Phytoplankton of the Curonian Lagoon as a New Interesting Source for Bioactive Natural Products. Special Impact on Cyanobacterial Metabolites

The bioprospecting of marine and brackish water systems has increased during the last decades. In this respect, microalgae, including cyanobacteria, and their metabolites are one of the most widely explored resources. Most of the bioactive compounds are isolated from ex situ cultures of microorganisms; however, analysis of field samples could also supply valuable information about the metabolic and biotechnological potential of microalgae communities. In this work, the activity of phytoplankton samples from the Curonian Lagoon was studied. The samples were active against antibiotic resistant clinical and environmental bacterial strains as well as against serine proteases and T47D human breast adenocarcinoma cells. No significant effect was found on Daphnia magna. In addition, using LC-MS/MS, we documented the diversity of metabolites present in field samples. A list of 117 detected cyanopeptides was presented. Cyanopeptolins constituted the largest class of cyanopeptides. As complex bloom samples were analyzed, no link between the observed activity and a specific sample component can be established. However, the results of the study showed a biotechnological potential of natural products from the Curonian Lagoon.

Structural Brain Alterations and Their Association with Cognitive Function and Symptoms in Attention-Deficit/Hyperactivity Disorder Families

Gray matter disruptions have been found consistently in Attention-deficit/Hyperactivity Disorder (ADHD). The organization of these alterations into brain structural networks remains largely unexplored. We investigated 508 participants (281 males) with ADHD (N = 210), their unaffected siblings (N = 108), individuals with subthreshold ADHD (N = 49), and unrelated healthy controls (N = 141) with an age range from 7 – 18 years old from 336 families in the Dutch NeuroIMAGE project. Source based morphometry was used to examine structural brain network alterations and their association with symptoms and cognitive performance. Two networks showed significant reductions in individuals with ADHD compared to unrelated healthy controls after False Discovery Rate correction. Component A, mainly located in bilateral Crus I, showed a case/control difference with sub-clinical cases being intermediate between cases and controls. The unaffected siblings were similar to controls. After correcting for IQ and medication status, component A showed a negative correlation with inattention symptoms across the entire sample. Component B included a maximum cluster in the bilateral insula, where unaffected siblings, similar to cases, showed significantly reduced loadings compared to controls; but no relationship with individual symptoms or cognitive measures was found for component B. This multivariate approach suggests that areas reflecting genetic liability within ADHD are partly separate from those areas modulating symptom severity.

Automated Pipeline for Purification, Biophysical and X-Ray Analysis of Biomacromolecular Solutions

Small angle X-ray scattering (SAXS), an increasingly popular method for structural analysis of biological macromolecules in solution, is often hampered by inherent sample polydispersity. We developed an all-in-one system combining in-line sample component separation with parallel biophysical and SAXS characterization of the separated components. The system coupled to an automated data analysis pipeline provides a novel tool to study difficult samples at the P12 synchrotron beamline (PETRA-3, EMBL/DESY, Hamburg).

Application of Locally Linear Embedding Based on Improved Distance in Neuron Classification

For locally linear embedding (LLE) algorithm of the shortcoming, an improved distance algorithm LLE is proposed, in locally linear embedding algorithm the distribution of sample component is different and the Euclidean distance can’t reflect sample distance actually. In the experiment, a sample of 231 neurons is obtained, and the morphological parameters of neurons are calculated firstly. Second, the improved locally linear embedding algorithm is used to reduce data dimensionality. Finally, support vector machine (SVM) algorithm is used to train and test samples. Experimental results show under certain conditions the classification of the method has good classification.

Input Data Influence on FEM Simulation of Steam Turbine Blades Materials Hot Forming

Computer simulation/optimization is widely applied to hot forming processes nowadays. A crucial point of any kind of computer simulation is the input data. There are implemented in all FEM codes some basic material database, but usually for limited materials and material states. As the input data decide about the output results quality, it is always necessary to pay attention, what are the simulation inputs. The best solution, but not always possible, is direct measurement of materials parameters for considered material and state. As this is in some cases not possible, materials data are searched in alternative ways. One possibility is survey of published data in literature. A reliability of published data is difficult to assess, as there are usually not available sufficient information about the material investigated in publications. Other possibility how to obtain material data nowadays is utilization of programs predicting material behavior on the basis of chemical composition. One of currently available software for material properties prediction is JMatPro. The program is able to calculate a broad range of properties and behavior with the use of established thermodynamics models on the basis of chemical composition and the initial state of the considered material state. There can be for example determined thermophysical and physical properties (from room temperature to the liquid state), time-temperature-transformation/ continuous-cooling transformation diagrams, stress/strain diagrams, proof and tensile stress, hardness, coarsening of γ and γ , and creep. The current paper is dealing with the simulation of hot forming of steam blade made of Ti-based alloy. As an input material data used for FEM simulation are conventionally measured data and data obtained from JMatPro. With the use of both material data sets, a sample component forming is simulated. The results obtained from both simulations are subsequently compared with the results obtained from physical forming of the sample component. Performance of both simulations is discussed here, taking into account results of physical forming results.

Contextual control of conditional discrimination of the own behavior in pigeons

An experiment in which a pigeon was trained in contextual discrimination of its own behavior was carried out. When the experimental chamber was illuminated with a constant light, the pigeon had to peck on a red (or green) key in the sample component after having been pecking to the left (or to the right). When the chamber was illuminated with an intermittent light, the reinforced sample-comparison sequences were the opposite. The subject learned the task in about 40 sessions and maintained high correct response ratios even though the reinforcement probability decreased from 1 to 0.2 after each correct trial. The results are discussed in terms of the kind of discriminative rule and the kind of hierarchic structure involved in the task.

A Simple Directly Combined Gas Chromatographic-Infrared Spectrometric System for Identification of Low Molecular Weight Hydrocarbons

A simple directly combined gas chromatographic-infrared spectrometric system suitable for the identification of low molecular weight hydrocarbon-type compounds is reported. It incorporates a 30-m × 0.5-mm i.d. SCOT Silicone DC-550 column and a micro light pipe gas cell (volume 0.6 ml) fitted on a kinematic mounting into the sample compartment of a conventional ir spectrophotometer. Sensitivity is enhanced by a gas chromatographic fraction concentrator, a 10-cm × 1.0-mm i.d. 10% Silicone SE-30/Chromport A (80 to 100 mesh) column, situated upstream of the gas cell. The performance of the system is demonstrated for synthetic mixtures of C6 — C10 paraffinic, olefinic, and aromatic types of hydrocarbons. Infrared spectra can be taken at 5- to 6-min intervals at levels of 14 to 19 µg per sample component. This system has potential for application in the field of trace analysis, e.g., air pollution.