A multiwavelength fluorescence probe: is one probe capable for on-line monitoring of recombinant protein production and biomass activity?

Monitoring cell culture performance requires maximizing the number and the quality of measured parameters and in situ 2D fluorescence spectroscopy could allow intensification of simultaneous data acquisition. The use of a multiwavelength fluorescence probe is proposed for monitoring GFP-producing cultures in bioreactor. The yeast Pichia pastoris and NSO mammalian cells were studied as model systems. Tryptophan, NAD(P)H and riboflavins (riboflavin, FMN, FAD) signals were effective for on-line yeast biomass estimation during the growth phase. During the GFP production phase, in situ measurements of the GFP concentration from the fluorescence probe were well correlated with off-line analyses. Tryptophan and NAD(P)H signals diverged from that of biomass during GFP production. With NSO mammalian cells, results showed that the culture parameters have to be optimized for the use of a fluorescence probe. The use of serum and phenol-red interfered with NAD(P)H and riboflavins fluorescence signals. Nevertheless, it appears that a multiwavelength probe could be useful for culture monitoring of biomass, cell activity and recombinant protein expression in an optimized culture medium.     

Plas’O'Soins: A software platform for modeling,planning and monitoring homecare activities

Demographic changes in recent years have contributed to a shift in care models, with the development of homecare as a new alternative to traditional hospitalization. We present a software platform dedicated to the modeling, planning and monitoring of homecare workflows, developed in the framework of the French research program TecSan. The platform is used on the desktop by care coordinators, and on the go by care workers using mobile devices.     

Nature’s untold stories: an overview on the availability and type of on-line data on long-term biodiversity monitoring

Long-term field-based monitoring is time and resource demanding. Consequently, there are few robust biodiversity databases that contain both a baseline and repeat measurements. On-line repositories represent a potential goldmine of conservation-relevant data, and are increasingly incentivized by funding agencies. However, there remains scarce information on their distribution and availability, limiting the possibility to exploit them to their full potential. Here we comprehensively searched and assessed open-access datasets where biodiversity has been monitored in the same site for at least 4 years, and where species and site locations were clearly reported. We located data on 75,669 field sites (9436 of which are in biodiversity hotspots), for a total of 28,723,226 records, monitoring a total of 15,046 different taxa. We found strong geographic and taxonomic biases. Monitoring sites were predominantly located in the Palearctic and Nearctic biogeographic realms and in the forest biome. Where fauna was monitored, the focus was mostly on amphibians and birds. Supporting open-access policies and developing strategies to fill the identified gaps will be crucial for improving our understanding of global biodiversity trends. Our results suggest, however, that we are on the right trajectory, with a vast storehouse of readily available (and often high quality) yet largely under-analysed biodiversity data now available online from a range of sources. We argue that such data can provide the required biodiversity baselines for national- or local-scale studies.     

Statistical methods for temporal and space–time analysis of community composition data

This review focuses on the analysis of temporal beta diversity, which is the variation in community composition along time in a study area. Temporal beta diversity is measured by the variance of the multivariate community composition time series and that variance can be partitioned using appropriate statistical methods. Some of these methods are classical, such as simple or canonical ordination, whereas others are recent, including the methods of temporal eigenfunction analysis developed for multiscale exploration (i.e. addressing several scales of variation) of univariate or multivariate response data, reviewed, to our knowledge for the first time in this review. These methods are illustrated with ecological data from 13 years of benthic surveys in Chesapeake Bay, USA. The following methods are applied to the Chesapeake data: distance-based Moran''s eigenvector maps, asymmetric eigenvector maps, scalogram, variation partitioning, multivariate correlogram, multivariate regression tree, and two-way MANOVA to study temporal and space–time variability. Local (temporal) contributions to beta diversity (LCBD indices) are computed and analysed graphically and by regression against environmental variables, and the role of species in determining the LCBD values is analysed by correlation analysis. A tutorial detailing the analyses in the R language is provided in an appendix.     

Avidin–biotin-immobilized liposome column for chromatographic fluorescence on-line analysis of solute–membrane interactions

Unilamellar liposomes with entrapped fluorescent dye calcein were stably immobilized in gel beads by avidin–biotin-binding. The immobilized liposomes remained extremely stable upon storage and chromatographic runs. The immobilized calcein-entrapped liposomes were utilized for fluorescent analysis of solute–membrane interactions, which in some cases are too weak to be detected by chromatographic retardation. A liposome column was used as a sensitive probe to detect the interactions of membranes with pharmaceutical drugs, peptides and proteins. Retardation of the solutes was monitored using a UV detector. Perturbation of the membranes, reflected as leakage of the entrapped calcein by some of the solutes, can thus be detected on-line using a flow-fluorescent detector. For the amphiphilic drugs or synthetic peptides, perturbation of membranes became more pronounced when the retardation (hydrophobicity) of the molecules increased. On the other hand, in the case of positively-charged peptides, polylysine, or partially denatured bovine carbonic anhydrase, significant dye leakage from the liposomes was observed although the retardation was hardly to be measured. Weak protein–membrane interactions can thus be assumed from the large leakage of calcein from the liposomes. This provides additional useful information for solute–membrane interactions, as perturbation of the membranes was also indicated by avidin–biotin-immobilized liposome chromatography (ILC).     

Scientific data and theories for salmonellosis dose–response assessment

An “expansive” risk assessment approach is illustrated, characterizing dose–response relationships for salmonellosis in light of the full body of evidence for human and murine superorganisms. Risk assessments often require analysis of costs and benefits for supporting public health decisions. Decision-makers and the public need to understand uncertainty in such analyses for two reasons. Uncertainty analyses provide a range of possibilities within a framework of present scientific knowledge, thus helping to avoid undesirable consequences associated with the selected policies. And, it encourages the risk assessors to scrutinize all available data and models, thus helping avoid subjective or systematic errors. Without the full analysis of uncertainty, decisions could be biased by judgments based solely on default assumptions, beliefs, and statistical analyses of selected correlative data. Alternative data and theories that incorporate variability and heterogeneity for the human and murine superorganisms, particularly colonization resistance, are emerging as major influences for microbial risk assessment. Salmonellosis risk assessments are often based on conservative default models derived from selected sets of outbreak data that overestimate illness. Consequently, the full extent of uncertainty of estimates of annual number of illnesses is not incorporated in risk assessments and the presently used models may be incorrect.     

Hyperspectral modeling of ecological indicators – A new approach for monitoring former military training areas

Military areas are valuable habitats and refuges for rare and endangered plants and animals. We developed a new approach applying innovative methods of hyperspectral remote sensing to bridge the existing gap between remote sensing technology and the demands of the nature conservation community. Remote sensing has already proven to be a valuable monitoring instrument. However, the approaches lack the consideration of the demands of applied nature conservation which includes the legal demands of the EU Habitat Directive. Following the idea of the Vital Signs Monitoring in the USA, we identified a subset of the highest priority monitoring indicators for our study area. We analyzed continuous spectral response curves and tested the measurability of N = 19 indicators on the basis of complexity levels aggregated from extensive vegetation assemblages. The spectral differentiability for the floristic as well as faunistic indicators revealed values up to 100% accuracy. We point out difficulties when it comes to distinguishing faunistic habitat requirements of several species adapted to dry open landscapes, which in this case results in Overall accuracy of 67, 87–95, and 35% in the error matrix. In summary, we provide an applicable and feasible method to facilitating monitoring military areas by hyperspectral remote sensing in the following.     

Bacterioplankton of the Kola Bay, Barents Sea, (micro-and nanoforms) based on 2002–2003 monitoring data

Hydrochemical and microbiological investigation in the Kola Bay in 2002–2003 demonstrated that the distribution of bacteria is notably influenced by biogeochemical barriers formed by mixing fresh and sea water. Seasonal changes in the appearance of filterable bacteria, considerable quantities of gram-positive bacteria with thick cell walls, dwarf bacteria, spheroplasts, elementary bodies, and cells with abnormal cell walls during the polar night have been revealed. Cultured bacterial colonies were represented by polymorphic cells. The data obtained refine our knowledge about organotrophic activity of bacterioplankton during the polar night.     

Analysis and modeling of time-variant amplitude–frequency couplings of and between oscillations of EEG bursts

Low-frequency (0.5-2.5 Hz) and individually defined high-frequency (7-11 or 8-12 Hz; 11-15 or 14-18 Hz) oscillatory components of the electroencephalogram (EEG) burst activity derived from thiopental-induced burst-suppression patterns (BSP) were investigated in seven sedated patients (17-26 years old) with severe head injury. The predominant high-frequency burst oscillations (>7 Hz) were detected for each patient by means of time-variant amplitude spectrum analysis. Thereafter, the instantaneous envelope (IE) and the instantaneous frequency (IF) were computed for these low- and high-frequency bands to quantify amplitude-frequency dependencies (envelope-envelope, envelope-frequency, and frequency-frequency correlations). Time-variant phase-locking, phase synchronization, and quadratic phase couplings are associated with the observed amplitude-frequency characteristics. Additionally, these time-variant analyses were carried out for modeled burst patterns. Coupled Duffing oscillators were adapted to each EEG burst and by means of these models data-based burst simulations were generated. Results are: (1) strong envelope-envelope correlations (IE courses) can be demonstrated; (2) it can be shown that a rise of the IE is associated with an increase of the IF (only for the frequency bands 0.5-2.5 and 7-11 or 8-12 Hz); (3) the rise characteristics of all individually averaged envelope-frequency courses (IE-IF) are strongly correlated; (4) for the 7-11 or 8-12 Hz oscillation these associations are weaker and the variation between the time courses of the patients is higher; (5) for both frequency ranges a quantitative amplitude-frequency dependency can be shown because higher IE peak maxima are accompanied by stronger IF changes; (6) the time range of significant phase-locking within the 7-11 or 8-12 Hz frequency bands and of the strongest quadratic phase couplings (between 0.5-2.5 and 7-11 or 8-12 Hz) is between 0 and 1,000 ms; (7) all phase coupling characteristics of the modeled bursts accord well with the corresponding characteristics of the measured EEG burst data. All amplitude-frequency dependencies and phase locking/coupling properties described here are known from and can be discussed using coupled Duffing oscillators which are characterized by autoresonance properties.     

Nucleotide binding domain 1 pharmacophore modeling for visualization and analysis of P-glycoprotein–flavonoid molecular interactions

Background

P-glycoprotein (P-gp) is a 170-kDa membrane protein. It provides a barrier function and help to excrete toxins from the body as a transporter. Some bioflavonoids have been shown to block P-gp activity.

Objective

To evaluate the important amino acid residues within nucleotide binding domain 1 (NBD1) of P-gp that play a key role in molecular interactions with flavonoids using structure-based pharmacophore model.

Methods

In the molecular docking with NBD1 models, a putative binding site of flavonoids was proposed and compared with the site for ATP. The binding modes for ligands were achieved using LigandScout to generate the P-gp–flavonoid pharmacophore models.

Results

The binding pocket for flavonoids was investigated and found these inhibitors compete with the ATP for binding site in NBD1 including the NBD1 amino acid residues identified by the in silico techniques to be involved in the hydrogen bonding and van der Waals (hydrophobic) interactions with flavonoids.

Conclusion

These flavonoids occupy with the same binding site of ATP in NBD1 proffering that they may act as an ATP competitive inhibitor.

     

‘Ferry-Boxes’ and data stations for improved monitoring and resolution of eutrophication-related processes: application in Southampton Water UK,a temperate latitude hypernutrified estuary

To provide detailed observations of algal bloom development in Southampton Water which is a hypernutrified, macro-tidal estuary (mean tidal range 3.2 m, low suspended load <100 g m^–3), a ferry running between Southampton and Cowes on the Isle of Wight, was fitted with an instrument package (Ferry-Box). Measurements were made of temperature, conductivity, turbidity, and chlorophyll-fluorescence at a data rate of 1Hz. For comparison a data station which measured the same variables was operated at a fixed site in the estuary. In 1999 the Ferry-Box achieved reliable operation with a data return over 95%, for the fixed data station the return was 92%. From this data spatial and temporal variations in chlorophyll a concentrations have been mapped. The maps show the development of blooms in different areas of the estuary, through the spring and summer, in relation to tidal and weather conditions. In 1999 conditions were such that the spring bloom increased in intensity through a spring tide (maximum chlorophyll a 55 mg m^–3), which coincided with calm weather with high light levels (irradiance). This was followed by a sequence of seven blooms, the development of which can be related to changes in the tidal energy, irradiance and nutrient supply.     

caBIG™ VISDA: Modeling, visualization, and discovery for cluster analysis of genomic data

Background

We sketch our species identification tool for palm sized computers that helps knowledgeable observers with census activities. An algorithm turns an identification matrix into a minimal length series of questions that guide the operator towards identification. Historic observation data from the census geographic area helps minimize question volume. We explore how much historic data is required to boost performance, and whether the use of history negatively impacts identification of rare species. We also explore how characteristics of the matrix interact with the algorithm, and how best to predict the probability of observing a previously unseen species.

Results

Point counts of birds taken at Stanford University's Jasper Ridge Biological Preserve between 2000 and 2005 were used to examine the algorithm. A computer identified species by correctly answering, and counting the algorithm's questions. We also explored how the character density of the key matrix and the theoretical minimum number of questions for each bird in the matrix influenced the algorithm. Our investigation of the required probability smoothing determined whether Laplace smoothing of observation probabilities was sufficient, or whether the more complex Good-Turing technique is required.

Conclusion

Historic data improved identification speed, but only impacted the top 25% most frequently observed birds. For rare birds the history based algorithms did not impose a noticeable penalty in the number of questions required for identification. For our dataset neither age of the historic data, nor the number of observation years impacted the algorithm. Density of characters for different taxa in the identification matrix did not impact the algorithms. Intrinsic differences in identifying different birds did affect the algorithm, but the differences affected the baseline method of not using historic data to exactly the same degree. We found that Laplace smoothing performed better for rare species than Simple Good-Turing, and that, contrary to expectation, the technique did not then adversely affect identification performance for frequently observed birds.     

How accurate are single site transect data for monitoring butterfly trends? Spatial and temporal issues identified in monitoring Lasiommata megera

Multiple transect counts following Butterfly Monitoring Scheme (UKBMS) guidelines and Jolly–Seber estimates of population size were used to monitor the abundance of second generation Lasiommata megera on a single site in southern England. The two methods resulted in different patterns of emergence being detected. The proportion of the population (estimated by Jolly–Seber) recorded with transect counts depended on the time of day and weather with afternoon transect counts best recording the trend in abundance over the flight period, but even then counts recorded a variable fraction of the population (6.2–51.3%). Increasing the frequency with which transect counts are carried out per week reduced variation and increased the fit of transect counts to Jolly–Seber generated population estimates. However, indices of abundance generated from randomly selected transect counts for L. megera within sampling weeks varied 4-fold and indices for other butterfly species were also highly variable. For L. megera, transect count variability is attributed to non-representative placement of the transect route and changes in the behaviour and spatial distribution in relation to population size and season. We suggest that transect counts need to be fully validated before the data are used to monitor changes of butterfly populations at individual sites.     

Ammonium removal using algae–bacteria consortia: the effect of ammonium concentration,algae biomass,and light

In this study, the effects of ammonium nitrogen concentration, algae biomass concentration, and light conditions (wavelength and intensity) on the ammonium removal efficiency of algae-bacteria consortia from wastewater were investigated. The results indicated that ammonium concentration and light intensity had a significant impact on nitrification. It was found that the highest ammonia concentration (430 mg N/L) in the influent resulted in the highest ammonia removal rate of 108 ± 3.6 mg N/L/days, which was two times higher than the influent with low ammonia concentration (40 mg N/L). At the lowest light intensity of 1000 Lux, algae biomass concentration, light wavelength, and light cycle did not show a significant effect on the performance of algal–bacterial consortium. Furthermore, the ammonia removal rate was approximately 83 ± 1.0 mg N/L/days, which was up to 40% faster than at the light intensity of 2500 Lux. It was concluded that the algae-bacteria consortia can effectively remove nitrogen from wastewater and the removal performance can be stabilized and enhanced using the low light intensity of 1000 Lux that is also a cost-effective strategy.     

Mathematical modeling of cancer–immune system,considering the role of antibodies

A mathematical model for the quantitative analysis of cancer–immune interaction, considering the role of antibodies has been proposed in this paper. The model is based on the clinical evidence, which states that antibodies can directly kill cancerous cells (Ivano et al. in J Clin Investig 119(8):2143–2159, 2009). The existence of transcritical bifurcation, which has been proved using Sotomayor theorem, provides strong biological implications. Through numerical simulations, it has been illustrated that under certain therapy (like monoclonal antibody therapy), which is capable of altering the parameters of the system, cancer-free state can be obtained.