Multidimensional analysis of human intestinal fluid composition

The oral administration of solid dosage forms is the commonest method to achieve systemic therapy and relies on the drug’s solubility in human intestinal fluid (HIF), a key factor that influences bioavailability and biopharmaceutical classification. However, HIF is difficult to obtain and is known to be variable, which has led to the development of a range of simulated intestinal fluid (SIF) systems to determine drug solubility in vitro. In this study we have applied a novel multidimensional approach to analyse and characterise HIF composition using a published data set in both fasted and fed states with a view to refining the existing SIF approaches. The data set provided 152 and 172 measurements of five variables (total bile salt, phospholipid, total free fatty acid, cholesterol and pH) in time-dependent HIF samples from 20 volunteers in the fasted and fed state, respectively. The variable data sets for both fasted state and fed state are complex, do not follow normal distributions but the amphiphilic variable concentrations are correlated. When plotted 2-dimensionally a generally ellipsoid shaped data cloud with a positive slope is revealed with boundaries that enclose published fasted or fed HIF compositions. The data cloud also encloses the majority of fasted state and fed state SIF recipes and illustrates that the structured nature of design of experiment (DoE) approaches does not optimally cover the variable space and may examine media compositions that are not biorelevant. A principal component analysis in either fasted or fed state in combination with fitting an ellipsoid shape to enclose the data results in 8 points that capture over 95% of the compositional variability of HIF. The variable’s average rate of concentration change in both fasted state and fed state over a short time scale (10 min) is zero and a Euclidean analysis highlights differences between the fasted and fed states and among individual volunteers. The results indicate that a 9-point DoE (8 + 1 central point) could be applied to investigate drug solubility in vitro and provide statistical solubility limits. In addition, a single point could provide a worst-case solubility measurement to define the lowest biopharmaceutical classification boundary or for use during drug development. This study has provided a novel description of HIF composition. The approach could be expanded in multiple ways by incorporation of further data sets to improve the statistical coverage or to cover specific patient groups (e.g., paediatric). Further development might also be possible to analyse information on the time dependent behaviour of HIF and to guide HIF sampling and analysis protocols

Electromagnetic field correlations near a surface with a nonlocal optical response

The coherence length of the thermal electromagnetic field near a planar surface has a minimum value related to the nonlocal dielectric response of the material. We perform two model calculations of the electric energy density and the field's degree of spatial coherence. Above a polar crystal, the lattice constant gives the minimum coherence length. It also gives the upper limit to the near field energy density, cutting off its $1/z^3$ divergence. Near an electron plasma described by the semiclassical Lindhard dielectric function, the corresponding length scale is fixed by plasma screening to the Thomas-Fermi length. The electron mean free path, however, sets a larger scale where significant deviations from the local description are visible.Comment: 15 pages, 7 figure files (.eps), \documentclass[global]{svjour}, accepted in special issue "Optics on the Nanoscale" (Applied Physics B, eds. V. Shalaev and F. Tr\"ager

Nest and foraging‐site selection in Yellowhammers Emberiza citrinella: implications for chick provisioning

Capsule Vegetation structure and invertebrate abundance interact to influence both foraging sites and nestling provisioning rate; when invertebrate availability is low, adults may take greater risks to provide food for their young. Aims To investigate nesting and foraging ecology in a declining farmland bird whose fledging success is influenced by the availability of invertebrate prey suitable for feeding to offspring, and where perceived predation risk during foraging can be mediated by vegetation structure. Methods Provisioning rates of adult Yellowhammers feeding nestlings were measured at nests on arable farmland. Foraging sites were compared with control sites of both the same and different microhabitats; provisioning rate was related to habitat features of foraging-sites. Results Foraging sites had low vegetation density, probably enhancing detection of predators, or high invertebrate abundance at high vegetation density. Parental provisioning rate decreased with increasing vegetation cover at foraging sites with high invertebrate abundance; conversely, where invertebrate abundance was low, provisioning rate increased with increasing vegetation cover. Conclusions Vegetation structure at foraging sites suggests that a trade-off between predator detection and prey availability influences foraging site selection in Yellowhammers. Associations between parental provisioning rate and vegetation variables suggest that where invertebrate abundance is high birds increase time spent scanning for predators at higher vegetation densities; however, when prey are scarce, adults may take more risks to provide food for their young

Small-scale solar magnetic fields

As we resolve ever smaller structures in the solar atmosphere, it has become clear that magnetism is an important component of those small structures. Small-scale magnetism holds the key to many poorly understood facets of solar magnetism on all scales, such as the existence of a local dynamo, chromospheric heating, and flux emergence, to name a few. Here, we review our knowledge of small-scale photospheric fields, with particular emphasis on quiet-sun field, and discuss the implications of several results obtained recently using new instruments, as well as future prospects in this field of research.Comment: 43 pages, 18 figure

Spectroscopic Coronal Observations during the Total Solar Eclipse of 11 July 2010

The flash spectrum of the solar chromosphere and corona was measured with a slitless spectrograph before, after, and during the totality of the solar eclipse, of 11 July 2010, at Easter Island, Chile. This eclipse took place at the beginning of the Solar Cycle 24, after an extended minimum of solar activity. The spectra taken during the eclipse show a different intensity ratio of the red and green coronal lines compared with those taken during the total solar eclipse of 1 August 2008, which took place towards the end of the Solar Cycle 23. The characteristic coronal forbidden emission line of forbidden Fe XIV (5303 {\AA}) was observed on the east and west solar limbs in four areas relatively symmetrically located with respect to the solar rotation axis. Subtraction of the continuum flash-spectrum background led to the identification of several extremely weak emission lines, including forbidden Ca XV (5694 {\AA}), which is normally detected only in regions of very high excitation, e.g., during flares or above large sunspots. The height of the chromosphere was measured spectrophotometrically, using spectral lines from light elements and compared with the equivalent height of the lower chromosphere measured using spectral lines from heavy elements.Comment: 14 pages, 8 figures, 1 table; Solar Physics, 2012, Februar

Scaling ozone responses of forest trees to the ecosystem level in a changing climate

Many uncertainties remain regarding how climate change will alter the structure and function of forest ecosystems. At the Aspen FACE experiment in northern Wisconsin, we are attempting to understand how an aspen/birch/maple forest ecosystem responds to long-term exposure to elevated carbon dioxide (CO 2 ) and ozone (O 3 ), alone and in combination, from establishment onward. We examine how O 3 affects the flow of carbon through the ecosystem from the leaf level through to the roots and into the soil micro-organisms in present and future atmospheric CO 2 conditions. We provide evidence of adverse effects of O 3 , with or without co-occurring elevated CO 2 , that cascade through the entire ecosystem impacting complex trophic interactions and food webs on all three species in the study: trembling aspen ( Populus tremuloides Michx . ), paper birch ( Betula papyrifera Marsh), and sugar maple ( Acer saccharum Marsh). Interestingly, the negative effect of O 3 on the growth of sugar maple did not become evident until 3 years into the study. The negative effect of O 3 effect was most noticeable on paper birch trees growing under elevated CO 2 . Our results demonstrate the importance of long-term studies to detect subtle effects of atmospheric change and of the need for studies of interacting stresses whose responses could not be predicted by studies of single factors. In biologically complex forest ecosystems, effects at one scale can be very different from those at another scale. For scaling purposes, then, linking process with canopy level models is essential if O 3 impacts are to be accurately predicted. Finally, we describe how outputs from our long-term multispecies Aspen FACE experiment are being used to develop simple, coupled models to estimate productivity gain/loss from changing O 3 .Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72464/1/j.1365-3040.2005.01362.x.pd

Clustering Algorithms: Their Application to Gene Expression Data

Gene expression data hide vital information required to understand the biological process that takes place in a particular organism in relation to its environment. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks and the volume of genes present increase the challenges of comprehending and interpretation of the resulting mass of data, which consists of millions of measurements; these data also inhibit vagueness, imprecision, and noise. Therefore, the use of clustering techniques is a first step toward addressing these challenges, which is essential in the data mining process to reveal natural structures and iden-tify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent in gene expression data, understanding gene functions, cellular processes, and subtypes of cells, mining useful information from noisy data, and understanding gene regulation. The other benefit of clustering gene expression data is the identification of homology, which is very important in vaccine design. This review examines the various clustering algorithms applicable to the gene expression data in order to discover and provide useful knowledge of the appropriate clustering technique that will guarantee stability and high degree of accuracy in its analysis procedure