Some factors affecting fertility in dry cows in southern Africa

No Abstrac

Variable selection for binary classification using error rate p-values applied to metabolomics data

BACKGROUND: Metabolomics datasets are often high-dimensional though only a limited number of variables are expected to be informative given a specific research question. The important task of selecting informative variables can therefore become complex. In this paper we look at discriminating between two groups. Two tasks need to be performed: (i) finding variables which differ between the two groups; and (ii) determining how the selected variables can be used to classify new subjects. We introduce an approach using minimum classification error rates as test statistics to find discriminatory and therefore informative variables. The thresholds resulting in the minimum error rates can be used to classify new subjects. This approach transforms error rates into p-values and is referred to as ERp. RESULTS: We show that non-parametric hypothesis testing, based on minimum classification error rates as test statistics, can find statistically significantly shifted variables. The discriminatory ability of variables becomes more apparent when error rates are evaluated based on their corresponding p-values, as relatively high error rates can still be statistically significant. ERp can handle unequal and small group sizes, as well as account for the cost of misclassification. ERp retains (if known) or reveals (if unknown) the shift direction, aiding in biological interpretation. The threshold resulting in the minimum error rate can immediately be used to classify new subjects. We use NMR generated metabolomics data to illustrate how ERp is able to discriminate subjects diagnosed with Mycobacterium tuberculosis infected meningitis from a control group. The list of discriminatory variables produced by ERp contains all biologically relevant variables with appropriate shift directions discussed in the original paper from which this data is taken. CONCLUSIONS: ERp performs variable selection and classification, is non-parametric and aids biological interpretation while handling unequal group sizes and misclassification costs. All this is achieved by a single approach which is easy to perform and interpret. ERp has the potential to address many other characteristics of metabolomics data. Future research aims to extend ERp to account for a large proportion of observations below the detection limit, as well as expand on interactions between variables

Metabolomics variable selection and classification in the presence of observations below the detection limit using an extension of ERp

BACKGROUND: ERp is a variable selection and classification method for metabolomics data. ERp uses minimized classification error rates, based on data from a control and experimental group, to test the null hypothesis of no difference between the distributions of variables over the two groups. If the associated p-values are significant they indicate discriminatory variables (i.e. informative metabolites). The p-values are calculated assuming a common continuous strictly increasing cumulative distribution under the null hypothesis. This assumption is violated when zero-valued observations can occur with positive probability, a characteristic of GC-MS metabolomics data, disqualifying ERp in this context. This paper extends ERp to address two sources of zero-valued observations: (i) zeros reflecting the complete absence of a metabolite from a sample (true zeros); and (ii) zeros reflecting a measurement below the detection limit. This is achieved by allowing the null cumulative distribution function to take the form of a mixture between a jump at zero and a continuous strictly increasing function. The extended ERp approach is referred to as XERp. RESULTS: XERp is no longer non-parametric, but its null distributions depend only on one parameter, the true proportion of zeros. Under the null hypothesis this parameter can be estimated by the proportion of zeros in the available data. XERp is shown to perform well with regard to bias and power. To demonstrate the utility of XERp, it is applied to GC-MS data from a metabolomics study on tuberculosis meningitis in infants and children. We find that XERp is able to provide an informative shortlist of discriminatory variables, while attaining satisfactory classification accuracy for new subjects in a leave-one-out cross-validation context. CONCLUSION: XERp takes into account the distributional structure of data with a probability mass at zero without requiring any knowledge of the detection limit of the metabolomics platform. XERp is able to identify variables that discriminate between two groups by simultaneously extracting information from the difference in the proportion of zeros and shifts in the distributions of the non-zero observations. XERp uses simple rules to classify new subjects and a weight pair to adjust for unequal sample sizes or sensitivity and specificity requirements

Reconstructing grazer assemblages for protected area restoration

Protected area management agencies often struggle to reliably reconstruct grazer assemblages due to a lack of historical distribution data for their regions. Wrong predictions of grazing assemblages could potentially affect biodiversity negatively. The objective of the study was to determine how well grazing herbivores have become established since introduction to the Mkambati Nature Reserve, South Africa, how this was influenced by facilitation and competition, and how indigenous grazer assemblages can best be predicted for effective ecological restoration. Population trends of several grazing species were investigated in in order to determine how well they have become established since introduction. Five different conceivable grazing assemblages reflecting a range of approaches that are commonly encountered during conservation planning and management decision making were assessed. Species packing was used to predict whether facilitation, competition or co-existence were more likely to occur, and the species packing of the different assemblages were assessed using ANCOVA. Reconstructing a species assemblage using biogeographic and biological information provides the opportunity for a grazer assemblage that allows for facilitatory effects, which in turn leads to an ecosystem that is able to maintain its grazer assemblage structure. The strength of this approach lies in the ability to overcome the problem of depauperate grazer assemblages, resulting from a lack of historical data, by using biogeographical and biological processes, to assist in more effectively reconstructing grazer assemblages. Adaptive management of grazer assemblage restoration through reintroduction, using this approach would further mitigate management risks

Dipotassium diaqua­bis(methyl­enedi­phospho­nato-κ2 O,O′)cobaltate(II)

In the title complex, K2[Co(CH4O6P2)2(H2O)2], the asymmetric unit contains two K+ cations and two half-anions in which the Co atoms lie on inversion centers. The CoII ions assume an octa­hedral CoO6 coordination geometry. In the crystal, a three-dimensional network is formed through O—H⋯O hydrogen-bond inter­actions as well as inter­molecular inter­actions between the K+ cations and neighbouring O atoms

Prospects for Observations of Pulsars and Pulsar Wind Nebulae with CTA

The last few years have seen a revolution in very-high gamma-ray astronomy (VHE; E>100 GeV) driven largely by a new generation of Cherenkov telescopes (namely the H.E.S.S. telescope array, the MAGIC and MAGIC-II large telescopes and the VERITAS telescope array). The Cherenkov Telescope Array (CTA) project foresees a factor of 5 to 10 improvement in sensitivity above 0.1 TeV, extending the accessible energy range to higher energies up to 100 TeV, in the Galactic cut-off regime, and down to a few tens GeV, covering the VHE photon spectrum with good energy and angular resolution. As a result of the fast development of the VHE field, the number of pulsar wind nebulae (PWNe) detected has increased from one PWN in the early '90s to more than two dozen firm candidates today. Also, the low energy threshold achieved and good sensitivity at TeV energies has resulted in the detection of pulsed emission from the Crab Pulsar (or its close environment) opening new and exiting expectations about the pulsed spectra of the high energy pulsars powering PWNe. Here we discuss the physics goals we aim to achieve with CTA on pulsar and PWNe physics evaluating the response of the instrument for different configurations.Comment: accepted for publication in Astroparticle Physic

Discovery of the Binary Pulsar PSR B1259-63 in Very-High-Energy Gamma Rays around Periastron with H.E.S.S

We report the discovery of very-high-energy (VHE) gamma-ray emission of the binary system PSR B1259-63/SS 2883 of a radio pulsar orbiting a massive, luminous Be star in a highly eccentric orbit. The observations around the 2004 periastron passage of the pulsar were performed with the four 13 m Cherenkov telescopes of the H.E.S.S. experiment, recently installed in Namibia and in full operation since December 2003. Between February and June 2004, a gamma-ray signal from the binary system was detected with a total significance above 13 sigma. The flux was found to vary significantly on timescales of days which makes PSR B1259-63 the first variable galactic source of VHE gamma-rays observed so far. Strong emission signals were observed in pre- and post-periastron phases with a flux minimum around periastron, followed by a gradual flux decrease in the months after. The measured time-averaged energy spectrum above a mean threshold energy of 380 GeV can be fitted by a simple power law F_0(E/1 TeV)^-Gamma with a photon index Gamma = 2.7+-0.2_stat+-0.2_sys and flux normalisation F_0 = (1.3+-0.1_stat+-0.3_sys) 10^-12 TeV^-1 cm^-2 s^-1. This detection of VHE gamma-rays provides unambiguous evidence for particle acceleration to multi-TeV energies in the binary system. In combination with coeval observations of the X-ray synchrotron emission by the RXTE and INTEGRAL instruments, and assuming the VHE gamma-ray emission to be produced by the inverse Compton mechanism, the magnetic field strength can be directly estimated to be of the order of 1 G.Comment: 10 pages, 8 figures, accepted in Astronomy and Astrophysics on 2 June 2005, replace: document unchanged, replaced author field in astro-ph entry - authors are all members of the H.E.S.S. collaboration and three additional authors (99+3, see document

Fire and herbivory drive fungal and bacterial communities through distinct above- and belowground mechanisms

Fire and herbivory are important natural disturbances in grassy biomes. Both drivers are likely to influence belowgroundmicrobial communities but no studies have unravelled the long-term impact of both fire and herbivory on bacterial and fungal communities. We hypothesized that soil bacterial communities change through disturbance-induced shifts in soil properties (e.g. pH, nutrients) while soil fungal communities change through vegetation modification (biomass and species composition). To test these ideas, we characterised soil physicochemical properties (pH, acidity, C, N, P and exchangeable cations content, texture, bulk density, moisture), plant species richness and biomass,microbial biomass and bacterial and fungal community composition and diversity (using 16S and ITS rRNA amplicon sequencing, respectively) in six long-term (18 to 70 years) ecological research sites in South African savanna and grassland ecosystems.We found that fire and herbivory regimes profoundly modified soil physico-chemical properties, plant species richness and standing biomass. In all sites, an increase in woody biomass (ranging from 12 to 50%) was observed when natural disturbances were excluded. The intensity and direction of changes in soil properties were highly dependent on the topo-pedo-climatic context. Overall, fire and herbivory shaped bacterial and fungal communities through distinct driving forces: edaphic properties (including Mg, pH, Ca) for bacteria, and vegetation (herbaceous biomass and woody cover) for fungi. Fire and herbivory explained on average 7.5 and 9.8% of the fungal community variability, respectively, compared to 6.0 and 5.6% for bacteria. The relatively small changes inmicrobial communities due to natural disturbance is in stark contrast to dramatic vegetation and edaphic changes and suggests that soilmicrobial communities, having evolved with disturbance, are resistant to change. This represents both a buffer to short-term anthropogenicinduced changes and a restoration challenge in the face of long-term changes.The National Research Foundation, South Africa and the Patterson Foundation via Conservation International, South Africa.http://www.elsevier.com/locate/scitotenvam2022BiochemistryGeneticsMicrobiology and Plant Patholog

Fire and herbivory drive fungal and bacterial communities through distinct above- and belowground mechanisms

Fire and herbivory are important natural disturbances in grassy biomes. Both drivers are likely to influence belowground microbial communities but no studies have unravelled the long-term impact of both fire and herbivory on bacterial and fungal communities. We hypothesized that soil bacterial communities change through disturbance-induced shifts in soil properties (e.g. pH, nutrients) while soil fungal communities change through vegetation modification (biomass and species composition). To test these ideas, we characterised soil physico-chemical properties (pH, acidity, C, N, P and exchangeable cations content, texture, bulk density, moisture), plant species richness and biomass, microbial biomass and bacterial and fungal community composition and diversity (using 16S and ITS rRNA amplicon sequencing, respectively) in six long-term (18 to 70 years) ecological research sites in South African savanna and grassland ecosystems. We found that fire and herbivory regimes profoundly modified soil physico-chemical properties, plant species richness and standing biomass. In all sites, an increase in woody biomass (ranging from 12 to 50%) was observed when natural disturbances were excluded. The intensity and direction of changes in soil properties were highly dependent on the topo-pedo-climatic context. Overall, fire and herbivory shaped bacterial and fungal communities through distinct driving forces: edaphic properties (including Mg, pH, Ca) for bacteria, and vegetation (herbaceous biomass and woody cover) for fungi. Fire and herbivory explained on average 7.5 and 9.8% of the fungal community variability, respectively, compared to 6.0 and 5.6% for bacteria. The relatively small changes in microbial communities due to natural disturbance is in stark contrast to dramatic vegetation and edaphic changes and suggests that soil microbial communities, having evolved with disturbance, are resistant to change. This represents both a buffer to short-term anthropogenic-induced changes and a restoration challenge in the face of long-term changes