Laparoscopic ventral hernia repair is safe and cost effective

Background: Ventral hernia repair is increasingly performed by laparoscopic means since the introduction of dual-layer meshes. This study aimed to compare the early complications and cost effectiveness of open hernia repair with those associated with laparoscopic repair. Methods: Open ventral hernia repair was performed for 92 consecutive patients using a Vypro mesh, followed by laparoscopic repair for 49 consecutive patients using a Parietene composite mesh. Results: The rate of surgical-site infections was significantly higher with open ventral hernia repair (13 vs 1; p = 0.03). The median length of hospital stay was significantly shorter with laparoscopic surgery (7 vs 6 days; p = 0.02). For laparoscopic repair, the direct operative costs were higher (2,314 vs 2,853 euros; p = 0.03), and the overall hospital costs were lower (9,787 vs 7,654 euros; p = 0.02). Conclusions: Laparoscopic ventral hernia repair leads to fewer surgical-site infections and a shorter hospital stay than open repair. Despite increased operative costs, overall hospital costs are lowered by laparoscopic ventral hernia repai

Analysis of neonatal brain lacking ATRX or MeCP2 reveals changes in nucleosome density, CTCF binding and chromatin looping

ATRX and MeCP2 belong to an expanding group of chromatin-associated proteins implicated in human neurodevelopmental disorders, although their gene-regulatory activities are not fully resolved. Loss of ATRX prevents full repression of an imprinted gene network in the postnatal brain and in this study we address the mechanistic aspects of this regulation. We show that ATRX binds many imprinted domains individually but that transient co-localization between imprinted domains in the nuclei of neurons does not require ATRX. We demonstrate that MeCP2 is required for ATRX recruitment and that deficiency of either ATRX or MeCP2 causes decreased frequency of long-range chromatin interactions associated with altered nucleosome density at CTCF-binding sites and reduced CTCF occupancy. These findings indicate that MeCP2 and ATRX regulate gene expression at a subset of imprinted domains by maintaining a nucleosome configuration conducive to CTCF binding and to the maintenance of higher order chromatin structure

Role of OH variability in the stalling of the global atmospheric CH4 growth rate from 1999 to 2006

The growth in atmospheric methane (CH4) concentrations over the past two decades has shown large variability on a timescale of several years. Prior to 1999 the globally averaged CH4 concentration was increasing at a rate of 6.0 ppb/yr, but during a stagnation period from 1999 to 2006 this growth rate slowed to 0.6 ppb/yr. From 2007 to 2009 the growth rate again increased to 4.9 ppb/yr. These changes in growth rate are usually ascribed to variations in CH4 emissions. We have used a 3-D global chemical transport model, driven by meteorological reanalyses and variations in global mean hydroxyl (OH) concentrations derived from CH3CCl3 observations from two independent networks, to investigate these CH4 growth variations. The model shows that between 1999 and 2006, changes in the CH4 atmospheric loss contributed significantly to the suppression in global CH4 concentrations relative to the pre-1999 trend. The largest factor in this is relatively small variations in global mean OH on a timescale of a few years, with minor contributions of atmospheric transport of CH4 to its sink region and of atmospheric temperature. Although changes in emissions may be important during the stagnation period, these results imply a smaller variation is required to explain the observed CH4 trends. The contribution of OH variations to the renewed CH4 growth after 2007 cannot be determined with data currently available

Identifying and Seeing beyond Multiple Sequence Alignment Errors Using Intra-Molecular Protein Covariation

BACKGROUND: There is currently no way to verify the quality of a multiple sequence alignment that is independent of the assumptions used to build it. Sequence alignments are typically evaluated by a number of established criteria: sequence conservation, the number of aligned residues, the frequency of gaps, and the probable correct gap placement. Covariation analysis is used to find putatively important residue pairs in a sequence alignment. Different alignments of the same protein family give different results demonstrating that covariation depends on the quality of the sequence alignment. We thus hypothesized that current criteria are insufficient to build alignments for use with covariation analyses. METHODOLOGY/PRINCIPAL FINDINGS: We show that current criteria are insufficient to build alignments for use with covariation analyses as systematic sequence alignment errors are present even in hand-curated structure-based alignment datasets like those from the Conserved Domain Database. We show that current non-parametric covariation statistics are sensitive to sequence misalignments and that this sensitivity can be used to identify systematic alignment errors. We demonstrate that removing alignment errors due to 1) improper structure alignment, 2) the presence of paralogous sequences, and 3) partial or otherwise erroneous sequences, improves contact prediction by covariation analysis. Finally we describe two non-parametric covariation statistics that are less sensitive to sequence alignment errors than those described previously in the literature. CONCLUSIONS/SIGNIFICANCE: Protein alignments with errors lead to false positive and false negative conclusions (incorrect assignment of covariation and conservation, respectively). Covariation analysis can provide a verification step, independent of traditional criteria, to identify systematic misalignments in protein alignments. Two non-parametric statistics are shown to be somewhat insensitive to misalignment errors, providing increased confidence in contact prediction when analyzing alignments with erroneous regions because of an emphasis on they emphasize pairwise covariation over group covariation

Neoadjuvant chemoradiotherapy with or without panitumumab in patients with wild-type KRAS, locally advanced rectal cancer (LARC): a randomized, multicenter, phase II trial SAKK 41/07

Background We conducted a randomized, phase II, multicenter study to evaluate the anti-epidermal growth factor receptor (EGFR) mAb panitumumab (P) in combination with chemoradiotherapy (CRT) with standard-dose capecitabine as neoadjuvant treatment for wild-type KRAS locally advanced rectal cancer (LARC). Patients and methods Patients with wild-type KRAS, T3-4 and/or N+ LARC were randomly assigned to receive CRT with or without P (6 mg/kg). The primary end-point was pathological near-complete or complete tumor response (pNC/CR), defined as grade 3 (pNCR) or 4 (pCR) histological regression by Dworak classification (DC). Results Forty of 68 patients were randomly assigned to P + CRT and 28 to CRT. pNC/CR was achieved in 21 patients (53%) treated with P + CRT [95% confidence interval (CI) 36%-69%] versus 9 patients (32%) treated with CRT alone (95% CI: 16%-52%). pCR was achieved in 4 (10%) and 5 (18%) patients, and pNCR in 17 (43%) and 4 (14%) patients. In immunohistochemical analysis, most DC 3 cells were not apoptotic. The most common grade ≥3 toxic effects in the P + CRT/CRT arm were diarrhea (10%/6%) and anastomotic leakage (15%/4%). Conclusions The addition of panitumumab to neoadjuvant CRT in patients with KRAS wild-type LARC resulted in a high pNC/CR rate, mostly grade 3 DC. The results of both treatment arms exceeded prespecified thresholds. The addition of panitumumab increased toxicit

Rising atmospheric methane: 2007-2014 growth and isotopic shift

From 2007 to 2013, the globally averaged mole fraction of methane in the atmosphere increased by 5.7±1.2ppb yr$^{-1}$. Simultaneously, $\delta^{13}$C$_\text{CH4}$ (a measure of the $^{13}$C/$^{12}$C isotope ratio in methane) has shifted to significantly more negative values since 2007. Growth was extreme in 2014, at 12.5±0.4ppb, with a further shift to more negative values being observed at most latitudes. The isotopic evidence presented here suggests that the methane rise was dominated by significant increases in biogenic methane emissions, particularly in the tropics, for example, from expansion of tropical wetlands in years with strongly positive rainfall anomalies or emissions from increased agricultural sources such as ruminants and rice paddies. Changes in the removal rate of methane by the OH radical have not been seen in other tracers of atmospheric chemistry and do not appear to explain short-term variations in methane. Fossil fuel emissions may also have grown, but the sustained shift to more $^{13}$C-depleted values and its significant interannual variability, and the tropical and Southern Hemisphere loci of post-2007 growth, both indicate that fossil fuel emissions have not been the dominant factor driving the increase. A major cause of increased tropical wetland and tropical agricultural methane emissions, the likely major contributors to growth, may be their responses to meteorological change.This work was supported by the UK Natural Environment Research Council projects NE/N016211/1 The Global Methane Budget, NE/M005836/1 Methane at the edge, NE/K006045/1 The Southern Methane Anomaly and NE/I028874/1 MAMM. We thank the UK Meteorological Office for flask collection and hosting the continuous measurement at Ascension, the Ascension Island Government for essential support, and Thumeka Mkololo for flask collection in Cape Tow

Computing and visually analyzing mutual information in molecular co-evolution

<p>Abstract</p> <p>Background</p> <p>Selective pressure in molecular evolution leads to uneven distributions of amino acids and nucleotides. In fact one observes correlations among such constituents due to a large number of biophysical mechanisms (folding properties, electrostatics, ...). To quantify these correlations the mutual information -after proper normalization - has proven most effective. The challenge is to navigate the large amount of data, which in a study for a typical protein cannot simply be plotted.</p> <p>Results</p> <p>To visually analyze mutual information we developed a matrix visualization tool that allows different views on the mutual information matrix: filtering, sorting, and weighting are among them. The user can interactively navigate a huge matrix in real-time and search e.g., for patterns and unusual high or low values. A computation of the mutual information matrix for a sequence alignment in FASTA-format is possible. The respective stand-alone program computes in addition proper normalizations for a null model of neutral evolution and maps the mutual information to <it>Z</it>-scores with respect to the null model.</p> <p>Conclusions</p> <p>The new tool allows to compute and visually analyze sequence data for possible co-evolutionary signals. The tool has already been successfully employed in evolutionary studies on HIV1 protease and acetylcholinesterase. The functionality of the tool was defined by users using the tool in real-world research. The software can also be used for visual analysis of other matrix-like data, such as information obtained by DNA microarray experiments. The package is platform-independently implemented in <monospace>Java</monospace> and free for academic use under a GPL license.</p

Modelling the Radiative Effects of Biomass Burning Aerosols on Carbon Fluxes in the Amazon Region

Every year, a dense smoke haze covers a large portion of South America originating from fires in the Amazon Basin and central parts of Brazil during the dry/biomass-burning season between August and October. Over a large portion of South America, the average aerosol optical depth at 550 nm exceeds 1.0 during the fire season while the background value during the rainy season is below 0.2. Biomass burning aerosol particles increase scattering and absorption of the incident solar radiation. The regional-scale aerosol layer reduces the amount of solar energy reaching the surface, cools the near surface air, and increases the diffuse radiation fraction over a large disturbed area of the Amazon rainforest. These factors affect the energy and CO2 fluxes at the surface. In this work, we applied a fully integrated atmospheric model to assess the impact of biomass burning aerosols in CO2 fluxes in the Amazon region during 2010. We address the effects of the attenuation of the global solar radiation and the enhancement of the diffuse solar radiation flux inside the vegetation canopy. Our results indicate that the biomass burning aerosols led to increases of about 27% of gross primary productivity of Amazonia, 10% of plant respiration and a decline in soil respiration of 3%. Consequently, in our model Amazonia, became a net carbon sink; net ecosystem exchange during September 2010 dropped from +101 to -104 TgC when the aerosol effects are considered, mainly due to the aerosol diffuse radiation effect. For the forest biome, our results point to a dominance of the diffuse radiation effect on CO2 fluxes, reaching a balance of 50% - 50% between the diffuse and direct aerosol effects for high aerosol loads. For C3 grasses and Savanna (cerrado), as expected, the contribution of the diffuse radiation effect is much lower, tending to zero with the increase of aerosol load. Taking all biomes together, our model shows the Amazon during the dry season, in the presence of high biomass burning aerosol loads, changing from being a source to being a sink of CO2 to the atmosphere

Sixteen years of MOPITT satellite data strongly constrain Amazon CO fire emissions

Despite consensus on the overall downward trend in Amazon forest loss in the previous decade, estimates of yearly carbon emissions from deforestation still vary widely. Estimated carbon emissions are currently often based on data from local logging activity reports, changes in remotely sensed biomass as well as remote detection of fire hotspots, and burned area. Here, we use sixteen years of satellite-derived carbon monoxide (CO) columns to constrain fire CO emissions from the Amazon basin between 2003 and 2018. Through data assimilation, we produce 3-daily maps of fire CO emissions over the Amazon that we verified to be consistent with a long-term monitoring program of aircraft CO profiles over five sites in the Amazon. Our new product independently confirms a long-term decrease of 54 % in deforestation-related CO emissions over the study period. Interannual variability is large, with known anomalously dry years showing a more than fourfold increase in basin-wide fire emissions. At the level of individual Brazilian states, we find that both soil moisture anomalies and human ignitions determine fire activity, suggesting that future carbon release from fires depends on drought intensity as much as on continued forest protection. Our study shows that the atmospheric composition perspective on deforestation is a valuable additional monitoring instrument that complements existing bottom-up and remote sensing methods for land-use change. Extension of such a perspective to an operational framework is timely considering the observed increased fire intensity in the Amazon basin in 2019&ndash;2021.</p