University of Kiel

About: University of Kiel is a education organization based out in Kiel, Germany. It is known for research contribution in the topics: Population & Crystal structure. The organization has 27816 authors who have published 57114 publications receiving 2061802 citations. The organization is also known as: Christian Albrechts University & Christian-Albrechts-Universität zu Kiel.

Combined evaluation of a panel of protein and miRNA serum-exosome biomarkers for pancreatic cancer diagnosis increases sensitivity and specificity.

Abstract: Late diagnosis contributes to pancreatic cancer (PaCa) dismal prognosis, urging for reliable, early detection. Serum-exosome protein and/or miRNA markers might be suitable candidates, which we controlled for patients with PaCa. Protein markers were selected according to expression in exosomes of PaCa cell line culture supernatants, but not healthy donors' serum-exosomes. miRNA was selected according to abundant recovery in microarrays of patients with PaCa, but not healthy donors' serum-exosomes and exosome-depleted serum. According to these preselections, serum-exosomes were tested by flow cytometry for the PaCa-initiating cell (PaCIC) markers CD44v6, Tspan8, EpCAM, MET and CD104. Serum-exosomes and exosome-depleted serum was tested for miR-1246, miR-4644, miR-3976 and miR-4306 recovery by qRT-PCR. The majority (95%) of patients with PaCa (131) and patients with nonPa-malignancies reacted with a panel of anti-CD44v6, -Tspan8, -EpCAM and -CD104. Serum-exosomes of healthy donors' and patients with nonmalignant diseases were not reactive. Recovery was tumor grading and staging independent including early stages. The selected miR-1246, miR-4644, miR-3976 and miR-4306 were significantly upregulated in 83% of PaCa serum-exosomes, but rarely in control groups. These miRNA were also elevated in exosome-depleted serum of patients with PaCa, but at a low level. Concomitant evaluation of PaCIC and miRNA serum-exosome marker panels significantly improved sensitivity (1.00, CI: 0.95-1) with a specificity of 0.80 (CI: 0.67-0.90) for PaCa versus all others groups and of 0.93 (CI: 0.81-0.98) excluding nonPa-malignancies. Thus, the concomitant evaluation of PaCIC and PaCa-related miRNA marker panels awaits retrospective analyses of larger cohorts, as it should allow for a highly sensitive, minimally-invasive PaCa diagnostics.

Crop pests and predators exhibit inconsistent responses to surrounding landscape composition

Abstract: The idea that noncrop habitat enhances pest control and represents a win-win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win-win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies.

Sdss dr7 white dwarf catalog

Abstract: We present a new catalog of spectroscopically confirmed white dwarf stars from the Sloan Digital Sky Survey (SDSS) Data Release 7 spectroscopic catalog. We find 20,407 white dwarf spectra, representing 19,712 stars, and provide atmospheric model fits to 14,120 DA and 1011 DB white dwarf spectra from 12,843 and 923 stars, respectively. These numbers represent more than a factor of two increase in the total number of white dwarf stars from the previous SDSS white dwarf catalogs based on DR4 data. Our distribution of subtypes varies from previous catalogs due to our more conservative, manual classifications of each star in our catalog, supplementing our automatic fits. In particular, we find a large number of magnetic white dwarf stars whose small Zeeman splittings mimic increased Stark broadening that would otherwise result in an overestimated log g if fit as a non-magnetic white dwarf. We calculate mean DA and DB masses for our clean, non-magnetic sample and find the DB mean mass is statistically larger than that for the DAs.