A fluorescence assay for monitoring and analyzing fusion biological membrane vesicles in vitro

A new technique has been developed to study fusion of biological membrane vesicles. Bovine chromaffin granule ghosts (CGG) were loaded with fluorescein isothiocyanate-dextran (FITC-dextran) at self-quenching concentrations. Loaded ghosts were then made to fuse with empty CGG. Fusion was induced by synexin, a protein previously proposed to be involved in exocytosis. The fusion process was monitored by measuring the dequenching of the fluorescence. Dequenching occurred as FITC-dextran was diluted into the increased volume due to fusion with empty ghosts. Spurious signals from leakage or breakage of vesicles were removed by including a specific anti-fluorescein antibody in the reaction medium. This new technique may prove to be of more general use for studying membrane fusion processes in other systems.     

A survey on methods for modeling and analyzing integrated biological networks

Understanding how cellular systems build up integrated responses to their dynamically changing environment is one of the open questions in Systems Biology. Despite their intertwinement, signaling networks, gene regulation and metabolism have been frequently modeled independently in the context of well-defined subsystems. For this purpose, several mathematical formalisms have been developed according to the features of each particular network under study. Nonetheless, a deeper understanding of cellular behavior requires the integration of these various systems into a model capable of capturing how they operate as an ensemble. With the recent advances in the "omics" technologies, more data is becoming available and, thus, recent efforts have been driven toward this integrated modeling approach. We herein review and discuss methodological frameworks currently available for modeling and analyzing integrated biological networks, in particular metabolic, gene regulatory and signaling networks. These include network-based methods and Chemical Organization Theory, Flux-Balance Analysis and its extensions, logical discrete modeling, Petri Nets, traditional kinetic modeling, Hybrid Systems and stochastic models. Comparisons are also established regarding data requirements, scalability with network size and computational burden. The methods are illustrated with successful case studies in large-scale genome models and in particular subsystems of various organisms.     

A computer-assisted technique for long-term gastric pH monitoring

A computer-assisted technique for prolonged gastric pH monitoring has been developed using a personal computer. Segments of signal from several studies performed in controls and on patients with duodenal ulcers were chosen for comparison between manual and digital pH readings; no significant difference was detected. In clinical practice this system might provide an additional tool in the diagnostic and therapeutic treatment of peptic ulcer disease.     

A process-orientated design and performance assessment methodology for passive mine water treatment systems

The aim of this paper is the development of a methodology for assessing the iron removal efficiency of passive mine water treatment settling lagoons and reed beds. Previous work in the design and sizing of coal mine drainage lagoons and wetlands has focussed on the use of standard hydraulic residence times or using the 10 g m⁻² d⁻¹ metric, these criteria have been applied without regard to the fundamental physical and chemical processes controlling iron removal in the system, namely the pH dependent rates of Fe(II) oxidation and physical settling of the particulate Fe(III). In this study field water quality data have been collected from lagoons and reed beds. These data are examined alongside data from the UK Coal Authority database and combined with simple mathematical formulations to provide a framework through which to understand passive treatment schemes from a process-orientated perspective. It is demonstrated that for the sites studied reed beds are more efficient for iron removal. This paper recommends that judgements of iron removal performance should be based on a derived treatment efficiency index (?) and that the modelling approach espoused in this paper should be used when designing passive mine water treatment schemes.     

A review of detection range testing in aquatic passive acoustic telemetry studies

Passive acoustic telemetry provides an important tool to study the spatial ecology and behaviour of organisms in marine and freshwater systems, but understanding the detection range of acoustic receivers is critical for interpreting acoustic data and establishing receiver spacing to maximize study efficiency. This study presents a comprehensive review of how acoustic detection range has been considered and assessed to date, summarizes important variables to monitor when determining the detection range of a receiver array, and provides recommendations to account for detection range during experimental design, analysis and data interpretation. A total of 378 passive acoustic telemetry studies (1986–2012) were scored against a set of pre-defined criteria to provide a standardized assessment of how well detection range was accounted for, from a maximum possible score of 45. Scores ranged from 0 to 39 (11.1 ± 0.4; mean ± 1 SE). Over the past decade mean scores have been consistently between 6.7 and 12.9 which indicates that detection range has not been adequately considered in most contemporary acoustic telemetry studies. Given the highly variable nature of detection range over space and time, it is necessary to create a culture of detection range testing among the scientific community. For robust telemetry studies it is recommended that consideration of detection range should be given a greater focus within study design, execution and data analysis. To aid array design in new systems, short-term detection range tests should be conducted in the most representative area of the study system prior to deployment. As well, fixed distance sentinel tags should ideally be deployed at a representative receiver site within the array to provide a continuous assessment of detection range and influential environmental parameters should be monitored to facilitate modeling of detection range variability over time. When warranted, data analysis should incorporate modeled variation in detection ranges.     

ATP microelectrode biosensor for stable long-term in vitro monitoring from gastrointestinal tissue

We have developed a stable and selective ATP biosensor for long-term in vitro tissue monitoring. The electrode was fabricated by entrapping glucose oxidase (GOx) and hexokinase (HEX) in a poly-phenol film on a Pt microelectrode. The biosensor was stable to a fixed concentration of glucose for over 20 min and had a limit of detection of 9.9 ± 3.2 nM, with a sensitivity of 45.8 ± 1.22 pA μM(-1). Most significantly of all, the response on the ATP biosensor did not alter in the presence of 1mM ascorbic acid, 5 μM dopamine, 5 μM serotonin, 5 μM ADP and 5 μM AMP. The ATP biosensor was also shown to have excellent stability over 7 days, and showed only a 23.92 ± 3.55% loss in sensitivity. The ATP biosensor was utilised for the in vitro detection of ATP from gastrointestinal tissue. The ATP biosensor response was stable for 5h during in vitro recordings from ileum tissue. ATP release was shown to be greater from the mucosal surface in the ileum compared to the colon.     

A probabilistic methodology for integrating knowledge and experiments on biological networks.

Biological systems are traditionally studied by focusing on a specific subsystem, building an intuitive model for it, and refining the model using results from carefully designed experiments. Modern experimental techniques provide massive data on the global behavior of biological systems, and systematically using these large datasets for refining existing knowledge is a major challenge. Here we introduce an extended computational framework that combines formalization of existing qualitative models, probabilistic modeling, and integration of high-throughput experimental data. Using our methods, it is possible to interpret genomewide measurements in the context of prior knowledge on the system, to assign statistical meaning to the accuracy of such knowledge, and to learn refined models with improved fit to the experiments. Our model is represented as a probabilistic factor graph, and the framework accommodates partial measurements of diverse biological elements. We study the performance of several probabilistic inference algorithms and show that hidden model variables can be reliably inferred even in the presence of feedback loops and complex logic. We show how to refine prior knowledge on combinatorial regulatory relations using hypothesis testing and derive p-values for learned model features. We test our methodology and algorithms on a simulated model and on two real yeast models. In particular, we use our method to explore uncharacterized relations among regulators in the yeast response to hyper-osmotic shock and in the yeast lysine biosynthesis system. Our integrative approach to the analysis of biological regulation is demonstrated to synergistically combine qualitative and quantitative evidence into concrete biological predictions.     

The monitoring of biological effects: the separation of natural changes from those induced by pollution.

An added mortality rate of eggs, larvae and juveniles of fish populations, or impact, is assumed to be density independent. The total mortality from hatching to recruitment is represented by the fecundity, and any increment in density independent mortality implies a decrement in density dependent mortality. At high stock the condequence is an increase in stock towards a position of less resilience: at low stock less resilience is found with a decrease in stock. In general impact generates a shift of K-strategy, the self-stabilizing strategy, to r-strategy, and opportunistic one. In a fish population very little impact should be tolerated at low stock because it would prevent recovery to a management objective such as maximum sustainable yield. At high stock, impact may generate more stock at an unknown risk.     

A hybrid on-line ECG segmenting system for long-term monitoring.

This paper introduces a new hybrid ECG beat segmenting system, which can be applied in the processing unit of single-channel, long-term ECG monitors for the on-line segmentation of the ECG signal. Numerous ECG segmentation techniques are already existing and applied, however sufficiently robust and reliable methods currently require more than one ECG signal channel and quite complex computations, which are practically not feasible in stand-alone, low-cost monitors. Our new system approach presents a time domain segmentation technique based on a priori physiological and morphological information of the ECG beat. The segmentation is carried out after classifying the ECG beat, using the linear approximation of the filtered ECG signal and considering the pathophysiological properties as well. The proposed algorithms require moderate computational power, allowing the practical realization in battery powered stand-alone long-term cardiac monitors or small-sized cardiac defibrillators. The prototype version of the system was implemented in Matlab. The test and evaluation of the system was carried out with the help of reference signal databases.     

A simple convenient biological dosimeter for monitoring solar UV-B radiation

The use of dry Bacillus subtilis spores as a biological dosimeter for the monitoring of solar UV-B (290-330 nm) radiation was described. Our field tests had supported the utility of this dosimeter as a reproducible and reliable sunlight dosimeter.     

A computational system for simulating and analyzing arrays of biological and artificial chemical sensors

We have designed an approach for modeling olfactory pathways by which one can explore how the properties of individual receptors affect the information coding capacity of an entire system. The effect of receptor tuning breadth on system performance was explored explicitly. We presented model sensory arrays with sets of stimuli randomly and uniformly distributed in an "olfactory space". Arrays of uniformly sized model receptors responding to 25-35% of the stimuli gave the best performance as measured by the ability to capture the most information about the stimulus set. Arrays of variably sized model receptors that were both more broadly and more narrowly tuned than this optimum could, however, perform better than uniform arrays. This method and the results obtained using it suggest a framework for considering the growing body of evidence on the functional properties of individual olfactory receptor and relay neurons from a systems coding perspective.     

Improved methodology for detecting aflatoxin production quantitatively in natural media

This report describes a simple, rapid, and quantitative method for screening the aflatoxin production by moulds of theAspergillus flavus group, using a natural media (moist wheat or rice), and a single chloroform extraction for aflatoxins. The aflatoxins were detected and quantified by thin layer chromatography. The methodology proposed was useful in detecting aflatoxin production on the 3rd day of incubation in more than 85 % of the strains studied (both culture collection strains and field isolates).     

A simple system for monitoring biodiversity in protected areas of a developing country

The achievements of initiatives to strengthen biodiversity conservation in developing countries may be difficult to assess, since most countries have no system for monitoring biodiversity. This paper describes a simple and cost-effective, field-based biodiversity monitoring system developed specifically for areas where specialist staff is lacking. We discuss the preliminary lessons learned from protected areas in the Philippines. Whilst the monitoring system aims to identify trends in biodiversity and its uses so as to guide management action, it also promotes the participation of local people in the management, stimulates discussions about conservation amongst stakeholders and builds the capacity of park staff and communities in management skills. In addition, it seeks to provide people with direction regarding the aims of protected areas, and reinforces the consolidation of existing livelihoods through strengthening community-based resource management systems. The field methods are: (1) standardised recording of routine observations, (2) fixed point photographing, (3) line transect survey, and (4) focus group discussion. Both bio-physical and socio-economic data are used and given equal importance. The system can be sustained using locally available resources. The approach is useful in countries embarking on shared management of park resources with local communities, where rural people depend on use of natural ecosystems, and where the economic resources for park management are limited. We hope this paper will encourage other countries to develop their own biodiversity monitoring system, letting its development become a means for capacity building whilst at the same time supporting the creation of ownership.     

A viscosity-dependent affinity sensor for continuous monitoring of glucose in biological fluids

We present a viscometric affinity biosensor for continuous monitoring of glucose in biological fluids such as blood and plasma. The sensing principle of this chemico-mechanical sensor is based upon the viscosity variation of a sensitive fluid with glucose concentration. Basically, this device includes both an actuating and a sensing piezoelectric diaphragms as well as a flow-resistive microchannel. In order to confine the sensitive fluid and allow glucose diffusion into the sensor, a free-standing alumina nanoporous membrane is also used as size-selective interface. Measurements carried out at nominal temperatures of 25 and 37 °C reveal that this sensor topology exhibits a high resolution in the current range of physiological blood glucose concentrations, i.e. 2-20 mM. In addition, complete reversibility was also demonstrated for at least 3 days. Finally, measurements performed in human blood serum confirm that this sensor fulfils all basic requirements for a use in continuous glucose monitoring of biological fluids.     

A metacommunity framework for enhancing the effectiveness of biological monitoring strategies

Because of inadequate knowledge and funding, the use of biodiversity indicators is often suggested as a way to support management decisions. Consequently, many studies have analyzed the performance of certain groups as indicator taxa. However, in addition to knowing whether certain groups can adequately represent the biodiversity as a whole, we must also know whether they show similar responses to the main structuring processes affecting biodiversity. Here we present an application of the metacommunity framework for evaluating the effectiveness of biodiversity indicators. Although the metacommunity framework has contributed to a better understanding of biodiversity patterns, there is still limited discussion about its implications for conservation and biomonitoring. We evaluated the effectiveness of indicator taxa in representing spatial variation in macroinvertebrate community composition in Atlantic Forest streams, and the processes that drive this variation. We focused on analyzing whether some groups conform to environmental processes and other groups are more influenced by spatial processes, and on how this can help in deciding which indicator group or groups should be used. We showed that a relatively small subset of taxa from the metacommunity would represent 80% of the variation in community composition shown by the entire metacommunity. Moreover, this subset does not have to be composed of predetermined taxonomic groups, but rather can be defined based on random subsets. We also found that some random subsets composed of a small number of genera performed better in responding to major environmental gradients. There were also random subsets that seemed to be affected by spatial processes, which could indicate important historical processes. We were able to integrate in the same theoretical and practical framework, the selection of biodiversity surrogates, indicators of environmental conditions, and more importantly, an explicit integration of environmental and spatial processes into the selection approach.