Stable isotope probing analysis of the influence of liming on root exudate utilization by soil microorganisms

Rhizosphere microorganisms play an important role in soil carbon flow, through turnover of root exudates, but there is little information on which organisms are actively involved or on the influence of environmental conditions on active communities. In this study, a (CO2)-C-13 pulse labelling field experiment was performed in an upland grassland soil, followed by RNA-stable isotope probing (SIP) analysis, to determine the effect of liming on the structure of the rhizosphere microbial community metabolizing root exudates. The lower limit of detection for SIP was determined in soil samples inoculated with a range of concentrations of C-13-labelled Pseudomonas fluorescens and was found to lie between 10(5) and 10(6) cells per gram of soil. The technique was capable of detecting microbial communities actively assimilating root exudates derived from recent photo-assimilate in the field. Denaturing gradient gel electrophoresis (DGGE) profiles of bacteria, archaea and fungi derived from fractions obtained from caesium trifluoroacetate (CsTFA) density gradient ultracentrifugation indicated that active communities in limed soils were more complex than those in unlimed soils and were more active in utilization of recently exuded C-13 compounds. In limed soils, the majority of the community detected by standard RNA-DGGE analysis appeared to be utilizing root exudates. In unlimed soils, DGGE profiles from C-12 and C-13 RNA fractions differed, suggesting that a proportion of the active community was utilizing other sources of organic carbon. These differences may reflect differences in the amount of root exudation under the different conditions.

A Bayesian framework for age modeling of radiocarbon-dated peat deposits: Case studies from the Netherlands

Recently, Bayesian statistical software has been developed for age-depth modeling (wiggle-match dating) of sequences of densely spaced radiocarbon dates from peat cores. The method is described in non-statistical terms, and is compared with an alternative method of chronological ordering of 14C dates. Case studies include the dating of the start of agriculture in the northeastern part of the Netherlands, and of a possible Hekla-3 tephra layer in the same country. We discuss future enhancements in Bayesian age modeling.

Nebular emission-line profiles of Type Ib/c supernovae - Probing the ejecta asphericity

In order to assess qualitatively the ejecta geometry of stripped-envelope core-collapse supernovae (SNe), we investigate 98 late-time spectra of 39 objects, many of them previously unpublished. We perform a Gauss-fitting of the [O ] ??6300, 6364 feature in all spectra, with the position, full width at half maximum and intensity of the ?6300 Gaussian as free parameters, and the ?6364 Gaussian added appropriately to account for the doublet nature of the [O ] feature. On the basis of the best-fitting parameters, the objects are organized into morphological classes, and we conclude that at least half of all Type Ib/c SNe must be aspherical. Bipolar jet models do not seem to be universally applicable, as we find too few symmetric double-peaked [O ] profiles. In some objects, the [O ] line exhibits a variety of shifted secondary peaks or shoulders, interpreted as blobs of matter ejected at high velocity and possibly accompanied by neutron-star kicks to assure momentum conservation. At phases earlier than ~200 d, a systematic blueshift of the [O ] ??6300, 6364 line centroids can be discerned. Residual opacity provides the most convincing explanation of this phenomenon, photons emitted on the rear side of the SN being scattered or absorbed on their way through the ejecta. Once modified to account for the doublet nature of the oxygen feature, the profile of Mg i] ?4571 at sufficiently late phases generally resembles that of [O ] ??6300, 6364, suggesting negligible contamination from other lines and confirming that O and Mg are similarly distributed within the ejecta. © 2009 RAS.

First-Order Reversal Curve Probing of Spatially Resolved Polarization Switching Dynamics in Ferroelectric Nanocapacitors

Spatially resolved polarization switching In ferroelectric nanocapacitors was studied on the sub-25 nm scale using the first-order reversal curve (FORC) method. The chosen capacitor geometry allows both high-veracity observation of the domain structure and mapping of polarization switching in a uniform field, synergistically combining microstructural observations and probing of uniform-field polarization responses as relevant to device operation. A classical Kolmogorov-Avrami-Ishibashi model has been adapted to the voltage domain, and the individual switching dynamics of the FORC response curves are well approximated by the adapted model. The comparison with microstructures suggests a strong spatial variability of the switching dynamics inside the nanocapacitors.

Probing Ferroelectrics Using Optical Second Harmonic Generation

Nonlinear optics is an essential component of modern laser systems and optoelectronic devices. It has also emerged as an important tool in probing the electronic, vibrational, magnetic, and crystallographic structure of materials ranging from oxides and metals, to polymers and biological samples. This review focuses on the specific technique of optical second harmonic generation (SHG), and its application in probing ferroelectric complex oxide crystals and thin films. As the dominant SHG interaction mechanism exists only in materials that lack inversion symmetry, SHG is a sensitive probe of broken inversion symmetry, and thus also of bulk polar phenomena in materials. By performing in-situ SHG polarimetry experiments in different experimental conditions such as sample orientation, applied electric field, and temperature, one can probe ferroelectric hysteresis loops and phase transitions. Careful modeling of the polarimetry data allows for the determination of the point group symmetry of the crystal. In epitaxial thin films with a two-dimensional arrangement of well-defined domain orientations, one can extract information about intrinsic material properties such as nonlinear coefficients, as well as microstructural information such as the local statistics of the different domain variants being probed. This review presents several detailed examples of ferroelectric systems where such measurements and modeling are performed. The use of SHG microscopic imaging is discussed, and its ability to reveal domain structures and phases not normally visible with linear optics is illustrated.

Probing myo-inositol 1-phosphate synthase with multisubstrate adducts

The synthesis of a series of carbohydrate-nucleotide hybrids, designed to be multisubstrate adducts mimicking myo-inositol 1-phosphate synthase first oxidative transition state, is reported. Their ability to inhibit the synthase has been assessed and results have been rationalised computationally to estimate their likely binding mode.

PROSTATIC INTRAEPITHELIAL NEOPLASIA (PIN) - PERFORMANCE OF BAYESIAN BELIEF NETWORK FOR DIAGNOSIS AND GRADING

Prostatic intraepithelial neoplasia (PIN) diagnosis and grading are affected by uncertainties which arise from the fact that almost all knowledge of PIN histopathology is expressed in concepts, descriptive linguistic terms, and words. A Bayesian belief network (BBN) was therefore used to reduce the problem of uncertainty in diagnostic clue assessment, while still considering the dependences between elements in the reasoning sequence. A shallow network was used with an open-tree topology, with eight first-level descendant nodes for the diagnostic clues (evidence nodes), each independently linked by a conditional probability matrix to a root node containing the diagnostic alternatives (decision node). One of the evidence nodes was based on the tissue architecture and the others were based on cell features. The system was designed to be interactive, in that the histopathologist entered evidence into the network in the form of likelihood ratios for outcomes at each evidence node. The efficiency of the network was tested on a series of 110 prostate specimens, subdivided as follows: 22 cases of non-neoplastic prostate or benign prostatic tissue (NP), 22 PINs of low grade (PINlow), 22 PINs of high grade (PINhigh), 22 prostatic adenocarcinomas with cribriform pattern (PACcri), and 22 prostatic adenocarcinomas with large acinar pattern (PAClgac). The results obtained in the benign and malignant categories showed that the belief for the diagnostic alternatives is very high, the values being in general more than 0.8 and often close to 1.0. When considering the PIN lesions, the network classified and graded most of the cases with high certainty. However, there were some cases which showed values less than 0.8 (13 cases out of 44), thus indicating that there are situations in which the feature changes are intermediate between contiguous categories or grades. Discrepancy between morphological grading and the BBN results was observed in four out of 44 PIN cases: one PINlow was classified as PINhigh and three PINhigh were classified as PINlow. In conclusion, the network can grade PlN lesions and differentiate them from other prostate lesions with certainty. In particular, it offers a descriptive classifier which is readily implemented and which allows the use of linguistic, fuzzy variables.

EXPERT-SYSTEM SUPPORT USING BAYESIAN BELIEF NETWORKS IN THE DIAGNOSIS OF FINE-NEEDLE ASPIRATION BIOPSY SPECIMENS OF THE BREAST

Aim-To develop an expert system model for the diagnosis of fine needle aspiration cytology (FNAC) of the breast.

Methods-Knowledge and uncertainty were represented in the form of a Bayesian belief network which permitted the combination of diagnostic evidence in a cumulative manner and provided a final probability for the possible diagnostic outcomes. The network comprised 10 cytological features (evidence nodes), each independently linked to the diagnosis (decision node) by a conditional probability matrix. The system was designed to be interactive in that the cytopathologist entered evidence into the network in the form of likelihood ratios for the outcomes at each evidence node.

Results-The efficiency of the network was tested on a series of 40 breast FNAC specimens. The highest diagnostic probability provided by the network agreed with the cytopathologists' diagnosis in 100% of cases for the assessment of discrete, benign, and malignant aspirates. A typical probably benign cases were given probabilities in favour of a benign diagnosis. Suspicious cases tended to have similar probabilities for both diagnostic outcomes and so, correctly, could not be assigned as benign or malignant. A closer examination of cumulative belief graphs for the diagnostic sequence of each case provided insight into the diagnostic process, and quantitative data which improved the identification of suspicious cases.

Conclusion-The further development of such a system will have three important roles in breast cytodiagnosis: (1) to aid the cytologist in making a more consistent and objective diagnosis; (2) to provide a teaching tool on breast cytological diagnosis for the non-expert; and (3) it is the first stage in the development of a system capable of automated diagnosis through the use of expert system machine vision.

Probing chemistry and kinetics of reactions in heterogeneous catalysts

Using benzene hydrogenation over Pt/SiO2 as an industrially-relevant example, we show that state-of-the-art neutron total scattering methods spanning a wide Q-range now permit relevant time-resolved catalytic chemistry to be probed directly in situ within the pore of the catalyst. The method gives access to the reaction rates on both nanometric and atomic length scales, whilst simultaneously providing an atomistic structural viewpoint on the reaction mechanism itself.