Expert Opinion on the Perceived Effectiveness and Importance of On-Farm Biosecurity Measures for Cattle and Swine Farms in Switzerland

Biosecurity is crucial for safeguarding livestock from infectious diseases. Despite the plethora of biosecurity recommendations, published scientific evidence on the effectiveness of individual biosecurity measures is limited. The objective of this study was to assess the perception of Swiss experts about the effectiveness and importance of individual on-farm biosecurity measures for cattle and swine farms (31 and 30 measures, respectively). Using a modified Delphi method, 16 Swiss livestock disease specialists (8 for each species) were interviewed. The experts were asked to rank biosecurity measures that were written on cards, by allocating a score from 0 (lowest) to 5 (highest). Experts ranked biosecurity measures based on their importance related to Swiss legislation, feasibility, as well as the effort required for implementation and the benefit of each biosecurity measure. The experts also ranked biosecurity measures based on their effectiveness in preventing an infectious agent from entering and spreading on a farm, solely based on transmission characteristics of specific pathogens. The pathogens considered by cattle experts were those causing Bluetongue (BT), Bovine Viral Diarrhea (BVD), Foot and Mouth Disease (FMD) and Infectious Bovine Rhinotracheitis (IBR). Swine experts expressed their opinion on the pathogens causing African Swine Fever (ASF), Enzootic Pneumonia (EP), Porcine Reproductive and Respiratory Syndrome (PRRS), as well as FMD. For cattle farms, biosecurity measures that improve disease awareness of farmers were ranked as both most important and most effective. For swine farms, the most important and effective measures identified were those related to animal movements. Among all single measures evaluated, education of farmers was perceived by the experts to be the most important and effective for protecting both Swiss cattle and swine farms from disease. The findings of this study provide an important basis for recommendation to farmers and policy makers.     

Integrated information increases with fitness in the evolution of animats

One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular since organismal functional complexity is not well-defined. We present here several candidate measures that quantify information and integration, and study their dependence on fitness as an artificial agent ("animat") evolves over thousands of generations to solve a navigation task in a simple, simulated environment. We compare the ability of these measures to predict high fitness with more conventional information-theoretic processing measures. As the animat adapts by increasing its "fit" to the world, information integration and processing increase commensurately along the evolutionary line of descent. We suggest that the correlation of fitness with information integration and with processing measures implies that high fitness requires both information processing as well as integration, but that information integration may be a better measure when the task requires memory. A correlation of measures of information integration (but also information processing) and fitness strongly suggests that these measures reflect the functional complexity of the animat, and that such measures can be used to quantify functional complexity even in the absence of fitness data.     

Metrics from nonlinear dynamics adapted for characterizing the behavior of nonequilibrium enzymatic rate functions

Several metrics from nonlinear dynamics and statistical mechanics have been characterized on computer-generated number series with various signal-to-noise ratios, demonstrating their individual reliability as a function of sample size and their relationships to each other. The root mean square (RMS) evaluates amplitude, and the power spectral density (PSD) provides a visual display of the frequency spectrum; both measures have very high reliability even for an N as low as 50. The Fractal Dimension (D) is shown to converge rapidly and also to be reliable when N is as low as 50. These three measures (RMS, PSD, and D) have been applied to the complex kinetics of tyrosine hydroxylase time courses (50-point curves) at various BH4 concentrations (near physiological, but far from equilibrium levels). Recently developed measures of spectral entropy and the Liapunov Exponent, -lambda are also characterized.     

Selecting ecological indicators to compare maintenance costs related to the compensation of damaged ecosystem services

The aim of this paper is to compare different maintenance costs of ecosystem service arising from a hypothetical case of environmental damage in order to help to understand how the different ecosystem services are considered in decision making processes. Compensatory measures are aimed precisely at maintaining the level of supply of ecosystem services. According to the literature, compensatory measures like restoration are usually applied to specific ecosystem services. We used the Millennium Ecosystem Assessment (MEA) categories of ecosystem service. For each MEA category, several ecological indicators are selected, and the cost of the compensatory measures required to fulfill the goal of no net loss is assessed using the Habitat Equivalency Analysis (HEA). The results of this analysis highlight differences between compensatory measures and their associated costs depending on the category of ecosystem services targeted. Maintenance costs are high for regulating services, low for provisioning services, and more difficult to determine for cultural services (high or low depending on the indicator selected). We discuss the implications of this result, noting that it is more rational for project developers to focus their attention on provisioning services if the legal regulation of compensation is lax or if indicators relative to cultural and regulating services are not precise enough.     

Quantifying the Components of Biocomplexity Along Ecological Perturbation Gradients

The study of ecological perturbation gradients provides a unique opportunity to investigate the utility of various biocomplexity indices. The ability of four measures of biocomplexity (quadratic entropy, taxonomic entropy, total complexity and total diversity) and their components to quantify the nature and degree of perturbation in plant communities was assessed by how closely each measure reflected the trends in biocomplexity that are expected to occur along a gradient of decreasing perturbation. The measures were applied to two landscapes, located near Sudbury, Canada and Harjavalta, Finland, perturbed by nickel–copper smelter emissions. Taxonomic entropy was determined to be the most useful of the four measures as it has a clear information-theoretical meaning, the relative contributions of classical diversity and taxonomic information can be easily isolated, and its computation is straightforward relative to the other measures. Additionally, it is relatively insensitive to community evenness, thereby rendering it less sample-size dependant and a more appropriate measure to use for comparisons between studies as well as for conservation and restoration purposes.     

Enhancing the Functional Content of Eukaryotic Protein Interaction Networks

Protein interaction networks are a promising type of data for studying complex biological systems. However, despite the rich information embedded in these networks, these networks face important data quality challenges of noise and incompleteness that adversely affect the results obtained from their analysis. Here, we apply a robust measure of local network structure called common neighborhood similarity (CNS) to address these challenges. Although several CNS measures have been proposed in the literature, an understanding of their relative efficacies for the analysis of interaction networks has been lacking. We follow the framework of graph transformation to convert the given interaction network into a transformed network corresponding to a variety of CNS measures evaluated. The effectiveness of each measure is then estimated by comparing the quality of protein function predictions obtained from its corresponding transformed network with those from the original network. Using a large set of human and fly protein interactions, and a set of over GO terms for both, we find that several of the transformed networks produce more accurate predictions than those obtained from the original network. In particular, the measure and other continuous CNS measures perform well this task, especially for large networks. Further investigation reveals that the two major factors contributing to this improvement are the abilities of CNS measures to prune out noisy edges and enhance functional coherence in the transformed networks.     

Restoration of riverine inland sand dune complexes: implications for the conservation of wild bees

1.  The evaluation of restoration measures is an important task of conservation biology. Inland sand dunes and dry, oligotrophic grasslands have become rare habitat types in large parts of Central Europe and their restoration and management is of major importance for the preservation of many endangered plant and insect species. Within such habitats, it is important to restore key ecosystem services, such as pollination networks. As wild bees are the most important pollinators in many ecosystems, they represent a suitable key group to evaluate restoration measures. Furthermore, the recent decline of many bee species and the potential ecological and economic consequences are currently topics of strong scientific interest.
2.  We studied the succession of bee communities in response to restoration measures of sand dunes and sand grasslands and compared these communities with those of old sand dune complexes.
3.  Our results show that wild bees respond rapidly to restoration measures indicated by a high species richness and abundance. The community structure of bees at restoration sites converged only slightly to those of the target sites. A higher similarity was found between bee communities at the restoration sites (sand dunes and grasslands), indicating that their close proximity was an important determinant of species overlap. Environmental factors such as the number of entomophilous plant species and moisture had a strong influence on wild bee species composition.
4.   Synthesis and applications . The restoration of inland sand dune complexes provides opportunities for colonization by a diverse wild bee community. Although it is difficult to establish a given target community, restoration measures gave rise to a high pollinator diversity and abundance, suggesting that community function can be re-established.     

A factor analysis of body build in the rat

Following a survey of the problems associated with the comparative study of measures of physique in domesticated and laboratory animals, techniques were developed for the measurement of body build in the adult albino laboratory rat (Rattus norvegicus). They involved anesthetisation of the animals and the use of calipers and a simple apparatus devised for the purpose. The 17 measures taken on 100 rats, 50 of each sex, are detailed and the reasons for excluding others given. Intercorrelations of all the measures and their reliability co-efficients, which were judged satisfactory, are presented. The tables of intercorrelations, one for each sex, were factor analysed separately, and rotations to simple structure performed. Two factors were identified, one having factor saturations on measures of body length and the other similarly defining body width. This pattern was similar for the two sexes and a single index of body build was therefore proposed in which the length of the rear foot is divided by the width of the shoulder girdle and multiplied by 100 to avoid decimals. The use of the index in other investigations is mentioned.     

Use of a mathematical model to study the dynamics of Ctenocephalides felis populations in the home environment and the impact of various control measures

The biology of fleas has been studied by a number of authors, as has the impact of various types of control measures. However, there are no mathematical models simulating the dynamics of a population of Ctenocephalides felis felis fleas on their host (the cat) and in their close environment (apartment). The model presented in this paper allows for integration of the numerous biological and behavioural parameters of the parasites and their hosts and for the variation of these same parameters. The various types of control measures can be programmed so that their impact over time can be studied. The model confirms the key role played by adult fleas, or emerged fleas contained in the cocoon. Only regular applications of persistent insecticides to the host animal will enable control of the parasite population. A combination of these insecticides with an IGR (Insect Growth Regulator) will accelerate decontamination of the home environment and see the disappearance of the parasites altogether if they are not reintroduced. The association of additional measures such as vacuum cleaning will accelerate the process of decontamination but will have no impact if carried out in isolation. One-off treatment with insecticide will not enable a reduction in the parasite population, even if carried out frequently. Use of insecticides on the home environment premises alone does not appear to be an adequate means of control. The present model can be used to test various integrated control measures which take into account different factors such as the number of host animals, the frequency of movement outdoors, the impact of the seasons.     

Tree shape‐based approaches for the comparative study of cophylogeny

Cophylogeny is the congruence of phylogenetic relationships between two different groups of organisms due to their long‐term interaction. We investigated the use of tree shape distance measures to quantify the degree of cophylogeny. We implemented a reverse‐time simulation model of pathogen phylogenies within a fixed host tree, given cospeciation probability, host switching, and pathogen speciation rates. We used this model to evaluate 18 distance measures between host and pathogen trees including two kernel distances that we developed for labeled and unlabeled trees, which use branch lengths and accommodate different size trees. Finally, we used these measures to revisit published cophylogenetic studies, where authors described the observed associations as representing a high or low degree of cophylogeny. Our simulations demonstrated that some measures are more informative than others with respect to specific coevolution parameters especially when these did not assume extreme values. For real datasets, trees’ associations projection revealed clustering of high concordance studies suggesting that investigators are describing it in a consistent way. Our results support the hypothesis that measures can be useful for quantifying cophylogeny. This motivates their usage in the field of coevolution and supports the development of simulation‐based methods, i.e., approximate Bayesian computation, to estimate the underlying coevolutionary parameters.     

Revisiting the potential of time-domain indexes in short-term HRV analysis.

In the context of HRV analysis, we evaluated the information content of two measures that can easily be derived from the classical RR time-domain indexes. The two measures are: 1) the ratio sd/rmssd, where sd is the RR standard deviation and rmssd is the root mean square of squared differences of consecutive RR beats; and 2) the ratio sd2/sd1, where sd2 and sd1 are extracted from the Poincaré plot and represent the transversal and longitudinal dispersion of the cloud of points (RR(i),RR(i)(+1)). We compared the performance of the two measures with that of the classical LF/HF ratio in a group of healthy subjects who underwent a 70 degrees upright tilt test. The goodness of the results obtained by the two measures, the simplicity of their calculation and their applicability free from a priori assumptions on the characteristics of the data are proposed to the attention of the community involved in the HRV analysis as a possible alternative to the LF/HF ratio.     

Expected life years compared to the general population

For cohorts with long-term follow-up, the number of years lost due to a certain disease yields a measure with a simple and appealing interpretation. Recently, an overview of the methodology used for this goal has been published, and two measures have been proposed. In this work, we consider a third option that may be useful in settings in which the other two are inappropriate. In all three measures, the survival of the given dataset is compared to the expected survival in the general population which is calculated using external mortality tables. We thoroughly analyze the differences between the three measures, their assumptions, interpretation, and the corresponding estimators. The first measure is defined in a competing risk setting and assumes an excess hazard compared to the population, while the other two measures also allow estimation for groups that live better than the general population. In this case, the observed survival of the patients is compared to that in the population. The starting point of this comparison depends on whether the entry into the study is a hazard changing event (e.g., disease diagnosis or the age at which the inclusion criteria were met). Focusing on the newly defined life years difference measure, we study the estimation of the variance and consider the possible challenges (e.g., extrapolation) that occur in practice. We illustrate its use with a dataset of French Olympic athletes. Finally, an efficient R implementation has been developed for all three measures which make this work easily available to subsequent users.     

Robustness of the Standard Deviation and Other Measures of Dispersion

Contaminated observations (e.g. outliers) and heavy tails in the underlying distribution influence the standard deviation as a measure of dispersion even more than, e.g., the mean. Other measures of dispersion, namely absolute deviation, (α, β)-trimmed standard deviation, interquartile range and median absolute deviation (MAD) are defined for population, their properties — especially robustness — are explained and estimators are given, discussed and computed for a medical example. It is investigated how these measures of dispersion can be used to estimate a scale parameter of the underlying distribution more robustly. In numerical comparisons and simulations the robustness of these measures is demonstrated for heavy tailed distributions and contaminated distributions. Among other proposals it is recommended to use the (α, β)-trimmed standard deviation and transform it to the ordinary standard deviation for easier interpretation, if possible.     

Graphical representations and summary indicators to assess the performance of risk predictors

The availability of novel biomarkers in several branches of medicine opens room for refining prognosis by adding factors on top of those having an established role. It is accepted that the impact of novel factors should not rely solely on regression coefficients and their significance but also on predictive power measures, such as Brier score and ROC‐based quantities. However, novel factors that are promising at the exploratory stage often result in disappointingly low impact in the predictive power. This motivated the proposal of the net reclassification improvement and the integrated discrimination improvement, as direct measures of predictive power gain due to additional factors based on the concept of reclassification tables. These measures became extremely popular in cardiovascular disease and cancer applications, given the apparently easy interpretation. However, recent contributions in the biostatistical literature enlightened the tendency to indicate as advantageous models obtained by adding unrelated factors. These measures should not be used in practice. A further measure proposed a decade ago, the net benefit, is becoming a standard in assessing the consequences in terms of costs and benefits when using a risk predictor in practice for classification. This work reviews the conceptual formulations and interpretations of the available graphical methods and summary measures for evaluating risk predictor models. The aim is to provide guidance in the evaluation process that from the model development brings the risk predictor to be used in clinical practice for binary decision rules.     

Biological Traits Successfully Predict the Effects of Restoration Management on Macroinvertebrates in Shallow Softwater Lakes

Many shallow softwater lakes are being affected by eutrophication and acidification. In these small lakes decaying organic material usually accumulates and characteristic plant and animal species disappear. In many degraded lakes organic matter and macrophytes are being removed in order to restore the lakes to their original state. To assess the effects of restoration management in softwater lakes on aquatic macroinvertebrates, changes in the species assemblages were studied in four degraded lakes in the Netherlands undergoing restoration measures. The degraded lakes still harboured species characteristic of pristine softwaters. However, most of these species were not recorded after restoration measures were taken. Species’ densities declined dramatically during the execution of restoration measures. Swimming and abundant species were more likely to survive the restoration measures than other species. The first years after restoration, the lakes did not meet the habitat requirements for a number of species. Species requiring vegetation for ovipositioning, animal food sources and swards of vegetation as habitat declined. Because recolonization is expected to be restricted, it is recommended to ensure the survival of relict populations when taking measures to restore degraded softwater lakes. This may be achieved by phasing restoration measures in space and time, hereby minimizing mortality during the execution of restoration measures and by preserving habitat conditions required by characteristic species.     

Probing the limits to positional information

The reproducibility and precision of biological patterning is limited by the accuracy with which concentration profiles of morphogen molecules can be established and read out by their targets. We consider four measures of precision for the Bicoid morphogen in the Drosophila embryo: the concentration differences that distinguish neighboring cells, the limits set by the random arrival of Bicoid molecules at their targets (which depends on absolute concentration), the noise in readout of Bicoid by the activation of Hunchback, and the reproducibility of Bicoid concentration at corresponding positions in multiple embryos. We show, through a combination of different experiments, that all of these quantities are approximately 10%. This agreement among different measures of accuracy indicates that the embryo is not faced with noisy input signals and readout mechanisms; rather, the system exerts precise control over absolute concentrations and responds reliably to small concentration differences, approaching the limits set by basic physical principles.     

Seasonal Variation in the Capacity for Plant Trait Measures to Predict Grassland Carbon and Water Fluxes

There is a need for accurate predictions of ecosystem carbon (C) and water fluxes in field conditions. Previous research has shown that ecosystem properties can be predicted from community abundance-weighted means (CWM) of plant functional traits and measures of trait variability within a community (FDvar). The capacity for traits to predict carbon (C) and water fluxes, and the seasonal dependency of these trait-function relationships has not been fully explored. Here we measured daytime C and water fluxes over four seasons in grasslands of a range of successional ages in southern England. In a model selection procedure, we related these fluxes to environmental covariates and plant biomass measures before adding CWM and FDvar plant trait measures that were scaled up from measures of individual plants grown in greenhouse conditions. Models describing fluxes in periods of low biological activity contained few predictors, which were usually abiotic factors. In more biologically active periods, models contained more predictors, including plant trait measures. Field-based plant biomass measures were generally better predictors of fluxes than CWM and FDvar traits. However, when these measures were used in combination traits accounted for additional variation. Where traits were significant predictors their identity often reflected seasonal vegetation dynamics. These results suggest that database derived trait measures can improve the prediction of ecosystem C and water fluxes. Controlled studies and those involving more detailed flux measurements are required to validate and explore these findings, a worthwhile effort given the potential for using simple vegetation measures to help predict landscape-scale fluxes.     

Evaluation of Breathing Pattern: Comparison of a Manual Assessment of Respiratory Motion (MARM) and Respiratory Induction Plethysmography

Altered breathing pattern is an aspect of dysfunctional breathing but few standardised techniques exist to evaluate it. This study investigates a technique for evaluating and quantifying breathing pattern, called the Manual Assessment of Respiratory Motion (MARM) and compares it to measures performed with Respiratory Induction Plethysmography (RIP). About 12 subjects altered their breathing and posture while 2 examiners assessed their breathing using the MARM. Simultaneous measurements with RIP were taken. Inter-examiner agreement and agreement between MARM and RIP were assessed. The ability of the measurement methods to differentiate between diverse breathing and postural patterns was compared. High levels of agreement between examiners were found with the MARM for measures of the upper rib cage relative to lower rib cage/abdomen motion during breathing but not for measures of volume. The measures of upper rib cage dominance during breathing correlated with similar measures obtained from RIP. Both RIP and MARM measures methods were able to differentiate between abdominal and thoracic breathing patterns, but only MARM was able to differentiate between breathing changes occurring as result of slumped versus erect sitting posture. This study suggests that the MARM is a reliable clinical tool for assessing breathing pattern.     

Characterization of the expression ratio noise structure in high-density oligonucleotide arrays

Background

High-density oligonucleotide microarrays provide a powerful tool for assessing differential mRNA expression levels. Characterizing the noise resulting from the enzymatic and hybridization steps, called type I noise, is essential for attributing significance measures to the differential expression scores. We introduce scoring functions for expression ratios, and associated quality measures. Both the PM (Perfect Match) probes and PM-MM differentials (MM is the single MisMatch) are considered as raw intensities. We then characterize the log-ratio noise structure using robust estimates of their intensity dependent variance.

Results

We show the relationships between the obtained ratios and their quality measures. The complementarity of PM and PM-MM methods is emphasized by the probe sets signal to noise measures. Using a large set of replicate experiments, we demonstrate that the noise structure in the log-ratios very closely follows a local log-normal distribution for both the PM and PM-MM cases. Therefore, significance relative to the type I noise can be quantified reliably using the local STD. We discuss the intensity dependence of the STD and show that ratio scores >1.25 are significant in the mid- to high-intensity range.

Conclusions

The ratio noise structure inherent to high-density oligonucleotide arrays can be well described in terms of local log-normal ratio distributions with characteristic intensity dependence. Therefore, robust estimates of the local STD of these distributions provide a simple and powerful way for assessing significance (relative to type I noise) in differential gene expression. This approach will be helpful for improving the reliability of predictions from hybridization experiments in general.     

Healthcare Workers' Challenges in the Implementation of Tuberculosis Infection Prevention and Control Measures in Mozambique

Objective

Healthcare Workers (HCWs) have a higher frequency of TB exposure than the general population and have therefore an occupational TB risk that infection prevention and control (IPC) measures aim to reduce. HCWs are crucial in the implementation of these measures. The objective of the study was to investigate Mozambican HCWs'' perceptions of their occupational TB risk and the measures they report using to reduce this risk. In addition, we explored the challenges HCWs encounter while using these TBIPC measures.

Methods

Focus group discussion. Analysis according content method.

Participants

Four categories of HCWs: auxiliary workers, medical (doctors and clinical officers), nurses and TB program staff.

Results

HCWs are aware of their occupational TB risk and use various measures to reduce their risk of infection. HCWs find it challenging to employ measures that minimize such risks and a lack of clear guidelines contributes to these challenges. HCWs'' and patient behavior further complicate the use of TBIPC measures.

Conclusion

HCWs in Mozambique perceive a high occupational risk of TB infection. They report several challenges using measures to reduce this risk such as shortage of material, lack of clear guidelines, insufficient motivation and inadequate training. Robust training with motivational approaches, alongside supervision and support for HCWs could improve implementation of TBIPC measures. Healthcare management should address the areas for improvement that are beyond the individual HCW''s control.