In situ degradability of dry matter and neutral-detergent fibre of thorn scrubland forage consumed by goats in the semi-arid region of north Mexico

Three goats provided with oesophageal and ruminal cannulae were used to determine variations in dry matter (DM) and neutral-detergent fibre (NDF) degradability of the forage consumed when grazing thorn scrubland in the semi-arid region of north Mexico, during two consecutive dry and wet periods. Ingesta samples were incubated intraruminally, the data were fitted to the exponential equation P = a + b (1-e(-ct)) and statistically analysed using a randomized-block design. Organic matter and crude protein (CP) contents were higher (P < 0.05) in the wet seasons. Values of NDF were similar in dry and wet season of both years whereas higher numerical values of acid-detergent fibre (ADF), lignin and cellulose were registered in the dry seasons. DM and NDF degradabilities after 24 and 48 h of ruminal incubation were higher (P < 0.05) in the wet seasons. Higher values (P < 0.05) in DM and NDF bag losses at zero time (A fraction) were registered in the two wet seasons. The insoluble but fermentable DM and NDF (B fractions) were higher (P < 0.05) in the 1999 wet season and variable in the rest of the studied period. Numerically higher values of DM and NDF c fraction were found in wet periods, whereas DM and NDF potential degradabilities were higher (P < 0.05) in the wet season in 1999 and similar across seasons in 2000. Lowest (P < 0.05) contents of CP in grazed forage, DM and NDF degradabilities after 48 h of ruminal incubation, and A, and B, and c fractions were observed in the dry seasons. Thus, these results may be related to both the lower feeding value of forage consumed by the animals and lower performance of livestock during this period. Then, the DM and NDF degradability after 48 h, together with the insoluble but fermentable matter and the c fraction permit the nutritive value of the forage consumed by grazing goats to be accurately described.

Landscape effects on crop pollination services: are there general patterns?

Pollination by bees and other animals increases the size, quality, or stability of harvests for 70% of leading global crops. Because native species pollinate many of these crops effectively, conserving habitats for wild pollinators within agricultural landscapes can help maintain pollination services. Using hierarchical Bayesian techniques, we synthesize the results of 23 studies - representing 16 crops on five continents - to estimate the general relationship between pollination services and distance from natural or semi-natural habitats. We find strong exponential declines in both pollinator richness and native visitation rate. Visitation rate declines more steeply, dropping to half of its maximum at 0.6 km from natural habitat, compared to 1.5 km for richness. Evidence of general decline in fruit and seed set - variables that directly affect yields - is less clear. Visitation rate drops more steeply in tropical compared with temperate regions, and slightly more steeply for social compared with solitary bees. Tropical crops pollinated primarily by social bees may therefore be most susceptible to pollination failure from habitat loss. Quantifying these general relationships can help predict consequences of land use change on pollinator communities and crop productivity, and can inform landscape conservation efforts that balance the needs of native species and people.

Study of the lactation curve in dairy cattle on farms in Central Mexico

Accurate knowledge of lactation curves has an important relevance to management and research of dairy production systems. A number of equations have been proposed to describe the lactation curve, the most widely applied being the gamma equation. The objective of this work was to compare and evaluate candidate functions for their predictive ability in describing lactation curves from central Mexican dairy cows reared under 2 contrasting management systems. Five equations were considered: Gaines ( exponential decay), Wood ( gamma equation), Rook ( Michaelis-Menten x exponential), and 2 more mechanistic ones (Dijkstra and Pollott). A database consisting of 701 and 1283 records of cows in small-scale and intensive systems, respectively, was used in the analysis. Before analysis, the database was divided into 6 groups representing first, second, and third and higher parity cows in both systems. In all cases except second and above parity cows in small-scale systems, all models improved on the Gaines equation. The Wood equation explained much of the variation, but its parameters do not have direct biological interpretation. Although the Rook equation fitted the data well, some of the parameter estimates were not significant. The Dijkstra equation consistently gave better predictions, and its parameters were usually statistically significant and lend themselves to physiological interpretation. As such, the differences between systems and parity could be explained due to variations in theoretical initial milk production at parturition, specific rates of secretory cell proliferation and death, and rate of decay, all of which are parameters in the model. The Pollott equation, although containing the most biology, was found to be over-parameterized and resulted in nonsignificant parameter estimates. For central Mexican dairy cows, the Dijkstra equation was the best option to use in describing the lactation curve.

Modelling heterotachy in phylogenetic inference by reversible-jump Markov chain Monte Carlo

The rate at which a given site in a gene sequence alignment evolves over time may vary. This phenomenon-known as heterotachy-can bias or distort phylogenetic trees inferred from models of sequence evolution that assume rates of evolution are constant. Here, we describe a phylogenetic mixture model designed to accommodate heterotachy. The method sums the likelihood of the data at each site over more than one set of branch lengths on the same tree topology. A branch-length set that is best for one site may differ from the branch-length set that is best for some other site, thereby allowing different sites to have different rates of change throughout the tree. Because rate variation may not be present in all branches, we use a reversible-jump Markov chain Monte Carlo algorithm to identify those branches in which reliable amounts of heterotachy occur. We implement the method in combination with our 'pattern-heterogeneity' mixture model, applying it to simulated data and five published datasets. We find that complex evolutionary signals of heterotachy are routinely present over and above variation in the rate or pattern of evolution across sites, that the reversible-jump method requires far fewer parameters than conventional mixture models to describe it, and serves to identify the regions of the tree in which heterotachy is most pronounced. The reversible-jump procedure also removes the need for a posteriori tests of 'significance' such as the Akaike or Bayesian information criterion tests, or Bayes factors. Heterotachy has important consequences for the correct reconstruction of phylogenies as well as for tests of hypotheses that rely on accurate branch-length information. These include molecular clocks, analyses of tempo and mode of evolution, comparative studies and ancestral state reconstruction. The model is available from the authors' website, and can be used for the analysis of both nucleotide and morphological data.

Statistical evaluation of alternative models of human evolution

An appropriate model of recent human evolution is not only important to understand our own history, but it is necessary to disentangle the effects of demography and selection on genome diversity. Although most genetic data support the view that our species originated recently in Africa, it is still unclear if it completely replaced former members of the Homo genus, or if some interbreeding occurred during its range expansion. Several scenarios of modern human evolution have been proposed on the basis of molecular and paleontological data, but their likelihood has never been statistically assessed. Using DNA data from 50 nuclear loci sequenced in African, Asian and Native American samples, we show here by extensive simulations that a simple African replacement model with exponential growth has a higher probability (78%) as compared with alternative multiregional evolution or assimilation scenarios. A Bayesian analysis of the data under this best supported model points to an origin of our species approximate to 141 thousand years ago (Kya), an exit out-of-Africa approximate to 51 Kya, and a recent colonization of the Americas approximate to 10.5 Kya. We also find that the African replacement model explains not only the shallow ancestry of mtDNA or Y-chromosomes but also the occurrence of deep lineages at some autosomal loci, which has been formerly interpreted as a sign of interbreeding with Homo erectus.

The population genetic structure of clonal organisms generated by exponentially bounded and fat-tailed dispersal

Long distance dispersal (LDD) plays an important role in many population processes like colonization, range expansion, and epidemics. LDD of small particles like fungal spores is often a result of turbulent wind dispersal and is best described by functions with power-law behavior in the tails ("fat tailed"). The influence of fat-tailed LDD on population genetic structure is reported in this article. In computer simulations, the population structure generated by power-law dispersal with exponents in the range of -2 to -1, in distinct contrast to that generated by exponential dispersal, has a fractal structure. As the power-law exponent becomes smaller, the distribution of individual genotypes becomes more self-similar at different scales. Common statistics like G(ST) are not well suited to summarizing differences between the population genetic structures. Instead, fractal and self-similarity statistics demonstrated differences in structure arising from fat-tailed and exponential dispersal. When dispersal is fat tailed, a log-log plot of the Simpson index against distance between subpopulations has an approximately constant gradient over a large range of spatial scales. The fractal dimension D-2 is linearly inversely related to the power-law exponent, with a slope of similar to -2. In a large simulation arena, fat-tailed LDD allows colonization of the entire space by all genotypes whereas exponentially bounded dispersal eventually confines all descendants of a single clonal lineage to a relatively small area.

Assembling spatially explicit landscape models of pollen and spore dispersal by wind for risk assessment

Models of windblown pollen or spore movement are required to predict gene flow from genetically modified (GM) crops and the spread of fungal diseases. We suggest a simple form for a function describing the distance moved by a pollen grain or fungal spore, for use in generic models of dispersal. The function has power-law behaviour over sub-continental distances. We show that air-borne dispersal of rapeseed pollen in two experiments was inconsistent with an exponential model, but was fitted by power-law models, implying a large contribution from distant fields to the catches observed. After allowance for this 'background' by applying Fourier transforms to deconvolve the mixture of distant and local sources, the data were best fit by power-laws with exponents between 1.5 and 2. We also demonstrate that for a simple model of area sources, the median dispersal distance is a function of field radius and that measurement from the source edge can be misleading. Using an inverse-square dispersal distribution deduced from the experimental data and the distribution of rapeseed fields deduced by remote sensing, we successfully predict observed rapeseed pollen density in the city centres of Derby and Leicester (UK).

Estimation of population growth or decline in genetically monitored populations

This article introduces a new general method for genealogical inference that samples independent genealogical histories using importance sampling (IS) and then samples other parameters with Markov chain Monte Carlo (MCMC). It is then possible to more easily utilize the advantages of importance sampling in a fully Bayesian framework. The method is applied to the problem of estimating recent changes in effective population size from temporally spaced gene frequency data. The method gives the posterior distribution of effective population size at the time of the oldest sample and at the time of the most recent sample, assuming a model of exponential growth or decline during the interval. The effect of changes in number of alleles, number of loci, and sample size on the accuracy of the method is described using test simulations, and it is concluded that these have an approximately equivalent effect. The method is used on three example data sets and problems in interpreting the posterior densities are highlighted and discussed.

Likelihood-based estimation of microsatellite mutation rates

Microsatellites are widely used in genetic analyses, many of which require reliable estimates of microsatellite mutation rates, yet the factors determining mutation rates are uncertain. The most straightforward and conclusive method by which to study mutation is direct observation of allele transmissions in parent-child pairs, and studies of this type suggest a positive, possibly exponential, relationship between mutation rate and allele size, together with a bias toward length increase. Except for microsatellites on the Y chromosome, however, previous analyses have not made full use of available data and may have introduced bias: mutations have been identified only where child genotypes could not be generated by transmission from parents' genotypes, so that the probability that a mutation is detected depends on the distribution of allele lengths and varies with allele length. We introduce a likelihood-based approach that has two key advantages over existing methods. First, we can make formal comparisons between competing models of microsatellite evolution; second, we obtain asymptotically unbiased and efficient parameter estimates. Application to data composed of 118,866 parent-offspring transmissions of AC microsatellites supports the hypothesis that mutation rate increases exponentially with microsatellite length, with a suggestion that contractions become more likely than expansions as length increases. This would lead to a stationary distribution for allele length maintained by mutational balance. There is no evidence that contractions and expansions differ in their step size distributions.

Ribosome modulation factor protects Escherichia coli during heat stress, but this may not be dependent on ribosome dimerisation

The role of ribosome modulation factor (RMF) in protecting heat-stressed Escherichia coli cells was identified by the observation that cultures of a mutant strain lacking functional RMF (HMY15) were highly heat sensitive in stationary phase compared to those of the parent strain (W3110). No difference in heat sensitivity was observed between these strains in exponential phase, during which RMF is not synthesised. Studies by differential scanning calorimetry demonstrated that the ribosomes of stationary-phase cultures of the mutant strain had lower thermal stability than those of the parent strain in stationary phase, or exponential-phase ribosomes. More rapid breakdown of ribosomes in the mutant strain during heating was confirmed by rRNA analysis and sucrose density gradient centrifugation. Analyses of ribosome composition showed that the 100S dimers dissociated more rapidly during heating than 70S particles. While ribosome dimerisation is a consequence of the conformational changes caused by RMF binding, it may not therefore be essential for RMF-mediated ribosome stabilisation.

The influence of ribosome modulation factor on the survival of stationary-phase Escherichia coli during acid stress

Ribosome modulation factor (RMF) was shown to have an influence on the survival of Escherichia coli under acid stress during stationary phase, since the viability of cultures of a mutant strain lacking functional RMF decreased more rapidly than that of the parent strain at pH 3. Loss of ribosomes was observed in both strains when exposed to low pH, although this occurred at a higher rate in the RMF-deficient mutant strain, which also suffered from higher levels of rRNA degradation. It was concluded that the action of RMF in limiting the damage to rRNA contributed to the protection of E coli under acid stress. Expression of the rmf gene was lower during stationary phase after growth in acidified media compared to media containing no added acid, and the increased rmf expression associated with transition from exponential phase to stationary phase was much reduced in acidified media. It was demonstrated that RMF was not involved in the stationary-phase acid-tolerance response in E coli by which growth under acidic conditions confers protection against subsequent acid shock. This response was sufficient to overcome the increased vulnerability of the RMF-deficient mutant strain to acid stress at pH values between 6.5 and 5.5.

The activity of ribosome modulation factor during growth of Escherichia coli under acidic conditions

Expression of the gene encoding ribosome modulation factor (RMF), as measured using an rmf-lacZ gene fusion, increased with decreasing pH in exponential phase cultures of Escherichia coli. Expression was inversely proportional to the growth rate and independent of the acidifying agent used and it was concluded that expression of rmf was growth rate controlled in exponential phase under acid conditions. Increased rmf expression during exponential phase was not accompanied by the formation of ribosome dimers as occurs during stationary phase. Nor did it appear to have a significant effect on cell survival under acid stress since the vulnerability of an RMF-deficient mutant strain was similar to that of the parent strain. Ribosome degradation was increased in the mutant strain compared to the parent strain at pH 3.75. Also, the peptide elongation rate was reduced in the mutant strain but not the parent during growth under acid conditions. It is speculated that the function of RMF during stress-induced reduction in growth rate is two-fold: firstly to prevent reduced elongation efficiency by inactivating surplus ribosomes and thus limiting competition for available protein synthesis factors, and secondly to protect inactivated ribosomes from degradation.

An RNA molecule that specifically inhibits G-protein-coupled receptor kinase 2 in vitro

G-protein-coupled receptors are desensitized by a two-step process. In a first step, G-protein-coupled receptor kinases (GRKs) phosphorylate agonist-activated receptors that subsequently bind to a second class of proteins, the arrestins. GRKs can be classified into three subfamilies, which have been implicated in various diseases. The physiological role(s) of GRKs have been difficult to study as selective inhibitors are not available. We have used SELEX (systematic evolution of ligands by exponential enrichment) to develop RNA aptamers that potently and selectively inhibit GRK2. This process has yielded an aptamer, C13, which bound to GRK2 with a high affinity and inhibited GRK2-catalyzed rhodopsin phosphorylation with an IC50 of 4.1 nM. Phosphorylation of rhodopsin catalyzed by GRK5 was also inhibited, albeit with 20-fold lower potency (IC50 of 79 nM). Furthermore, C13 reveals significant specificity, since almost no inhibitory activity was detectable testing it against a panel of 14 other kinases. The aptamer is two orders of magnitude more potent than the best GRK2 inhibitors described previously and shows high selectivity for the GRK family of protein kinases.

Cannabinoid influences on palatability: microstructural analysis of sucrose drinking after Delta(9)-tetrahydrocannabinol, anandamide, 2-arachidonoyl glycerol and SR141716

Rationale: Central cannabinoid systems have been implicated in appetite control through the respective hyperphagic and anorectic actions of CB1 agonists and antagonists. The motivational changes underlying these actions remain to be determined, but may involve alterations to food palatability. Objectives: The mode of action of cannabinoids on ingestion was investigated by examining the effects of exogenous and endogenous agonists, and a selective CB1 receptor antagonist, on licking microstructure in rats ingesting a palatable sucrose solution. Methods: Microstructural analyses of licking for a 10% sucrose solution was performed over a range of agonist and antagonist doses administered to non-deprived, male Lister hooded rats. Results: Delta(9)-tetrahydrocannabinol (0.5, 1 and 3 mg/kg) and anandamide (1 mg/kg and 3 mg/kg) significantly increased total number of licks. This was primarily due to an increase in bout duration rather than bout number. There was a nonsignificant increase in total licks following administration of 2-arachidonoyl glycerol (0.2, 1.0 and 2.0 mg/kg), whereas administration of the CB1 antagonist SR141716 (1 mg/kg and 3 mg/kg) significantly decreased total licks. All drugs, with the exception of anandamide, significantly decreased the intra-bout lick rate. An exponential function fitted to the cumulative lick rate curves for each drug revealed that all compounds altered the asymptote of this function without having any marked effects on the exponent. Conclusions: These data are consistent with endocannabinoid involvement in the mediation of food palatability.

Perspex machine IX: transreal analysis

We introduce transreal analysis as a generalisation of real analysis. We find that the generalisation of the real exponential and logarithmic functions is well defined for all transreal numbers. Hence, we derive well defined values of all transreal powers of all non-negative transreal numbers. In particular, we find a well defined value for zero to the power of zero. We also note that the computation of products via the transreal logarithm is identical to the transreal product, as expected. We then generalise all of the common, real, trigonometric functions to transreal functions and show that transreal (sin x)/x is well defined everywhere. This raises the possibility that transreal analysis is total, in other words, that every function and every limit is everywhere well defined. If so, transreal analysis should be an adequate mathematical basis for analysing the perspex machine - a theoretical, super-Turing machine that operates on a total geometry. We go on to dispel all of the standard counter "proofs" that purport to show that division by zero is impossible. This is done simply by carrying the proof through in transreal arithmetic or transreal analysis. We find that either the supposed counter proof has no content or else that it supports the contention that division by zero is possible. The supposed counter proofs rely on extending the standard systems in arbitrary and inconsistent ways and then showing, tautologously, that the chosen extensions are not consistent. This shows only that the chosen extensions are inconsistent and does not bear on the question of whether division by zero is logically possible. By contrast, transreal arithmetic is total and consistent so it defeats any possible "straw man" argument. Finally, we show how to arrange that a function has finite or else unmeasurable (nullity) values, but no infinite values. This arithmetical arrangement might prove useful in mathematical physics because it outlaws naked singularities in all equations.