TY  - JOUR
A1  - Chan, Lili
A1  - Jaladanki, Suraj K.
A1  - Somani, Sulaiman
A1  - Paranjpe, Ishan
A1  - Kumar, Arvind
A1  - Zhao, Shan
A1  - Kaufman, Lewis
A1  - Leisman, Staci
A1  - Sharma, Shuchita
A1  - He, John Cijiang
A1  - Murphy, Barbara
A1  - Fayad, Zahi A.
A1  - Levin, Matthew A.
A1  - Böttinger, Erwin
A1  - Charney, Alexander W.
A1  - Glicksberg, Benjamin
A1  - Coca, Steven G.
A1  - Nadkarni, Girish N.
T1  - Outcomes of patients on maintenance dialysis hospitalized with COVID-19
JF  - Clinical journal of the American Society of Nephrology : CJASN
KW  - chronic dialysis
KW  - COVID-19
KW  - end-stage kidney disease
Y1  - 2021
U6  - https://doi.org/10.2215/CJN.12360720
SN  - 1555-9041
SN  - 1555-905X
VL  - 16
IS  - 3
SP  - 452
EP  - 455
PB  - American Society of Nephrology
CY  - Washington
ER  - 
TY  - JOUR
A1  - Chan, Lili
A1  - Chaudhary, Kumardeep
A1  - Saha, Aparna
A1  - Chauhan, Kinsuk
A1  - Vaid, Akhil
A1  - Zhao, Shan
A1  - Paranjpe, Ishan
A1  - Somani, Sulaiman
A1  - Richter, Felix
A1  - Miotto, Riccardo
A1  - Lala, Anuradha
A1  - Kia, Arash
A1  - Timsina, Prem
A1  - Li, Li
A1  - Freeman, Robert
A1  - Chen, Rong
A1  - Narula, Jagat
A1  - Just, Allan C.
A1  - Horowitz, Carol
A1  - Fayad, Zahi
A1  - Cordon-Cardo, Carlos
A1  - Schadt, Eric
A1  - Levin, Matthew A.
A1  - Reich, David L.
A1  - Fuster, Valentin
A1  - Murphy, Barbara
A1  - He, John C.
A1  - Charney, Alexander W.
A1  - Böttinger, Erwin
A1  - Glicksberg, Benjamin
A1  - Coca, Steven G.
A1  - Nadkarni, Girish N.
T1  - AKI in hospitalized patients with COVID-19
JF  - Journal of the American Society of Nephrology : JASN
N2  - Background:
Early reports indicate that AKI is common among patients with coronavirus disease 2019 (COVID-19) and associatedwith worse outcomes. However, AKI among hospitalized patients with COVID19 in the United States is not well described. 

Methods:
This retrospective, observational study involved a review of data from electronic health records of patients aged >= 18 years with laboratory-confirmed COVID-19 admitted to the Mount Sinai Health System from February 27 to May 30, 2020. We describe the frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aORs) with mortality. 

Results:
Of 3993 hospitalized patients with COVID-19, AKI occurred in 1835 (46%) patients; 347 (19%) of the patientswith AKI required dialysis. The proportionswith stages 1, 2, or 3 AKIwere 39%, 19%, and 42%, respectively. A total of 976 (24%) patients were admitted to intensive care, and 745 (76%) experienced AKI. Of the 435 patients with AKI and urine studies, 84% had proteinuria, 81% had hematuria, and 60% had leukocyturia. Independent predictors of severe AKI were CKD, men, and higher serum potassium at admission. In-hospital mortality was 50% among patients with AKI versus 8% among those without AKI (aOR, 9.2; 95% confidence interval, 7.5 to 11.3). Of survivors with AKI who were discharged, 35% had not recovered to baseline kidney function by the time of discharge. An additional 28 of 77 (36%) patients who had not recovered kidney function at discharge did so on posthospital follow-up. 

Conclusions:
AKI is common among patients hospitalized with COVID-19 and is associated with high mortality. Of all patients with AKI, only 30% survived with recovery of kidney function by the time of discharge.
KW  - acute renal failure
KW  - clinical nephrology
KW  - dialysis
KW  - COVID-19
Y1  - 2021
U6  - https://doi.org/10.1681/ASN.2020050615
SN  - 1046-6673
SN  - 1533-3450
VL  - 32
IS  - 1
SP  - 151
EP  - 160
PB  - American Society of Nephrology
CY  - Washington
ER  - 
TY  - JOUR
A1  - Vaid, Akhil
A1  - Somani, Sulaiman
A1  - Russak, Adam J.
A1  - De Freitas, Jessica K.
A1  - Chaudhry, Fayzan F.
A1  - Paranjpe, Ishan
A1  - Johnson, Kipp W.
A1  - Lee, Samuel J.
A1  - Miotto, Riccardo
A1  - Richter, Felix
A1  - Zhao, Shan
A1  - Beckmann, Noam D.
A1  - Naik, Nidhi
A1  - Kia, Arash
A1  - Timsina, Prem
A1  - Lala, Anuradha
A1  - Paranjpe, Manish
A1  - Golden, Eddye
A1  - Danieletto, Matteo
A1  - Singh, Manbir
A1  - Meyer, Dara
A1  - O'Reilly, Paul F.
A1  - Huckins, Laura
A1  - Kovatch, Patricia
A1  - Finkelstein, Joseph
A1  - Freeman, Robert M.
A1  - Argulian, Edgar
A1  - Kasarskis, Andrew
A1  - Percha, Bethany
A1  - Aberg, Judith A.
A1  - Bagiella, Emilia
A1  - Horowitz, Carol R.
A1  - Murphy, Barbara
A1  - Nestler, Eric J.
A1  - Schadt, Eric E.
A1  - Cho, Judy H.
A1  - Cordon-Cardo, Carlos
A1  - Fuster, Valentin
A1  - Charney, Dennis S.
A1  - Reich, David L.
A1  - Böttinger, Erwin
A1  - Levin, Matthew A.
A1  - Narula, Jagat
A1  - Fayad, Zahi A.
A1  - Just, Allan C.
A1  - Charney, Alexander W.
A1  - Nadkarni, Girish N.
A1  - Glicksberg, Benjamin S.
T1  - Machine learning to predict mortality and critical events in a cohort of patients with COVID-19 in New York City: model development and validation
JF  - Journal of medical internet research : international scientific journal for medical research, information and communication on the internet ; JMIR
N2  - Background:
COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking.

Objective:
The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points. 

Methods:
We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions.

Results:
Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction. 

Conclusions:
We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.
KW  - machine learning
KW  - COVID-19
KW  - electronic health record
KW  - TRIPOD
KW  - clinical
KW  - informatics
KW  - prediction
KW  - mortality
KW  - EHR
KW  - cohort
KW  - hospital
KW  - performance
Y1  - 2020
U6  - https://doi.org/10.2196/24018
SN  - 1439-4456
SN  - 1438-8871
VL  - 22
IS  - 11
PB  - Healthcare World
CY  - Richmond, Va.
ER  - 
TY  - JOUR
A1  - Warrington, Nicole
A1  - Beaumont, Robin
A1  - Horikoshi, Momoko
A1  - Day, Felix R.
A1  - Helgeland, Øyvind
A1  - Laurin, Charles
A1  - Bacelis, Jonas
A1  - Peng, Shouneng
A1  - Hao, Ke
A1  - Feenstra, Bjarke
A1  - Wood, Andrew R.
A1  - Mahajan, Anubha
A1  - Tyrrell, Jessica
A1  - Robertson, Neil R.
A1  - Rayner, N. William
A1  - Qiao, Zhen
A1  - Moen, Gunn-Helen
A1  - Vaudel, Marc
A1  - Marsit, Carmen
A1  - Chen, Jia
A1  - Nodzenski, Michael
A1  - Schnurr, Theresia M.
A1  - Zafarmand, Mohammad Hadi
A1  - Bradfield, Jonathan P.
A1  - Grarup, Niels
A1  - Kooijman, Marjolein N.
A1  - Li-Gao, Ruifang
A1  - Geller, Frank
A1  - Ahluwalia, Tarunveer Singh
A1  - Paternoster, Lavinia
A1  - Rueedi, Rico
A1  - Huikari, Ville
A1  - Hottenga, Jouke-Jan
A1  - Lyytikäinen, Leo-Pekka
A1  - Cavadino, Alana
A1  - Metrustry, Sarah
A1  - Cousminer, Diana L.
A1  - Wu, Ying
A1  - Thiering, Elisabeth Paula
A1  - Wang, Carol A.
A1  - Have, Christian Theil
A1  - Vilor-Tejedor, Natalia
A1  - Joshi, Peter K.
A1  - Painter, Jodie N.
A1  - Ntalla, Ioanna
A1  - Myhre, Ronny
A1  - Pitkänen, Niina
A1  - van Leeuwen, Elisabeth M.
A1  - Joro, Raimo
A1  - Lagou, Vasiliki
A1  - Richmond, Rebecca C.
A1  - Espinosa, Ana
A1  - Barton, Sheila J.
A1  - Inskip, Hazel M.
A1  - Holloway, John W.
A1  - Santa-Marina, Loreto
A1  - Estivill, Xavier
A1  - Ang, Wei
A1  - Marsh, Julie A.
A1  - Reichetzeder, Christoph
A1  - Marullo, Letizia
A1  - Hocher, Berthold
A1  - Lunetta, Kathryn L.
A1  - Murabito, Joanne M.
A1  - Relton, Caroline L.
A1  - Kogevinas, Manolis
A1  - Chatzi, Leda
A1  - Allard, Catherine
A1  - Bouchard, Luigi
A1  - Hivert, Marie-France
A1  - Zhang, Ge
A1  - Muglia, Louis J.
A1  - Heikkinen, Jani
A1  - Morgen, Camilla S.
A1  - van Kampen, Antoine H. C.
A1  - van Schaik, Barbera D. C.
A1  - Mentch, Frank D.
A1  - Langenberg, Claudia
A1  - Scott, Robert A.
A1  - Zhao, Jing Hua
A1  - Hemani, Gibran
A1  - Ring, Susan M.
A1  - Bennett, Amanda J.
A1  - Gaulton, Kyle J.
A1  - Fernandez-Tajes, Juan
A1  - van Zuydam, Natalie R.
A1  - Medina-Gomez, Carolina
A1  - de Haan, Hugoline G.
A1  - Rosendaal, Frits R.
A1  - Kutalik, Zoltán
A1  - Marques-Vidal, Pedro
A1  - Das, Shikta
A1  - Willemsen, Gonneke
A1  - Mbarek, Hamdi
A1  - Müller-Nurasyid, Martina
A1  - Standl, Marie
A1  - Appel, Emil V. R.
A1  - Fonvig, Cilius Esmann
A1  - Trier, Caecilie
A1  - van Beijsterveldt, Catharina E. M.
A1  - Murcia, Mario
A1  - Bustamante, Mariona
A1  - Bonàs-Guarch, Sílvia
A1  - Hougaard, David M.
A1  - Mercader, Josep M.
A1  - Linneberg, Allan
A1  - Schraut, Katharina E.
A1  - Lind, Penelope A.
A1  - Medland, Sarah Elizabeth
A1  - Shields, Beverley M.
A1  - Knight, Bridget A.
A1  - Chai, Jin-Fang
A1  - Panoutsopoulou, Kalliope
A1  - Bartels, Meike
A1  - Sánchez, Friman
A1  - Stokholm, Jakob
A1  - Torrents, David
A1  - Vinding, Rebecca K.
A1  - Willems, Sara M.
A1  - Atalay, Mustafa
A1  - Chawes, Bo L.
A1  - Kovacs, Peter
A1  - Prokopenko, Inga
A1  - Tuke, Marcus A.
A1  - Yaghootkar, Hanieh
A1  - Ruth, Katherine S.
A1  - Jones, Samuel E.
A1  - Loh, Po-Ru
A1  - Murray, Anna
A1  - Weedon, Michael N.
A1  - Tönjes, Anke
A1  - Stumvoll, Michael
A1  - Michaelsen, Kim Fleischer
A1  - Eloranta, Aino-Maija
A1  - Lakka, Timo A.
A1  - van Duijn, Cornelia M.
A1  - Kiess, Wieland
A1  - Koerner, Antje
A1  - Niinikoski, Harri
A1  - Pahkala, Katja
A1  - Raitakari, Olli T.
A1  - Jacobsson, Bo
A1  - Zeggini, Eleftheria
A1  - Dedoussis, George V.
A1  - Teo, Yik-Ying
A1  - Saw, Seang-Mei
A1  - Montgomery, Grant W.
A1  - Campbell, Harry
A1  - Wilson, James F.
A1  - Vrijkotte, Tanja G. M.
A1  - Vrijheid, Martine
A1  - de Geus, Eco J. C. N.
A1  - Hayes, M. Geoffrey
A1  - Kadarmideen, Haja N.
A1  - Holm, Jens-Christian
A1  - Beilin, Lawrence J.
A1  - Pennell, Craig E.
A1  - Heinrich, Joachim
A1  - Adair, Linda S.
A1  - Borja, Judith B.
A1  - Mohlke, Karen L.
A1  - Eriksson, Johan G.
A1  - Widen, Elisabeth E.
A1  - Hattersley, Andrew T.
A1  - Spector, Tim D.
A1  - Kaehoenen, Mika
A1  - Viikari, Jorma S.
A1  - Lehtimaeki, Terho
A1  - Boomsma, Dorret I.
A1  - Sebert, Sylvain
A1  - Vollenweider, Peter
A1  - Sorensen, Thorkild I. A.
A1  - Bisgaard, Hans
A1  - Bonnelykke, Klaus
A1  - Murray, Jeffrey C.
A1  - Melbye, Mads
A1  - Nohr, Ellen A.
A1  - Mook-Kanamori, Dennis O.
A1  - Rivadeneira, Fernando
A1  - Hofman, Albert
A1  - Felix, Janine F.
A1  - Jaddoe, Vincent W. V.
A1  - Hansen, Torben
A1  - Pisinger, Charlotta
A1  - Vaag, Allan A.
A1  - Pedersen, Oluf
A1  - Uitterlinden, Andre G.
A1  - Jarvelin, Marjo-Riitta
A1  - Power, Christine
A1  - Hypponen, Elina
A1  - Scholtens, Denise M.
A1  - Lowe, William L.
A1  - Smith, George Davey
A1  - Timpson, Nicholas J.
A1  - Morris, Andrew P.
A1  - Wareham, Nicholas J.
A1  - Hakonarson, Hakon
A1  - Grant, Struan F. A.
A1  - Frayling, Timothy M.
A1  - Lawlor, Debbie A.
A1  - Njolstad, Pal R.
A1  - Johansson, Stefan
A1  - Ong, Ken K.
A1  - McCarthy, Mark I.
A1  - Perry, John R. B.
A1  - Evans, David M.
A1  - Freathy, Rachel M.
T1  - Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors
JF  - Nature genetics
N2  - Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.
Y1  - 2019
SN  - 1061-4036
SN  - 1546-1718
VL  - 51
IS  - 5
SP  - 804
EP  - +
PB  - Nature Publ. Group
CY  - New York
ER  - 
TY  - JOUR
A1  - Rothe, Martin
A1  - Zhao, Yuhang
A1  - Kewes, Günter
A1  - Kochovski, Zdravko
A1  - Sigle, Wilfried
A1  - van Aken, Peter A.
A1  - Koch, Christoph
A1  - Ballauff, Matthias
A1  - Lu, Yan
A1  - Benson, Oliver
T1  - Silver nanowires with optimized silica coating as versatile plasmonic resonators
JF  - Scientific reports
N2  - Metal nanoparticles are the most frequently used nanostructures in plasmonics. However, besides nanoparticles, metal nanowires feature several advantages for applications. Their elongation offers a larger interaction volume, their resonances can reach higher quality factors, and their mode structure provides better coupling into integrated hybrid dielectric-plasmonic circuits. It is crucial though, to control the distance of the wire to a supporting substrate, to another metal layer or to active materials with sub-nanometer precision. A dielectric coating can be utilized for distance control, but it must not degrade the plasmonic properties. In this paper, we introduce a controlled synthesis and coating approach for silver nanowires to fulfill these demands. We synthesize and characterize silver nanowires of around 70 nm in diameter. These nanowires are coated with nm-sized silica shells using a modified Stober method to achieve a homogeneous and smooth surface quality. We use transmission electron microscopy, dark-field microscopy and electron-energy loss spectroscopy to study morphology and plasmonic resonances of individual nanowires and quantify the influence of the silica coating. Thorough numerical simulations support the experimental findings showing that the coating does not deteriorate the plasmonic properties and thus introduce silver nanowires as usable building blocks for integrated hybrid plasmonic systems.
Y1  - 2019
U6  - https://doi.org/10.1038/s41598-019-40380-5
SN  - 2045-2322
VL  - 9
PB  - Nature Publ. Group
CY  - London
ER  - 
TY  - JOUR
A1  - Khider, D.
A1  - Emile-Geay, J.
A1  - McKay, N. P.
A1  - Gil, Y.
A1  - Garijo, D.
A1  - Ratnakar, V
A1  - Alonso-Garcia, M.
A1  - Bertrand, S.
A1  - Bothe, O.
A1  - Brewer, P.
A1  - Bunn, A.
A1  - Chevalier, M.
A1  - Comas-Bru, L.
A1  - Csank, A.
A1  - Dassie, E.
A1  - DeLong, K.
A1  - Felis, T.
A1  - Francus, P.
A1  - Frappier, A.
A1  - Gray, W.
A1  - Goring, S.
A1  - Jonkers, L.
A1  - Kahle, M.
A1  - Kaufman, D.
A1  - Kehrwald, N. M.
A1  - Martrat, B.
A1  - McGregor, H.
A1  - Richey, J.
A1  - Schmittner, A.
A1  - Scroxton, N.
A1  - Sutherland, E.
A1  - Thirumalai, Kaustubh
A1  - Allen, K.
A1  - Arnaud, F.
A1  - Axford, Y.
A1  - Barrows, T.
A1  - Bazin, L.
A1  - Birch, S. E. Pilaar
A1  - Bradley, E.
A1  - Bregy, J.
A1  - Capron, E.
A1  - Cartapanis, O.
A1  - Chiang, H-W
A1  - Cobb, K. M.
A1  - Debret, M.
A1  - Dommain, Réne
A1  - Du, J.
A1  - Dyez, K.
A1  - Emerick, S.
A1  - Erb, M. P.
A1  - Falster, G.
A1  - Finsinger, W.
A1  - Fortier, D.
A1  - Gauthier, Nicolas
A1  - George, S.
A1  - Grimm, E.
A1  - Hertzberg, J.
A1  - Hibbert, F.
A1  - Hillman, A.
A1  - Hobbs, W.
A1  - Huber, M.
A1  - Hughes, A. L. C.
A1  - Jaccard, S.
A1  - Ruan, J.
A1  - Kienast, M.
A1  - Konecky, B.
A1  - Le Roux, G.
A1  - Lyubchich, V
A1  - Novello, V. F.
A1  - Olaka, L.
A1  - Partin, J. W.
A1  - Pearce, C.
A1  - Phipps, S. J.
A1  - Pignol, C.
A1  - Piotrowska, N.
A1  - Poli, M-S
A1  - Prokopenko, A.
A1  - Schwanck, F.
A1  - Stepanek, C.
A1  - Swann, G. E. A.
A1  - Telford, R.
A1  - Thomas, E.
A1  - Thomas, Z.
A1  - Truebe, S.
A1  - von Gunten, L.
A1  - Waite, A.
A1  - Weitzel, N.
A1  - Wilhelm, B.
A1  - Williams, J.
A1  - Winstrup, M.
A1  - Zhao, N.
A1  - Zhou, Y.
T1  - PaCTS 1.0: A Crowdsourced Reporting Standard for Paleoclimate Data
JF  - Paleoceanography and paleoclimatology
N2  - The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches.
KW  - standards
KW  - FAIR
KW  - paleoclimate
KW  - paleoceanography
KW  - data
KW  - best practices
Y1  - 2019
U6  - https://doi.org/10.1029/2019PA003632
SN  - 2572-4517
SN  - 2572-4525
VL  - 34
IS  - 10
SP  - 1570
EP  - 1596
PB  - American Geophysical Union
CY  - Washington
ER  - 
TY  - JOUR
A1  - Kong, Xiang-Zhao
A1  - Deuber, Claudia A.
A1  - Kittilä, Anniina
A1  - Somogyvári, Márk
A1  - Mikutis, Gediminas
A1  - Bayer, Peter
A1  - Stark, Wendelin J.
A1  - Saar, Martin O.
T1  - Tomographic Reservoir Imaging with DNA-Labeled Silica Nanotracers: The First Field Validation
JF  - Environmental science & technology
N2  - This study presents the first field validation of using DNA-labeled silica nanoparticles as tracers to image subsurface reservoirs by travel time based tomography. During a field campaign in Switzerland, we performed short-pulse tracer tests under a forced hydraulic head gradient to conduct a multisource-multireceiver tracer test and tomographic inversion, determining the two-dimensional hydraulic conductivity field between two vertical wells. Together with three traditional solute dye tracers, we injected spherical silica nanotracers, encoded with synthetic DNA molecules, which are protected by a silica layer against damage due to chemicals, microorganisms, and enzymes. Temporal moment analyses of the recorded tracer concentration breakthrough curves (BTCs) indicate higher mass recovery, less mean residence time, and smaller dispersion of the DNA-labeled nanotracers, compared to solute dye tracers. Importantly, travel time based tomography, using nanotracer BTCs, yields a satisfactory hydraulic conductivity tomogram, validated by the dye tracer results and previous field investigations. These advantages of DNA-labeled nanotracers, in comparison to traditional solute dye tracers, make them well-suited for tomographic reservoir characterizations in fields such as hydrogeology, petroleum engineering, and geothermal energy, particularly with respect to resolving preferential flow paths or the heterogeneity of contact surfaces or by enabling source zone characterizations of dense nonaqueous phase liquids.
Y1  - 2018
U6  - https://doi.org/10.1021/acs.est.8b04367
SN  - 0013-936X
SN  - 1520-5851
VL  - 52
IS  - 23
SP  - 13681
EP  - 13689
PB  - American Chemical Society
CY  - Washington
ER  - 
TY  - GEN
A1  - Licht, Alexis
A1  - Dupont-Nivet, Guillaume
A1  - Pullen, Alex
A1  - Kapp, Paul
A1  - Abels, Hemmo A.
A1  - Lai, Zulong
A1  - Guo, ZhaoJie
A1  - Abell, Jordan
A1  - Giesler, Dominique
T1  - Resilience of the Asian atmospheric circulation shown by paleogene dust provenance
T2  - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
N2  - The onset of modern central Asian atmospheric circulation is traditionally linked to the interplay of surface uplift of the Mongolian and Tibetan-Himalayan orogens, retreat of the Paratethys sea from central Asia and Cenozoic global cooling. Although the role of these players has not yet been unravelled, the vast dust deposits of central China support the presence of arid conditions and modern atmospheric pathways for the last 25 million years (Myr). Here, we present provenance data from older (42-33 Myr) dust deposits, at a time when the Tibetan Plateau was less developed, the Paratethys sea still present in central Asia and atmospheric pCO(2) much higher. Our results show that dust sources and near-surface atmospheric circulation have changed little since at least 42 Myr. Our findings indicate that the locus of central Asian high pressures and concurrent aridity is a resilient feature only modulated by mountain building, global cooling and sea retreat.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1114 
KW  - Chinese Loess Plateau
KW  - last glacial maximum
KW  - Tibetan Plateau
KW  - Yellow-River
KW  - climate
KW  - basin
KW  - evolution
KW  - ardification
KW  - monsoons
KW  - desert
Y1  - 2021
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-436381
SN  - 1866-8372
IS  - 1114
ER  - 
TY  - JOUR
A1  - Horikoshi, Momoko
A1  - Yaghootkar, Hanieh
A1  - Mook-Kanamori, Dennis O.
A1  - Sovio, Ulla
A1  - Taal, H. Rob
A1  - Hennig, Branwen J.
A1  - Bradfield, Jonathan P.
A1  - St Pourcain, Beate
A1  - Evans, David M.
A1  - Charoen, Pimphen
A1  - Kaakinen, Marika
A1  - Cousminer, Diana L.
A1  - Lehtimaki, Terho
A1  - Kreiner-Moller, Eskil
A1  - Warrington, Nicole M.
A1  - Bustamante, Mariona
A1  - Feenstra, Bjarke
A1  - Berry, Diane J.
A1  - Thiering, Elisabeth
A1  - Pfab, Thiemo
A1  - Barton, Sheila J.
A1  - Shields, Beverley M.
A1  - Kerkhof, Marjan
A1  - van Leeuwen, Elisabeth M.
A1  - Fulford, Anthony J.
A1  - Kutalik, Zoltan
A1  - Zhao, Jing Hua
A1  - den Hoed, Marcel
A1  - Mahajan, Anubha
A1  - Lindi, Virpi
A1  - Goh, Liang-Kee
A1  - Hottenga, Jouke-Jan
A1  - Wu, Ying
A1  - Raitakari, Olli T.
A1  - Harder, Marie N.
A1  - Meirhaeghe, Aline
A1  - Ntalla, Ioanna
A1  - Salem, Rany M.
A1  - Jameson, Karen A.
A1  - Zhou, Kaixin
A1  - Monies, Dorota M.
A1  - Lagou, Vasiliki
A1  - Kirin, Mirna
A1  - Heikkinen, Jani
A1  - Adair, Linda S.
A1  - Alkuraya, Fowzan S.
A1  - Al-Odaib, Ali
A1  - Amouyel, Philippe
A1  - Andersson, Ehm Astrid
A1  - Bennett, Amanda J.
A1  - Blakemore, Alexandra I. F.
A1  - Buxton, Jessica L.
A1  - Dallongeville, Jean
A1  - Das, Shikta
A1  - de Geus, Eco J. C.
A1  - Estivill, Xavier
A1  - Flexeder, Claudia
A1  - Froguel, Philippe
A1  - Geller, Frank
A1  - Godfrey, Keith M.
A1  - Gottrand, Frederic
A1  - Groves, Christopher J.
A1  - Hansen, Torben
A1  - Hirschhorn, Joel N.
A1  - Hofman, Albert
A1  - Hollegaard, Mads V.
A1  - Hougaard, David M.
A1  - Hyppoenen, Elina
A1  - Inskip, Hazel M.
A1  - Isaacs, Aaron
A1  - Jorgensen, Torben
A1  - Kanaka-Gantenbein, Christina
A1  - Kemp, John P.
A1  - Kiess, Wieland
A1  - Kilpelainen, Tuomas O.
A1  - Klopp, Norman
A1  - Knight, Bridget A.
A1  - Kuzawa, Christopher W.
A1  - McMahon, George
A1  - Newnham, John P.
A1  - Niinikoski, Harri
A1  - Oostra, Ben A.
A1  - Pedersen, Louise
A1  - Postma, Dirkje S.
A1  - Ring, Susan M.
A1  - Rivadeneira, Fernando
A1  - Robertson, Neil R.
A1  - Sebert, Sylvain
A1  - Simell, Olli
A1  - Slowinski, Torsten
A1  - Tiesler, Carla M. T.
A1  - Toenjes, Anke
A1  - Vaag, Allan
A1  - Viikari, Jorma S.
A1  - Vink, Jacqueline M.
A1  - Vissing, Nadja Hawwa
A1  - Wareham, Nicholas J.
A1  - Willemsen, Gonneke
A1  - Witte, Daniel R.
A1  - Zhang, Haitao
A1  - Zhao, Jianhua
A1  - Wilson, James F.
A1  - Stumvoll, Michael
A1  - Prentice, Andrew M.
A1  - Meyer, Brian F.
A1  - Pearson, Ewan R.
A1  - Boreham, Colin A. G.
A1  - Cooper, Cyrus
A1  - Gillman, Matthew W.
A1  - Dedoussis, George V.
A1  - Moreno, Luis A.
A1  - Pedersen, Oluf
A1  - Saarinen, Maiju
A1  - Mohlke, Karen L.
A1  - Boomsma, Dorret I.
A1  - Saw, Seang-Mei
A1  - Lakka, Timo A.
A1  - Koerner, Antje
A1  - Loos, Ruth J. F.
A1  - Ong, Ken K.
A1  - Vollenweider, Peter
A1  - van Duijn, Cornelia M.
A1  - Koppelman, Gerard H.
A1  - Hattersley, Andrew T.
A1  - Holloway, John W.
A1  - Hocher, Berthold
A1  - Heinrich, Joachim
A1  - Power, Chris
A1  - Melbye, Mads
A1  - Guxens, Monica
A1  - Pennell, Craig E.
A1  - Bonnelykke, Klaus
A1  - Bisgaard, Hans
A1  - Eriksson, Johan G.
A1  - Widen, Elisabeth
A1  - Hakonarson, Hakon
A1  - Uitterlinden, Andre G.
A1  - Pouta, Anneli
A1  - Lawlor, Debbie A.
A1  - Smith, George Davey
A1  - Frayling, Timothy M.
A1  - McCarthy, Mark I.
A1  - Grant, Struan F. A.
A1  - Jaddoe, Vincent W. V.
A1  - Jarvelin, Marjo-Riitta
A1  - Timpson, Nicholas J.
A1  - Prokopenko, Inga
A1  - Freathy, Rachel M.
T1  - New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism
JF  - Nature genetics
N2  - Birth weight within the normal range is associated with a variety of adult-onset diseases, but the mechanisms behind these associations are poorly understood(1). Previous genome-wide association studies of birth weight identified a variant in the ADCY5 gene associated both with birth weight and type 2 diabetes and a second variant, near CCNL1, with no obvious link to adult traits(2). In an expanded genome-wide association metaanalysis and follow-up study of birth weight (of up to 69,308 individuals of European descent from 43 studies), we have now extended the number of loci associated at genome-wide significance to 7, accounting for a similar proportion of variance as maternal smoking. Five of the loci are known to be associated with other phenotypes: ADCY5 and CDKAL1 with type 2 diabetes, ADRB1 with adult blood pressure and HMGA2 and LCORL with adult height. Our findings highlight genetic links between fetal growth and postnatal growth and metabolism.
Y1  - 2013
U6  - https://doi.org/10.1038/ng.2477
SN  - 1061-4036
VL  - 45
IS  - 1
SP  - 76
EP  - U115
PB  - Nature Publ. Group
CY  - New York
ER  - 
TY  - JOUR
A1  - Nitschke, Felix
A1  - Wang, Peixiang
A1  - Schmieder, Peter
A1  - Girard, Jean-Marie
A1  - Awrey, Donald E.
A1  - Wang, Tony
A1  - Israelian, Johan
A1  - Zhao, XiaoChu
A1  - Turnbull, Julie
A1  - Heydenreich, Matthias
A1  - Kleinpeter, Erich
A1  - Steup, Martin
A1  - Minassian, Berge A.
T1  - Hyperphosphorylation of glucosyl C6 carbons and altered structure of glycogen in the neurodegenerative epilepsy lafora disease
JF  - Cell metabolism
N2  - Laforin or malin deficiency causes Lafora disease, characterized by altered glycogen metabolism and teenage-onset neurodegeneration with intractable and invariably fatal epilepsy. Plant starches possess small amounts of metabolically essential monophosphate esters. Glycogen contains similar phosphate amounts, which are thought to originate from a glycogen synthase error side reaction and therefore lack any specific function. Glycogen is also believed to lack monophosphates at glucosyl carbon C6, an essential phosphorylation site in plant starch metabolism. We now show that glycogen phosphorylation is not due to a glycogen synthase side reaction, that C6 is a major glycogen phosphorylation site, and that C6 monophosphates predominate near centers of glycogen molecules and positively correlate with glycogen chain lengths. Laforin or malin deficiency causes C6 hyperphosphorylation, which results in malformed long-chained glycogen that accumulates in many tissues, causing neurodegeneration in brain. Our work advances the understanding of Lafora disease pathogenesis and suggests that glycogen phosphorylation has important metabolic function.
Y1  - 2013
U6  - https://doi.org/10.1016/j.cmet.2013.04.006
SN  - 1550-4131
SN  - 1932-7420
VL  - 17
IS  - 5
SP  - 756
EP  - 767
PB  - Cell Press
CY  - Cambridge
ER  -