A minimum-relaxation model for large eddy simulation

This paper is about a relaxation model for large-eddy simulation of turbulent flow that truncates the small scales of motion for which numerical resolution is not available by making sure that they do not get energy from the larger, resolved, eddies. The resolved scales are defined with the help of a box filter. The relaxation parameter is determined in such a way that the production of too small, box-fitting, scales is counteracted by the modeled dissipation. This dissipation-production balance is worked out with the help of Poincaré’s inequality, which results in a relaxation model that depends on the invariants of the velocity gradient. This model is discretized and equipped with a Schumann filter. It is successfully tested for isotropic turbulence as well as for turbulent channel flow

Host autophagy machinery is diverted to the pathogen interface to mediate focal defense responses against the Irish potato famine pathogen

During plant cell invasion, the oomycete Phytophthora infestans remains enveloped by host-derived membranes whose functional properties are poorly understood. P. infestans secretes a myriad of effector proteins through these interfaces for plant colonization. Recently we showed that the effector protein PexRD54 reprograms host-selective autophagy by antagonising antimicrobial-autophagy receptor Joka2/NBR1 for ATG8CL binding (Dagdas et al., 2016). Here, we show that during infection, ATG8CL/Joka2 labelled defense-related autophagosomes are diverted toward the perimicrobial host membrane to restrict pathogen growth. PexRD54 also localizes to autophagosomes across the perimicrobial membrane, consistent with the view that the pathogen remodels host-microbe interface by co-opting the host autophagy machinery. Furthermore, we show that the host-pathogen interface is a hotspot for autophagosome biogenesis. Notably, overexpression of the early autophagosome biogenesis protein ATG9 enhances plant immunity. Our results implicate selective autophagy in polarized immune responses of plants and point to more complex functions for autophagy than the widely known degradative roles

Diagnostic accuracy of procalcitonin in critically ill immunocompromised patients

<p>Abstract</p> <p>Background</p> <p>Recognizing infection is crucial in immunocompromised patients with organ dysfunction. Our objective was to assess the diagnostic accuracy of procalcitonin (PCT) in critically ill immunocompromised patients.</p> <p>Methods</p> <p>This prospective, observational study included patients with suspected sepsis. Patients were classified into one of three diagnostic groups: no infection, bacterial sepsis, and nonbacterial sepsis.</p> <p>Results</p> <p>We included 119 patients with a median age of 54 years (interquartile range [IQR], 42-68 years). The general severity (SAPSII) and organ dysfunction (LOD) scores on day 1 were 45 (35-62.7) and 4 (2-6), respectively, and overall hospital mortality was 32.8%. Causes of immunodepression were hematological disorders (64 patients, 53.8%), HIV infection (31 patients, 26%), and solid cancers (26 patients, 21.8%). Bacterial sepsis was diagnosed in 58 patients and nonbacterial infections in nine patients (7.6%); 52 patients (43.7%) had no infection. PCT concentrations on the first ICU day were higher in the group with bacterial sepsis (4.42 [1.60-22.14] vs. 0.26 [0.09-1.26] ng/ml in patients without bacterial infection, <it>P </it>< 0.0001). PCT concentrations on day 1 that were > 0.5 ng/ml had 100% sensitivity but only 63% specificity for diagnosing bacterial sepsis. The area under the receiver operating characteristic (ROC) curve was 0.851 (0.78-0.92). In multivariate analyses, PCT concentrations > 0.5 ng/ml on day 1 independently predicted bacterial sepsis (odds ratio, 8.6; 95% confidence interval, 2.53-29.3; <it>P </it>= 0.0006). PCT concentrations were not significantly correlated with hospital mortality.</p> <p>Conclusion</p> <p>Despite limited specificity in critically ill immunocompromised patients, PCT concentrations may help to rule out bacterial infection.</p

Gully cut- and- fill cycles as related to agromanagement : a historical curve number simulation in the Tigray Highlands

Gully cut-and-fill dynamics are often thought to be driven by climate and/or deforestation related to population pressure. However, in this case-study of nine representative catchments in the Northern Ethiopian Highlands, we find that neither climate changes nor deforestation can explain gully morphology changes over the twentieth century. Firstly, by using a Monte Carlo simulation to estimate historical catchment-wide curve numbers, we show that the landscape was already heavily degraded in the nineteenth and early twentieth century – a period with low population density. The mean catchment-wide curve number (> 80) one century ago was, under the regional climatic conditions, already resulting in considerable simulated historical runoff responses. Secondly, twentieth century land-cover and runoff coefficient changes were confronted with twentieth century changing gully morphologies. As the results show, large-scale land-cover changes and deforestation cannot explain the observed processes. The study therefore invokes interactions between authigenic factors, small-scale plot boundary changes, cropland management and sociopolitical forces to explain the gully cut processes. Finally, semi-structured interviews and sedistratigraphic analysis of three filled gullies confirm the dominant impact of (crop)land management (tillage, check dams in gullies and channel diversions) on gully cut-and-fill processes. Since agricultural land management – including land tenure and land distribution – has been commonly neglected in earlier related research, we argue therefore that it can be a very strong driver of twentieth century gully morphodynamics

ACSL3 is a novel GABARAPL2 interactor that links ufmylation and lipid droplet biogenesis

ABSTRACT While studies of the autophagy-related (ATG) genes in knockout models have led to an explosion of knowledge about the functions of autophagy components, the exact roles of LC3 and GABARAP family proteins (human ATG8 equivalents) are still poorly understood. A major drawback in understanding their roles is that the available interactome data has largely been acquired using overexpression systems. To overcome these limitations, we employed CRISPR/Cas9-based genome-editing to generate a panel of cells in which human ATG8 genes were tagged at their natural chromosomal locations with an N-terminal affinity epitope. This cellular resource was employed to map endogenous GABARAPL2 protein complexes using interaction proteomics. This approach identified the ER-associated protein and lipid droplet (LD) biogenesis factor ACSL3 as a stabilizing GABARAPL2-binding partner. GABARAPL2 bound ACSL3 in a manner dependent on its LC3-interacting regions, whose binding site in GABARAPL2 was required to recruit the latter to the ER. Through this interaction, the UFM1-activating enzyme UBA5 became anchored at the ER. Furthermore, ACSL3 depletion and LD induction affected the abundance of several ufmylation components and ER-phagy. Together these data allow us to define ACSL3 as a novel regulator of the enigmatic UFM1 conjugation pathway

Procalcitonin levels in acute exacerbation of COPD admitted in ICU: a prospective cohort study

<p>Abstract</p> <p>Background</p> <p>Antibiotics are recommended for severe acute exacerbation of chronic obstructive pulmonary disease (AECOPD) admitted to intensive care units (ICU). Serum procalcitonin (PCT) could be a useful tool for selecting patients with a lower probability of developing bacterial infection, but its measurement has not been investigated in this population.</p> <p>Methods</p> <p>We conducted a single center prospective cohort study in consecutive COPD patients admitted to the ICU for AECOPD between September 2005 and September 2006. Sputum samples or tracheal aspirates were tested for the presence of bacteria and viruses. PCT levels were measured at the time of admittance, six hours, and 24 hours using a sensitive immunoassay.</p> <p>Results</p> <p>Thirty nine AECOPD patients were included, 31 of which (79%) required a ventilator support at admission. The median [25%–75% interquartile range] PCT level, assessed in 35/39 patients, was: 0.096 μg/L [IQR, 0.065 to 0.178] at the time of admission, 0.113 μg/L [IQR, 0.074 to 0.548] at six hours, and 0.137 μg/L [IQR, 0.088 to 0.252] at 24 hours. The highest PCT (PCTmax) levels were less than 0.1 μg/L in 14/35 (40%) patients and more than 0.25 μg/L in 10/35 (29%) patients, suggesting low and high probability of bacterial infection, respectively. Five species of bacteria and nine species of viruses were detected in 12/39 (31%) patients. Among the four patients positive for <it>Pseudomonas aeruginosa</it>, one had a PCTmax less than 0.25 μg/L and three had a PCTmax less than 0.1 μg/L. The one patient positive for <it>Haemophilus influenzae </it>had a PCTmax more than 0.25 μg/L. The presence or absence of viruses did not influence PCT at time of admission (0.068 vs 0.098 μg/L respectively, <it>P </it>= 0.80).</p> <p>Conclusion</p> <p>The likelihood of bacterial infection is low among COPD patients admitted to ICU for AECOPD (40% with PCT < 0.1 μg/L) suggesting a possible inappropriate use of antibiotics. Further studies are necessary to assess the impact of a procalcitonin-based therapeutic strategy in critically ill COPD patients.</p

Notch ligand activity is modulated by glycosphingolipid membrane composition in Drosophila melanogaster

A specific glycosphingolipid regulates the E3 ubiquitin ligase Mindbomb1, which promotes the ligand endocytosis necessary for Notch activation

Identification of integrated proteomics and transcriptomics signature of alcohol-associated liver disease using machine learning.

Distinguishing between alcohol-associated hepatitis (AH) and alcohol-associated cirrhosis (AC) remains a diagnostic challenge. In this study, we used machine learning with transcriptomics and proteomics data from liver tissue and peripheral mononuclear blood cells (PBMCs) to classify patients with alcohol-associated liver disease. The conditions in the study were AH, AC, and healthy controls. We processed 98 PBMC RNAseq samples, 55 PBMC proteomic samples, 48 liver RNAseq samples, and 53 liver proteomic samples. First, we built separate classification and feature selection pipelines for transcriptomics and proteomics data. The liver tissue models were validated in independent liver tissue datasets. Next, we built integrated gene and protein expression models that allowed us to identify combined gene-protein biomarker panels. For liver tissue, we attained 90% nested-cross validation accuracy in our dataset and 82% accuracy in the independent validation dataset using transcriptomic data. We attained 100% nested-cross validation accuracy in our dataset and 61% accuracy in the independent validation dataset using proteomic data. For PBMCs, we attained 83% and 89% accuracy with transcriptomic and proteomic data, respectively. The integration of the two data types resulted in improved classification accuracy for PBMCs, but not liver tissue. We also identified the following gene-protein matches within the gene-protein biomarker panels: CLEC4M-CLC4M, GSTA1-GSTA2 for liver tissue and SELENBP1-SBP1 for PBMCs. In this study, machine learning models had high classification accuracy for both transcriptomics and proteomics data, across liver tissue and PBMCs. The integration of transcriptomics and proteomics into a multi-omics model yielded improvement in classification accuracy for the PBMC data. The set of integrated gene-protein biomarkers for PBMCs show promise toward developing a liquid biopsy for alcohol-associated liver disease

From ductile to brittle: evolution and localization of deformation below a crustal detachment (Tinos, Cyclades, Greece)

International audienceThe Cycladic Oligo-Miocene detachment of Tinos island is an example of a flat-lying extensional shear zone evolving into a low-angle brittle detachment. A clear continuum of extensional strain from ductile to brittle regime is observed in the footwall. The main brittle structures marking extension are shallow- and steeply dipping normal faults associated with subvertical extensional joints and veins. The earliest brittle structures are lowangle normal faults which commonly superimpose on, and reactivate, earlier (precursory) ductile shear bands, but newly formed low-angle normal faults could also be observed. Low-angle normal faults are cut by late steeply dipping normal faults. The inversion of fault slip data collected within, and away from, the main detachment zone shows that the direction of the minimum stress axis is strictly parallel to the NE-SW stretching lineation and that the maximum principal stress axis remained subvertical during the whole brittle evolution, in agreement with the subvertical attitude of veins throughout the island. The high angle of s1 to the main detachment suggests that the detachment was weak. This observation, together with the presence of a thick layer of cataclasites below the main detachment and the kinematic continuum from ductile to brittle, leads us to propose a kinematic model for the formation of the detachment. Boudinage at the crustal scale induces formation, near the brittle-ductile transition, of ductile shear zones near the edges of boudins. Shear zones are progressively exhumed and replaced by shallowdipping cataclastic shear zones when they reached the brittle field. Most of the displacement is achieved through cataclastic flow in the upper crust and only the last increment of strain gives rise to the formation of brittle faults. The formation of the low-angle brittle detachment is thus ''prepared'' by the ductile shear zone and the cataclasites and favored by the circulation of surface-derived fluids in the shear zone