Some comments on interpretations of Viking biological experiments

Data from Viking experiments are analyzed from a biological viewpoint. The lack of organic matter in Martian soil could be due to the specificity of regions with optimal landing conditions. All data of labeled release experiments may be explained by assuming the existence of psychrophilic organisms, cultivated at temperatures above optimal ones, and other factors of a biological orgin. The biological interpretation does not contradict the results of other life search experiments.     

Assessment method for a power analysis to identify differentially expressed pathways

Gene expression data can provide a very rich source of information for elucidating the biological function on the pathway level if the experimental design considers the needs of the statistical analysis methods. The purpose of this paper is to provide a comparative analysis of statistical methods for detecting the differentially expression of pathways (DEP). In contrast to many other studies conducted so far, we use three novel simulation types, producing a more realistic correlation structure than previous simulation methods. This includes also the generation of surrogate data from two large-scale microarray experiments from prostate cancer and ALL. As a result from our comprehensive analysis of 41,004 parameter configurations, we find that each method should only be applied if certain conditions of the data from a pathway are met. Further, we provide method-specific estimates for the optimal sample size for microarray experiments aiming to identify DEP in order to avoid an underpowered design. Our study highlights the sensitivity of the studied methods on the parameters of the system.     

Methoden zum Vergleich des Leistungsvermögens biologischer und technischer Systeme

Summary In this work the methods of the communication theory for binary detection, multiple detection and extraction are applied to biological systems. It is the objective of this investigation to compare the performance of optimal and biological systems in receiving signals superimposed by noise. The required mathematical relations and methods of measurements are derived.In the second part of this work pattern recognition experiments (multiple detection) at the human visual system with stationary and time variant patterns are described. The comparison of the performance between optimal and biological system shows that the human visual system acts in a suboptimal way. From some other detection experiments it can be concluded that the recognition process is describable by spatial cross-correlation.

---

---

Herr Dr. von Seelen ist seit dem 1. Januar 1971 Mitarbeiter des Battelle-Instituts, Frankfurt.

---

Von Herrn Dr. Reinig wurden die optischen Versuche zum großen Teil aufgebaut und durchgeführt.

---

Die Verfasser danken dem Bundesministerium für Bildung und Wissenschaft für die Förderung dieser Arbeit im Rahmen des Technologieprogrammes sowie Herrn Dr. H. Niemann und Herrn Dr. P. Barlai für ihre Unterstützung bei Rechnerbzw. Holographieproblemen.     

Two in one: cryptic species discovered in biological control agent populations using molecular data and crossbreeding experiments

There are many examples of cryptic species that have been identified through DNA‐barcoding or other genetic techniques. There are, however, very few confirmations of cryptic species being reproductively isolated. This study presents one of the few cases of cryptic species that has been confirmed to be reproductively isolated and therefore true species according to the biological species concept. The cryptic species are of special interest because they were discovered within biological control agent populations. Two geographically isolated populations of Eccritotarsus catarinensis (Carvalho) [Hemiptera: Miridae], a biological control agent for the invasive aquatic macrophyte, water hyacinth, Eichhornia crassipes (Mart.) Solms [Pontederiaceae], in South Africa, were sampled from the native range of the species in South America. Morphological characteristics indicated that both populations were the same species according to the current taxonomy, but subsequent DNA analysis and breeding experiments revealed that the two populations are reproductively isolated. Crossbreeding experiments resulted in very few hybrid offspring when individuals were forced to interbreed with individuals of the other population, and no hybrid offspring were recorded when a choice of mate from either population was offered. The data indicate that the two populations are cryptic species that are reproductively incompatible. Subtle but reliable diagnostic characteristics were then identified to distinguish between the two species which would have been considered intraspecific variation without the data from the genetics and interbreeding experiments. These findings suggest that all consignments of biological control agents from allopatric populations should be screened for cryptic species using genetic techniques and that the importation of multiple consignments of the same species for biological control should be conducted with caution.     

Optimal Experimental Design for Parameter Estimation of a Cell Signaling Model

Differential equation models that describe the dynamic changes of biochemical signaling states are important tools to understand cellular behavior. An essential task in building such representations is to infer the affinities, rate constants, and other parameters of a model from actual measurement data. However, intuitive measurement protocols often fail to generate data that restrict the range of possible parameter values. Here we utilized a numerical method to iteratively design optimal live-cell fluorescence microscopy experiments in order to reveal pharmacological and kinetic parameters of a phosphatidylinositol 3,4,5-trisphosphate (PIP₃) second messenger signaling process that is deregulated in many tumors. The experimental approach included the activation of endogenous phosphoinositide 3-kinase (PI3K) by chemically induced recruitment of a regulatory peptide, reversible inhibition of PI3K using a kinase inhibitor, and monitoring of the PI3K-mediated production of PIP₃ lipids using the pleckstrin homology (PH) domain of Akt. We found that an intuitively planned and established experimental protocol did not yield data from which relevant parameters could be inferred. Starting from a set of poorly defined model parameters derived from the intuitively planned experiment, we calculated concentration-time profiles for both the inducing and the inhibitory compound that would minimize the predicted uncertainty of parameter estimates. Two cycles of optimization and experimentation were sufficient to narrowly confine the model parameters, with the mean variance of estimates dropping more than sixty-fold. Thus, optimal experimental design proved to be a powerful strategy to minimize the number of experiments needed to infer biological parameters from a cell signaling assay.     

A review of the integration of classical biological control with other techniques to manage invasive weeds in natural areas and rangelands

Integrating classical biological control with other management techniques such as herbicide, fire, mechanical control, grazing, or plant competition, can be the most effective way to manage invasive weeds in natural areas and rangelands. Biological control agents can be protected from potential negative impacts of these weed control methods through untreated refugia or by applying the treatment at a time when the agent is not vulnerable. A literature review of experiments that integrated biological control with other management strategies from 1987 to 2017 yielded 39 terrestrial and 16 aquatic studies. The tactics most frequently integrated with biological control were herbicide applications and plant competition. Despite numerous examples of successful programs and calls for more widespread integration of biological control with other weed management strategies, there was no increase in the number of studies reported annually over time. Additional studies investigating the ecological and economic benefits of integrated weed management are needed.     

Using parthenogenesis‐inducing Wolbachia for the selection of optimal lines of the egg parasitoid Trichogramma pretiosum for use in biocontrol

Trichogramma wasps (Hymenoptera: Trichogrammatidae) are egg parasitoids commonly employed in augmentative biological control releases against a variety of mainly lepidopteran pests. By exploiting the mechanism by which the endosymbiotic bacterium Wolbachia induces parthenogenesis in this genus, we created a set of completely homozygous Wolbachia‐infected recombinant isofemale lines (RILs), each consisting of a different combination of the genome of two well‐characterized lines of Trichogramma pretiosum Riley. We subsequently use 16 of these RILs to investigate the effect of genetic variation on various measures associated with offspring production under laboratory conditions. Unsurprisingly, substantial differences were found between the RILs in their propensity to parasitize hosts, the number of hosts they parasitize, and the levels of mortality in their offspring. Such measures can be used to choose an optimal line for biological control purposes. A method was also developed to characterize the 16 RILs using their allelic state at five loci. Essentially, this binary system uses high‐resolution melt analysis to resolve identity at each locus, with alleles originating from either the grandmaternal or grandpaternal line, and is such that each RIL can be distinguished from each other RIL by their allelic state at one or more loci. The method facilitates the easy diagnosis of line origin when two or more lines are competing with each other in competition assays, allowing for the design of more complicated tests of parasitoid quality. Future field experiments will determine which genetic line performs best under more realistic biological control conditions. The fact that these lines are infected with parthenogenesis‐inducing Wolbachia will allow for prolonged rearing without appreciable change in their genetic makeup, which should lead to a predictable biological control performance.     

A four coil exposure system (tetracoil) producing a highly uniform magnetic field

We propose a magnetic field exposure system (tetracoil) for in vitro and in vivo experiments, composed of two couples of circular coils satisfying a spherical constraint, whose characteristics are chosen in order to maximize the uniformity region of the magnetic field. Analytical calculations and computer simulations show that our system, as compared to the other most largely used magnetic field exposure systems, represents an optimal compromise in terms of field uniformity, accessibility for biological experiments, and ratio between overall dimension and uniformity region.     

A novel moderately halophilic bacterium for decolorizing azo dye under high salt condition

Halomonas sp strain GTW was newly isolated from coastal sediments contaminated by chemical wastewater and was identified to be a member of the genus Halomonas by 16S rDNA sequence analysis and physical and biochemical tests. The optimal decolorization conditions were as follows: temperature 30°C, pH 6.5.0–8.5, NaCl 10–20% (w/v) and the optimal carbon source was yeast exact. The results of experiments demonstrated that the bacteria could decolorize different azo dyes under high salt concentration conditions, and the decolorization rate of five tested azo dyes could be above 90% in 24 h. The exploitation of the salt-tolerant bacteria in the bio-treatment system would be a great improvement of conventional biological treatment systems and the bio-treatment concept.     

High‐throughput screening of optimal solution conditions for structural biological studies by fluorescence correlation spectroscopy

Protein aggregation is an essential molecular event in a wide variety of biological situations, and is a causal factor in several degenerative diseases. The aggregation of proteins also frequently hampers structural biological analyses, such as solution NMR studies. Therefore, precise detection and characterization of protein aggregation are of crucial importance for various research fields. In this study, we demonstrate that fluorescence correlation spectroscopy (FCS) using a single‐molecule fluorescence detection system enables the detection of otherwise invisible aggregation of proteins at higher protein concentrations, which are suitable for structural biological experiments, and consumes relatively small amounts of protein over a short measurement time. Furthermore, utilizing FCS, we established a method for high‐throughput screening of protein aggregation and optimal solution conditions for structural biological experiments.     

A stochastic model for simulation of interactions between phytophagous spider mites and their phytoseiid predators

A stochastic predator/prey model describing the interaction betweenTetranychus urticae andPhytoseiulus persimilis in investigated via computer simulations and pilot experiments on Lima beans in a greenhouse. Most demographic events, including predation, death due to unknown causes, dispersal, and oviposition, are modelled as stochastic processes. Transitions from eggs to nymphs and from nymphs to adults are deterministic, as are management decisions (release of predators and application of miticide). Computer simulations provide adequate and realistic representations of biological processes, and the model shows stability over a range of inputs. Experimental validation of the model continues. Predictions of the model for optimal predator release or optimal timing of acaricide application have yet to be tested experimentally.     

Optimal allocation of replicates for measurement evaluation studies

Optimal experimental design is important for the efficient use of modern highthroughput technologies such as microarrays and proteomics. Multiple factors including the reliability of measurement system, which itself must be estimated from prior experimental work, could influence design decisions. In this study, we describe how the optimal number of replicate measures （technical replicates） for each biological sample （biological replicate） can be determined. Different allocations of biological and technical replicates were evaluated by minimizing the variance of the ratio of technical variance （measurement error） to the total variance （sum of sampling error and measurement error）. We demonstrate that if the number of biological replicates and the number of technical replicates per biological sample are variable, while the total number of available measures is fixed, then the optimal allocation of replicates for measurement evaluation experiments requires two technical replicates for each biological replicate. Therefore, it is recommended to use two technical replicates for each biological replicate if the goal is to evaluate the reproducibility of measurements.     

A metabolome pipeline: from concept to data to knowledge

Metabolomics, like other omics methods, produces huge datasets of biological variables, often accompanied by the necessary metadata. However, regardless of the form in which these are produced they are merely the ground substance for assisting us in answering biological questions. In this short tutorial review and position paper we seek to set out some of the elements of “best practice” in the optimal acquisition of such data, and in the means by which they may be turned into reliable knowledge. Many of these steps involve the solution of what amount to combinatorial optimization problems, and methods developed for these, especially those based on evolutionary computing, are proving valuable. This is done in terms of a “pipeline” that goes from the design of good experiments, through instrumental optimization, data storage and manipulation, the chemometric data processing methods in common use, and the necessary means of validation and cross-validation for giving conclusions that are credible and likely to be robust when applied in comparable circumstances to samples not used in their generation.This revised version was published online in June 2005. The previous version did not contain colour images.     

Computational analysis of microarray data

Microarray experiments are providing unprecedented quantities of genome-wide data on gene-expression patterns. Although this technique has been enthusiastically developed and applied in many biological contexts, the management and analysis of the millions of data points that result from these experiments has received less attention. Sophisticated computational tools are available, but the methods that are used to analyse the data can have a profound influence on the interpretation of the results. A basic understanding of these computational tools is therefore required for optimal experimental design and meaningful data analysis.     

Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty

This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm’s scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements.     

Circular permutation within the coenzyme binding domain of the tetrameric glyceraldehyde-3-phosphate dehydrogenase from Bacillus stearothermophilus.

A circularly permuted (cp) variant of the phosphorylating NAD-dependent glyceraldehyde-3-phosphate dehydrogenase (GAPDH) from Bacillus stearothermophilus has been constructed with N- and C-termini created within the coenzyme binding domain. The cp variant has a kcat value equal to 40% of the wild-type value, whereas Km and KD values for NAD show a threefold decrease compared to wild type. These results indicate that the folding process and the conformational changes that accompany NAD binding during the catalytic event occur efficiently in the permuted variant and that NAD binding is tighter. Reversible denaturation experiments show that the stability of the variant is only reduced by 0.7 kcal/mol compared to the wild-type enzyme. These experiments confirm and extend results obtained recently on other permuted proteins. For multimeric proteins, such as GAPDH, which harbor subunits with two structural domains, the natural location of the N- and C-termini is not a prerequisite for optimal folding and biological activity.     

Hypothesis testing in high-throughput screening for drug discovery

Following the success of small-molecule high-throughput screening (HTS) in drug discovery, other large-scale screening techniques are currently revolutionizing the biological sciences. Powerful new statistical tools have been developed to analyze the vast amounts of data in DNA chip studies, but have not yet found their way into compound screening. In HTS, characterization of single-point hit lists is often done only in retrospect after the results of confirmation experiments are available. However, for prioritization, for optimal use of resources, for quality control, and for comparison of screens it would be extremely valuable to predict the rates of false positives and false negatives directly from the primary screening results. Making full use of the available information about compounds and controls contained in HTS results and replicated pilot runs, the Z score and from it the p value can be estimated for each measurement. Based on this consideration, we have applied the concept of p-value distribution analysis (PVDA), which was originally developed for gene expression studies, to HTS data. PVDA allowed prediction of all relevant error rates as well as the rate of true inactives, and excellent agreement with confirmation experiments was found.     

Quantum information teleportation through biological wires,gravitational micro-bio-holes and holographic micro-bio-systems: A hypothesis

Biological systems like cells, bacteria, chloroplasts and other micro-organisms could exchange quantum particles like electrons, photons and gravitational waves and have large distant information teleportation. This is because that their DNAs and membranes are formed from quantum particles like electrons and protons and by their motions, some currents and waves are emerged. These waves have the main role in information teleportation. There are different methods which could be used for quantum information teleportation in biological system. Some of these mechanisms are: 1. Microbes, micro-bubbles and some other biological molecules like to form some biological lines specially near the cellular gates. Also, some biological lines may be formed between two cells. These biological lines could play the role of wires which transmit information from a place to another one. For example, some signatures of this quantum information teleportation could be seen in biological lines which are emerged near the plant cell walls or gates or close to chloroplasts. Chloroplasts shoot some spinors which maybe confined within the micro-bubbles or absorb by microbes. These bubbles and microbes may join to each other and form some biological lines which may be strengthen from a plant cell to another. These biological lines could be seen near the plant cell walls or on a metal which connects two parts of a leaf. 2. Some another signatures of “quantum photon exchange or quantum information teleportation” could be seen between microbes under the objective lenses and macro-objects on the eye lenses of a light microscope. It seems that as microscope make big images from microbes for us, produce small pictures of macro-objects for microbes such as they could diagnose them and interact with them. This property could be used in controlling microbes. 3. Another way for controlling microbes is using of virtual shapes which are induced by a special light source. For example, using a multi-gonal lamp, one can induce multi-gonal shape within the micro-bubbles. Also, this special lamp could force microbes and micro-bubbles to build multi-gonal colonies on a metal-glass slide. Maybe, by using this property, one can build a light source with the shape of anti-microbial matter and induce anti-microbial property within micro-bubbles. 4. Another main way for quantum teleportation is using of gravitational holes which may be emerged by increasing concentration of microbes and heavy cells in some points. These holes absorb microbes and micro-bubbles and conduct them to the heavy cells. Usually, there are some white holes near these dark holes which as a proposal, one can assume that these white holes are another end of gravitational holes and emit photons which are entered from dark end. 5. And finally, a very main mechanism for quantum information teleportation with microbes and controlling them is using of a holography and inducing virtual microbes and biological molecules in biological systems. For example, by a combinations of two lights with different colors under a light microscope in a dark room, one may induce some non-virtual microbes in biological systems such as each microbe interacts with a virtual microbe. This is because that light waves take photos of microbes, collide with lenses of microscopes and return to the slide and form virtual microbes or biological molecules. This technique could be used in curing diseases. Although, results of our experiments show the correctness of these mechanisms and theories, however, for the moment, we propose them only as a proposal and hypothesis and hope that other scientists do similar experiments. Also, some of our experiments may be at preliminary stages; however they could be used as a hypothesis, proposal and guidance.     

Workflow and metrics for image quality control in large-scale high-content screens

Automated microscopes have enabled the unprecedented collection of images at a rate that precludes visual inspection. Automated image analysis is required to identify interesting samples and extract quantitative information for high-content screening (HCS). However, researchers are impeded by the lack of metrics and software tools to identify image-based aberrations that pollute data, limiting experiment quality. The authors have developed and validated approaches to identify those image acquisition artifacts that prevent optimal extraction of knowledge from high-content microscopy experiments. They have implemented these as a versatile, open-source toolbox of algorithms and metrics readily usable by biologists to improve data quality in a wide variety of biological experiments.     

Plant growth using EMCS hardware on the ISS

Under separate contracts with ESA (FUMO and ERM Study) and as a link in the development of the European Modular Cultivation System's (EMCS) functionality and biocompatibility, plant studies have been performed at The Plant Biocentre in Trondheim, Norway. The main goal was to test whether the breadboards containing the major components planned for use in the EMCS would be optimal for space experiments with plant material. The test plans and the experimental set-up for the verification of biocompatibility and biological functionality included the use of a few model plant species including cress (Lepidium sativum L.) and Arabidopsis thaliana. The plants were tested at different developmental levels of morphological and physiological complexity (illumination, life support, humidity control, water supply, observation, short- and long-term plant growth experiments and contamination prevention). Results from the tests show that the EMCS concept is useful for long duration plant growth on the ISS.