186 research outputs found
Feeding, growth and grazing rates of various Ciliate cultures determined experimentally
No full textCarbon per cell of grazer calculated using the following equation of Menden-Deuer and Lessard (2000): picogram carbon per cell = 0.216*biovolume**0.939
Growth rate of the marine planktonic ciliate Strombidinopsis cheshiri determined experimentally
No full textCarbon per cell of grazer calculated using the following equation of Menden-Deuer and Lessard (2000): picogram carbon per cell = 0.216*biovolume**0.939
Ermittlung und Überprüfung der Datengrundlage für das Modell zur Einsparung von Treibhausgasen durch stoffliche Holznutzung im Bauwesen im Holzbau-GIS für die Stadt Menden
No full textUm Entscheidungsträger von Kommunen in die Lage zu versetzen, die erreichbaren Treibhausgaseinsparungen durch den Einsatz von Holz als Baumaterial in ihre kommunalen Klimaschutzkonzepte in Selbstverwaltung integrieren zu können, wurde ein Berechnungsmodell entwickelt, welches die potenziellen Treibhausgaseinsparungen abschätzt. In diesem Beitrag wird die Ermittlung der Datengrundlage für dieses Modell vorgestellt. Grundlage des Berechnungsmodells bilden Datensätze, mit denen die Gebäude der Beispielkommune (Menden in Nordrhein-Westfalen) möglichst detailliert beschrieben werden können. Unter Berücksichtigung der Anforderungen an die Daten eignen sich hierfür vor allem Daten des Amtlichen Liegenschaftskatasters sowie ein 3d-Datensatz der Gebäude. Da das Gebäudealter aus diesen Datensätzen nicht bestimmt werden kann, wird die Ermittlung des Baualters anhand von historischen Orthophotos vorgenommen
Biochemische Analysen zur Bedeutung von Phenolsäuren und Lignin für Resistenz und Anfälligkeit von Weizenpflanzen gegen Schwarzrost (Puccinia graminis f. sp. tritici)
No full textSeasonal similarity in rates of protistan herbivory in fjords along the Western Antarctic Peninsula
No full textWe quantified phytoplankton growth and protistan grazing rates during late austral autumn 2013 and late austral spring 2014, in several glacio-marine fjords and connecting channels along the Western Antarctic Peninsula (WAP). During austral autumn, low and declining chlorophyll a (Chl a) concentrations (≤ 0.4 μg L−1) were almost entirely composed of pico/nanophytoplankton, whereas during austral spring, high but patchy Chl a concentrations in the fjords (up to 18.5 μg L−1) reflected a diatom bloom. These contrasting dynamics were associated with high seasonal differences in irradiance, but not temperature, and were consistent with the balance resulting from lower phytoplankton growth rates in autumn (−0.01 d−1 to 0.19 d−1) than in spring (0.06–0.93 d−1) but similar magnitudes of herbivorous grazing in both seasons. Grazing was either absent or low (0.11–0.26 d−1) and restricted to the picophytoplankton and nanophytoplankton. In the productive fjords lining the WAP, a fraction of primary production was channelled through a persistent and across-seasons equally active microbial food web, while during spring an increasing fraction of organic carbon shifted from trophic transfer and recycling to an export pathway
Avoidance, movement, and mortality: The interactions between a protistan grazer and <i>Heterosigma akashiwo</i> , a harmful algal bloom species
No full textA reduction in predator-induced grazing pressure may be a mechanism that facilitates the formation and persistence of harmful algal blooms. Here, the hypothesis was tested that the heterotrophic ciliate Favella ehrenbergii would use avoidance behaviors to reduce encounters with the toxic bloom-forming alga, Heterosigma akashiwo. Using video and image-analysis, population distributions and three-dimensional movements of F. ehrenbergii and H. akashiwo were quantified in triplicate, hourly for 11 h, at nine horizons in a 1-liter experimental column. The salinity structure in the column was manipulated to include a halocline, resulting in layer formation by H. akashiwo. The ciliate\u27s vertical distributions were restricted to high-salinity waters below the halocline, while H. akashiwo was broadly halo-tolerant and could occupy the whole water column. When observed together, F. ehrenbergii did not avoid layers of H. akashiwo. In the presence of H. akashiwo, F. ehrenbergii mortality rates were higher than in either no prey or beneficial prey controls. Swimming behaviors of F. ehrenbergii were erratic, in response to H. akashiwo, compared to aggregative movements in response to beneficial prey, indicating either a behavioral response or the effect of H. akashiwo toxicity on the ciliate. The inability of F. ehrenbergii to avoid H. akashiwo enhanced predator mortality and may contribute to the survival of the harmful algal bloom species, ultimately promoting the formation of H. akashiwo harmful algal blooms. © 2011, by the American Society of Limnology and Oceanography, Inc
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Screening of Commercial Lettuce Cultivars for Resistance to Fusarium Wilt
No full textFusarium wilt of lettuce is one of the most serious fungal diseases affecting lettuce worldwide. It is caused by a soil-borne fungus, Fusarium oxysporum f. sp. lactucae (FOL), which is found in most areas where lettuce is produced. In this study, 56 commercial lettuce cultivars were tested against three different strains of FOL Race 1 collected from infected fields in Yuma, Arizona: BMP3769, BMP3958, and BMP3932, to quantify resistance and susceptibility. Three-week-old lettuce seedlings were inoculated with an FOL spore suspension during transplantation in greenhouse trials. Each plant was monitored for disease expression and scored using an ordinal wilt scale from 1-6. Plant height data was also collected during the trial period. Several lettuce cultivars were identified as resistant to Fusarium wilt, while others exhibited severe disease incidence or diminished growth due to Fusarium infection. Some cultivars also exhibited differential susceptibility among Fusarium strains and varied susceptibility between repeated trials. Of 32 crisphead cultivars tested, Meridian, Powerball GCHD Progreen Oxy E, and Fredonia were found to be resistant to all three FOL isolates. Only one romaine cultivar, Bondi, of the 16 romaine varieties tested was determined to be susceptible to FOL
Identification and validation of a tear fluid-derived protein biomarker signature in patients with amyotrophic lateral sclerosis
No full textAbstract The diagnosis of Amyotrophic Lateral Sclerosis (ALS) remains challenging, particularly in early stages, where characteristic symptoms may be subtle and nonspecific. The development of disease-specific and clinically validated biomarkers is crucial to optimize diagnosis. Here, we explored tear fluid (TF) as a promising ALS biomarker source, given its accessibility, anatomical proximity to the brainstem as an important site of neurodegeneration, and proven discriminative power in other neurodegenerative diseases. Using a discovery approach, we profiled protein abundance in TF of ALS patients (n = 49) and controls (n = 54) via data-independent acquisition mass spectrometry. Biostatistical analysis and machine learning identified differential protein abundance and pathways in ALS, leading to a protein signature. These proteins were validated by Western blot in an independent cohort (ALS n = 51; controls n = 52), and their discriminatory performance was assessed in-silico employing machine learning. 876 proteins were consistently detected in TF, with 106 differentially abundant in ALS. A six-protein signature, including CRYM, PFKL, CAPZA2, ALDH16A1, SERPINC1, and HP, exhibited discriminatory potential. We replicated significant differences of SERPINC1 and HP levels between ALS and controls across the cohorts, and their combination yielded the best in-silico performance. Overall, this investigation of TF proteomics in ALS and controls revealed dysregulated proteins and pathways, highlighting inflammation as a key disease feature, strengthening the potential of TF as a source for biomarker discovery
Landwirtschaftliche Emissionen, Teilbericht zum F&E-Vorhaben "Strategien zur Verminderung der Feinstaubbelastung - PAREST"
No full textIdentification of Intrinsic Drug Resistance and Its Biomarkers in High-Throughput Pharmacogenomic and CRISPR Screens
No full textHigh-throughput drug screens in cancer cell lines test compounds at low concentrations, thereby enabling the identification of drug-sensitivity biomarkers, while resistance biomarkers remain underexplored. Dissecting meaningful drug responses at high concentrations is challenging due to cytotoxicity, i.e., off-target effects, thus limiting resistance biomarker discovery to frequently mutated cancer genes. To address this, we interrogate subpopulations carrying sensitivity biomarkers and consecutively investigate unexpectedly resistant (UNRES) cell lines for unique genetic alterations that may drive resistance. By analyzing the GDSC and CTRP datasets, we find 53 and 35 UNRES cases, respectively. For 24 and 28 of them, we highlight putative resistance biomarkers. We find clinically relevant cases such as EGFRT790M mutation in NCI-H1975 or PTEN loss in NCI-H1650 cells, in lung adenocarcinoma treated with EGFR inhibitors. Interrogating the underpinnings of drug resistance with publicly available CRISPR phenotypic assays assists in prioritizing resistance drivers, offering hypotheses for drug combinations. Cancer drug resistance is the major challenge of modern oncology. Identifying resistance and its biomarkers will empower the next generation of precision medicines. High-throughput pharmacology screens in cancer cell lines have successfully identified drug-sensitivity biomarkers, but drug-resistance biomarkers are underexplored. Intrinsic drug-resistance events are often rare and experimentally indistinguishable from cytotoxicity or artifacts without prior knowledge. To address this, we investigate cell-line populations sensitized to a drug treatment (i.e., carrying established sensitivity biomarkers) and characterize those cell lines that do not respond as expected. We highlight unique genetic features harbored by these cell lines and confirm their linkage to drug resistance using CRISPR gene essentiality data. Our analysis and results pave the way for enhanced precision medicine, guide further CRISPR screens, and identify potential drug combinations to tackle resistance. Identifying cancer drug resistance and its biomarkers will empower the next generation of anti-cancer medicines, tailoring treatments to individual patients. Detecting drug resistance in high-throughput pharmacology screens is experimentally challenging. We present a computational framework identifying rare intrinsically resistant cancer cell lines. Our observations provide hypotheses for associated drug-resistance biomarkers, which we validate with independent CRISPR essentiality screens. Our results pave the way for enhancing cancer precision medicine and effective drug combinations to overcome resistance. © 2020 The Author
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