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  • 1
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    The @journal of physical chemistry 〈Washington, DC〉 84 (1980), S. 793-798 
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology , Physics
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] Hedgehog signalling—an essential pathway during embryonic pancreatic development, the misregulation of which has been implicated in several forms of cancer—may also be an important mediator in human pancreatic carcinoma. Here we report that sonic hedgehog, a secreted hedgehog ...
    Type of Medium: Electronic Resource
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  • 3
    ISSN: 0173-0835
    Keywords: Randomly amplified polymorphic DNA ; Microsatellites ; Gene pool ; Genetic resources ; Chemistry ; Biochemistry and Biotechnology
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Biology , Chemistry and Pharmacology
    Notes: Plant genetic resources are an important component of biodiversity and provide the basic genetic variability that allow new and improved cultivars to be developed. Numerous germplasm collections have been established and it is important to establish that such collections are representative and accessible to breeders and biotechnologists. Molecular markers provide the best estimate of genetic diversity since they are independent of the confounding effects of environmental factors. Assays based on the polymerase chain reaction (PCR) are considered to meet both the technical and genetical requirements for the characterisation of plant and animal genetic resources. Two main approaches are described, based on anonymous and defined primers. The use of both randomly amplified polymorphic DNA (RAPD) and microsatellites or simple sequence repeats (SSR) for the characterisation of perennial tree species, and distribution of variability within gene pools is reported. The detection of interspecific gene introgression between coffee species with RAPD markers is described together with the use of microsatellites to genotype potato. The use of PCR-based assays will facilitate the evaluation and utilisation of plant genetic resources.
    Additional Material: 4 Ill.
    Type of Medium: Electronic Resource
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  • 4
    Publication Date: 2023-03-14
    Keywords: Carbon, inorganic, dissolved; Carbon, organic, particulate; Carbon/Nitrogen ratio; Carbon dioxide, partial pressure; Chlorophyll a; CTD; Date/Time of event; DEPTH, water; Environment; Event label; Latitude of event; Longitude of event; LowpHOX-II; Lowphox-II_T3; Lowphox-II_T5; Nitrate; Nitrite; Nitrogen, organic, particulate; Oxygen, dissolved; pH; Phosphate; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 221 data points
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  • 5
    Publication Date: 2023-03-06
    Description: These data are part of the LowpHOX-2 cruise off the northern coast of Chile investigating the distribution of intact polar lipids above, through, and below the oxygen minimum zone at two stations. We report intact polar lipid concentrations in addition to a number of water column chemistry parameters. Used in a manuscript under review at Frontiers in Marine Science.
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 6
    Publication Date: 2023-03-06
    Keywords: Archaeol; CTD; Date/Time of event; DEPTH, water; Diacylglyceryl carboxyhydroxymethylcholine 16:0; Diacylglyceryl carboxyhydroxymethylcholine 17:0; Diacylglyceryl carboxyhydroxymethylcholine 19:0; Diacylglyceryl carboxyhydroxymethylcholine 21:0; Diacylglyceryl carboxyhydroxymethylcholine 22:4; Diacylglyceryl carboxyhydroxymethylcholine 23:0; Diacylglyceryl carboxyhydroxymethylcholine 23:1; Diacylglyceryl carboxyhydroxymethylcholine 23:6; Diacylglyceryl carboxyhydroxymethylcholine 24:2; Diacylglyceryl carboxyhydroxymethylcholine 26:0; Diacylglyceryl carboxyhydroxymethylcholine 27:0; Diacylglyceryl carboxyhydroxymethylcholine 28:0; Diacylglyceryl carboxyhydroxymethylcholine 29:0; Diacylglyceryl carboxyhydroxymethylcholine 30:0; Diacylglyceryl carboxyhydroxymethylcholine 31:1; Diacylglyceryl carboxyhydroxymethylcholine 32:0; Diacylglyceryl carboxyhydroxymethylcholine 33:0; Diacylglyceryl carboxyhydroxymethylcholine 36:6; Diacylglyceryl carboxyhydroxymethylcholine 38:6; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 19:0; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 24:0; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 25:0; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 26:0; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 28:0; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 29:0; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 30:0; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 30:1; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 32:1; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 32:2; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 33:1; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 34:1; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 34:2; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 34:4; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 34:5; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 35:1; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 36:2; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 36:6; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 38:0; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 38:5; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 39:0; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 40:10; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 42:11; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 44:11; Diacylglyceryl hydroxymethyl-trimethyl-beta-alanine 44:12; Diacylglyceryl trimethylhomoserine 25:0; Diacylglyceryl trimethylhomoserine 26:0; Diacylglyceryl trimethylhomoserine 26:2; Diacylglyceryl trimethylhomoserine 27:0; Diacylglyceryl trimethylhomoserine 28:0; Diacylglyceryl trimethylhomoserine 28:1; Diacylglyceryl trimethylhomoserine 29:0; Diacylglyceryl trimethylhomoserine 29:1; Diacylglyceryl trimethylhomoserine 30:0; Diacylglyceryl trimethylhomoserine 30:1; Diacylglyceryl trimethylhomoserine 31:0; Diacylglyceryl trimethylhomoserine 31:1; Diacylglyceryl trimethylhomoserine 32:0; Diacylglyceryl trimethylhomoserine 32:1; Diacylglyceryl trimethylhomoserine 32:2; Diacylglyceryl trimethylhomoserine 32:3; Diacylglyceryl trimethylhomoserine 32:4; Diacylglyceryl trimethylhomoserine 33:0; Diacylglyceryl trimethylhomoserine 33:1; Diacylglyceryl trimethylhomoserine 34:0; Diacylglyceryl trimethylhomoserine 34:1; Diacylglyceryl trimethylhomoserine 34:2; Diacylglyceryl trimethylhomoserine 34:3; Diacylglyceryl trimethylhomoserine 34:4; Diacylglyceryl trimethylhomoserine 34:5; Diacylglyceryl trimethylhomoserine 34:6; Diacylglyceryl trimethylhomoserine 34:8; Diacylglyceryl trimethylhomoserine 35:0; Diacylglyceryl trimethylhomoserine 35:1; Diacylglyceryl trimethylhomoserine 36:2; Diacylglyceryl trimethylhomoserine 36:3; Diacylglyceryl trimethylhomoserine 36:4; Diacylglyceryl trimethylhomoserine 36:5; Diacylglyceryl trimethylhomoserine 36:6; Diacylglyceryl trimethylhomoserine 37:1; Diacylglyceryl trimethylhomoserine 37:2; Diacylglyceryl trimethylhomoserine 37:5; Diacylglyceryl trimethylhomoserine 37:6; Diacylglyceryl trimethylhomoserine 38:0; Diacylglyceryl trimethylhomoserine 38:1; Diacylglyceryl trimethylhomoserine 39:1; Diacylglyceryl trimethylhomoserine 40:1; Diacylglyceryl trimethylhomoserine OH-34:1; Digalactosyldiacylglycerol 28:0; Digalactosyldiacylglycerol 30:0; Digalactosyldiacylglycerol 30:2; Digalactosyldiacylglycerol 31:1; Digalactosyldiacylglycerol 32:0; Digalactosyldiacylglycerol 32:1; Digalactosyldiacylglycerol 32:2; Digalactosyldiacylglycerol 32:4; Digalactosyldiacylglycerol 32:5; Digalactosyldiacylglycerol 32:6; Digalactosyldiacylglycerol 34:0; Digalactosyldiacylglycerol 34:1; Digalactosyldiacylglycerol 34:2; Digalactosyldiacylglycerol 34:3; Digalactosyldiacylglycerol 34:4; Digalactosyldiacylglycerol 34:6; Digalactosyldiacylglycerol 34:7; Digalactosyldiacylglycerol 35:3; Digalactosyldiacylglycerol 36:0; Diglycosyl dietherglyceride 36:4; Diglycosyl dietherglyceride 37:5; Environment; Event label; Latitude of event; Longitude of event; LowpHOX-II; Lowphox-II_T3; Lowphox-II_T5; Monogalactosyldiacylglycerol 24:0; Monogalactosyldiacylglycerol 27:2; Monogalactosyldiacylglycerol 28:0; Monogalactosyldiacylglycerol 28:1; Monogalactosyldiacylglycerol 30:0; Monogalactosyldiacylglycerol 30:1; Monogalactosyldiacylglycerol 30:2; Monogalactosyldiacylglycerol 30:3; Monogalactosyldiacylglycerol 31:0; Monogalactosyldiacylglycerol 31:1; Monogalactosyldiacylglycerol 32:0; Monogalactosyldiacylglycerol 32:1; Monogalactosyldiacylglycerol 32:2; Monogalactosyldiacylglycerol 33:0; Monogalactosyldiacylglycerol 34:0; Monogalactosyldiacylglycerol 34:1; Monogalactosyldiacylglycerol 34:7; Monogalactosyldiacylglycerol 36:0; Monogalactosyldiacylglycerol 36:10; Monogalactosyldiacylglycerol 36:5; Monogalactosyldiacylglycerol 39:5; Monoglycosyl archaeol; Monoglycosyl ceramide 22:2; Monoglycosyl ceramide 25:6; Monoglycosyl ceramide 29:4; Monoglycosyl ceramide 31:4; Monoglycosyl ceramide 36:1; Monoglycosyl ceramide 37:4; Monoglycosyl ceramide 38:4; Monoglycosyl glyceroldialkylglyceroltetraether 0; Monoglycosyl glyceroldialkylglyceroltetraether 4; Monoglycosyl glyceroldialkylglyceroltetraether 5; Ornithine lipid 33:0; Ornithine lipid 33:1; Ornithine lipid 34:0; Ornithine lipid 35:1; Ornithine lipid 35:6; Ornithine lipid 36:1; Ornithine lipid 36:6; Ornithine lipid 37:1; Ornithine lipid 38:1; Ornithine lipid 38:6; Phosphatidylcholinediacylglycerol 24:0; Phosphatidylcholinediacylglycerol 26:0; Phosphatidylcholinediacylglycerol 27:0; Phosphatidylcholinediacylglycerol 28:0; Phosphatidylcholinediacylglycerol 29:0; Phosphatidylcholinediacylglycerol 29:1; Phosphatidylcholinediacylglycerol 29:2; Phosphatidylcholinediacylglycerol 30:0; Phosphatidylcholinediacylglycerol 30:1; Phosphatidylcholinediacylglycerol 30:2; Phosphatidylcholinediacylglycerol 31:0; Phosphatidylcholinediacylglycerol 31:1; Phosphatidylcholinediacylglycerol 31:2; Phosphatidylcholinediacylglycerol 32:0; Phosphatidylcholinediacylglycerol 32:1; Phosphatidylcholinediacylglycerol 32:2; Phosphatidylcholinediacylglycerol 32:6; Phosphatidylcholinediacylglycerol 33:0; Phosphatidylcholinediacylglycerol 33:1; Phosphatidylcholinediacylglycerol 33:2; Phosphatidylcholinediacylglycerol 33:5; Phosphatidylcholinediacylglycerol 33:6; Phosphatidylcholinediacylglycerol 34:1; Phosphatidylcholinediacylglycerol 34:4; Phosphatidylcholinediacylglycerol 35:0; Phosphatidylcholinediacylglycerol 35:1; Phosphatidylcholinediacylglycerol 36:1; Phosphatidylcholinediacylglycerol 36:10; Phosphatidylcholinediacylglycerol 36:3; Phosphatidylcholinediacylglycerol 36:5; Phosphatidylcholinediacylglycerol 37:6; Phosphatidylcholinediacylglycerol 38:1; Phosphatidylcholinediacylglycerol 38:2; Phosphatidylcholinediacylglycerol 38:5; Phosphatidylcholinediacylglycerol 38:6; Phosphatidylcholinediacylglycerol 39:5; Phosphatidylcholinediacylglycerol 40:10; Phosphatidylcholinediacylglycerol 40:9; Phosphatidylcholinediacylglycerol 42:0; Phosphatidylcholinediacylglycerol 42:11; Phosphatidylcholinediacylglycerol 44:12;
    Type: Dataset
    Format: text/tab-separated-values, 3223 data points
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  • 7
    Publication Date: 2019-12-16
    Description: Transcriptional profiling has defined pancreatic ductal adenocarcinoma (PDAC) into distinct subtypes with the majority being classical epithelial (E) or quasi-mesenchymal (QM). Despite clear differences in clinical behavior, growing evidence indicates these subtypes exist on a continuum with features of both subtypes present and suggestive of interconverting cell states. Here, we investigated the impact of different therapies being evaluated in PDAC on the phenotypic spectrum of the E/QM state. We demonstrate using RNA-sequencing and RNA-in situ hybridization (RNA-ISH) that FOLFIRINOX combination chemotherapy induces a common shift of both E and QM PDAC toward a more QM state in cell lines and patient tumors. In contrast, Vitamin D, another drug under clinical investigation in PDAC, induces distinct transcriptional responses in each PDAC subtype, with augmentation of the baseline E and QM state. Importantly, this translates to functional changes that increase metastatic propensity in QM PDAC, but decrease dissemination in E PDAC in vivo models. These data exemplify the importance of both the initial E/QM subtype and the plasticity of E/QM states in PDAC in influencing response to therapy, which highlights their relevance in guiding clinical trials.
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
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  • 8
  • 9
    Publication Date: 2018-05-29
    Description: Achieving the upper limits of face identification accuracy in forensic applications can minimize errors that have profound social and personal consequences. Although forensic examiners identify faces in these applications, systematic tests of their accuracy are rare. How can we achieve the most accurate face identification: using people and/or machines working alone or in collaboration? In a comprehensive comparison of face identification by humans and computers, we found that forensic facial examiners, facial reviewers, and superrecognizers were more accurate than fingerprint examiners and students on a challenging face identification test. Individual performance on the test varied widely. On the same test, four deep convolutional neural networks (DCNNs), developed between 2015 and 2017, identified faces within the range of human accuracy. Accuracy of the algorithms increased steadily over time, with the most recent DCNN scoring above the median of the forensic facial examiners. Using crowd-sourcing methods, we fused the judgments of multiple forensic facial examiners by averaging their rating-based identity judgments. Accuracy was substantially better for fused judgments than for individuals working alone. Fusion also served to stabilize performance, boosting the scores of lower-performing individuals and decreasing variability. Single forensic facial examiners fused with the best algorithm were more accurate than the combination of two examiners. Therefore, collaboration among humans and between humans and machines offers tangible benefits to face identification accuracy in important applications. These results offer an evidence-based roadmap for achieving the most accurate face identification possible.
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
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  • 10
    Publication Date: 2016-09-16
    Description: Southwest Oklahoma is one of the most productive regions in the Great Plains (USA) where winter wheat is produced. To assess the effect of climate change on the growing degree days (GDD) available for winter wheat production, we selected from the CMIP5 archive, two of the best performing Global Climate Models (GCMs) for the region (MIROC5 and CCSM4) to project the future change in GDD under the Representative Concentration Pathways (RCP) 8.5 and 4.5 future trajectories for greenhouse gas concentrations. Two quantile mapping methods were applied to both GCMs to obtain local scale projections. The local scale outputs were applied to a GDD formula to show the GDD changes between the historical period (1961–2004) and the future period (2006–2098) in terms of mean differences. The results show that at the end of the 2098 growing season, the increase in GDD is expected to be between 440 °C and 1300 °C, for RCP 4.5, and between 700 °C and 1350 °C for RCP 8.5. This increase in GDD might cause a decrease in the number of days required to reach crop maturity, as all the GCM/statistical post-processing combinations showed a decreasing trend of those timings during the 21st century. Furthermore, we conclude, that when looking at the influence of the selected GCMs and the quantile mapping methods on the GDD calculation, the GCMs differences originated from the significant spatial and temporal variations of GDD over the region and not the statistical methods tested.
    Electronic ISSN: 2077-0472
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Published by MDPI
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