Glucose concentrations after insulin‐induced hypoglycemia and glycemic variability in healthy and diabetic cats          下载免费PDF全文

Eric Zini  Elena Salesov  Perrine Dupont  Laura Moretto  Barbara Contiero  Thomas A. Lutz  Claudia E. Reusch 《Journal of veterinary internal medicine / American College of Veterinary Internal Medicine》2018,32(3):978-985

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What is your diagnosis? Nasal discharge from a sheep          下载免费PDF全文

Austin K. Viall  Alejandro Larios Mora  Matthew T. Brewer  Joseph S. Smith  Amanda J. Kreuder  Ryan M. Breuer  Amanda J. Fales‐Williams 《Veterinary clinical pathology / American Society for Veterinary Clinical Pathology》2018,47(3):503-504

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III. Buchbesprechungen     

E. Rohmeder  v. Pechmann  Mägdefrau  A. Bernhart  J. L. Lutz 《European Journal of Forest Research》1961,80(11-12):393-396

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III. Buchbesprechungen     

Zwölfer  Wehrmann  E. Rohmeder  Schwenke  J. L. Lutz  J. Jung 《European Journal of Forest Research》1960,79(7-8):254-256

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Oceanographic basis of the global surface distribution of Prochlorococcus ecotypes     

Bouman HA  Ulloa O  Scanlan DJ  Zwirglmaier K  Li WK  Platt T  Stuart V  Barlow R  Leth O  Clementson L  Lutz V  Fukasawa M  Watanabe S  Sathyendranath S 《Science (New York, N.Y.)》2006,312(5775):918-921

By using data collected during a continuous circumnavigation of the Southern Hemisphere, we observed clear patterns in the population-genetic structure of Prochlorococcus, the most abundant photosynthetic organism on Earth, between and within the three Southern Subtropical Gyres. The same mechanisms that were previously invoked to account for the vertical distribution of ecotypes at local scales accounted for the global (horizontal) patterns we observed. Basin-scale and seasonal variations in the structure and strength of vertical stratification provide a basis for understanding large-scale horizontal distribution in genetic and physiological traits of Prochlorococcus, and perhaps of marine microbial communities in general.  相似文献   

Toxic potential of materials at the nanolevel   总被引：12，自引：0，他引：12  

Nel A  Xia T  Mädler L  Li N 《Science (New York, N.Y.)》2006,311(5761):622-627

Nanomaterials are engineered structures with at least one dimension of 100 nanometers or less. These materials are increasingly being used for commercial purposes such as fillers, opacifiers, catalysts, semiconductors, cosmetics, microelectronics, and drug carriers. Materials in this size range may approach the length scale at which some specific physical or chemical interactions with their environment can occur. As a result, their properties differ substantially from those bulk materials of the same composition, allowing them to perform exceptional feats of conductivity, reactivity, and optical sensitivity. Possible undesirable results of these capabilities are harmful interactions with biological systems and the environment, with the potential to generate toxicity. The establishment of principles and test procedures to ensure safe manufacture and use of nanomaterials in the marketplace is urgently required and achievable.  相似文献   

An adaptive composite density estimator for <Emphasis Type="Italic">k</Emphasis>-tree sampling     

Steen Magnussen  Lutz Fehrman  William J. Platt 《European Journal of Forest Research》2012,131(2):307-320

Density estimators for k-tree distance sampling are sensitive to the amount of extra Poisson variance in distances to the kth tree. To lessen this sensitivity, we propose an adaptive composite estimator (COM). In simulated sampling from 16 test populations, a three-component composite density estimator (COM)–with weights determined by a multinomial logistic function of four readily available ancillary variables–was identified as superior in terms of average relative absolute bias. Results from a different set of nine validation populations–with widely different stem densities and spatial patterns of tree locations—confirmed that relative root mean squared errors (RRMSE) of COM were, on average, considerably lower than those obtained with the three-component k-tree density estimators. The RRMSE performance of COM improved with increasing values of k. With k = 6 and sample sizes of 10, 20, and 30, the average relative bias of COM was between −5 and 5% in seven validation populations but in an open low-density savanna-like population bias reached −12% (1979 data) and 7% (1996 data). For k = 6 and n = 10, the RRMSE of COM was, in six of the nine validation populations, within 3.3 percentage points of the RRMSE for sampling with fixed-area plots. Jackknife estimates of the precision of COM estimates of density were negatively biased, leading to under-coverage (7%) of computed 95% confidence intervals.  相似文献   

Erratum to: An adaptive composite density estimator for k-tree sampling     

Steen Magnussen  Lutz Fehrman  William J. Platt 《European Journal of Forest Research》2012,131(2):321-321

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Ocean science. A dive to Challenger Deep     

Lutz RA  Falkowski PG 《Science (New York, N.Y.)》2012,336(6079):301-302

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Bordetella bronchiseptica infection in cats. ABCD guidelines on prevention and management     

Herman Egberink  Diane Addie  Sándor Belák  Corine Boucraut-Baralon  Tadeusz Frymus  Tim Gruffydd-Jones  Katrin Hartmann  Margaret J. Hosie  Albert Lloret  Hans Lutz  Fulvio Marsilio  Maria Grazia Pennisi  Alan D. Radford  Etienne Thiry  Uwe Truyen  Marian C. Horzinek 《Journal of Feline Medicine and Surgery》2009,11(7):610-614

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