CCDC 1978291: Experimental Crystal Structure Determination;Normand, Adrien T.;2020;Cambridge Crystallographic Data Centre


CCDC 1978295: Experimental Crystal Structure Determination;Normand, Adrien T.;2020;Cambridge Crystallographic Data Centre

Related Article: Adrien T. Normand, Raluca Malacea-Kabbara, Rosita Lapenta, Aymeric Dajnak, Philippe Richard, Hélène Cattey, Anaëlle Bolley, Alfonso Grassi, Stefano Milione, Audrey Auffrant, Samuel Dagorne, Pierre Le Gendre|2020|Dalton Trans.|49|6989|doi:10.1039/D0DT00972E


CCDC 1980213: Experimental Crystal Structure Determination;Longhi, Elena;2020;Cambridge Crystallographic Data Centre

bis[2-(benzo[k]phenanthridin-6-yl)phenyl]-(pyridine-2-carboxylato)-iridium(iii) diethyl ether solvate

Related Article: Elena Longhi, Jesus M. Fernandez-Hernandez, Adriana Iordache, Roland Fröhlich, Hans-Peter Josel, Luisa De Cola|2020|Inorg.Chem.|59|7435|doi:10.1021/acs.inorgchem.0c00107


CCDC 1978294: Experimental Crystal Structure Determination;Normand, Adrien T.;2020;Cambridge Crystallographic Data Centre


CCDC 1980214: Experimental Crystal Structure Determination;Longhi, Elena;2020;Cambridge Crystallographic Data Centre


CCDC 1999611: Experimental Crystal Structure Determination;Romo-Islas, Guillermo;2020;Cambridge Crystallographic Data Centre

Related Article: Guillermo Romo-Islas, Guillermo Moreno-Alcántar, Marcos Flores-Álamo, Hugo Torrens|2020|J.Fluorine Chem.|236|109578|doi:10.1016/j.jfluchem.2020.109578


CCDC 1987948: Experimental Crystal Structure Determination;Ristić, Predrag;2020;Cambridge Crystallographic Data Centre

Related Article: Predrag Ristić, Tamara R. Todorović, Vladimir Blagojević, Olivera R. Klisurić, Ivana Marjanović, Berta Barta Holló, Predrag Vulić, Mihaela Gulea, Morgan Donnard, Miguel Monge, María Rodríguez-Castillo, José M. López-de-Luzuriaga, Nenad R. Filipović|2020|Cryst.Growth Des.|20|4461|doi:10.1021/acs.cgd.0c00287


CCDC 1990303: Experimental Crystal Structure Determination;Ristić, Predrag;2020;Cambridge Crystallographic Data Centre


CCDC 1981706: Experimental Crystal Structure Determination;Wei, Yi;2020;Cambridge Crystallographic Data Centre

Related Article: Yi Wei, Abing Duan, Pan-Ting Tang, Jia-Wei Li, Rou-Ming Peng, Zheng-Xin Zhou, Xiao-Peng Luo, Mohamedally Kurmoo, Yue-Jin Liu, Ming-Hua Zeng|2020|Org.Lett.|22|4129|doi:10.1021/acs.orglett.0c01208


CCDC 1999614: Experimental Crystal Structure Determination;Romo-Islas, Guillermo;2020;Cambridge Crystallographic Data Centre


CCDC 1999613: Experimental Crystal Structure Determination;Romo-Islas, Guillermo;2020;Cambridge Crystallographic Data Centre


CCDC 1969979: Experimental Crystal Structure Determination;Brzechwa-Chodzyńska, Anna;2020;Cambridge Crystallographic Data Centre

tris[5-([2,2'-bipyridin]-5-yl)pyrimidin-2-amine]-iron(ii) hemikis(hexafluoridosilicate) tetrafluoroborate hexahydrate

Related Article: Anna Brzechwa-Chodzyńska, Michał Zieliński, Mirosław Gilski, Jack M. Harrowfield, Artur R. Stefankiewicz|2020|Inorg.Chem.|59|8552|doi:10.1021/acs.inorgchem.0c01019


CCDC 1906977: Experimental Crystal Structure Determination;Ren, Yufeng;2020;Cambridge Crystallographic Data Centre

Related Article: Yufeng Ren, Jeremy Forté, Khaled Cheaib, Nicolas Vanthuyne, Louis Fensterbank, Hervé Vezin, Maylis Orio, Sébastien Blanchard, Marine Desage-El Murr|2020|iScience|23|100955|doi:10.1016/j.isci.2020.100955


CCDC 1906978: Experimental Crystal Structure Determination;Ren, Yufeng;2020;Cambridge Crystallographic Data Centre


CCDC 1983289: Experimental Crystal Structure Determination;Liu, Chun-Yu;2020;Cambridge Crystallographic Data Centre

Related Article: Chun-Yu Liu, Xu-Ran Chen, Hui-Xian Chen, Zheng Niu, Hajime Hirao, Pierre Braunstein, Jian-Ping Lang|2020|J.Am.Chem.Soc.|142|6690|doi:10.1021/jacs.0c00368


CCDC 1983290: Experimental Crystal Structure Determination;Liu, Chun-Yu;2020;Cambridge Crystallographic Data Centre


CCDC 1898825: Experimental Crystal Structure Determination;Ovsyannikov, A. S.;2020;Cambridge Crystallographic Data Centre

Related Article: A. S. Ovsyannikov, I. V. Khariushin, S. E. Solovieva, I. S. Antipin, H. Komiya, N. Marets, H. Tanaka, H. Ohmagari, M. Hasegawa, J. J. Zakrzewski, S. Chorazy, N. Kyritsakas, M. W. Hosseini, S. Ferlay|2020|RSC Advances|10|11755|doi:10.1039/D0RA01263G


CCDC 1898826: Experimental Crystal Structure Determination;Ovsyannikov, A. S.;2020;Cambridge Crystallographic Data Centre


CCDC 1991271: Experimental Crystal Structure Determination;Zazouli, S.;2020;Cambridge Crystallographic Data Centre

Related Article: S. Zazouli, M. Chigr, A. Jouaiti, N. Kyritsakas, E.M. Ketatni|2020|Acta Crystallogr.,Sect.E:Cryst.Commun.|76|576|doi:10.1107/S2056989020003965


CCDC 1966912: Experimental Crystal Structure Determination;Ristić, Predrag;2020;Cambridge Crystallographic Data Centre

Related Article: Predrag Ristić, Vladimir Blagojević, Goran Janjić, Marko Rodić, Predrag Vulić, Morgan Donnard, Mihaela Gulea, Agnieszka Chylewska, Mariusz Makowski, Tamara Todorović, Nenad Filipović|2020|Cryst.Growth Des.|20|3018|doi:10.1021/acs.cgd.9b01661


CCDC 1966913: Experimental Crystal Structure Determination;Ristić, Predrag;2020;Cambridge Crystallographic Data Centre


CCDC 1966073: Experimental Crystal Structure Determination;Frey, Johanna;2020;Cambridge Crystallographic Data Centre

Related Article: Johanna Frey, Alaleh Malekafzali, Isabel Delso, Sabine Choppin, Françoise Colobert, Joanna Wencel-Delord|2020|Angew.Chem.,Int.Ed.|59|8844|doi:10.1002/anie.201914876


CCDC 1565996: Experimental Crystal Structure Determination;Balaji, Sundarraman;2020;Cambridge Crystallographic Data Centre

Related Article: Sundarraman Balaji, Mohamed Kasim Mohamed Subarkhan, Rengan Ramesh, Hangxiang Wang, David Semeril|2020|Organometallics|39|1366|doi:10.1021/acs.organomet.0c00092


CCDC 1833167: Experimental Crystal Structure Determination;Balaji, Sundarraman;2020;Cambridge Crystallographic Data Centre


CCDC 1949765: Experimental Crystal Structure Determination;Boussadia, Ahlem;2020;Cambridge Crystallographic Data Centre

Related Article: Ahlem Boussadia, Adel Beghidja, Lynda Gali, Chahrazed Beghidja, Mourad Elhabiri, Pierre Rabu, Guillaume Rogez|2020|Inorg.Chim.Acta|508|119656|doi:10.1016/j.ica.2020.119656


CCDC 1949766: Experimental Crystal Structure Determination;Boussadia, Ahlem;2020;Cambridge Crystallographic Data Centre


CCDC 1949764: Experimental Crystal Structure Determination;Boussadia, Ahlem;2020;Cambridge Crystallographic Data Centre


CCDC 1949768: Experimental Crystal Structure Determination;Boussadia, Ahlem;2020;Cambridge Crystallographic Data Centre


CCDC 1966028: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre

Related Article: Pierre Thuéry, Youssef Atoini, Jack Harrowfield|2020|Inorg.Chem.|59|2503|doi:10.1021/acs.inorgchem.9b03404


CCDC 1966029: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1966030: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1966031: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1966032: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1966033: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1966034: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1966035: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1966036: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1966037: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1966038: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1966039: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre

catena-(bis(guanidinium) tris(mu-2,2'-(1,2-phenylene)diacetato)-tetraoxo-di-uranium acetonitrile solvate hemihydrate)


CCDC 1966040: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1966041: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1966042: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1966043: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1979590: Experimental Crystal Structure Determination;Gafurov, Zufar N.;2020;Cambridge Crystallographic Data Centre

Related Article: Zufar N. Gafurov, Giyjaz E. Bekmukhamedov, Alexey A. Kagilev, Artyom O. Kantyukov, Il'yas F. Sakhapov, Ilya K. Mikhailov, Khasan R. Khayarov, Ruslan B. Zaripov, Daut R. Islamov, Konstantin S. Usachev, Lapo Luconi, Andrea Rossin, Giuliano Giambastiani, Dmitry G. Yakhvarov|2020|J.Organomet.Chem.|912|121163|doi:10.1016/j.jorganchem.2020.121163


CCDC 1887201: Experimental Crystal Structure Determination;Li, Jia-Wei;2020;Cambridge Crystallographic Data Centre

Related Article: Jia-Wei Li, Liang-Neng Wang, Ming Li, Pan-Ting Tang, Ni-Juan Zhang, Tian Li, Xiao-Peng Luo, Mohamedally Kurmoo, Yue-Jin Liu, Ming-Hua Zeng|2020|Org.Lett.|22|1331|doi:10.1021/acs.orglett.9b04590


CCDC 1887202: Experimental Crystal Structure Determination;Li, Jia-Wei;2020;Cambridge Crystallographic Data Centre


CCDC 1887203: Experimental Crystal Structure Determination;Li, Jia-Wei;2020;Cambridge Crystallographic Data Centre


CCDC 1887204: Experimental Crystal Structure Determination;Li, Jia-Wei;2020;Cambridge Crystallographic Data Centre


CCDC 1889125: Experimental Crystal Structure Determination;Li, Jia-Wei;2020;Cambridge Crystallographic Data Centre


CCDC 1968987: Experimental Crystal Structure Determination;Gu, Yaqi;2020;Cambridge Crystallographic Data Centre

Related Article: Yaqi Gu, Qi Li, Yichao Huang, Yingting Zhu, Yongge Wei, Laurent Ruhlmann|2020|Chem.Commun.|56|2869|doi:10.1039/C9CC09944A


CCDC 1895362: Experimental Crystal Structure Determination;Tufenkjian, Elsa;2020;Cambridge Crystallographic Data Centre

Related Article: Elsa Tufenkjian, Abdelaziz Jouaiti, Nathalie Kyritsakas, Mir Wais Hosseini, Veronique Bulach
|2020|Tetrahedron|76|130966|doi:10.1016/j.tet.2020.130966


CCDC 1895363: Experimental Crystal Structure Determination;Tufenkjian, Elsa;2020;Cambridge Crystallographic Data Centre


CCDC 1895366: Experimental Crystal Structure Determination;Tufenkjian, Elsa;2020;Cambridge Crystallographic Data Centre


CCDC 1950409: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre

Related Article: Eric J. Chan, Jack M. Harrowfield, Brian W. Skelton, Allan H. White|2020|Aust.J.Chem.|73|539|doi:10.1071/CH19506


CCDC 1950410: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 1950411: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 1950412: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 1950414: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 1950413: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 1950415: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 1950416: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 1950417: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 1950418: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 1950419: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 1950420: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 1950421: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 1950422: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 1950423: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 1946675: Experimental Crystal Structure Determination;Jouaiti, Abdelaziz;2020;Cambridge Crystallographic Data Centre

catena-((mu-cyclohexane-1,2-diyl bis(pyridine-4-carboxylate))-dichloro-mercury chloroform solvate)

Related Article: Abdelaziz Jouaiti, Philippe Grosshans, Nathalie Kyritsakas, Sylvie Ferlay, Marc Henry, Mir Wais Hosseini|2020|CrystEngComm|22|1746|doi:10.1039/C9CE01781J


CCDC 1949896: Experimental Crystal Structure Determination;Jouaiti, Abdelaziz;2020;Cambridge Crystallographic Data Centre


CCDC 1869404: Experimental Crystal Structure Determination;Pavlik, Ján;2020;Cambridge Crystallographic Data Centre

Related Article: Ján Pavlik, Petra Masárová, Ivan Nemec, Olaf Fuhr, Mario Ruben, Ivan Šalitroš|2020|Inorg.Chem.|59|2747|doi:10.1021/acs.inorgchem.9b03097


CCDC 1954726: Experimental Crystal Structure Determination;Pavlik, Ján;2020;Cambridge Crystallographic Data Centre


CCDC 1963751: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre

Related Article: Pierre Thuéry, Youssef Atoini, Jack Harrowfield|2020|Inorg.Chem.|59|2923|doi:10.1021/acs.inorgchem.9b03273


CCDC 1963749: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1963750: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1963752: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1963753: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1963754: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1963755: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1963756: Experimental Crystal Structure Determination;Thuéry, Pierre;2020;Cambridge Crystallographic Data Centre


CCDC 1955628: Experimental Crystal Structure Determination;Pertschi, Romain;2020;Cambridge Crystallographic Data Centre

Related Article: Romain Pertschi, Delphine Hatey, Patrick Pale, Pierre de Frémont, Aurélien Blanc|2020|Organometallics|39|804|doi:10.1021/acs.organomet.9b00850


CCDC 1957068: Experimental Crystal Structure Determination;Chen, Weiguang;2020;Cambridge Crystallographic Data Centre

Related Article: Weiguang Chen, Julien Egly, Amalia I. Poblador-Bahamonde, Aline Maisse-Francois, Stéphane Bellemin-Laponnaz, Thierry Achard|2020|Dalton Trans.|49|3243|doi:10.1039/C9DT04825A


CCDC 1957070: Experimental Crystal Structure Determination;Chen, Weiguang;2020;Cambridge Crystallographic Data Centre


CCDC 1973530: Experimental Crystal Structure Determination;Bonfiglio, Anna;2020;Cambridge Crystallographic Data Centre

Related Article: Anna Bonfiglio, Kévin Magra, Cristina Cebrián, Federico Polo, Philippe C. Gros, Pierluigi Mercandelli, Matteo Mauro|2020|Dalton Trans.|49|3102|doi:10.1039/C9DT04890A


CCDC 1966328: Experimental Crystal Structure Determination;Craig, Gavin A.;2020;Cambridge Crystallographic Data Centre

Related Article: Gavin A. Craig, Patrick Larpent, Hinano Urabe, Alexandre Legrand, Mickaele Bonneau, Shinpei Kusaka, Shuhei Furukawa|2020|Chem.Commun.|56|3689|doi:10.1039/D0CC00932F


CCDC 1966329: Experimental Crystal Structure Determination;Craig, Gavin A.;2020;Cambridge Crystallographic Data Centre


CCDC 1980932: Experimental Crystal Structure Determination;Bonfiglio, Anna;2020;Cambridge Crystallographic Data Centre


CCDC 1943588: Experimental Crystal Structure Determination;Su, Qian-Qian;2020;Cambridge Crystallographic Data Centre

Related Article: Qian-Qian Su, Kun Fan, Xin-Da Huang, Jing Xiang, Shun-Cheung Cheng, Chi-Chiu Ko, Li-Min Zheng, Mohamedally Kurmoo, Tai-Chu Lau|2020|Dalton Trans.|49|4084|doi:10.1039/D0DT00295J


CCDC 1943589: Experimental Crystal Structure Determination;Su, Qian-Qian;2020;Cambridge Crystallographic Data Centre


CCDC 1859259: Experimental Crystal Structure Determination;Gosset, Alexis;2020;Cambridge Crystallographic Data Centre

4,4'-(naphthalene-1,8-diyl)bis(1-methylpyridin-1-ium) bis(hexafluorophosphate) acetonitrile solvate

Related Article: Alexis Gosset,  Liam Wilbraham,  Štěpánka Nováková Lachmanová,  Romana Sokolová,  Grégory Dupeyre,  Fabien Tuyèras,  Philippe Ochsenbein,  Christian Perruchot,  Henri-Pierre Jacquot de Rouville,  Hyacinthe Randriamahazaka,  Lubomír Pospíšil,  Ilaria Ciofini,  Magdaléna Hromadová,  Philippe P. Lainé|2020|J.Am.Chem.Soc.|142|5162|doi:10.1021/jacs.9b12762


CCDC 1859260: Experimental Crystal Structure Determination;Gosset, Alexis;2020;Cambridge Crystallographic Data Centre


CCDC 1912134: Experimental Crystal Structure Determination;Gosset, Alexis;2020;Cambridge Crystallographic Data Centre


CCDC 1947521: Experimental Crystal Structure Determination;Ayme, Jean-François;2020;Cambridge Crystallographic Data Centre

Related Article: Jean-François Ayme,  Jean-Marie Lehn,  Corinne Bailly,  Lydia Karmazin|2020|J.Am.Chem.Soc.|142|5819|doi:10.1021/jacs.0c00896


CCDC 1947518: Experimental Crystal Structure Determination;Ayme, Jean-François;2020;Cambridge Crystallographic Data Centre


CCDC 1947520: Experimental Crystal Structure Determination;Ayme, Jean-François;2020;Cambridge Crystallographic Data Centre

tetrakis(mu-(4,7-phenanthroline-3,8-diyl)bis{N-[(2-methoxyphenyl)methyl]methanimine})-tetra-copper tetrakis(tetraphenylborate) benzene unknown solvate


CCDC 1947519: Experimental Crystal Structure Determination;Ayme, Jean-François;2020;Cambridge Crystallographic Data Centre

bis(mu-[ethane-1,2-diylbis(pyridine-5,2-diyl)]bis[N-(2-methylquinolin-8-yl)methanimine])-di-iron(ii) tetrakis(hexafluorophosphate) acetonitrile unknown solvate


CCDC 1942809: Experimental Crystal Structure Determination;Godde, B.;2020;Cambridge Crystallographic Data Centre

Related Article: B. Godde, S. Ferlay, N. Kyritsakas, M.W. Hosseini, A. Jouaiti|2020|Inorg.Chim.Acta|503|119427|doi:10.1016/j.ica.2020.119427


CCDC 1942811: Experimental Crystal Structure Determination;Godde, B.;2020;Cambridge Crystallographic Data Centre


CCDC 1942812: Experimental Crystal Structure Determination;Godde, B.;2020;Cambridge Crystallographic Data Centre


CCDC 1942813: Experimental Crystal Structure Determination;Godde, B.;2020;Cambridge Crystallographic Data Centre


CCDC 1585211: Experimental Crystal Structure Determination;Zhang, Yu‐Yi;2020;Cambridge Crystallographic Data Centre

tetrakis(mu-1,2-bis(1H-benzimidazol-2-yl)ethane-1,2-diol)-dichloro-tetra-manganese dichloride methanol solvate pentahydrate

Related Article: Yu‐Yi Zhang, De‐Shan Zhang, Tian Li, Mohamedally Kurmoo, Ming‐Hua Zeng|2020|Chem.-Eur.J.|26|721|doi:10.1002/chem.201904128


CCDC 1585215: Experimental Crystal Structure Determination;Zhang, Yu‐Yi;2020;Cambridge Crystallographic Data Centre


CCDC 1870950: Experimental Crystal Structure Determination;Plá, Jessica M. López;2020;Cambridge Crystallographic Data Centre

Related Article: Jessica M. López Plá, Athanassios K. Boudalis, Joshua Telser, Raphael G. Raptis|2020|Inorg.Chim.Acta|502|119299|doi:10.1016/j.ica.2019.119299


CCDC 1915924: Experimental Crystal Structure Determination;Hu, Zhao-Bo;2020;Cambridge Crystallographic Data Centre

Related Article: Zhao-Bo Hu, Xin Feng, Jing Li, Yi-Quan Zhang, Lei Yin, Zhenxing Wang, Zhongwen Ouyang, Mohamedally Kurmoo, You Song|2020|Dalton Trans.|49|2159|doi:10.1039/C9DT04403E


CCDC 1973791: Experimental Crystal Structure Determination;Bechu, Damien;2020;Cambridge Crystallographic Data Centre

Related Article: Damien Bechu, Lilia S. Xie, Nolwenn Le Breton, Sylvie Choua, Mircea Dincă, Mir Wais Hosseini, Stéphane A. Baudron|2020|Chem.Commun.|56|2407|doi:10.1039/C9CC09960C


CCDC 1973792: Experimental Crystal Structure Determination;Bechu, Damien;2020;Cambridge Crystallographic Data Centre


CCDC 1973793: Experimental Crystal Structure Determination;Bechu, Damien;2020;Cambridge Crystallographic Data Centre


CCDC 1955230: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre

Related Article: Xiaoyu Ren,  Marcel Wesolek,  Corinne Bailly,  Lydia Karmazin,  and Pierre Braunstein|2019|Eur.J.Inorg.Chem.|2019|1073|doi:10.1002/ejic.201901064


CCDC 1955231: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1955232: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1955234: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1955235: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1955236: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1955239: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1955240: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1955241: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1955242: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1955243: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1956078: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1955233: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1955237: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


Related Article: Paulo H. S. Paioti, Juan del Pozo, Malte S. Mikus, Jaehee Lee, Ming Joo Koh, Filippo Romiti, Sebastian Torker, Amir H. Hoveyda|2019|J.Am.Chem.Soc.|141|19917|doi:10.1021/jacs.9b11382

CCDC 1960817: Experimental Crystal Structure Determination;Paioti, Paulo H. S.;2019;Cambridge Crystallographic Data Centre


CCDC 1960818: Experimental Crystal Structure Determination;Paioti, Paulo H. S.;2019;Cambridge Crystallographic Data Centre


CCDC 1960831: Experimental Crystal Structure Determination;Paioti, Paulo H. S.;2019;Cambridge Crystallographic Data Centre


CCDC 1960832: Experimental Crystal Structure Determination;Paioti, Paulo H. S.;2019;Cambridge Crystallographic Data Centre


CCDC 1960833: Experimental Crystal Structure Determination;Paioti, Paulo H. S.;2019;Cambridge Crystallographic Data Centre


Related Article: Pierre Thuéry, Youssef Atoini, Jack Harrowfield|2018|Cryst.Growth Des.|18|2609|doi:10.1021/acs.cgd.8b00250

CCDC 1822640: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1822638: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1822641: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1822642: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1822637: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


catena-[tetraphenylphosphonium (mu-cyclohexane-1,4-dicarboxylato)-(nitrato)-dioxo-uranium acetonitrile solvate]

CCDC 1822639: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1822643: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


Related Article: Kuppusamy Senthil Kumar, Sergi Vela, Benoît Heinrich, Nithin Suryadevara, Lydia Karmazin, Corinne Bailly, Mario Ruben|2020|Dalton Trans.|49|1022|doi:10.1039/C9DT04411F

CCDC 1839481: Experimental Crystal Structure Determination;Kumar, Kuppusamy Senthil;2019;Cambridge Crystallographic Data Centre


bis[4-(pyren-1-yl)butyl 2-(1H-pyrazol-1-yl)-6-(1H-tetrazol-5-yl)pyridine-4-carboxylatato]-iron methanol unknown solvate

CCDC 1407913: Experimental Crystal Structure Determination;Kumar, Kuppusamy Senthil;2019;Cambridge Crystallographic Data Centre


Related Article: Félicien Beaubras, Jean-Michel Rueff, Olivier Perez, Fabien Veillon, Vincent Caignaert, Jean-François Lohier, Julien Cardin, Guillaume Rogez, Charlotte Jestin, Hélène Couthon, Paul-Alain Jaffrès|2020|Dalton Trans.|49|3877|doi:10.1039/C9DT03947C

CCDC 1956355: Experimental Crystal Structure Determination;Beaubras, Félicien;2019;Cambridge Crystallographic Data Centre


CCDC 1956356: Experimental Crystal Structure Determination;Beaubras, Félicien;2019;Cambridge Crystallographic Data Centre


CCDC 1956357: Experimental Crystal Structure Determination;Beaubras, Félicien;2019;Cambridge Crystallographic Data Centre


bis[methyl 2-(1H-pyrazol-1-yl)-6-(1H-tetrazol-5-yl)pyridine-4-carboxylatato]-zinc(ii) methanol solvate

CCDC 1957514: Experimental Crystal Structure Determination;Kumar, Kuppusamy Senthil;2019;Cambridge Crystallographic Data Centre


Related Article: Pierre Thuéry, Youssef Atoini, Jack Harrowfield|2020|Dalton Trans.|49|817|doi:10.1039/C9DT04126E

CCDC 1958810: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1958811: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1958812: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1958813: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1958814: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1958815: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1958816: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1958817: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1958818: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


Related Article: Lucía Álvarez-Miguel, Inés Álvarez-Miguel, Jose M. Martín-Álvarez, Celedonio M. Álvarez, Guillaume Rogez, Raúl García-Rodríguez, Daniel Miguel|2019|Dalton Trans.|48|17544|doi:10.1039/C9DT03822A

CCDC 1491835: Experimental Crystal Structure Determination;Álvarez-Miguel, Lucía;2019;Cambridge Crystallographic Data Centre


CCDC 1955681: Experimental Crystal Structure Determination;Álvarez-Miguel, Lucía;2019;Cambridge Crystallographic Data Centre


CCDC 1955683: Experimental Crystal Structure Determination;Álvarez-Miguel, Lucía;2019;Cambridge Crystallographic Data Centre


CCDC 1491837: Experimental Crystal Structure Determination;Álvarez-Miguel, Lucía;2019;Cambridge Crystallographic Data Centre


CCDC 1491838: Experimental Crystal Structure Determination;Álvarez-Miguel, Lucía;2019;Cambridge Crystallographic Data Centre


CCDC 1955682: Experimental Crystal Structure Determination;Álvarez-Miguel, Lucía;2019;Cambridge Crystallographic Data Centre


CCDC 1491836: Experimental Crystal Structure Determination;Álvarez-Miguel, Lucía;2019;Cambridge Crystallographic Data Centre


CCDC 1491839: Experimental Crystal Structure Determination;Álvarez-Miguel, Lucía;2019;Cambridge Crystallographic Data Centre


CCDC 1491840: Experimental Crystal Structure Determination;Álvarez-Miguel, Lucía;2019;Cambridge Crystallographic Data Centre


CCDC 1491841: Experimental Crystal Structure Determination;Álvarez-Miguel, Lucía;2019;Cambridge Crystallographic Data Centre


CCDC 1955678: Experimental Crystal Structure Determination;Álvarez-Miguel, Lucía;2019;Cambridge Crystallographic Data Centre


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CCDC 1960543: Experimental Crystal Structure Determination;Noel, Florent;2019;Cambridge Crystallographic Data Centre


CCDC 1960571: Experimental Crystal Structure Determination;Noel, Florent;2019;Cambridge Crystallographic Data Centre


Related Article: Jovana V. Milić, Cédric Schaack, Nora Hellou, Florin Isenrich, Renana Gershoni-Poranne, Dmytro Neshchadin, Sylvain Egloff, Nils Trapp, Laurent Ruhlmann, Corinne Boudon, Georg Gescheidt, Jeanne Crassous, François Diederich

|2018|J.Phys.Chem.C|122|19100|doi:10.1021/acs.jpcc.8b05019

CCDC 1535912: Experimental Crystal Structure Determination;Milić, Jovana V.;2019;Cambridge Crystallographic Data Centre


CCDC 1535919: Experimental Crystal Structure Determination;Milić, Jovana V.;2019;Cambridge Crystallographic Data Centre


CCDC 1535918: Experimental Crystal Structure Determination;Milić, Jovana V.;2019;Cambridge Crystallographic Data Centre


(allyl)-[1,3-bis(5-diphenylphosphino-25,26,27,28-tetrapropoxy-calix[4]aren-17-yl)benzene]-palladium(ii) tetrafluoroborate dichloromethane pentane solvate

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CCDC 768418: Experimental Crystal Structure Determination;Elaieb, Fethi;2019;Cambridge Crystallographic Data Centre


CCDC 771989: Experimental Crystal Structure Determination;Elaieb, Fethi;2019;Cambridge Crystallographic Data Centre


Related Article: Morgane Diebold, Elliot Christ, Laure Biniek, Lydia Karmazin, Benoît Heinrich, Christophe Contal, Suhrit Ghosh, Philippe J. Mesini, Martin Brinkmann|2019|J.Mater.Chem.C|7|13120|doi:10.1039/C9TC04402G

CCDC 1867282: Experimental Crystal Structure Determination;Diebold, Morgane;2019;Cambridge Crystallographic Data Centre


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CCDC 1950509: Experimental Crystal Structure Determination;Thuery, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1950510: Experimental Crystal Structure Determination;Thuery, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1950511: Experimental Crystal Structure Determination;Thuery, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1950512: Experimental Crystal Structure Determination;Thuery, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1950513: Experimental Crystal Structure Determination;Thuery, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1950514: Experimental Crystal Structure Determination;Thuery, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1950515: Experimental Crystal Structure Determination;Thuery, Pierre;2019;Cambridge Crystallographic Data Centre


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CCDC 1947980: Experimental Crystal Structure Determination;Miller, Jessica J.;2019;Cambridge Crystallographic Data Centre


CCDC 1947981: Experimental Crystal Structure Determination;Miller, Jessica J.;2019;Cambridge Crystallographic Data Centre


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CCDC 1950706: Experimental Crystal Structure Determination;Wang, Zhi;2019;Cambridge Crystallographic Data Centre


CCDC 1950707: Experimental Crystal Structure Determination;Wang, Zhi;2019;Cambridge Crystallographic Data Centre


CCDC 1950708: Experimental Crystal Structure Determination;Wang, Zhi;2019;Cambridge Crystallographic Data Centre


CCDC 1950709: Experimental Crystal Structure Determination;Wang, Zhi;2019;Cambridge Crystallographic Data Centre


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CCDC 1946047: Experimental Crystal Structure Determination;Liao, Chwen-Haw;2019;Cambridge Crystallographic Data Centre


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CCDC 1844907: Experimental Crystal Structure Determination;Wu, Yan Fang;2019;Cambridge Crystallographic Data Centre


CCDC 1563168: Experimental Crystal Structure Determination;Wu, Yan Fang;2019;Cambridge Crystallographic Data Centre


CCDC 1563177: Experimental Crystal Structure Determination;Wu, Yan Fang;2019;Cambridge Crystallographic Data Centre


CCDC 1563186: Experimental Crystal Structure Determination;Wu, Yan Fang;2019;Cambridge Crystallographic Data Centre


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CCDC 1890732: Experimental Crystal Structure Determination;Wang, Wenqing;2019;Cambridge Crystallographic Data Centre


CCDC 1924068: Experimental Crystal Structure Determination;Wang, Wenqing;2019;Cambridge Crystallographic Data Centre


Related Article: Damien Bechu, Guillaume Rogez, Mir Wais Hosseini, Stéphane A. Baudron|2019|New J.Chem.|43|14291|doi:10.1039/C9NJ03572A

CCDC 1917164: Experimental Crystal Structure Determination;Bechu, Damien;2019;Cambridge Crystallographic Data Centre


CCDC 1917170: Experimental Crystal Structure Determination;Bechu, Damien;2019;Cambridge Crystallographic Data Centre


CCDC 1917171: Experimental Crystal Structure Determination;Bechu, Damien;2019;Cambridge Crystallographic Data Centre


CCDC 1917172: Experimental Crystal Structure Determination;Bechu, Damien;2019;Cambridge Crystallographic Data Centre


CCDC 1917165: Experimental Crystal Structure Determination;Bechu, Damien;2019;Cambridge Crystallographic Data Centre


CCDC 1917166: Experimental Crystal Structure Determination;Bechu, Damien;2019;Cambridge Crystallographic Data Centre


CCDC 1917167: Experimental Crystal Structure Determination;Bechu, Damien;2019;Cambridge Crystallographic Data Centre


CCDC 1917168: Experimental Crystal Structure Determination;Bechu, Damien;2019;Cambridge Crystallographic Data Centre


CCDC 1917169: Experimental Crystal Structure Determination;Bechu, Damien;2019;Cambridge Crystallographic Data Centre


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CCDC 1911386: Experimental Crystal Structure Determination;Le Fouler, Vincent;2019;Cambridge Crystallographic Data Centre


CCDC 1911387: Experimental Crystal Structure Determination;Le Fouler, Vincent;2019;Cambridge Crystallographic Data Centre


CCDC 1911671: Experimental Crystal Structure Determination;Le Fouler, Vincent;2019;Cambridge Crystallographic Data Centre


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CCDC 1938540: Experimental Crystal Structure Determination;Huang, Xin-Da;2019;Cambridge Crystallographic Data Centre


CCDC 1938541: Experimental Crystal Structure Determination;Huang, Xin-Da;2019;Cambridge Crystallographic Data Centre


CCDC 1938542: Experimental Crystal Structure Determination;Huang, Xin-Da;2019;Cambridge Crystallographic Data Centre


CCDC 1938543: Experimental Crystal Structure Determination;Huang, Xin-Da;2019;Cambridge Crystallographic Data Centre


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CCDC 1916787: Experimental Crystal Structure Determination;Filipović, Nenad R.;2019;Cambridge Crystallographic Data Centre


Related Article: Snežana K. Bjelogrlić, Tamara R. Todorović, Milan Kojić, Milan Senćanski, Milan Nikolić, Aleksandar Višnjevac, Jovana Araškov, Marija Miljković, Christian D. Muller, Nenad R. Filipović|2019|J.Inorg.Biochem.|199|110758|doi:10.1016/j.jinorgbio.2019.110758

CCDC 1847413: Experimental Crystal Structure Determination;Bjelogrlić, Snežana K.;2019;Cambridge Crystallographic Data Centre


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CCDC 1883896: Experimental Crystal Structure Determination;Elahi, Syed Meheboob;2019;Cambridge Crystallographic Data Centre


CCDC 1883897: Experimental Crystal Structure Determination;Elahi, Syed Meheboob;2019;Cambridge Crystallographic Data Centre


Related Article: Emilie Macker, Laurent Barloy, Alain Chaumont, Nathalie Kyritsakas, Bruno Vincent, Marc Henry, Pierre Mobian|2019|Inorg.Chim.Acta|498|119119|doi:10.1016/j.ica.2019.119119

CCDC 1916728: Experimental Crystal Structure Determination;Macker, Emilie;2019;Cambridge Crystallographic Data Centre


CCDC 1883894: Experimental Crystal Structure Determination;Elahi, Syed Meheboob;2019;Cambridge Crystallographic Data Centre


Related Article: Pierre Thuéry, Youssef Atoini, Jack Harrowfield|2019|Cryst.Growth Des.|19|6611|doi:10.1021/acs.cgd.9b01032

CCDC 1944962: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1944963: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1944964: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1944965: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1944966: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1944969: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1944967: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1944968: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1944971: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1944972: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1944970: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1944973: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1944974: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1944975: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


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CCDC 1901442: Experimental Crystal Structure Determination;Su, Yan-Hui;2019;Cambridge Crystallographic Data Centre


Related Article: Sheng-Bo Liu, Xin-Da Huang, Song-Song Bao, Mohamedally Kurmoo, Li-Min Zheng|2019|Cryst.Growth Des.|19|4836|doi:10.1021/acs.cgd.9b00827

CCDC 1883132: Experimental Crystal Structure Determination;Liu, Sheng-Bo;2019;Cambridge Crystallographic Data Centre


CCDC 1883134: Experimental Crystal Structure Determination;Liu, Sheng-Bo;2019;Cambridge Crystallographic Data Centre


CCDC 1883133: Experimental Crystal Structure Determination;Liu, Sheng-Bo;2019;Cambridge Crystallographic Data Centre


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CCDC 1897946: Experimental Crystal Structure Determination;Sun, Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1896866: Experimental Crystal Structure Determination;Sun, Yu;2019;Cambridge Crystallographic Data Centre


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CCDC 1875502: Experimental Crystal Structure Determination;Sodreau, Alexandre;2019;Cambridge Crystallographic Data Centre


CCDC 1875503: Experimental Crystal Structure Determination;Sodreau, Alexandre;2019;Cambridge Crystallographic Data Centre


CCDC 1875504: Experimental Crystal Structure Determination;Sodreau, Alexandre;2019;Cambridge Crystallographic Data Centre


CCDC 1875505: Experimental Crystal Structure Determination;Sodreau, Alexandre;2019;Cambridge Crystallographic Data Centre


CCDC 1875506: Experimental Crystal Structure Determination;Sodreau, Alexandre;2019;Cambridge Crystallographic Data Centre


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CCDC 1856447: Experimental Crystal Structure Determination;L’Her, Matthieu;2019;Cambridge Crystallographic Data Centre


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CCDC 1908303: Experimental Crystal Structure Determination;Forquin, Benjamin;2019;Cambridge Crystallographic Data Centre


CCDC 1908304: Experimental Crystal Structure Determination;Forquin, Benjamin;2019;Cambridge Crystallographic Data Centre


CCDC 1908305: Experimental Crystal Structure Determination;Forquin, Benjamin;2019;Cambridge Crystallographic Data Centre


CCDC 1908306: Experimental Crystal Structure Determination;Forquin, Benjamin;2019;Cambridge Crystallographic Data Centre


CCDC 1908307: Experimental Crystal Structure Determination;Forquin, Benjamin;2019;Cambridge Crystallographic Data Centre


CCDC 1908308: Experimental Crystal Structure Determination;Forquin, Benjamin;2019;Cambridge Crystallographic Data Centre


CCDC 1908309: Experimental Crystal Structure Determination;Forquin, Benjamin;2019;Cambridge Crystallographic Data Centre


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CCDC 1896575: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1896576: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1590360: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1896577: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1896578: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


Related Article: Zouhair Asfari, Eric J. Chan, Jack M. Harrowfield, Brian W. Skelton, Alexandre N. Sobolev, Pirrre Thuéry', Allan H. White|2020|Aust.J.Chem.|73|447|doi:10.1071/CH19169

CCDC 1907022: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


CCDC 1907023: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


CCDC 1907024: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


CCDC 1907025: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


CCDC 1907026: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


CCDC 1907027: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


CCDC 1907028: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


CCDC 1907029: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


CCDC 1907031: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


CCDC 1907030: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


CCDC 1907032: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


CCDC 1907033: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


CCDC 1907034: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


CCDC 1907035: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


CCDC 1907036: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


CCDC 1907037: Experimental Crystal Structure Determination;Asfari, Zouhair;2019;Cambridge Crystallographic Data Centre


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CCDC 1900808: Experimental Crystal Structure Determination;Wang, Zhi;2019;Cambridge Crystallographic Data Centre


CCDC 1900809: Experimental Crystal Structure Determination;Wang, Zhi;2019;Cambridge Crystallographic Data Centre


CCDC 1900810: Experimental Crystal Structure Determination;Wang, Zhi;2019;Cambridge Crystallographic Data Centre


Related Article: Lapo Luconi, Umit B. Demirci, Maurizio Peruzzini, Giuliano Giambastiani, Andrea Rossin|2019|Sustainable Energy Fuels|3|2583|doi:10.1039/C9SE00241C

CCDC 1907146: Experimental Crystal Structure Determination;Luconi, Lapo;2019;Cambridge Crystallographic Data Centre


CCDC 1907147: Experimental Crystal Structure Determination;Luconi, Lapo;2019;Cambridge Crystallographic Data Centre


CCDC 1907148: Experimental Crystal Structure Determination;Luconi, Lapo;2019;Cambridge Crystallographic Data Centre


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CCDC 1882952: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882953: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882954: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882955: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882956: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


Related Article: Jia zyh|2019|CSD Communication||| Related Article: Yan-Hui Su, Jia-Ge Jia, Xin-Da Huang, Jian-Shen Feng, Song-Song Bao, Min Ren, Mohamedally Kurmoo, Li-Min Zheng|2019|RSC Advances|55|31911|doi:10.1039/C9RA05722F

CCDC 1920728: Experimental Crystal Structure Determination;zyh, Jia;2019;Cambridge Crystallographic Data Centre


catena-[(mu-7,7,8,8-tetracyanoquinodimethane radical)-bis(mu-tetra(4-pyridyl)tetrathiafulvalene)-di-cadmium 7,7,8,8-tetracyanoquinodimethane radical bis(nitrate) dichloromethane solvate]

Related Article: Hai-Ying Wang,  Jian Su,  Jian-Ping Ma,  Fei Yu,  Chanel F. Leong,  Deanna M. D’Alessandro,  Mohamedally Kurmoo,  Jing-Lin Zuo|2019|Inorg.Chem.|58|8657|doi:10.1021/acs.inorgchem.9b01000

CCDC 1855243: Experimental Crystal Structure Determination;Wang, Hai-Ying;2019;Cambridge Crystallographic Data Centre


catena-[(mu-(1,4-phenylene)dimethanyldicarbonitrile)-bis(mu-tetra(4-pyridyl)tetrathiafulvalene)-di-cadmium 7,7,8,8-tetracyanoquinodimethane radical nitrate dichloromethane methanol solvate]

CCDC 1855246: Experimental Crystal Structure Determination;Wang, Hai-Ying;2019;Cambridge Crystallographic Data Centre


CCDC 1882937: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


bis(mu-2,2-bis[(diphenylphosphanyl)methyl]-N-phenylhydrazine-1-carbothioamide)-di-gold bis(chloride) chloroform solvate

CCDC 1882938: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882939: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882940: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882941: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882942: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882943: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882944: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882945: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882946: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882947: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882948: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882949: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


CCDC 1882950: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


bis(mu-{2-[(diphenylphosphanyl)methyl]-2-[(diphenylphosphanyl)methyl]-N-phenylhydrazine-1-carbothioamide})-di-gold(i) dichloride methanol ethanol solvate

CCDC 1882951: Experimental Crystal Structure Determination;Liu, Chun-Yu;2019;Cambridge Crystallographic Data Centre


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CCDC 1889476: Experimental Crystal Structure Determination;Kaya, Zeyneb;2019;Cambridge Crystallographic Data Centre


CCDC 1894694: Experimental Crystal Structure Determination;Kaya, Zeyneb;2019;Cambridge Crystallographic Data Centre


Related Article: Pierre Thuéry, Youssef Atoini, Jack Harrowfield
|2019|Cryst.Growth Des.|19|4109|doi:10.1021/acs.cgd.9b00546

CCDC 1911946: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1911947: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1911948: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1911949: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1911950: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1911951: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1911952: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


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CCDC 1877078: Experimental Crystal Structure Determination;Bai, Shao-Tao;2019;Cambridge Crystallographic Data Centre


CCDC 1877079: Experimental Crystal Structure Determination;Bai, Shao-Tao;2019;Cambridge Crystallographic Data Centre


Related Article: Jean-Charles Bruyere,  Christophe Gourlaouen,  Lydia Karmazin,  Corinne Bailly,  Corinne Boudon,  Laurent Ruhlmann,  Pierre de Frémont,  Samuel Dagorne|2019|Organometallics|38|2748|doi:10.1021/acs.organomet.9b00304

CCDC 1906336: Experimental Crystal Structure Determination;Bruyere, Jean-Charles;2019;Cambridge Crystallographic Data Centre


CCDC 1906341: Experimental Crystal Structure Determination;Bruyere, Jean-Charles;2019;Cambridge Crystallographic Data Centre


CCDC 1906342: Experimental Crystal Structure Determination;Bruyere, Jean-Charles;2019;Cambridge Crystallographic Data Centre


CCDC 1906343: Experimental Crystal Structure Determination;Bruyere, Jean-Charles;2019;Cambridge Crystallographic Data Centre


CCDC 1906344: Experimental Crystal Structure Determination;Bruyere, Jean-Charles;2019;Cambridge Crystallographic Data Centre


CCDC 1906345: Experimental Crystal Structure Determination;Bruyere, Jean-Charles;2019;Cambridge Crystallographic Data Centre


CCDC 1906346: Experimental Crystal Structure Determination;Bruyere, Jean-Charles;2019;Cambridge Crystallographic Data Centre


CCDC 1906347: Experimental Crystal Structure Determination;Bruyere, Jean-Charles;2019;Cambridge Crystallographic Data Centre


CCDC 1906348: Experimental Crystal Structure Determination;Bruyere, Jean-Charles;2019;Cambridge Crystallographic Data Centre


CCDC 1906349: Experimental Crystal Structure Determination;Bruyere, Jean-Charles;2019;Cambridge Crystallographic Data Centre


Related Article: Pierre Farger, Cédric Leuvrey, Guillaume Rogez, Michel François, Pierre Rabu, Emilie Delahaye|2019|Cryst.Growth Des.|19|4264|doi:10.1021/acs.cgd.8b01725

CCDC 1475567: Experimental Crystal Structure Determination;Farger, Pierre;2019;Cambridge Crystallographic Data Centre


catena-[(mu-2,2'-(1H-imidazol-3-ium-1,3-diyl)diacetato)-tetra-aqua-cobalt chloride ethane-1,2-diol solvate]

CCDC 1873828: Experimental Crystal Structure Determination;Farger, Pierre;2019;Cambridge Crystallographic Data Centre


catena-[(mu-2,2'-(1H-imidazol-3-ium-1,3-diyl)diacetato)-tetra-aqua-nickel chloride ethane-1,2-diol solvate]

CCDC 1873829: Experimental Crystal Structure Determination;Farger, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1475568: Experimental Crystal Structure Determination;Farger, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1475565: Experimental Crystal Structure Determination;Farger, Pierre;2019;Cambridge Crystallographic Data Centre


(1,4,8,11-tetraazacyclotetradecane)-nickel(ii) diaqua-bis(oxido)-bis[4-sulfobenzoato]-uranium(vi) acetonitrile solvate

Related Article: Pierre Thuéry, Youssef Atoini, Jack Harrowfield|2019|Dalton Trans.|48|8756|doi:10.1039/C9DT01024F

CCDC 1893014: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1893015: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1893016: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1893017: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1893018: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1893019: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1893020: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1893021: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1893022: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


CCDC 1893023: Experimental Crystal Structure Determination;Thuéry, Pierre;2019;Cambridge Crystallographic Data Centre


Related Article: Samantha Brown-Xu, Maria Fumanal, Christophe Gourlaouen, Lea Gimeno, Alessia Quatela, Christine Thobie-Gautier, Errol Blart, Aurélien Planchat, François Riobé, Cyrille Monnereau, Lin X. Chen, Chantal Daniel, Yann Pellegrin|2019|Inorg.Chem.|58|7730|doi:10.1021/acs.inorgchem.9b00042

CCDC 1884336: Experimental Crystal Structure Determination;Brown-Xu, Samantha;2019;Cambridge Crystallographic Data Centre


Related Article: Catalin Maxim, Sylvie Ferlay, Cyrille Train|2019|Comptes Rendus Chimie|22|534|doi:10.1016/j.crci.2019.03.009

CCDC 1890603: Experimental Crystal Structure Determination;Maxim, Catalin;2019;Cambridge Crystallographic Data Centre


CCDC 1890604: Experimental Crystal Structure Determination;Maxim, Catalin;2019;Cambridge Crystallographic Data Centre


Related Article: Damien Bissessar, Julien Egly, Thierry Achard, Pascal Steffanut, Stéphane Bellemin-Laponnaz|2019|RSC Advances|9|27250|doi:10.1039/C9RA04896K Related Article: Damien Bissessar, a Julien Egly, Thierry Achard, Pascal Steffanut, Stéphane Bellemin-Laponnaz|2019|CSD Communication|||

CCDC 1916028: Experimental Crystal Structure Determination;Bissessar, Damien;2019;Cambridge Crystallographic Data Centre


CCDC 1916029: Experimental Crystal Structure Determination;Bissessar, Damien;2019;Cambridge Crystallographic Data Centre


Related Article: Pierre Mobian|2019|CSD Communication||| Related Article: Emilie Macker, Laurent Barloy, Alain Chaumont, Nathalie Kyritsakas, Bruno Vincent, Marc Henry, Pierre Mobian|2019|Inorg.Chim.Acta|498|119119|doi:10.1016/j.ica.2019.119119

CCDC 1916725: Experimental Crystal Structure Determination;Mobian, Pierre;2019;Cambridge Crystallographic Data Centre


Related Article: Yi-Xiang Shi, Wen-Hua Zhang, Brendan F. Abrahams, Pierre Braunstein, Jian-Ping Lang|2019|Angew.Chem.,Int.Ed.|58|9453|doi:10.1002/anie.201903757

CCDC 1883295: Experimental Crystal Structure Determination;Shi, Yi-Xiang;2019;Cambridge Crystallographic Data Centre


CCDC 1883297: Experimental Crystal Structure Determination;Shi, Yi-Xiang;2019;Cambridge Crystallographic Data Centre


CCDC 1883296: Experimental Crystal Structure Determination;Shi, Yi-Xiang;2019;Cambridge Crystallographic Data Centre


Related Article: Kaige Shi, Logesh Mathivathanan, Athanassios K. Boudalis, Philippe Turek, Indranil Chakraborty, Raphael G. Raptis|2019|Inorg.Chem.|58|7537|doi:10.1021/acs.inorgchem.9b00748

CCDC 1857948: Experimental Crystal Structure Determination;Shi, Kaige;2019;Cambridge Crystallographic Data Centre


CCDC 1857949: Experimental Crystal Structure Determination;Shi, Kaige;2019;Cambridge Crystallographic Data Centre


Related Article: Jie Wang, Yan-Fang Wu, Mohamedally Kurmoo, Ming-Hua Zeng|2019|Inorg.Chem.|58|7472|doi:10.1021/acs.inorgchem.9b00666

CCDC 1876312: Experimental Crystal Structure Determination;Wang, Jie;2019;Cambridge Crystallographic Data Centre


CCDC 1876313: Experimental Crystal Structure Determination;Wang, Jie;2019;Cambridge Crystallographic Data Centre


CCDC 1876314: Experimental Crystal Structure Determination;Wang, Jie;2019;Cambridge Crystallographic Data Centre


CCDC 1876315: Experimental Crystal Structure Determination;Wang, Jie;2019;Cambridge Crystallographic Data Centre


Related Article: Wen-Jing Lang, Mohamedally Kurmoo, Ming-Hua Zeng|2019|Inorg.Chem.|58|7236|doi:10.1021/acs.inorgchem.9b00269

CCDC 1888163: Experimental Crystal Structure Determination;Lang, Wen-Jing;2019;Cambridge Crystallographic Data Centre


Related Article: Zhao-Bo Hu|2019|CSD Communication||| Related Article: Zhao-Bo Hu, Xin Feng, Jing Li, Yi-Quan Zhang, Lei Yin, Zhenxing Wang, Zhongwen Ouyang, Mohamedally Kurmoo, You Song|2020|Dalton Trans.|49|2159|doi:10.1039/C9DT04403E

CCDC 1915642: Experimental Crystal Structure Determination;Hu, Zhao-Bo;2019;Cambridge Crystallographic Data Centre


Related Article: Adam Gorczyński, Damian Marcinkowski, Dawid Pakulski, Maciej Kubicki, Jack M. Harrowfield, Artur R. Stefankiewicz, Zbigniew Hnatejko, Violetta Patroniak|2016|Arab.J.Chem.|12|729|doi:10.1016/j.arabjc.2016.04.006

CCDC 1005802: Experimental Crystal Structure Determination;Gorczyński, Adam;2016;Cambridge Crystallographic Data Centre


CCDC 1045908: Experimental Crystal Structure Determination;Gorczyński, Adam;2016;Cambridge Crystallographic Data Centre


CCDC 1400326: Experimental Crystal Structure Determination;Gorczyński, Adam;2016;Cambridge Crystallographic Data Centre


Related Article: Olga Kazarina, Christophe Gourlaouen, Lydia Karmazin, Alexander G. Morozov, Igor L. Fedushkin, Samuel Dagorne|2018|CSD Communication||| Related Article: Olga V. Kazarina, Christophe Gourlaouen, Lydia Karmazin, Alexander G. Morozov, Igor L. Fedushkin, Samuel Dagorne|2018|Dalton Trans.|47|13800|doi:10.1039/C8DT02614A

CCDC 1851717: Experimental Crystal Structure Determination;Kazarina, Olga;2018;Cambridge Crystallographic Data Centre


Related Article: Pierre Thuéry, Youssef Atoini, Jack Harrowfield|2018|Cryst.Growth Des.|18|2609|doi:10.1021/acs.cgd.8b00250

CCDC 1822644: Experimental Crystal Structure Determination;Thuéry, Pierre;2018;Cambridge Crystallographic Data Centre


CCDC 1822636: Experimental Crystal Structure Determination;Thuéry, Pierre;2018;Cambridge Crystallographic Data Centre


Related Article: Michel Holler,  Timothée Stoerkler,  Alexandra Louis,  Fanny Fischer,  Jean-Francois Nierengarten|2019|Eur.J.Org.Chem.|2019|3401|doi:10.1002/ejoc.201900153

CCDC 1894194: Experimental Crystal Structure Determination;Holler, Michel;2019;Cambridge Crystallographic Data Centre


CCDC 1894195: Experimental Crystal Structure Determination;Holler, Michel;2019;Cambridge Crystallographic Data Centre


Related Article: L. Barloy, B. Heinrich, L. Douce, M. Henry, M. Scarpi-Luttenauer, N. Kyritsakas, P. Mobian|2019|Dalton Trans.|48|1960|doi:10.1039/C8DT04972F

CCDC 1880954: Experimental Crystal Structure Determination;Barloy, L.;2019;Cambridge Crystallographic Data Centre


Related Article: Minghua Zeng, Jun-Quan Zhang, De-Shan Zhang, Qiu-Jie Chen, Hai-Bing Xu, Mohamedally Kurmoo, Ming-Hua Zeng|2019|Chem.-Eur.J.|25|5177|doi:10.1002/chem.201900204

CCDC 1887746: Experimental Crystal Structure Determination;Zeng, Minghua;2019;Cambridge Crystallographic Data Centre


Abstract: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

CCDC 1589358: Experimental Crystal Structure Determination;Aline Nonat;2019;Cambridge Crystallographic Data Centre

Related Article: Aline Nonat,  Sylvana Bahamyirou,  Alexandre Lecointre,  Frédéric Przybilla,  Yves Mély,  Carlos Platas-Iglesias,  Franck Camerel,  Olivier Jeannin,  Loïc J. Charbonnière|2019|J.Am.Chem.Soc.|141|1568|doi:10.1021/jacs.8b10932


CCDC 1535494: Experimental Crystal Structure Determination;Lei Wu;2019;Cambridge Crystallographic Data Centre

Related Article: Lei Wu, Gérald Chaplais, Ming Xue, Shilun Qiu, Joël Patarin, Angélique Simon-Masseron, Huaxin Chen|2019|RSC Advances|9|1918|doi:10.1039/C8RA08522F


CCDC 1535495: Experimental Crystal Structure Determination;Lei Wu;2019;Cambridge Crystallographic Data Centre


CCDC 1535496: Experimental Crystal Structure Determination;Lei Wu;2019;Cambridge Crystallographic Data Centre


CCDC 1864130: Experimental Crystal Structure Determination;Frédéric Beltran;2019;Cambridge Crystallographic Data Centre

Related Article: Frédéric Beltran, Lucile Andna, Laurence Miesch|2019|Org.Chem.Front.|6|373|doi:10.1039/C8QO00937F


CCDC 1868711: Experimental Crystal Structure Determination;Qian Hu;2019;Cambridge Crystallographic Data Centre

Related Article: Qian Hu, Suyun Jie, Pierre Braunstein, Bo-Geng Li|2019|J.Organomet.Chem.|882|1|doi:10.1016/j.jorganchem.2018.12.013


CCDC 1821986: Experimental Crystal Structure Determination;Dawid Lichosyt;2019;Cambridge Crystallographic Data Centre

Related Article: Dawid Lichosyt, Yang Zhang, Karolina Hurej, Paweł Dydio |2019|Nat. Catal.|2|114|doi:10.1038/s41929-018-0207-1


Abstract: Abstract Background Prevalence of multiple organ failure (MOF) in critically ill patients is increasing and associated mortality remains high. Extracorporeal organ support is a cornerstone in the management of MOF. We report data of an advanced hemodialysis system based on albumin dialysis (ADVOS multi device) that can regulate acid–base balance in addition to the established properties of renal replacement therapy and albumin dialysis systems in critically ill patients with MOF. Methods 34 critically ill patients with MOF received 102 ADVOS treatment sessions in the Department of Intensive Care Medicine of the University Medical Center Hamburg-Eppendorf. Markers of metabolic detoxification and acid–base regulation were collected and blood gas analyses were performed. A subgroup analyses were performed in patients with severe acidemia (pH

Advanced organ support (ADVOS) in the critically ill: first clinical experience in patients with multiple organ failure;Valentin Fuhrmann;2020;figshare


CCDC 1555873: Experimental Crystal Structure Determination;Frédéric Beltran;2019;Cambridge Crystallographic Data Centre


CCDC 1844757: Experimental Crystal Structure Determination;Frédéric Beltran;2019;Cambridge Crystallographic Data Centre


CCDC 1844758: Experimental Crystal Structure Determination;Frédéric Beltran;2019;Cambridge Crystallographic Data Centre


CCDC 1565980: Experimental Crystal Structure Determination;Thimma Sambamoorthy Manikandan;2018;Cambridge Crystallographic Data Centre

Related Article: Thimma Sambamoorthy Manikandan, Rengan Ramesh, David Semeril|2018|Organometallics|38|319|doi:10.1021/acs.organomet.8b00714


Abstract: Abstract Background Fabry disease (FD) is a rare, X-linked, inherited lysosomal disease caused by absent or reduced α-galactosidase A activity. Due to the heterogeneity of disease presentation and progression, generic patient-reported outcome (PRO) tools do not provide accurate insight into patients’ daily lives and impact of disease specific treatments. Also, the French National Health Authority, (HAS) actively encourages a patient-centric approach to improve the quality of care throughout the patient journey. In response to this initiative, we aimed to develop and validate a specific, self-reported, Patient Needs Questionnaire for people living with Fabry disease to appraise patient needs and expectations towards their treatment (PNQ Fabry). This endeavour was led with the help of French patient associations (APMF & VML) and dedicated expert centres. PNQ Fabry was developed according to the FDA/EMA methodologies and best practices for the development of PRO tools in rare diseases. Our approach comprised of three steps, as follows: concept elicitation and item generation, item reduction, and final validation of the questionnaire through a two-stage survey. Results Intrinsic and extrinsic reliability was established, using a validated benchmark questionnaire. With the invaluable help of patient associations, we recruited a satisfactory population in this rare disease setting, to ensure robust participation to validate our PNQ (final number of questionnaires: 76). At the end of the process, a 26-item patient-reported questionnaire was obtained with excellent psychometric properties, exhibiting very satisfactory measurement outcomes for reliability and validity. The results of this initiative demonstrate that the PNQ Fabry is accurate, suitable and tailored to FD patients, as it addresses themes identified during patient interviews, that were further validated through statistical analyses of quantitative surveys. An ongoing phase IV study is using this tool. Conclusion We believe the PNQ Fabry will be a reliable and insightful tool in clinical practice, to improve patient management in FD.

Treatment needs and expectations for Fabry disease in France: development of a new Patient Needs Questionnaire;Esther Noël;2019;figshare


Abstract: Abstract Background Flavonoids are produced in all flowering plants in a wide range of tissues including in berry fruits. These compounds are of considerable interest for their biological activities, health benefits and potential pharmacological applications. However, transcriptomic and genomic resources for wild and cultivated berry fruit species are often limited, despite their value in underpinning the in-depth study of metabolic pathways, fruit ripening as well as in the identification of genotypes rich in bioactive compounds. Results To access the genetic diversity of wild and cultivated berry fruit species that accumulate high levels of phenolic compounds in their fleshy berry(-like) fruits, we selected 13 species from Europe, South America and Asia representing eight genera, seven families and seven orders within three clades of the kingdom Plantae. RNA from either ripe fruits (ten species) or three ripening stages (two species) as well as leaf RNA (one species) were used to construct, assemble and analyse de novo transcriptomes. The transcriptome sequences are deposited in the BacHBerryGEN database (http://jicbio.nbi.ac.uk/berries) and were used, as a proof of concept, via its BLAST portal (http://jicbio.nbi.ac.uk/berries/blast.html) to identify candidate genes involved in the biosynthesis of phenylpropanoid compounds. Genes encoding regulatory proteins of the anthocyanin biosynthetic pathway (MYB and basic helix-loop-helix (bHLH) transcription factors and WD40 repeat proteins) were isolated using the transcriptomic resources of wild blackberry (Rubus genevieri) and cultivated red raspberry (Rubus idaeus cv. Prestige) and were shown to activate anthocyanin synthesis in Nicotiana benthamiana. Expression patterns of candidate flavonoid gene transcripts were also studied across three fruit developmental stages via the BacHBerryEXP gene expression browser (http://www.bachberryexp.com) in R. genevieri and R. idaeus cv. Prestige. Conclusions We report a transcriptome resource that includes data for a wide range of berry(-like) fruit species that has been developed for gene identification and functional analysis to assist in berry fruit improvement. These resources will enable investigations of metabolic processes in berries beyond the phenylpropanoid biosynthetic pathway analysed in this study. The RNA-seq data will be useful for studies of berry fruit development and to select wild plant species useful for plant breeding purposes.

RNA-seq, de novo transcriptome assembly and flavonoid gene analysis in 13 wild and cultivated berry fruit species with high content of phenolics;Vera Thole;2019;figshare


Abstract: Abstract Background The national ranking examination (NRE) marks the end of the second cycle (6th university year) of French medical studies and ranks students allowing them to choose their specialty and city of residency. We studied the potential predictive factors of success at the 2015 NRE by students attending a French School of Medicine. Methods From March 2016 to March 2017, a retrospective study of factors associated with the 2015 NRE success was conducted and enrolled 242 students who attended their sixth year at the school of medicine of Reims. Demographic and academic data collected by a home-made survey was studied using univariate and then multivariate analysis by generalized linear regression with a threshold of p

Predictive factors of success at the French National Ranking Examination (NRE): a retrospective study of the student performance from a French medical school;Martin Lhuaire;2019;figshare


Abstract: Abstract Background Daily rhythms have been widely investigated in various mammals but, surprisingly, literature is scarce and conflicting regarding the domestic cat, Felis catus. This may come from the difficulty to analyse rhythms in a species showing high interindividual variability and from the common idea that the rhythms of the cat are rather random. To elucidate the subject, two groups of indoor cats (14 in total) living in a cattery room, were followed on a 24 h/7 day basis, using advanced telemetry technologies, i.e. passive RFID, automated weighing of electronic scales and UWB technology with accuracy ensuring a good reliability of the results. Results While covering on average 1.74 ± 0.4 km and eating 46.4 ± 3.6 g (≈ 179 kcal) of dry food per day, findings indicate 24 h periodicity in the locomotor and feeding rhythms of the cats. Systematically, their locomotor behaviour was more rhythmic than their eating behaviour (p

Daily rhythms in food intake and locomotor activity in a colony of domestic cats;Marine Parker;2019;figshare

Earth and related environmental sciences


Abstract: Abstract Background Numerous tests have been proposed to evaluate sperm DNA integrity. To assess the sperm chromatin dispersion (SCD) test in an andrology laboratory, twenty-five men attending Clermont-Ferrand (France) University Hospital’s Center for Reproductive Medicine were recruited. Sperm DNA damage was measured in the same semen samples using the SCD test and the Terminal Uridine Nick-end Labeling by flow cytometry technique (TUNEL/FCM) after density gradient centrifugation. Results SCD test reliability between readings, readers or slides was clearly established with very high agreement between measurements (Intraclass correlation coefficient (ICC) at 0.97, 0.95 and 0.98 respectively). Despite very good agreement between the SCD test and TUNEL/FCM (ICC at 0.94), the SCD test tended to slightly but significantly underestimate DNA damage compared with TUNEL (p = 0.0127). This systematic difference between the two techniques was − 3.39 ± 1.45% (mean ± SE). Conclusions Andrology laboratories using the SCD test to measure sperm DNA damage need to know that it appears to give slightly underestimated measurements compared to TUNEL/FCM. However, this systematic underestimation is very small in amplitude. Both techniques give almost perfectly congruent results. Our study underlines the importance for each laboratory to validate its method to assess sperm DNA damage before implementing it in routine andrology lab practice.

Can the SCD test and terminal uridine nick-end labeling by flow cytometry technique (TUNEL/FCM) be used interchangeably to measure sperm DNA damage in routine laboratory practice?;Cécile Grèze;2019;figshare


Abstract: Abstract Background Pueraria candollei var. mirifica, a Thai medicinal plant used traditionally as a rejuvenating herb, is known as a rich source of phytoestrogens, including isoflavonoids and the highly estrogenic miroestrol and deoxymiroestrol. Although these active constituents in P. candollei var. mirifica have been known for some time, actual knowledge regarding their biosynthetic genes remains unknown. Results Miroestrol biosynthesis was reconsidered and the most plausible mechanism starting from the isoflavonoid daidzein was proposed. A de novo transcriptome analysis was conducted using combined P. candollei var. mirifica tissues of young leaves, mature leaves, tuberous cortices, and cortex-excised tubers. A total of 166,923 contigs was assembled for functional annotation using protein databases and as a library for identification of genes that are potentially involved in the biosynthesis of isoflavonoids and miroestrol. Twenty-one differentially expressed genes from four separate libraries were identified as candidates involved in these biosynthetic pathways, and their respective expressions were validated by quantitative real-time reverse transcription polymerase chain reaction. Notably, isoflavonoid and miroestrol profiling generated by LC-MS/MS was positively correlated with expression levels of isoflavonoid biosynthetic genes across the four types of tissues. Moreover, we identified R2R3 MYB transcription factors that may be involved in the regulation of isoflavonoid biosynthesis in P. candollei var. mirifica. To confirm the function of a key-isoflavone biosynthetic gene, P. candollei var. mirifica isoflavone synthase identified in our library was transiently co-expressed with an Arabidopsis MYB12 transcription factor (AtMYB12) in Nicotiana benthamiana leaves. Remarkably, the combined expression of these proteins led to the production of the isoflavone genistein. Conclusions Our results provide compelling evidence regarding the integration of transcriptome and metabolome as a powerful tool for identifying biosynthetic genes and transcription factors possibly involved in the isoflavonoid and miroestrol biosyntheses in P. candollei var. mirifica.

Transcriptome analysis of Pueraria candollei var. mirifica for gene discovery in the biosyntheses of isoflavones and miroestrol;Nithiwat Suntichaikamolkul;2019;figshare


Abstract: Abstract Objective Gene–environment interactions contribute to the development of HIV-associated neurocognitive disorders. We examined whether childhood trauma, apolipoprotein E isoforms and viral protein R (Vpr) variants were associated with change in cognitive performance. Seventy-three seropositive women completed neuropsychological assessments at baseline and 1-year follow-up. We conducted genetic analyses using DNA obtained from blood and calculated risk scores based on Vpr amino acid 37, 41 and 55 variants that were previously associated with cognitive performance. Results Global cognitive scores declined significantly over the 1-year study period (p = 0.029). A reduction in global cognitive scores was associated with childhood trauma experience (p = 0.039).

The effect of childhood trauma, ApoE genotype and HIV-1 viral protein R variants on change in cognitive performance;Jacqueline Womersley;2019;figshare


Abstract: Abstract The Upper Rhine Graben (URG) has been extensively studied for geothermal exploitation over the past decades. Yet, the thermal conductivity of the sedimentary cover is still poorly constrained, limiting our ability to provide robust heat flow density estimates. To improve our understanding of heat flow density in the URG, we present a new large thermal conductivity database for sedimentary rocks collected at outcrops in the area including measurements on (1) dry rocks at ambient temperature (dry); (2) dry rocks at high temperature (hot) and (3) water-saturated rocks at ambient temperature (wet). These measurements, covering the various lithologies composing the sedimentary sequence, are associated with equilibrium-temperature profiles measured in the Soultz-sous-Forêts wells and in the GRT-1 borehole (Rittershoffen) (all in France). Heat flow density values considering the various experimental thermal conductivity conditions were obtained for different depth intervals in the wells along with average values for the whole boreholes. The results agree with the previous heat flow density estimates based on dry rocks but more importantly highlight that accounting for the effect of temperature and water saturation of the formations is crucial to providing accurate heat flow density estimates in a sedimentary basin. For Soultz-sous-Forêts, we calculate average conductive heat flow density to be 127 mW/m2 when considering hot rocks and 184 mW/m2 for wet rocks. Heat flow density in the GRT-1 well is estimated at 109 and 164 mW/m2 for hot and wet rocks, respectively. Results from the Rittershoffen well suggest that heat flow density is nearly constant with depth, contrary to the observations for the Soultz-sous-Forêts site. Our results show a positive heat flow density anomaly in the Jurassic formations, which could be explained by a combined effect of a higher radiogenic heat production in the Jurassic sediments and thermal disturbance caused by the presence of the major faults close to the Soultz-sous-Forêts geothermal site. Although additional data are required to improve these estimates and our understanding of the thermal processes, we consider the heat flow densities estimated herein as the most reliable currently available for the URG.

Heat flow density estimates in the Upper Rhine Graben using laboratory measurements of thermal conductivity on sedimentary rocks;Pauline Harlé;2019;figshare


Abstract:
Supplementary tables S3 and S4.
Supplementary Table 3. Fold Change in Expression (mean, median and p value) of all genes.Supplementary Table 4. Fold Change in Expression (mean, median and p value) of genes that are displaced from more than 5% relative to the nuclear periphery, according to the models.

Supplemental Material for Di Stefano et al., 2020;Marco Di Stefano;2020;GSA Journals


Abstract: Abstract Background Evidence suggests that aerobic-type training confers physical benefits and appears to contribute positively to brain health. This study aims to compare the effect of 9-weeks continuous (CAT) to interval aerobic training (IAT) on brain derived neurotrophic factor (BDNF) plasma level, aerobic fitness, cognitive performance, and quality of life among senior with Alzheimer’s disease (AD). Methods 52 participants were randomly allocated into three groups (CAT n = 14; IAT n = 17; and Controls n = 21). CAT and IAT consisted of 18 sessions of 30-min cycling, twice a week, over 9 weeks. During the same period, controls were engaged in interactive information sessions. Plasma BDNF level; aerobic fitness parameters (Metabolic equivalent task - METs; Maximal Tolerated Power – MTP); functional capacities (6-Minute Walk Test - 6MWT); cognitive performance (Mini Mental State Examination; Rey auditory verbal learning test; and digit span test) and quality of life (Quality Of Life of Alzheimer’s Disease scale - QoL-AD) were measured in all participants at baseline and 9 weeks later. A third plasma BDNF level was quantified following a 4 weeks detraining. Results No significant change was measured in terms of plasma BDNF level and cognitive performance after interventions, in all groups compared to baseline. After 9 weeks, CAT and IAT significantly improved aerobic fitness parameters compared to controls (METs: + 0.6 and + 1.0 vs. + 0.4; MTP: + 16 watts and + 20 watts vs. + 10 watts; and functional capacities (6MWT: + 22 m and + 31 m vs. -40 m). Compared to controls, QoL-AD after CAT was improved (+ 2 points; p = 0.02). Conclusions Neither aerobic exercise modalities significantly modified plasma BDNF levels and cognitive performances. CAT and IAT enhanced aerobic fitness and functional capacities in AD patients and CAT their QoL. Trial registration ClinicalTrials.gov website (NCT02968875); registration date: 7 September 2016. “Retrospectively registered”.

Effect of 9 weeks continuous vs. interval aerobic training on plasma BDNF levels, aerobic fitness, cognitive capacity and quality of life among seniors with mild to moderate Alzheimer’s disease: a randomized controlled trial;Lievyn Enette;2020;figshare


Abstract: Abstract Background Fluctuations are one of the core clinical features characterizing dementia with Lewy bodies (DLB). They represent a determining factor for its diagnosis and strongly impact the quality of life of patients and their caregivers. However, the neural correlates of this complex symptom remain poorly understood. This study aimed to investigate the structural and functional changes in DLB patients, compared to Alzheimer’s disease (AD) patients and healthy elderly subjects, and their potential links with fluctuations. Methods Structural and resting-state functional MRI data were collected from 92 DLB patients, 70 AD patients, and 22 control subjects, who also underwent a detailed clinical examination including the Mayo Clinic Fluctuation Scale. Gray matter volume changes were analyzed using whole-brain voxel-based morphometry, and resting-state functional connectivity was investigated using a seed-based analysis, with regions of interest corresponding to the main nodes of the salience network (SN), frontoparietal network (FPN), dorsal attention network (DAN), and default mode network (DMN). Results At the structural level, fluctuation scores in DLB patients did not relate to the atrophy of insular, temporal, and frontal regions typically found in this pathology, but instead showed a weak correlation with more subtle volume reductions in different regions of the cholinergic system. At the functional level, the DLB group was characterized by a decreased connectivity within the SN and attentional networks, while the AD group showed decreases within the SN and DMN. In addition, higher fluctuation scores in DLB patients were correlated to a greater connectivity of the SN with the DAN and left thalamus, along with a decreased connectivity between the SN and DMN, and between the right thalamus and both the FPN and DMN. Conclusions Functional connectivity changes, rather than significant gray matter loss, could play an important role in the emergence of fluctuations in DLB. Notably, fluctuations in DLB patients appeared to be related to a disturbed external functional connectivity of the SN, which may lead to less relevant transitions between different cognitive states in response to internal and environmental stimuli. Our results also suggest that the thalamus could be a key region for the occurrence of this symptom.

Changes in gray matter volume and functional connectivity in dementia with Lewy bodies compared to Alzheimer’s disease and normal aging: implications for fluctuations;Eléna Chabran;2020;figshare


Abstract: Abstract Objective To describe successful therapeutic strategies in statin-induced anti-HMGCR myopathy. Methods Retrospective data from a cohort of 55 patients with statin-induced anti-HMGCR myopathy, sequentially stratified by the presence of proximal weakness, early remission, and corticosteroid and IVIG use at treatment induction, were analyzed for optimal successful induction and maintenance of remission strategies. Results A total of 14 patients achieved remission with a corticosteroid-free induction strategy (25%). In 41 patients treated with corticosteroids, only 4 patients (10%) failed an initial triple steroid/IVIG/steroid-sparing immunosuppressant (SSI) induction strategy. Delay in treatment initiation was independently associated with lower odds of successful maintenance with immunosuppressant monotherapy (OR 0.92, 95% CI 0.85 to 0.97, P = 0.015). While 22 patients (40%) presented with normal strength, only 9 had normal strength at initiation of treatment. Conclusion While corticosteroid-free treatment of anti-HMGCR myopathy is now a safe option in selected cases, initial triple steroid/IVIG/SSI was very efficacious in induction. Delays in treatment initiation and, as a corollary, delays in achieving remission decrease the odds of achieving successful maintenance with an SSI alone. Avoiding such delays, most notably in patients with normal strength, may reset the natural history of anti-HMGCR myopathy from a refractory entity to a treatable disease.

Statin-induced anti-HMGCR myopathy: successful therapeutic strategies for corticosteroid-free remission in 55 patients;Alain Meyer;2020;figshare


Abstract: Abstract Background Lake Baikal is one of the oldest freshwater lakes and has constituted a stable environment for millions of years, in stark contrast to small, transient bodies of water in its immediate vicinity. A highly diverse endemic endemic amphipod fauna is found in one, but not the other habitat. We ask here whether differences in stress response can explain the immiscibility barrier between Lake Baikal and non-Baikal faunas. To this end, we conducted exposure experiments to increased temperature and the toxic heavy metal cadmium as stressors. Results Here we obtained high-quality de novo transcriptome assemblies, covering mutiple conditions, of three amphipod species, and compared their transcriptomic stress responses. Two of these species, Eulimnogammarus verrucosus and E. cyaneus, are endemic to Lake Baikal, while the Holarctic Gammarus lacustris is a potential invader. Conclusions Both Baikal species possess intact stress response systems and respond to elevated temperature with relatively similar changes in their expression profiles. G. lacustris reacts less strongly to the same stressors, possibly because its transcriptome is already perturbed by acclimation conditions.

Comparison between transcriptomic responses to short-term stress exposures of a common Holarctic and endemic Lake Baikal amphipods;Polina Drozdova;2019;figshare


Abstract: Abstract Background The early life of marine apex predators is poorly known, particularly for diving species. The orientation and foraging skills are presumably less developed in juveniles than in adults, especially during their first year at sea when juveniles might disperse further than adults. Methods Over two years of monitoring, we tracked the movements of 17 juvenile king penguins (Aptenodytes patagonicus, ~â 1â year old) using satellite relay tags from Crozet Archipelago (Southern Indian Ocean), starting when birds left their natal colony for the first time. For comparison we also tagged 6 non-breeding adults, which at that stage, similar to juveniles, are unhampered by reproductive constraints and might roam further than breeders. We used a combination of cluster analysis and habitat modelling to investigate and compare the movement patterns and habitat use of experienced (non-breeding adults) and non-experienced (juveniles) individuals. Results While juvenile penguins and non-breeding adults followed similar routes, the movements by adults started later in the season and ranged over a considerably smaller area than juveniles. Net squared displacement analysis revealed that both groups did not move to a specific wintering area. Changes in direction of juveniles in respect to their departure island were similar and synchronous for both years. Habitat models revealed that foraging behaviour was affected by environmental variables such as wind or current speeds, sea surface temperature, or oceanic productivity, for both stages. Analysis of tracks revealed that birds moved predominately perpendicular or against the main direction of the Antarctic Circumpolar Current and the prevailing wind during austral summer (juveniles only) and autumn (juveniles and non-breeding adults). However, both juveniles and adults were more likely to move against the prevailing winds if productivity increased along their trajectories. Conclusions The exceptional duration of our tracking study provided unprecedented insights into the distribution, habitat preferences and orientation of two poorly known life history stages of an expert avian diver. Our study suggests that juveniles might use both innate and learnt skills to reach profitable foraging areas during their first year at sea, which is critical in long-lived species.

Exploration during early life: distribution, habitat and orientation preferences in juvenile king penguins;F. Orgeret;2019;figshare


Some DNM2 mutations cause extremely severe congenital myopathy and phenocopy myotubular myopathy;ValĂŠrie Biancalana;2019;figshare


Abstract: Abstract Background Diffuse large B-cell lymphomas (DLBCLs) are aggressive lymphomas accounting for approximately a third of non-Hodgkin lymphomas. Prohibitin 1 (PHB1) and prohibitin 2 (PHB2) are scaffold proteins that promote mitochondria homeostasis and consequently cell survival, but biological functions of cytoplasmic PHBs remain largely unknown in DLBCL. Methods PHB expression was analyzed in 82 DLBCL biopsies and five DLBCL cell lines by immunohistochemistry (IHC) and Western blotting. Pharmacological inhibition of PHB using the synthetic flavagline FL3 was realized in vitro to gain insight PHB cellular functions. Effects of FL3 on DLBCL cell line viability, apoptosis, C-Raf-ERK–MNK–eIF4E signaling pathway and eIF4F complex formation and activity were evaluated by XTT assay, annexin V-FITC/PI dual staining and Western blotting respectively. Subcutaneous DLBCL xenograft model in SCID mice was also performed to determine in vivo FL3 effect. Results As in DLBCL cell lines, PHB1 and PHB2 were expressed in germinal center B-cell–like (GCB) and activated B-cell–like (ABC) subtypes. In patient samples, high PHB levels were associated with higher serum LDH (PHB1 and PHB2), IPIaa (PHB2), and Ki-67 (PHB2) expression. Higher PHB1 expression tends to be associated with shorter event-free survival (EFS) in patients, especially in male patients. FL3 induced apoptosis of DLBCL cell lines that was associated with inhibition of the ERK-MNK-eIF4E signaling pathway, including aggressive double/triple-hit DLBCL cell lines. This resulted in altered eIF4F complex formation and activity leading to a reduction of Bcl-2 and c-Myc expression levels. Moreover, FL3 strongly downregulated DLBCL cellular levels of Akt protein and AKT mRNA. FL3 antitumor activity was also confirmed in vivo in a murine xenograft model. Conclusion Our data indicate that PHB overexpression is associated with markers of tumor aggressiveness in DLBCL, and that targeting PHBs may be a therapeutic option, notably in aggressive subtypes.

Prohibitin (PHB) expression is associated with aggressiveness in DLBCL and flavagline-mediated inhibition of cytoplasmic PHB functions induces anti-tumor effects;Hafidha Bentayeb;2019;figshare


Abstract: Abstract The QM9 dataset has become the golden standard for Machine Learning (ML) predictions of various chemical properties. QM9 is based on the GDB, which is a combinatorial exploration of the chemical space. ML molecular predictions have been recently published with an accuracy on par with Density Functional Theory calculations. Such ML models need to be tested and generalized on real data. PC9, a new QM9 equivalent dataset (only H, C, N, O and F and up to 9 “heavy” atoms) of the PubChemQC project is presented in this article. A statistical study of bonding distances and chemical functions shows that this new dataset encompasses more chemical diversity. Kernel Ridge Regression, Elastic Net and the Neural Network model provided by SchNet have been used on both datasets. The overall accuracy in energy prediction is higher for the QM9 subset. However, a model trained on PC9 shows a stronger ability to predict energies of the other dataset.

Dataset’s chemical diversity limits the generalizability of machine learning predictions;Marta Glavatskikh;2019;figshare


Abstract: Drops loaded in calcium ions detach from stalactites and impact the underlying stalagmites, thereby allowing these latter to grow through calcite precipitation. Nevertheless, little is known about the influence of the drop free fall and splash dynamics on stalagmite shape and width. Through high-speed imaging of impacting drops on stalagmites from several caves, we observed that the impact point position of the drops is scattered, sometimes over several centimetres. We show that this dispersal has no external cause and must, therefore, be self-induced. Using a Langevin-like equation, we then propose a prediction of the impact point dispersal as a function of the falling height travelled by the drops. We finally show that measured stalagmite widths are correlated to the dispersal in the impact point position of the drop.

Supplementary material from "A drop does not fall in a straight line: a rationale for the width of stalagmites";J. Parmentier;2019;The Royal Society


Abstract: Abstract Background There is little descriptive data on Stenotrophomonas maltophilia hospital-acquired pneumonia (HAP) in critically ill patients. The optimal modalities of antimicrobial therapy remain to be determined. Our objective was to describe the epidemiology and prognostic factors associated with S. maltophilia pneumonia, focusing on antimicrobial therapy. Methods This nationwide retrospective study included all patients admitted to 25 French mixed intensive care units between 2012 and 2017 with hospital-acquired S. maltophilia HAP during intensive care unit stay. Primary endpoint was time to in-hospital death. Secondary endpoints included microbiologic effectiveness and antimicrobial therapeutic modalities such as delay to appropriate antimicrobial treatment, mono versus combination therapy, and duration of antimicrobial therapy. Results Of the 282 patients included, 84% were intubated at S. maltophilia HAP diagnosis for duration of 11 [5–18] days. The Simplified Acute Physiology Score II was 47 [36–63], and the in-hospital mortality was 49.7%. Underlying chronic pulmonary comorbidities were present in 14.1% of cases. Empirical antimicrobial therapy was considered effective on S. maltophilia according to susceptibility patterns in only 30% of cases. Delay to appropriate antimicrobial treatment had, however, no significant impact on the primary endpoint. Survival analysis did not show any benefit from combination antimicrobial therapy (HR = 1.27, 95%CI [0.88; 1.83], p = 0.20) or prolonged antimicrobial therapy for more than 7 days (HR = 1.06, 95%CI [0.6; 1.86], p = 0.84). No differences were noted in in-hospital death irrespective of an appropriate and timely empiric antimicrobial therapy between mono- versus polymicrobial S. maltophilia HAP (p = 0.273). The duration of ventilation prior to S. maltophilia HAP diagnosis and ICU length of stay were shorter in patients with monomicrobial S. maltophilia HAP (p = 0.031 and p = 0.034 respectively). Conclusions S. maltophilia HAP occurred in severe, long-stay intensive care patients who mainly required prolonged invasive ventilation. Empirical antimicrobial therapy was barely effective while antimicrobial treatment modalities had no significant impact on hospital survival. Trial registration clinicaltrials.gov, NCT03506191

Outcomes of Stenotrophomonas maltophilia hospital-acquired pneumonia in intensive care unit: a nationwide retrospective study;Philippe Guerci;2019;figshare