Zobrazení zdroje stránky Meierbond3675

Medicinal plants represent a valuable commodity due to beneficial effects of their natural products on human health, prompting a need for finding a way to optimize/increase their production. In this study, a novel growing media with various perlite particle size and its mixture with peat moss was tested for hydroponic-based production of Echinacea purpurea medicinal plant under greenhouse conditions. The plant growth parameters such as plant height, total fresh leave weight, fresh root weight, total biomass, total chlorophyll, leaf area, and essential oil compositions were assessed. Perlite particle size in the growing media was varied from very coarse (more than 2 mm) to very fine (less than 0.5 mm), and the ratio between perlite and peat moss varied from 5050 v/v to 3070 v/v. In addition, two nitrate (NO3-) to ammonium (NH4+) ratios (9010 and 7030) were tested for each growing media. The medium containing very fine-grade perlite and 5050 v/v perlite to peat moss ratio was found to be most optimal and beneficial for E. purpurea performance, resulting in maximal plant height, fresh and dry weight, leaf surface area, and chlorophyll content. It was also found that an increase in NO3-/NH4+ ratio caused a significant increase in plant growth parameters and increase the plant essential oil content. The major terpene hydrocarbons found in extract of E. purpurea with the best growth parameters were germacrene D (51%), myrcene (15%), α-pinene (12%), β-caryophyllene (11%), and 1-Pentadecene (4.4%), respectively. The percentages of these terpene hydrocarbons were increased by increasing of NO3-/NH4+ ratio. It can be concluded that decreasing the perlite particle size and increasing the NO3-/NH4+ ratio increased the plant growth parameters and essential oil compositions in E. purpurea.In the past decade neutron dark-field contrast imaging has developed from a qualitative tool depicting microstructural inhomogeneities in bulk samples on a macroscopic scale of tens to hundreds of micrometers to a quantitative spatial resolved small-angle scattering instrument. While the direct macroscopic image resolution around tens of micrometers remains untouched microscopic structures have become assessable quantitatively from the nanometer to the micrometer range. Although it was found that magnetic structures provide remarkable contrast we could only recently introduce polarized neutron grating interferometric imaging. Here we present a polarized and polarization analyzed dark-field contrast method for spatially resolved small-angle scattering studies of magnetic microstructures. It is demonstrated how a polarization analyzer added to a polarized neutron grating interferometer does not disturb the interferometric measurements but allows to separate and measure spin-flip and non-spin-flip small-angle scattering and thus also the potential for a distinction of nuclear and different magnetic contributions in the analyzed small-angle scattering.The 2019 Coronavirus Disease (COVID-19) has become an unprecedented public crisis. We retrospectively investigated the clinical data of 197 COVID-19 patients and identified 88 patients as disease aggravation cases. Compared with patients without disease aggravation, the aggravation cases had more comorbidities, including hypertension (25.9%) and diabetes (20.8%), and presented with dyspnoea (23.4%), neutrophilia (31.5%), and lymphocytopenia (46.7%). These patients were more prone to develop organ damage in liver, kidney, and heart (P  less then  0.05). A multivariable regression analysis showed that advanced age, comorbidities, dyspnea, lymphopenia, and elevated levels of Fbg, CTnI, IL-6, and serum ferritin were significant predictors of disease aggravation. Further, we performed a Kaplan-Meier analysis to evaluate the prognosis of COVID-19 patients, which suggested that 64.9% of the patients had not experienced ICU transfers and survival from the hospital.Mutagenicity exerts adverse effects on humans. Conventional methods cannot simultaneously predict the toxicity of a large number of compounds. Most mutagenicity prediction models are based on a single experimental type and lack other experimental combination data as support, resulting in limited application scope and predictive ability. In this study, we partitioned data from GENE-TOX, CPDB, and Chemical Carcinogenesis Research Information System according to the weight-of-evidence method for modelling. In our data set, in vivo and in vitro experiments in groups as well as prokaryotic and eukaryotic cell experiments were included in accordance with the ICH guideline. We compared the two experimental combinations mentioned in the weight-of-evidence method and reintegrated the experimental data into three groups. Nine sub-models and three fusion models were established using random forest (RF), support vector machine (SVM), and back propagation (BP) neural network algorithms. When fusing base models under the same algorithm according to the ensemble rules, all models showed excellent predictive performance. The RF, SVM, and BP fusion models reached a prediction accuracy rate of 83.4%, 80.5%, 79.0% respectively. The area under the curve (AUC) reached 0.853, 0.897, 0.865 respectively. Therefore, the established fusion QSAR models can serve as an early warning system for mutagenicity of compounds.Mammalian cytosine DNA methylation (5mC) is associated with the integrity of the genome and the transcriptional status of nuclear DNA. Due to technical limitations, it has been less clear if mitochondrial DNA (mtDNA) is methylated and whether 5mC has a regulatory role in this context. [https://www.selleckchem.com/products/PHA-793887.html PHA-793887 cell line] Here, we used bisulfite-independent single-molecule sequencing of native human and mouse DNA to study mitochondrial 5mC across different biological conditions. We first validated the ability of long-read nanopore sequencing to detect 5mC in CpG (5mCpG) and non-CpG (5mCpH) context in nuclear DNA at expected genomic locations (i.e. promoters, gene bodies, enhancers, and cell type-specific transcription factor binding sites). Next, using high coverage nanopore sequencing we found low levels of mtDNA CpG and CpH methylation (with several exceptions) and little variation across biological processes differentiation, oxidative stress, and cancer. 5mCpG and 5mCpH were overall higher in tissues compared to cell lines, with small additional variation between cell lines of different origin.