Comparing ecosystem and soil respiration : Review and key challenges of tower-based and soil measurements

The net ecosystem exchange (NEE) is the difference between ecosystem CO2 assimilation and CO2 losses to the atmosphere. Ecosystem respiration (R-eco), the efflux of CO2 from the ecosystem to the atmosphere, includes the soil-to-atmosphere carbon flux (i.e., soil respiration; R-soil) and aboveground plant respiration. Therefore, R-soil is a fraction of R-eco and theoretically has to be smaller than R-eco at daily, seasonal, and annual scales. However, several studies estimating R-eco with the eddy covariance technique and measuring R-soll within the footprint of the tower have reported higher R-soil than R-eco, at different time scales. Here, we compare four different and contrasting ecosystems (from forest to grasslands, and from boreal to semiarid) to test if measurements of R-eco are consistently higher than R-soil. In general, both fluxes showed similar temporal patterns, but R-eco, was not consistently higher than R-soil from daily to annual scales across sites. We identified several issues that apply for measuring NEE and measuring/upscaling R-soil that could result in an underestimation of R-eco and/or an overestimation of R-soil. These issues are discussed based on (a) nighttime measurements of NEE, (b) R-soil measurements, and (c) the interpretation of the functional relationships of these fluxes with temperature (i.e., Q(10)). We highlight that there is still a need for better integration of R-soil with eddy covariance measurements to address challenges related to the spatial and temporal variability of R-eco, and R-soil.Peer reviewe

Polarimetric Multi-View Inverse Rendering

A polarization camera has great potential for 3D reconstruction since the angle of polarization (AoP) of reflected light is related to an object's surface normal. In this paper, we propose a novel 3D reconstruction method called Polarimetric Multi-View Inverse Rendering (Polarimetric MVIR) that effectively exploits geometric, photometric, and polarimetric cues extracted from input multi-view color polarization images. We first estimate camera poses and an initial 3D model by geometric reconstruction with a standard structure-from-motion and multi-view stereo pipeline. We then refine the initial model by optimizing photometric and polarimetric rendering errors using multi-view RGB and AoP images, where we propose a novel polarimetric rendering cost function that enables us to effectively constrain each estimated surface vertex's normal while considering four possible ambiguous azimuth angles revealed from the AoP measurement. Experimental results using both synthetic and real data demonstrate that our Polarimetric MVIR can reconstruct a detailed 3D shape without assuming a specific polarized reflection depending on the material.Comment: Paper accepted in ECCV 202

A miniaturized passive sampling-based workflow for monitoring chemicals of emerging concern in water

The miniaturization of a full workflow for identification and monitoring of contaminants of emerging concern (CECs) is presented. Firstly, successful development of a low-cost small 3D-printed passive sampler device (3D-PSD), based on a two-piece methacrylate housing that held up to five separate 9 mm disk sorbents, is discussed. Secondly, a highly sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method reduced the need for large scale in-laboratory apparatus, solvent, reagents and reference material quantities for in-laboratory passive sampler device (PSD) calibration and extraction. Using hydrophilic-lipophilic balanced sorbents, sampling rates (Rs) were determined after a low 50 ng L−1 exposure over seven days for 39 pesticides, pharmaceuticals, drug metabolites and illicit drugs over the range 0.3 to 12.3 mL day−1. The high sensitivity LC-MS/MS method enabled rapid analysis of river water using only 10 μL of directly injected sample filtrate to measure occurrence of 164 CECs and sources along 19 sites on the River Wandle, (London, UK). The new 3D-PSD was then field-tested over seven days at the site with the highest number and concentration of CECs, which was down-river from a wastewater treatment plant. Almost double the number of CECs were identified in 3D-PSD extracts across sites in comparison to water samples (80 versus 42 CECs, respectively). Time-weighted average CEC concentrations ranged from 8.2 to 845 ng L−1, which were generally comparable to measured concentrations in grab samples. Lastly, high resolution mass spectrometry-based suspect screening of 3D-PSD extracts enabled 113 additional compounds to be tentatively identified via library matching, many of which are currently or are under consideration for the EU Watch List. This miniaturized workflow represents a new, cost-effective, and more practically efficient means to perform passive sampling chemical monitoring at a large scale

Differential protein profiling as a potential multi-marker approach for TSE diagnosis

Rona Barron - ORCID: 0000-0003-4512-9177 https://orcid.org/0000-0003-4512-9177This "proof of concept" study, examines the use of differential protein expression profiling using surface enhanced laser desorption and ionisationtime of flight mass spectrometry (SELDI-TOF) for the diagnosis of TSE disease. Spectral output from all proteins selectively captured from individual murine brain homogenate samples, are compared as "profiles" in groups of infected and non-infected animals. Differential protein expression between groups is thus highlighted and statistically significant protein "peaks" used to construct a panel of disease specific markers. Studies at both terminal stages of disease and throughout the time course of disease have shown a disease specific protein profile or "disease fingerprint" which could be used to distinguish between groups of TSE infected and uninfected animals at an early time point of disease. Results Our results show many differentially expressed proteins in diseased and control animals, some at early stages of disease. Three proteins identified by SELDI-TOF analysis were verified by immunohistochemistry in brain tissue sections. We demonstrate that by combining the most statistically significant changes in expression, a panel of markers can be constructed that can distinguish between TSE diseased and normal animals. Conclusion Differential protein expression profiling has the potential to be used for the detection of disease in TSE infected animals. Having established that a "training set" of potential markers can be constructed, more work would be required to further test the specificity and sensitivity of the assay in a "testing set". Based on these promising results, further studies are being performed using blood samples from infected sheep to assess the potential use of SELDI-TOF as a pre-mortem blood based diagnostic.https://doi.org/10.1186/1471-2334-9-1889pubpub

Cerebrospinal fluid matrix metalloproteinase-9 increases during treatment of recurrent malignant gliomas

<p>Abstract</p> <p>Background</p> <p>Matrix metalloproteinases (MMPs) are enzymes that promote tumor invasion and angiogenesis by enzymatically remodeling the extracellular matrix. MMP-2 and MMP-9 are the most abundant forms of MMPs in malignant gliomas, while a 130 kDa MMP is thought to be MMP-9 complexed to other proteinases. This study determined whether doxycycline can block MMP activity <it>in vitro</it>. We also measured MMP-2 and MMP-9 levels in cerebrospinal fluid (CSF) from patients with recurrent malignant gliomas.</p> <p>Methods</p> <p>To determine whether doxycycline can block MMP activity, we measured the extent of doxycyline-mediated MMP-2 and MMP-9 inhibition <it>in vitro </it>using epidermal growth factor receptor (EGFR) transfected U251 glioma cell lines. MMP activity was measured using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) zymography. In addition, patients underwent lumbar puncture for CSF sampling at baseline, after 6 weeks (1 cycle), and after 12 weeks (2 cycles), while being treated with a novel chemotherapy regimen of irinotecan, thalidomide, and doxycycline designed to block growth/proliferation, angiogenesis, and invasion. Irinotecan was given at 125 mg/m²/week for 4 weeks in 6-week cycles, together with continuous doxycycline at 100 mg twice daily on Day 1 and 50 mg twice daily thereafter. Daily thalidomide dose in our cohort was 400 mg. Tumor progression was monitored by magnetic resonance imaging (MRI).</p> <p>Results</p> <p>Doxycyline <it>in vitro </it>completely abolished MMP-9 activity at 500 μg/ml while there was only 30 to 50% inhibition of MMP-2 activity. Four patients respectively completed 4, 3, 1, and 2 cycles of irinotecan, thalidomide, and doxycycline. Patient enrollment was terminated after one patient developed radiologically defined pulmonary embolism, and another had probable pulmonary embolism. Although CSF MMP-2 and 130 kDa MMP levels were stable, MMP-9 level progressively increased during treatment despite stable MRI.</p> <p>Conclusion</p> <p>Doxycycline can block MMP-2 and MMP-9 activities from glioma cells <it>in vitro</it>. Increased CSF MMP-9 activity could be a biomarker of disease activity in patients with malignant gliomas, before any changes are detectable on MRI.</p

Bank performance and executive pay: tournament or teamwork

We investigate the relationship between the dispersion of executive pay and bank performance/valuation by examining two competing theories, the tournament theory (hierarchical wage structure) and the equity fairness theory (compressed wage structure). The key variable of executive pay dispersion is measured using a hand-collected dataset composed of 63 banks from OECD countries and 29 banks from developing countries. The dataset covers the period 2004 to 2012. By combining and modifying a translog profit function and a pay-dispersion model, we are able to address the potential problems of relying on reduced-form estimation. In our subsample of developed and civil law countries, where bank performance is measured by either Tobin’s Q or by the price-to-book ratio, the overall impact of executive pay dispersion is mostly negative, and we find supporting evidence for the equity fairness theory, except for very high levels of dispersion. There is a non-linear effect, as banks perform best when there is either very low or very high executive pay dispersion. For developing country sample banks, greater executive pay dispersion has a negative impact on bank profit. In our subsample of common law countries, however, we find no evidence of a significant impact of executive pay dispersion on bank performance. We conclude that lower executive pay dispersion, a proxy for teamwork, is mostly effective in enhancing bank performance in a significant section of sample banks, i.e., civil law and developing countries

A model-based approach to selection of tag SNPs

BACKGROUND: Single Nucleotide Polymorphisms (SNPs) are the most common type of polymorphisms found in the human genome. Effective genetic association studies require the identification of sets of tag SNPs that capture as much haplotype information as possible. Tag SNP selection is analogous to the problem of data compression in information theory. According to Shannon's framework, the optimal tag set maximizes the entropy of the tag SNPs subject to constraints on the number of SNPs. This approach requires an appropriate probabilistic model. Compared to simple measures of Linkage Disequilibrium (LD), a good model of haplotype sequences can more accurately account for LD structure. It also provides a machinery for the prediction of tagged SNPs and thereby to assess the performances of tag sets through their ability to predict larger SNP sets. RESULTS: Here, we compute the description code-lengths of SNP data for an array of models and we develop tag SNP selection methods based on these models and the strategy of entropy maximization. Using data sets from the HapMap and ENCODE projects, we show that the hidden Markov model introduced by Li and Stephens outperforms the other models in several aspects: description code-length of SNP data, information content of tag sets, and prediction of tagged SNPs. This is the first use of this model in the context of tag SNP selection. CONCLUSION: Our study provides strong evidence that the tag sets selected by our best method, based on Li and Stephens model, outperform those chosen by several existing methods. The results also suggest that information content evaluated with a good model is more sensitive for assessing the quality of a tagging set than the correct prediction rate of tagged SNPs. Besides, we show that haplotype phase uncertainty has an almost negligible impact on the ability of good tag sets to predict tagged SNPs. This justifies the selection of tag SNPs on the basis of haplotype informativeness, although genotyping studies do not directly assess haplotypes. A software that implements our approach is available