Computational methods for exploring the dynamics of cancer : the potential of state variables for description of complex biological systems

Observing dynamic patterns in silico and comparing them to experimental data in vitro or in vivo could help us identify and quantify dynamic processes. Since modellers are faced with a high degree of complexity of biological systems, appropriate concepts of system descriptions are needed. The use of state variables is expected to make models applicable to a wider range of the dynamics of biological systems. This is demonstrated by the Multi-Hit-Repair (MHR-)model which is based on a transient dose equivalent. The model calculates the survival of cells irradiated by ionizing radiation and it describes correctly a large variety of radio-biological observations. In addition, the MHR-model is bridging the gap between processes at the molecular or cellular level and tissue dynamics

Seasonality of microbial genetic functions in the Arctic Ocean revealed by autonomous sampling

The functional diversity of microbes along the seasonal extremes in the Arctic Ocean including the Polar Night are virtually unknown. Here, using PacBio long-read metagenomes derived from automated samplers over an annual cycle, we elucidate functional microbial seasonality in the Fram Strait in the context of a high-resolution amplicon time-series. In the ice-free West Spitsbergen Current, the transition from the phototrophy-dominated spring and summer ecosystem states to the dark winter was evident in bacterial genomes. Proteorhodopsin- and DMSP-utilizing genes peaked in late summer, marking a transition phase. Winter mixing of the water column covaried with microbial taxa encoding ammonia- and urea-metabolizing genes, with probable implications for nitrogen recycling and the following phytoplankton bloom. In the ice-covered East Greenland Current, functional diversity varied with the extent of ice cover and polar water masses. During intermittent low-ice conditions in winter, the metagenomic repertoire resembled that during summer, indicating rapidly (i.e. within weeks) shifting ecosystem states with ice cover. Overall, we provide a baseline to understand ecological and biogeochemical processes in a region severely affected by climate change, with implications for the present and future Arctic Ocean

Direct Observation of Strong Anomalous Hall Effect and Proximity-induced Ferromagnetic State in SrIrO₃

The 5d iridium-based transition metal oxides have gained broad interest because of their strong spin-orbit coupling which favors new or exotic quantum electronic states. On the other hand, they rarely exhibit more mainstream orders like ferromagnetism due to generally weak electron-electron correlation strength. Here, we show a proximity-induced ferromagnetic (FM) state with TC ≈ 100 K and strong magnetocrystalline anisotropy in a SrIrO3 (SIO) heterostructure via interfacial charge transfer by using a ferromagnetic insulator in contact with SIO. Electrical transport allows to selectively probe the FM state of the SIO layer and the direct observation of a strong, intrinsic and positive anomalous Hall effect (AHE). For T ≤ 20 K, the AHE displays unusually large coercive and saturation field, a fingerprint of a strong pseudospin-lattice coupling. A Hall angle, σxyAHE/σxx, larger by an order of magnitude than in typical 3d metals and a FM net moment of about 0.1 μB/Ir, is reported. This emphasizes how efficiently the nontrivial topological band properties of SIO can be manipulated by structural modifications and the exchange interaction with 3d TMOs

Graphical representation of ribosomal RNA probe accessibility data using ARB software package

BACKGROUND: Taxon specific hybridization probes in combination with a variety of commonly used hybridization formats nowadays are standard tools in microbial identification. A frequently applied technology, fluorescence in situ hybridization (FISH), besides single cell identification, allows the localization and functional studies of the microbial community composition. Careful in silico design and evaluation of potential oligonucleotide probe targets is therefore crucial for performing successful hybridization experiments. RESULTS: The PROBE Design tools of the ARB software package take into consideration several criteria such as number, position and quality of diagnostic sequence differences while designing oligonucleotide probes. Additionally, new visualization tools were developed to enable the user to easily examine further sequence associated criteria such as higher order structure, conservation, G+C content, transition-transversion profiles and in situ target accessibility patterns. The different types of sequence associated information (SAI) can be visualized by user defined background colors within the ARB primary and secondary structure editors as well as in the PROBE Match tool. CONCLUSION: Using this tool, in silico probe design and evaluation can be performed with respect to in situ probe accessibility data. The evaluation of proposed probe targets with respect to higher-order rRNA structure is of importance for successful design and performance of in situ hybridization experiments. The entire ARB software package along with the probe accessibility data is available from the ARB home page

Preservice teachers' online self-regulated learning: does digital readiness matter?

(1) Background: Teaching in today’s schools asks teachers to foster self-regulated learning and digital competences in children and young people. In order to do so, teachers first need to acquire and use these competences themselves. (2) Methods: Based on a mixed-methods approach, the study investigates self-regulated learning in online courses of N = 129 preservice teachers at a German university. (3) Results and conclusions: Perceiving their digital readiness as generally high, preservice teachers appear to not overly self-regulate their learning in the online environment. Finally, preservice teachers’ digital readiness was related only weakly to their online self-regulated learning. A discussion is offered which shows teacher education as a broader phenomenon and implies the need for professional development for teacher educators. Additionally, it is argued to link research on self-regulated learning more closely to research on online learning environments in teacher education

In situ cell division and mortality rates of SAR11, SAR86, Bacteroidetes, and Aurantivirga during phytoplankton blooms reveal differences in population controls

Net growth of microbial populations, i.e., changes in abundances over time, can be studied using 16S rRNA fluorescence in situ hybridization (FISH). However, this approach does not differentiate between mortality and cell division rates. We used FISH-based image cytometry in combination with dilution culture experiments to study net growth, cell division, and mortality rates of four bacterial taxa over two distinct phytoplankton blooms: the oligotrophs SAR11 and SAR86, the copiotrophic phylum Bacteroidetes, and its genus Aurantivirga. Cell volumes, ribosome content, and frequency of dividing cells (FDC) co-varied over time. Among the three, FDC was the most suitable predictor to calculate the cell division rates for the selected taxa. The FDC-derived cell division rates for SAR86 of up to 0.8 d-1 and Aurantivirga of up to 1.9 d-1 differed, as expected for oligotrophs and copiotrophs. Surprisingly, SAR11 also reached high cell division rates of up to 1.9 d-1, even before the onset of phytoplankton blooms. For all four taxonomic groups, the abundance-derived net growth (-0.6 to 0.5 d-1) was about an order of magnitude lower than the cell division rates. Consequently, mortality rates were comparably high to cell division rates, indicating that about 90% of bacterial production is recycled without apparent time lag within one day. Our study shows that determining taxon-specific cell division rates complements omics-based tools and provides unprecedented clues on individual bacterial growth strategies including bottom-up and top-down controls

Smart antimicrobial efficacy employing pH-sensitive ZnO-doped diamond-like carbon coatings

One of the main challenges in endoprosthesis surgeries are implant-associated infections and aseptic-loosenings, caused by wear debris. To combat these problems, the requirements to surfaces of endoprostheses are wear-resistance, low cytotoxicity and antimicrobial efficacy. We here present antimicrobial coatings with a smart, adaptive release of metal ions in case of infection, based on ZnO-nanoparticles embedded in diamond-like carbon (DLC). The Zn2+ ion release of these coatings in aqueous environments reacts and adapts smartly on inflammations accompanied by acidosis. Moreover, we show that this increased ion release comes along with an increased toxicity to fibroblastic cells (L929) and bacteria (Staphylococcus aureus subsp. aureus, resistant to methicillin and oxacillin. (ATCC 43300, MRSA) and Staphylococcus epidermidis (ATCC 35984, S. epidermidis). Interestingly, the antimicrobial effect and the cytotoxicity of the coatings increase with a reduction of the pH value from 7.4 to 6.4, but not further to pH 5.4