askanas1924, Eric Asselin1867, Ryuichiro Atarashi794, \nSally S Atherton369, Julie D Atkin713, Laura D Attardi1131, Patrick Auberger1787, Georg Auburger379, Laure Aurelian1727, \nRiccardo Autelli1992, Laura Avagliano1029,1755, Maria Laura Avantaggiati364, Limor Avrahami1166, Suresh Awale1986, \nNeelam Azad404, Tiziana Bachetti568, Jonathan M Backer28, Dong-Hun Bae1933, Jae-sung Bae677, Ok-Nam Bae409, \nSoo Han Bae2117, Eric H Baehrecke1729, Seung-Hoon Baek17, Stephen Baghdiguian1368, \nAgnieszka Bagniewska-Zadworna2, Hua Bai90, Jie Bai667, Xue-Yuan Bai1133, Yannick Bailly884, \nKithiganahalli Narayanaswamy Balaji473, Walter Balduini2002, Andrea Ballabio316, Rena Balzan1711, Rajkumar Banerjee239, \nG abor B anhegyi1052, Haijun Bao2109, Benoit Barbeau1363, Maria D Barrachina2007, Esther Barreiro467, Bonnie Bartel997, \nAlberto Bartolom e222, Diane C Bassham550, Maria Teresa Bassi1046, Robert C Bast Jr1273, Alakananda Basu1798, \nMaria Teresa Batista1578, Henri Batoko1336, Maurizio Battino970, Kyle Bauckman2085, Bradley L Baumgarner1909, \nK Ulrich Bayer1594, Rupert Beale1553, Jean-Fran¸cois Beaulieu1360, George R. Beck Jr48,294, Christoph Becker336, \nJ David Beckham1595, Pierre-Andr e B edard749, Patrick J Bednarski301, Thomas J Begley1135, Christian Behl1419, \nChristian Behrends757, Georg MN Behrens406, Kevin E Behrns1627, Eloy Bejarano26, Amine Belaid490, \nFrancesca Belleudi1041, Giovanni B enard497, Guy Berchem706, Daniele Bergamaschi983, Matteo Bergami1401, \nBen Berkhout1441, Laura Berliocchi714, Am elie Bernard1749, Monique Bernard1354, Francesca Bernassola1880, \nAnne Bertolotti791, Amanda S Bess272, S ebastien Besteiro1351, Saverio Bettuzzi1828, Savita Bhalla913, \nShalmoli Bhattacharyya973, Sujit K Bhutia838, Caroline Biagosch1159, Michele Wolfe Bianchi520,1378,1381, \nMartine Biard-Piechaczyk210, Viktor Billes298, Claudia Bincoletto1314, Baris Bingol350, Sara W Bird1128, Marc Bitoun1112, \nIvana Bjedov1258, Craig Blackstone843, Lionel Blanc1183, Guillermo A Blanco1496, Heidi Kiil Blomhoff1812, \nEmilio Boada-Romero1297, Stefan B€ockler1464, Marianne Boes1423, Kathleen Boesze-Battaglia1835, Lawrence H Boise286,287, \nAlessandra Bolino2063, Andrea Boman693, Paolo Bonaldo1823, Matteo Bordi897, J€urgen Bosch608, Luis M Botana1308, \nJoelle Botti1375, German Bou1405, Marina Bouch e1038, Marion Bouchecareilh1331, Marie-Jos ee Boucher1901, \nMichael E Boulton481, Sebastien G Bouret1926, Patricia Boya133, Micha€el Boyer-Guittaut1345, Peter V Bozhkov1141, \nNathan Brady374, Vania MM Braga469, Claudio Brancolini1997, Gerhard H Braus353, Jos e M Bravo-San Pedro299,393,508,1374, \nLisa A Brennan322, Emery H Bresnick2022, Patrick Brest490, Dave Bridges1939, Marie-Agn es Bringer124, Marisa Brini1822, \nGlauber C Brito1311, Bertha Brodin631, Paul S Brookes1872, Eric J Brown352, Karen Brown1690, Hal E Broxmeyer480, \nAlain Bruhat486,1339, Patricia Chakur Brum1893, John H Brumell446, Nicola Brunetti-Pierri315,1171, \nRobert J Bryson-Richardson781, Shilpa Buch1777, Alastair M Buchan1819, Hikmet Budak1022, Dmitry V Bulavin118,505,1789, \nScott J Bultman1792, Geert Bultynck665, Vladimir Bumbasirevic1470, Yan Burelle1356, Robert E Burke216,217, \nMargit Burmeister1750, Peter B€utikofer1473, Laura Caberlotto1987, Ken Cadwell896, Monika Cahova112, Dongsheng Cai24, \nJingjing Cai2099, Qian Cai1018, Sara Calatayud2007, Nadine Camougrand1343, Michelangelo Campanella1700, \nGrant R Campbell1525, Matthew Campbell1249, Silvia Campello556,1876, Robin Candau1769, Isabella Caniggia1983, \nLavinia Cantoni560, Lizhi Cao116, Allan B Caplan1656, Michele Caraglia1051, Claudio Cardinali1043, Sandra Morais Cardoso1579, Jennifer S Carew208, Laura A Carleton874, Cathleen R Carlin101, Silvia Carloni2002, \nSven R Carlsson1267, Didac Carmona-Gutierrez1643, Leticia AM Carneiro312, Oliana Carnevali971, Serena Carra1318, \nAlice Carrier120, Bernadette Carroll900, Caty Casas1324, Josefina Casas1116, Giuliana Cassinelli324, Perrine Castets1462, \nSusana Castro-Obregon214, Gabriella Cavallini1841, Isabella Ceccherini568, Francesco Cecconi253,555,1884, \nArthur I Cederbaum459, Valent ın Ce~na199,1281, Simone Cenci1323,2064, Claudia Cerella444, Davide Cervia1996, \nSilvia Cetrullo1478, Hassan Chaachouay2028, Han-Jung Chae187, Andrei S Chagin634, Chee-Yin Chai626,628, \nGopal Chakrabarti1502, Georgios Chamilos1601, Edmond YW Chan1142, Matthew TV Chan181, Dhyan Chandra1003, \nPallavi Chandra548, Chih-Peng Chang818, Raymond Chuen-Chung Chang1653, Ta Yuan Chang345, John C Chatham1434, \nSaurabh Chatterjee1910, Santosh Chauhan527, Yongsheng Che62, Michael E Cheetham1263, Rajkumar Cheluvappa1783, \nChun-Jung Chen1153, Gang Chen598,1676, Guang-Chao Chen9, Guoqiang Chen1078, Hongzhuan Chen1077, Jeff W Chen1514, \nJian-Kang Chen370,371, Min Chen249, Mingzhou Chen2104, Peiwen Chen1823, Qi Chen1674, Quan Chen172, \nShang-Der Chen138, Si Chen325, Steve S-L Chen10, Wei Chen2125, Wei-Jung Chen829, Wen Qiang Chen979, Wenli Chen1113, \nXiangmei Chen1133, Yau-Hung Chen1157, Ye-Guang Chen1250, Yin Chen1447, Yingyu Chen953,955, Yongshun Chen2135, \nYu-Jen Chen712, Yue-Qin Chen1145, Yujie Chen1208, Zhen Chen339, Zhong Chen2123, Alan Cheng1702, \nChristopher HK Cheng184, Hua Cheng1728, Heesun Cheong814, Sara Cherry1836, Jason Chesney1703, \nChun Hei Antonio Cheung817, Eric Chevet1359, Hsiang Cheng Chi140, Sung-Gil Chi656, Fulvio Chiacchiera308, \nHui-Ling Chiang958, Roberto Chiarelli1826, Mario Chiariello235,567,577, Marcello Chieppa835, Lih-Shen Chin290, \nMario Chiong1285, Gigi NC Chiu878, Dong-Hyung Cho676, Ssang-Goo Cho650, William C Cho982, Yong-Yeon Cho105, \nYoung-Seok Cho1064, Augustine MK Choi2095, Eui-Ju Choi656, Eun-Kyoung Choi387,400,685, Jayoung Choi1563, \nMary E Choi2093, Seung-Il Choi2116, Tsui-Fen Chou412, Salem Chouaib395, Divaker Choubey1574, Vinay Choubey1936, \nKuan-Chih Chow822, Kamal Chowdhury730, Charleen T Chu1856, Tsung-Hsien Chuang827, Taehoon Chun657, \nHyewon Chung652, Taijoon Chung978, Yuen-Li Chung1194, Yong-Joon Chwae18, Valentina Cianfanelli254, \nRoberto Ciarcia1775, Iwona A Ciechomska886, Maria Rosa Ciriolo1876, Mara Cirone1042, Sofie Claerhout1694, \nMichael J Clague1698, Joan Cl aria1457, Peter GH Clarke1687, Robert Clarke361, Emilio Clementi1045,1398, C edric Cleyrat1781, \nMiriam Cnop1366, Eliana M Coccia574, Tiziana Cocco1459, Patrice Codogno1375, J€orn Coers271, Ezra EW Cohen1533, \nDavid Colecchia235,567,577, Luisa Coletto25, N uria S Coll123, Emma Colucci-Guyon516, Sergio Comincini1829, \nMaria Condello578, Katherine L Cook2073, Graham H Coombs1929, Cynthia D Cooper2076, J Mark Cooper1395, \nIsabelle Coppens601, Maria Tiziana Corasaniti1387, Marco Corazzari485,1884, Ramon Corbalan1566, \nElisabeth Corcelle-Termeau251, Mario D Cordero1899, Cristina Corral-Ramos1289, Olga Corti507,1109, Andrea Cossarizza1767, \nPaola Costelli1993, Safia Costes1518, Susan L Cotman721, Ana Coto-Montes946, Sandra Cottet566,1688, Eduardo Couve1301, \nLori R Covey1015, L Ashley Cowart762, Jeffery S Cox1536, Fraser P Coxon1427, Carolyn B Coyne1846, Mark S Cragg1919, \nRolf J Craven1679, Tiziana Crepaldi1995, Jose L Crespo1300, Alfredo Criollo1285, Valeria Crippa558, Maria Teresa Cruz1576, \nAna Maria Cuervo26, Jose M Cuezva1277, Taixing Cui1907, Pedro R Cutillas987, Mark J Czaja27, Maria F Czyzyk-Krzeska1572, \nRuben K Dagda2068, Uta Dahmen1404, Chunsun Dai800, Wenjie Dai1187, Yun Dai2059, Kevin N Dalby1940, \nLuisa Dalla Valle1822, Guillaume Dalmasso1340, Marcello D’Amelio557, Markus Damme188, Arlette Darfeuille-Michaud1340, \nCatherine Dargemont950, Victor M Darley-Usmar1433, Srinivasan Dasarathy205, Biplab Dasgupta202, Srikanta Dash1254, \nCrispin R Dass242, Hazel Marie Davey8, Lester M Davids1560, David D avila227, Roger J Davis1731, Ted M Dawson604, \nValina L Dawson606, Paula Daza1898, Jackie de Belleroche470, Paul de Figueiredo1180,1182, \nRegina Celia Bressan Queiroz de Figueiredo135, Jos e de la Fuente1023, Luisa De Martino1775, \nAntonella De Matteis1171, Guido RY De Meyer1443, Angelo De Milito631, Mauro De Santi2002,
The first edition of the European LeukemiaNet (ELN) recommendations for diagnosis and management of acute myeloid leukemia (AML) in adults, published in 2010, has found broad acceptance by physicians and investigators caring for patients with AML. Recent advances, for example, in the discovery of the genomic landscape of the disease, in the development of assays for genetic testing and for detecting minimal residual disease (MRD), as well as in the development of novel antileukemic agents, prompted an international panel to provide updated evidence- and expert opinion-based recommendations. The recommendations include a revised version of the ELN genetic categories, a proposal for a response category based on MRD status, and criteria for progressive disease.
An empirical method to account for van der Waals interactions in practical calculations with the density functional theory (termed DFT-D) is tested for a wide variety of molecular complexes. As in previous schemes, the dispersive energy is described by damped interatomic potentials of the form C6R(-6). The use of pure, gradient-corrected density functionals (BLYP and PBE), together with the resolution-of-the-identity (RI) approximation for the Coulomb operator, allows very efficient computations for large systems. Opposed to previous work, extended AO basis sets of polarized TZV or QZV quality are employed, which reduces the basis set superposition error to a negligible extend. By using a global scaling factor for the atomic C6 coefficients, the functional dependence of the results could be strongly reduced. The "double counting" of correlation effects for strongly bound complexes is found to be insignificant if steep damping functions are employed. The method is applied to a total of 29 complexes of atoms and small molecules (Ne, CH4, NH3, H2O, CH3F, N2, F2, formic acid, ethene, and ethine) with each other and with benzene, to benzene, naphthalene, pyrene, and coronene dimers, the naphthalene trimer, coronene. H2O and four H-bonded and stacked DNA base pairs (AT and GC). In almost all cases, very good agreement with reliable theoretical or experimental results for binding energies and intermolecular distances is obtained. For stacked aromatic systems and the important base pairs, the DFT-D-BLYP model seems to be even superior to standard MP2 treatments that systematically overbind. The good results obtained suggest the approach as a practical tool to describe the properties of many important van der Waals systems in chemistry. Furthermore, the DFT-D data may either be used to calibrate much simpler (e.g., force-field) potentials or the optimized structures can be used as input for more accurate ab initio calculations of the interaction energies.
The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.
Abstract The International Mineralogical Association's approved amphibole nomenclature has been revised in order to simplify it, make it more consistent with divisions generally at 50%, define prefixes and modifiers more precisely and include new amphibole species discovered and named since 1978, when the previous scheme was approved. The same reference axes form the basis of the new scheme and most names are little changed but compound species names like tremolitic hornblende (now magnesiohornblende) are abolished and also crossite (now glaucophane or ferroglaucophane or magnesioriebeckite or riebeckite), tirodite (now manganocummingtonite) and dannemorite (now manganogrunerite). The 50% rule has been broken only to retain tremolite and actinolite as in the 1978 scheme so the sodic calcic amphibole range has therefore been expanded. Alkali amphiboles are now sodic amphiboles. The use of hyphens is defined. New amphibole names approved since 1978 include nyböite, leakeite, kornite, ungarettiite, sadanagaite and cannilloite. All abandoned names are listed. The formulae and source of the amphibole end member names are listed and procedures outlined to calculate Fe 3+ and Fe 2+ when not determined by analysis.
In 2003, an international working group last reported on recommendations for diagnosis, response assessment, and treatment outcomes in acute myeloid leukemia (AML). Since that time, considerable progress has been made in elucidating the molecular pathogenesis of the disease that has resulted in the identification of new diagnostic and prognostic markers. Furthermore, therapies are now being developed that target disease-associated molecular defects. Recent developments prompted an international expert panel to provide updated evidence- and expert opinion-based recommendations for the diagnosis and management of AML, that contain both minimal requirements for general practice as well as standards for clinical trials. A new standardized reporting system for correlation of cytogenetic and molecular genetic data with clinical data is proposed.
A new hybrid density functional for general chemistry applications is proposed. It is based on a mixing of standard generalized gradient approximations (GGAs) for exchange by Becke (B) and for correlation by Lee, Yang, and Parr (LYP) with Hartree-Fock (HF) exchange and a perturbative second-order correlation part (PT2) that is obtained from the Kohn-Sham (GGA) orbitals and eigenvalues. This virtual orbital-dependent functional contains only two global parameters that describe the mixture of HF and GGA exchange (a(x)) and of the PT2 and GGA correlation (c), respectively. The parameters are obtained in a least-squares-fit procedure to the G297 set of heat of formations. Opposed to conventional hybrid functionals, the optimum a(x) is found to be quite large (53% with c=27%) which at least in part explains the success for many problematic molecular systems compared to conventional approaches. The performance of the new functional termed B2-PLYP is assessed by the G297 standard benchmark set, a second test suite of atoms, molecules, and reactions that are considered as electronically very difficult (including transition-metal compounds, weakly bonded complexes, and reaction barriers) and comparisons with other hybrid functionals of GGA and meta-GGA types. According to many realistic tests, B2-PLYP can be regarded as the best general purpose density functional for molecules (e.g., a mean absolute deviation for the two test sets of only 1.8 and 3.2 kcal/mol compared to about 3 and 5 kcal/mol, respectively, for the best other density functionals). Very importantly, also the maximum and minimum errors (outliers) are strongly reduced (by about 10-20 kcal/mol). Furthermore, very good results are obtained for transition state barriers but unlike previous attempts at such a good description, this definitely comes not at the expense of equilibrium properties. Preliminary calculations of the equilibrium bond lengths and harmonic vibrational frequencies for diatomic molecules and transition-metal complexes also show very promising results. The uniformity with which B2-PLYP improves for a wide range of chemical systems emphasizes the need of (virtual) orbital-dependent terms that describe nonlocal electron correlation in accurate exchange-correlation functionals. From a practical point of view, the new functional seems to be very robust and it is thus suggested as an efficient quantum chemical method of general purpose.
Chronic pain is a major source of suffering. It interferes with daily functioning and often is accompanied by distress. Yet, in the International Classification of Diseases, chronic pain diagnoses are not represented systematically. The lack of appropriate codes renders accurate epidemiological investigations difficult and impedes health policy decisions regarding chronic pain such as adequate financing of access to multimodal pain management. In cooperation with the WHO, an IASP Working Group has developed a classification system that is applicable in a wide range of contexts, including pain medicine, primary care, and low-resource environments. Chronic pain is defined as pain that persists or recurs for more than 3 months. In chronic pain syndromes, pain can be the sole or a leading complaint and requires special treatment and care. In conditions such as fibromyalgia or nonspecific low-back pain, chronic pain may be conceived as a disease in its own right; in our proposal, we call this subgroup "chronic primary pain." In 6 other subgroups, pain is secondary to an underlying disease: chronic cancer-related pain, chronic neuropathic pain, chronic secondary visceral pain, chronic posttraumatic and postsurgical pain, chronic secondary headache and orofacial pain, and chronic secondary musculoskeletal pain. These conditions are summarized as "chronic secondary pain" where pain may at least initially be conceived as a symptom. Implementation of these codes in the upcoming 11th edition of International Classification of Diseases will lead to improved classification and diagnostic coding, thereby advancing the recognition of chronic pain as a health condition in its own right.
Major depression is a debilitating psychiatric illness that is typically associated with low mood and anhedonia. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximize sample size, we meta-analyzed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 genesets associated with depression, including both genes and gene pathways associated with synaptic structure and neurotransmission. An enrichment analysis provided further evidence of the importance of prefrontal brain regions. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant after multiple testing correction. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding etiology and developing new treatment approaches.
The chemistry of heterocyclic carbenes has experienced a rapid development over the last years. In addition to the imidazolin-2-ylidenes, a large number of cyclic diaminocarbenes with different ring sizes have been described. Aside from diaminocarbenes, P-heterocyclic carbenes, and derivatives with only one, or even no heteroatom within the carbene ring are known. New methods for the synthesis of complexes with N-heterocyclic carbene ligands such as the oxidative addition or the metal atom template controlled cyclization of beta-functionalized isocyanides have been developed recently. This review summarizes the new developments regarding the synthesis of N-heterocyclic carbenes and their metal complexes.
1. Introduction Chronic pain has been recognized as pain that persists past normal healing time5 and hence lacks the acute warning function of physiological nociception.35 Usually pain is regarded as chronic when it lasts or recurs for more than 3 to 6 months.29 Chronic pain is a frequent condition, affecting an estimated 20% of people worldwide6,13,14,18 and accounting for 15% to 20% of physician visits.25,28 Chronic pain should receive greater attention as a global health priority because adequate pain treatment is a human right, and it is the duty of any health care system to provide it.4,13 The current version of the International Classification of Diseases (ICD) of the World Health Organization (WHO) includes some diagnostic codes for chronic pain conditions, but these diagnoses do not reflect the actual epidemiology of chronic pain, nor are they categorized in a systematic manner. The ICD is the preeminent tool for coding diagnoses and documenting investigations or therapeutic measures within the health care systems of many countries. In addition, ICD codes are commonly used to report target diseases and comorbidities of participants in clinical research. Consequently, the current lack of adequate coding in the ICD makes the acquisition of accurate epidemiological data related to chronic pain difficult, prevents adequate billing for health care expenses related to pain treatment, and hinders the development and implementation of new therapies.10,11,16,23,27,31,37 Responding to these shortcomings, the International Association for the Study of Pain (IASP) contacted the WHO and established a Task Force for the Classification of Chronic Pain. The IASP Task Force, which comprises pain experts from across the globe,19 has developed a new and pragmatic classification of chronic pain for the upcoming 11th revision of the ICD. The goal is to create a classification system that is applicable in primary care and in clinical settings for specialized pain management. A major challenge in this process was finding a rational principle of classification that suits the different types of chronic pain and fits into the general ICD-11 framework. Pain categories are variably defined based on the perceived location (headache), etiology (cancer pain), or the primarily affected anatomical system (neuropathic pain). Some diagnoses of pain defy these classification principles (fibromyalgia). This problem is not unique to the classification of pain, but exists throughout the ICD. The IASP Task Force decided to give first priority to pain etiology, followed by underlying pathophysiological mechanisms, and finally the body site. Developing this multilayered classification was greatly facilitated by a novel principle of assigning diagnostic codes in ICD-11, termed “multiple parenting.” Multiple parenting allows the same diagnosis to be subsumed under more than 1 category (for a glossary of ICD terms refer to Table 1). Each diagnosis retains 1 category as primary parent, but is cross-referenced to other categories that function as secondary parents.Table 1: Glossary of ICD-11 terms.The new ICD category for “Chronic Pain” comprises the most common clinically relevant disorders. These disorders were divided into 7 groups (Fig. 1): (1) chronic primary pain, (2) chronic cancer pain, (3) chronic posttraumatic and postsurgical pain, (4) chronic neuropathic pain, (5) chronic headache and orofacial pain, (6) chronic visceral pain, and (7) chronic musculoskeletal pain. Experts assigned to each group are responsible for the definition of diagnostic criteria and the selection of the diagnoses to be included under these subcategories of chronic pain. Thanks to Bedirhan Üstün and Robert Jakob of the WHO, these pain diagnoses are now integrated in the beta version of ICD-11 (http://id.who.int/icd/entity/1581976053). The Task Force is generating content models for single entities to describe their clinical characteristics. After peer review overseen by the WHO Steering Committee,39 the classification of chronic pain will be voted into action by the World Health Assembly in 2017.Figure 1: Organizational chart of Task Force, IASP, and WHO interactions. The IASP Task Force was created by the IASP council and its scope defined in direct consultation of the chairs (R.D.T. and W.R.) with WHO representatives in 2012. The Task Force reports to the IASP Council on an annual basis.2. Classification of chronic pain Chronic pain was defined as persistent or recurrent pain lasting longer than 3 months. This definition according to pain duration has the advantage that it is clear and operationalized. Optional specifiers for each diagnosis record evidence of psychosocial factors and the severity of the pain. Pain severity can be graded based on pain intensity, pain-related distress, and functional impairment. 2.1. Chronic primary pain Chronic primary pain is pain in 1 or more anatomic regions that persists or recurs for longer than 3 months and is associated with significant emotional distress or significant functional disability (interference with activities of daily life and participation in social roles) and that cannot be better explained by another chronic pain condition. This is a new phenomenological definition, created because the etiology is unknown for many forms of chronic pain. Common conditions such as, eg, back pain that is neither identified as musculoskeletal or neuropathic pain, chronic widespread pain, fibromyalgia, and irritable bowel syndrome will be found in this section and biological findings contributing to the pain problem may or may not be present. The term “primary pain” was chosen in close liaison with the ICD-11 revision committee, who felt this was the most widely acceptable term, in particular, from a nonspecialist perspective. 2.2. Chronic cancer pain Pain is a frequent and debilitating accompaniment of cancer8 that as yet has not been represented in the ICD. The Task Force decided to list it as a separate entity because there are specific treatment guidelines.7,38 Chronic cancer pain includes pain caused by the cancer itself (the primary tumor or metastases) and pain that is caused by the cancer treatment (surgical, chemotherapy, radiotherapy, and others). Cancer-related pain will be subdivided based on location into visceral, bony (or musculoskeletal), and somatosensory (neuropathic). It will be described as either continuous (background pain) or intermittent (episodic pain) if associated with physical movement or clinical procedures. The treatment-related pain will be cross-referenced from the chapters on postsurgical pain and neuropathic pain. 2.3. Chronic postsurgical and posttraumatic pain Because pain that persists beyond normal healing is frequent after surgery and some types of injuries, the entity of postsurgical and posttraumatic pain was created. This is defined as pain that develops after a surgical procedure or a tissue injury (involving any trauma, including burns) and persists at least 3 months after surgery or tissue trauma26; this is a definition of exclusion, as all other causes of pain (infection, recurring malignancy) as well as pain from a pre-existing pain problem need to be excluded. In view of the different causality, as well as from a medicolegal point of view, a separation between postsurgical pain and pain after all other trauma is regarded as useful. Depending on the type of surgery, chronic postsurgical pain is often neuropathic pain (on average 30% of cases with a range from 6% to 54% and more).15 Pain including such a neuropathic component is usually more severe than nociceptive pain and often affects the quality of life more adversely.21 2.4. Chronic neuropathic pain Chronic neuropathic pain is caused by a lesion or disease of the somatosensory nervous system.20,22 The somatosensory nervous system provides information about the body including skin, musculoskeletal, and visceral organs. Neuropathic pain may be spontaneous or evoked, as an increased response to a painful stimulus (hyperalgesia) or a painful response to a normally nonpainful stimulus (allodynia). The diagnosis of neuropathic pain requires a history of nervous system injury, for example, by a stroke, nerve trauma, or diabetic neuropathy, and a neuroanatomically plausible distribution of the pain.22 For the identification of definite neuropathic pain, it is necessary to demonstrate the lesion or disease involving the nervous system, for example, by imaging, biopsy, neurophysiological, or laboratory tests. In addition, negative or positive sensory signs compatible with the innervation territory of the lesioned nervous structure must be present.36 Diagnostic entities within this category will be divided into conditions of peripheral or central neuropathic pain. 2.5. Chronic headache and orofacial pain The International Headache Society (IHS) has created a headache classification17 that is implemented in full in the chapter on neurology. This classification differentiates between primary (idiopathic), secondary (symptomatic) headache, and orofacial pain including cranial neuralgias. In the section on chronic pain, only chronic headache and chronic orofacial pain will be included. Chronic headache and chronic orofacial pain is defined as headaches or orofacial pains that occur on at least 50% of the days during at least 3 months. For most purposes, patients receive a diagnosis according to the headache phenotypes or orofacial pains that they currently present. The section will list the most frequent chronic headache conditions. The most common chronic orofacial pains are temporomandibular disorders,32 which have been included in this subchapter of chronic pain. Chronic orofacial pain can be a localized presentation of a primary headache.2 This is common in the trigeminal autonomic cephalalgias, less common in migraines, and rare in tension-type headache. Several chronic orofacial pains such as post-traumatic trigeminal neuropathic pain,3 persistent idiopathic orofacial pain, and burning mouth syndrome are cross-referenced to, eg, primary chronic pain and neuropathic pain. The temporal definition of “chronic” has been extrapolated from that of chronic headaches.1 2.6. Chronic visceral pain Chronic visceral pain is persistent or recurrent pain that originates from the internal organs of the head and neck region and the thoracic, abdominal, and pelvic cavities.24,33,34 The pain is usually perceived in the somatic tissues of the body wall (skin, subcutis, muscle) in areas that receive the same sensory innervation as the internal organ at the origin of the symptom (referred visceral pain).12 In these areas, secondary hyperalgesia (increased sensitivity to painful stimuli in areas other than the primary site of the nociceptive input) often occurs30; the intensity of the symptom may bear no relationship with the extent of the internal damage or noxious visceral stimulation.9 The section on visceral pain will be subdivided according to the major underlying mechanisms, ie, persistent inflammation, vascular mechanisms (ischemia, thrombosis), obstruction and distension, traction and compression, combined mechanisms (eg, obstruction and inflammation concurrently), and referral from other locations. Pain due to cancer will be cross-referenced to the chapter chronic cancer pain and pain due to functional or unexplained mechanisms to chronic primary pain. 2.7. Chronic musculoskeletal pain Chronic musculoskeletal pain is defined as persistent or recurrent pain that arises as part of a disease process directly affecting bone(s), joint(s), muscle(s), or related soft tissue(s). According to the constraints of the approach as described in the Introduction, this category is therefore limited to nociceptive pain and does not include pain that may be perceived in musculoskeletal tissues but does not arise therefrom, such as the pain of compression neuropathy or somatic referred pain. The entities subsumed in this approach include those characterized by persistent inflammation of infectious, autoimmune or metabolic etiology, such as rheumatoid arthritis, and by structural changes affecting bones, joints, tendons, or muscles, such as symptomatic osteoarthrosis. Musculoskeletal pain of neuropathic origin will be cross-referenced to neuropathic pain. Well-described apparent musculoskeletal conditions for which the causes are incompletely understood, such as nonspecific back pain or chronic widespread pain, will be included in the section on chronic primary pain. 3. Outlook Irrespective of its etiology, chronic pain is a major source of suffering and requires special treatment and care. Our proposal may not represent a perfect solution for the classification of all manifestations of chronic pain. However, it does represent the first systematic approach to implementing a classification of chronic pain in the ICD. It is based on international expertise and agreement, and consistent with the requirements of the ICD regarding the structure and format of content models. The 7 major categories of chronic pain were identified after considerable research and discussion. They represent a compromise between comprehensiveness and practical applicability of the classification system. Several clinically important conditions that were neglected in former ICD revisions will now be mentioned, eg, chronic cancer pain or chronic neuropathic pain. Etiological factors, pain intensity, and disability related to pain will be reflected. With the introduction of chronic primary pain as a new diagnostic entity, the classification recognizes conditions that affect a broad group of patients with pain and would be neglected in etiologically defined categories. We hope that this classification strengthens the representation of chronic pain conditions in clinical practice and research and welcome comments to improve it further. Conflict of interest statement Q. Aziz has attended advisory board meetings for Almirall pharmaceuticals and Grunenthal. He has also received funding for clinical trials from Ono Pharmaceutical and Protexin. M.I. Bennett has received consultancy or speaker fees from Pfizer, Bayer, Astellas, and Grunenthal in the last 5 years. M. Cohen has received honoraria for contributions to educational programs from Mundipharma Pty Limited and Pfizer. S. Evers received honoraria (as speaker and/or member of advisory boards) and research grants within the past 5 years by AGA Medical (now St Jude), Allergan, Almirall, Astra Zeneca, Berlin-Chemie, CoLucid, Desitin, Eisai, GlaxoSmithKline, Ipsen Pharma, Menarini, MSD, Novartis, Pfizer, Reckitt-Benckiser, UCB. N.B. Finnerup has received speaker's honoraria from Pfizer, Grunenthal, and Norpharma, research grant from Grünenthal, and consultancy fee from Astellas and is member of the IMI “Europain” collaboration where industry members of this are: Astra Zeneca, Pfizer, Esteve, UCB-Pharma, Sanofi Aventis, Grünenthal, Eli Lilly, Boehringer Ingelheim, Astellas, Abbott, and Lundbeck. M.B. First on the faculty of the Lundbeck International Neuroscience Foundation. In the past 2 years, M.A. Giamberardino received research funding or honoraria (participation in Advisory Board) from Bayer Healthcare, Helsinn, and Epitech Group. S. Kaasa declares no conflict of interest related to this work. In the past year he received honoraria from Helsinn related to participation in Advisory Board. E. Kosek has received consultancy and speaker fees in the past 24 months from Eli Lilly and Company and Orion and has ongoing research collaborations with Eli Lilly and Company and Abbott and Pierre Fabre. M. Nicholas received honoraria for contributing to educational sessions for Mundipharma and Pfizer in the last 5 years. S. Perrot received honoraria as a speaker and/or member of the advisory board in the past 5 years from Pfizer, BMS, Grunenthal, Elli Lilly, Sanofi, Daichi-Sankyo, Astellas, and Mundipharma. He has received grant support from BMS. W. Rief received honoraria (as speaker and/or member of advisory boards on topics such as adherence, placebo mechanisms) within the past 5 years from Berlin Chemie, Astra Zeneca, Bayer, Heel (research grant). J. Scholz has received speaker fees from Convergence, GlaxoSmithKline, Pfizer, St Jude Medical, and Zalicus. He has served on advisory boards or consulted for Convergence, Pfizer, Sanofi Aventis, and Zalicus Pharmaceuticals. He has received grant support from GlaxoSmithKline and Pfizer. In the last 5 years, the Anaesthesiology Unit of the University of Western Australia, but not S. Schug personally, has received research and travel funding and speaking and consulting honoraria from bioCSL, Bionomics, Eli Lilly, Grunenthal, Janssen, Mundipharma, Pfizer, Phosphagenics and iX Biopharma within the last 2 years. B.H. Smith has received lecture and consultancy fees, on behalf of his institution, from Pfizer, Grunenthal, Eli Lilly, and Napp. He has received unconditional educational grants from Pfizer Ltd; and he has received travel and accommodation support from Napp. P. Svensson served as a paid consultant for Sunstar Suisse SA. R.-D. Treede has received speaker's honoraria, research grants or consultancy fees from AbbVie, Acron, Astellas, Bauerfeind, Boehringer Ingelheim, Grünenthal, Hydra, Mundipharma, and Pfizer and is a member of the IMI “Europain” collaboration where industry members of this are: Astra Zeneca, Pfizer, Esteve, UCB-Pharma, Sanofi Aventis, Grünenthal, Eli Lilly, Boehringer Ingelheim, Astellas, Abbott, and Lundbeck. J.W.S. Vlaeyen is a member of the PHILIPS advisory board on pain management and declares no conflicts of interest with regard to this work. S.-J. Wang has served on the advisory boards of Allergan and Eli Lilly, Taiwan. He has received speaking honoraria from local companies (Taiwan branches) of Pfizer, Elli Lilly, and GSK. He has received research grants from the Novartis Taiwan, Taiwan Ministry of Science and Technology, Taipei-Veterans General Hospital and Taiwan Headache Society. The other authors have no conflicts of interest to declare. Acknowledgements The authors are members of the Classification of Pain Diseases Task Force of the International Association for the Study of Pain (IASP), which gave logistical and financial support to perform this work. We acknowledge the contributions of the following IASP Special Interest Groups (SIGs): Abdominal & Pelvic Pain SIG, Acute Pain SIG, Cancer Pain SIG, Neuropathic Pain SIG and the Orofacial Pain SIG, and the Classification Committee of the International Headache Society (IHS). Author contributions: R.-D. Treede, W. Rief, and A. Barke contributed equally to this topical review.
Abstract Dispersion corrections to standard Kohn–Sham density functional theory (DFT) are reviewed. The focus is on computationally efficient methods for large systems that do not depend on virtual orbitals or rely on separated fragments. The recommended approaches (van der Waals density functional and DFT‐D) are asymptotically correct and can be used in combination with standard or slightly modified (short‐range) exchange–correlation functionals. The importance of the dispersion energy in intramolecular cases (conformational problems and thermochemistry) is highlighted. © 2011 John Wiley & Sons, Ltd. WIREs Comput Mol Sci 2011 1 211‐228 DOI: 10.1002/wcms.30 This article is categorized under: Electronic Structure Theory > Density Functional Theory
, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.
<h3>Importance</h3> Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data. <h3>Objective</h3> To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. <h3>Evidence Review</h3> We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence. <h3>Findings</h3> In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572 000 deaths and 15.2 million DALYs), and stomach cancer (542 000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819 000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601 000 deaths and 17.4 million DALYs), TBL cancer (596 000 deaths and 12.6 million DALYs), and colorectal cancer (414 000 deaths and 8.3 million DALYs). <h3>Conclusions and Relevance</h3> The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer care.
A total of 2128 calcitic and phosphatic shells, mainly brachiopods with some conodonts and belemnites, were measured for their δ18O, δ13C and 87Sr/86Sr values. The dataset covers the Cambrian to Cretaceous time interval. Where possible, these samples were collected at high temporal resolution, up to 0.7 Ma (one biozone), from the stratotype sections of all continents but Antarctica and from many sedimentary basins. Paleogeographically, the samples are mostly from paleotropical domains. The scanning electron microscopy (SEM), petrography, cathodoluminescence and trace element results of the studied calcitic shells and the conodont alteration index (CAI) data of the phosphatic shells are consistent with an excellent preservation of the ultrastructure of the analyzed material. These datasets are complemented by extensive literature compilations of Phanerozoic low-Mg calcitic, aragonitic and phosphatic isotope data for analogous skeletons. The oxygen isotope signal exhibits a long-term increase of δ18O from a mean value of about −8‰ (PDB) in the Cambrian to a present mean value of about 0‰ (PDB). Superimposed on the general trend are shorter-term oscillations with their apexes coincident with cold episodes and glaciations. The carbon isotope signal shows a similar climb during the Paleozoic, an inflexion in the Permian, followed by an abrupt drop and subsequent fluctuations around the modern value. The 87Sr/86Sr ratios differ from the earlier published curves in their greater detail and in less dispersion of the data. The means of the observed isotope signals for 87Sr/86Sr, δ18O, δ13C and the less complete δ34S (sulfate) are strongly interrelated at any geologically reasonable (1 to 40 Ma) time resolution. All correlations are valid at the 95% level of confidence, with the most valid at the 99% level. Factor analysis indicates that the 87Sr/86Sr, δ18O, δ13C and δ34S isotope systems are driven by three factors. The first factor links oxygen and strontium isotopic evolution, the second 87Sr/86Sr and δ34S, and the third one the δ13C and δ34S. These three factors explain up to 79% of the total variance. We tentatively identify the first two factors as tectonic, and the third one as a (biologically mediated) redox linkage of the sulfur and carbon cycles. On geological timescales (≥1 Ma), we are therefore dealing with a unified exogenic (litho-, hydro-, atmo-, biosphere) system driven by tectonics via its control of (bio)geochemical cycles.