570 Biowissenschaften; Biologie
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- Gelatine (2)
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A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
Quantifying uncertainty, variability and likelihood for ordinary differential equation models
(2010)
Background
In many applications, ordinary differential equation (ODE) models are subject to uncertainty or variability in initial conditions and parameters. Both, uncertainty and variability can be quantified in terms of a probability density function on the state and parameter space.
Results
The partial differential equation that describes the evolution of this probability density function has a form that is particularly amenable to application of the well-known method of characteristics. The value of the density at some point in time is directly accessible by the solution of the original ODE extended by a single extra dimension (for the value of the density). This leads to simple methods for studying uncertainty, variability and likelihood, with significant advantages over more traditional Monte Carlo and related approaches especially when studying regions with low probability.
Conclusions
While such approaches based on the method of characteristics are common practice in other disciplines, their advantages for the study of biological systems have so far remained unrecognized. Several examples illustrate performance and accuracy of the approach and its limitations.
Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues.
Results: Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach. Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available.
Conclusions: The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in realistically noisy conditions and with moderate sample sizes.
Live cell flattening
(2010)
Eukaryotic cell flattening is valuable for improving microscopic observations, ranging from bright field (BF) to total internal reflection fluorescence (TIRF) microscopy. Fundamental processes, such as mitosis and in vivo actin polymerization, have been investigated using these techniques. Here, we review the well known agar overlayer protocol and the oil overlay method. In addition, we present more elaborate microfluidics-based techniques that provide us with a greater level of control. We demonstrate these techniques on the social amoebae Dictyostelium discoideum, comparing the advantages and disadvantages of each method.
Multi-color fluorescence imaging experiments of wave forming Dictyostelium cells have revealed that actin waves separate two domains of the cell cortex that differ in their actin structure and phosphoinositide composition. We propose a bistable model of actin dynamics to account for these experimental observation. The model is based on the simplifying assumption that the actin cytoskeleton is composed of two distinct network types, a dendritic and a bundled network. The two structurally different states that were observed in experiments correspond to the stable fixed points in the bistable regime of this model. Each fixed point is dominated by one of the two network types. The experimentally observed actin waves can be considered as trigger waves that propagate transitions between the two stable fixed points.
How much is too much?
(2010)
Although dietary nutrient intake is often adequate, nutritional supplement use is common among elite athletes. However, high-dose supplements or the use of multiple supplements may exceed the recommended daily allowance (RDA) of particular nutrients or even result in a daily intake above tolerable upper limits (UL). The present case report presents nutritional intake data and supplement use of a highly trained male swimmer competing at international level. Habitual energy and micronutrient intake were analysed by 3 d dietary reports. Supplement use and dosage were assessed, and total amount of nutrient supply was calculated. Micronutrient intake was evaluated based on RDA and UL as presented by the European Scientific Committee on Food, and maximum permitted levels in supplements (MPL) are given. The athlete’s diet provided adequate micronutrient content well above RDA except for vitamin D. Simultaneous use of ten different supplements was reported, resulting in excess intake above tolerable UL for folate, vitamin E and Zn. Additionally, daily supplement dosage was considerably above MPL for nine micronutrients consumed as artificial products. Risks and possible side effects of exceeding UL by the athlete are discussed. Athletes with high energy intake may be at risk of exceeding UL of particular nutrients if multiple supplements are added. Therefore, dietary counselling of athletes should include assessment of habitual diet and nutritional supplement intake. Educating athletes to balance their diets instead of taking supplements might be prudent to prevent health risks
that may occur with long-term excess nutrient intake.
This work describes the realization of physically crosslinked networks based on gelatin by the introduction of functional groups enabling specific supramolecular interactions. Molecular models were developed in order to predict the material properties and permit to establish a knowledge-based approach to material design. The effect of additional supramolecular interactions with hydroxyapaptite was then studied in composite materials. The calculated properties are compared to experimental results to validate the models. The models are then further used for the study of physically crosslinked networks. Gelatin was functionalized with desaminotyrosine (DAT) and desaminotyrosyl-tyrosine (DATT) side groups, derived from the natural amino acid tyrosine. These group can potentially undergo to π-π and hydrogen bonding interactions also under physiological conditions. Molecular dynamics (MD) simulations were performed on models with 0.8 wt.-% or 25 wt.-% water content, using the second generation forcefield CFF91. The validation of the models was obtained by the comparison with specific experimental data such as, density, peptide conformational angles and X-ray scattering spectra. The models were then used to predict the supramolecular organization of the polymer chain, analyze the formation of physical netpoints and calculate the mechanical properties. An important finding of simulation was that with the increase of aromatic groups also the number of observed physical netpoints increased. The number of relatively stable physical netpoints, on average zero 0 for natural gelatin, increased to 1 and 6 for DAT and DATT functionalized gelatins respectively. A comparison with the Flory-Rehner model suggested reduced equilibrium swelling by factor 6 of the DATT-functionalized materials in water. The functionalized gelatins could be synthesized by chemoselective coupling of the free carboxylic acid groups of DAT and DATT to the free amino groups of gelatin. At 25 wt.-% water content, the simulated and experimentally determined elastic mechanical properties (e.g. Young Modulus) were both in the order of GPa and were not influenced by the degree of aromatic modification. The experimental equilibrium degree of swelling in water decreased with increasing the number of inserted aromatic functions (from 2800 vol.-% for pure gelatin to 300 vol.-% for the DATT modified gelatin), at the same time, Young’s modulus, elongation at break, and maximum tensile strength increased. It could be show that the functionalization with DAT and DATT influences the chain organization of gelatin based materials together with a controlled drying condition. Functionalization with DAT and DATT lead to a drastic reduction of helical renaturation, that could be more finely controlled by the applied drying conditions. The properties of the materials could then be influenced by application of two independent methods. Composite materials of DAT and DATT functionalized gelatins with hydroxyapatite (HAp) show a drastic reduction of swelling degree. In tensile tests and rheological measurements, the composites equilibrated in water had increased Young’s moduli (from 200 kPa up to 2 MPa) and tensile strength (from 57 kPa up to 1.1 MPa) compared to the natural polymer matrix without affecting the elongation at break. Furthermore, an increased thermal stability from 40 °C to 85 °C of the networks could be demonstrated. The differences of the behaviour of the functionalized gelatins to pure gelatin as matrix suggested an additional stabilizing bond between the incorporated aromatic groups to the hydroxyapatite.
Ghrelin is a unique hunger-inducing stomach-borne hormone. It activates orexigenic circuits in the central nervous system (CNS) when acylated with a fatty acid residue by the Ghrelin O-acyltransferase (GOAT). Soon after the discovery of ghrelin a theoretical model emerged which suggests that the gastric peptide ghrelin is the first “meal initiation molecule
In a very simplified view, the plant leaf growth can be reduced to two processes, cell division and cell expansion, accompanied by expansion of their surrounding cell walls. The vacuole, as being the largest compartment of the plant cell, plays a major role in controlling the water balance of the plant. This is achieved by regulating the osmotic pressure, through import and export of solutes over the vacuolar membrane (the tonoplast) and by controlling the water channels, the aquaporins. Together with the control of cell wall relaxation, vacuolar osmotic pressure regulation is thought to play an important role in cell expansion, directly by providing cell volume and indirectly by providing ion and pH homestasis for the cytosoplasm. In this thesis the role of tonoplast protein coding genes in cell expansion in the model plant Arabidopsis thaliana is studied and genes which play a putative role in growth are identified. Since there is, to date, no clearly identified protein localization signal for the tonoplast, there is no possibility to perform genome-wide prediction of proteins localized to this compartment. Thus, a series of recent proteomic studies of the tonoplast were used to compile a list of cross-membrane tonoplast protein coding genes (117 genes), and other growth-related genes from notably the growth regulating factor (GRF) and expansin families were included (26 genes). For these genes a platform for high-throughput reverse transcription quantitative real time polymerase chain reaction (RT-qPCR) was developed by selecting specific primer pairs. To this end, a software tool (called QuantPrime, see http://www.quantprime.de) was developed that automatically designs such primers and tests their specificity in silico against whole transcriptomes and genomes, to avoid cross-hybridizations causing unspecific amplification. The RT-qPCR platform was used in an expression study in order to identify candidate growth related genes. Here, a growth-associative spatio-temporal leaf sampling strategy was used, targeting growing regions at high expansion developmental stages and comparing them to samples taken from non-expanding regions or stages of low expansion. Candidate growth related genes were identified after applying a template-based scoring analysis on the expression data, ranking the genes according to their association with leaf expansion. To analyze the functional involvement of these genes in leaf growth on a macroscopic scale, knockout mutants of the candidate growth related genes were screened for growth phenotypes. To this end, a system for non-invasive automated leaf growth phenotyping was established, based on a commercially available image capture and analysis system. A software package was developed for detailed developmental stage annotation of the images captured with the system, and an analysis pipeline was constructed for automated data pre-processing and statistical testing, including modeling and graph generation, for various growth-related phenotypes. Using this system, 24 knockout mutant lines were analyzed, and significant growth phenotypes were found for five different genes.
Das ITC SFN und der Mikronährstoff Se sind bekannt als chemopräventive Inhaltsstoffe von Gemüse der Brassica-Familie, welcher auch Brokkoli angehört. Die Wirkungen von sowohl SFN als auch Se beruhen auf zahlreichen verschiedenen Mechanismen. Es existieren jedoch Schnittstellen, an welchen Interaktionen beider Substanzen möglich sind. Basierend auf diesem Wissen wurden in dieser Arbeit Wechselwirkungen zwischen SFN und Se auf die Aktivität sowie Expression von Phase II Enzymen und Selenoproteinen untersucht. Der Einfluss der Kombination von SFN und Se auf die unter physiologischen Bedingungen stattfindende Proliferation und Apoptose war ebenso Gegenstand der Arbeit wie die Modulation von Entzündungsprozessen sowie der Tumorentstehung während der entzündungsverstärkten Colonkanzerogenese im Mausmodell. Das hinsichtlich seiner Wirksamkeit mit aus GRA hydrolysiertem SFN zunächst als vergleichbar befundene synthetische SFN wurde für die Untersuchung im AOM/DSS-induzierten Colontumormodell gewählt und in Kombination mit 3 verschiedenen Selendiäten verabreicht. Der Einfluss von SFN und Se auf Phase II Enzyme und Selenoproteine entlang des GIT war organabhängig und nach 4 Wochen geringer als nach 7 Tagen. Die schwächere Induktion deutet auf eine Anpassung des Organismus hin. Ein SFN-vermittelter Effekt auf NQO1 war im Selenmangel am deutlichsten. Die Aktivität des Selenoproteins TrxR wurde hingegen erst bei ausreichender Selenversorgung durch SFN beeinflusst. Die als Nrf2-Zielgen bekannte und in der Hierarchie der Selenoproteine einen hohen Rang einnehmende GPx2 konnte in bestimmten Organen bereits unter selenarmen Bedingungen durch SFN induziert werden. Eine Überexpression des Enzyms war jedoch nicht möglich. SFN steigerte, unabhängig vom Selenstatus, im oberen Abschnitt des GIT und im Colon die Aktivität der GST. Eine Induktion des eigenen Metabolismus wäre somit denkbar. Im Falle eines Mangels an GPx2 wurde GPx1 bei hinreichender Selenversorgung stärker exprimiert, allerdings konnte sie die Funktion von GPx2 nicht völlig erset-zen. Im Selenmangel kann die Aktivitätssteigerung der TrxR im Dünndarm, dem Ab-schnitt der Selenabsorption, als ein Versuch der GPx2-Kompensation angesehen werden. SFN war nicht in der Lage, über eine Aktivierung des Nrf2/ARE-Signalweges kompensatorische Effekte zu induzieren. Apoptotische Prozesse wurden unter physiologischen Bedingungen nur marginal durch SFN und Se moduliert. Das elektrophile ITC konnte lediglich im Selenmangel Apoptose im luminalen Bereich der Colonkrypten induzieren. Die durch supranutritive Selenkonzentration induzierte Apoptose im Kryptengrund wurde nicht durch SFN beeinflusst. Einer bei Abwesenheit der GPx2 erhöhten Apoptoserate im Kryptengrund wirkte SFN bei adäquater Selenversorgung entgegen, war indessen proapoptotisch unter selendefizienten Konditionen. Der Einfluss von SFN auf die Entzündung war deutlich abhängig vom Selenstatus. Während SFN im Selenmangel anscheinend prooxidative Prozesse induzierte und die Entzündungssymptome verschlimmerte, wirkte es unter adäquatem Selenstatus an-tiinflammatorisch. Den vergleichsweise milden Grad der Entzündung im selensupplementierten Status konnte SFN nicht zusätzlich beeinflussen. SFN veränderte die Inzi-denz colorektaler Tumore nicht. Ein, die Tumorinitiation blockierender SFN-Effekt durch direkte Hemmung der metabolischen Aktivierung des Prokanzerogens im selenadäquaten Zustand scheint offensichtlich. Eine Überversorgung mit Se kann protektiv im Hinblick auf Entzündung oder Colonkanzerogenese sein, jedoch bewirkt SFN keinen zusätzlichen Schutz. Kombinationseffekte von SFN und Se in Bezug auf Phase II Enzyme, Selenoproteine und Apoptose sowie die entzündungsverstärkte Colonkanzerogenese sind nicht eindeutiger Natur und können, abhängig vom Endpunkt, synergistische oder antagonistische Züge aufweisen. Eine bei Selendefizienz deutlichere Wirkung von SFN kann mit Hilfe der gesteigerten Aktivierung von Nrf2 erklärt werden, dies muss jedoch nicht von Vorteil sein. Bei adäquater Selenversorgung kann SFN kurzfristig antiinflammatorische und antikanzerogene Prozesse induzieren. Von einer längerfristigen ständigen SFN-Aufnahme in Form von GRA-reichen Brassicacea ist jedoch abzuraten, da von einer Adaptation auszugehen ist. Die Wirkung von SFN innerhalb der komplexen Pflanzenmatrix bleibt Gegenstand zukünftiger Untersuchungen.