Reliability Criteria of Two-Dimensional Shear Wave Elastography: Analysis of 4277 Measurements in 788 Patients.

BACKGROUND & AIMS: Two-dimensional shear wave elastography (2D-SWE) is an accurate method for the non-invasive evaluation of liver fibrosis. We aimed to determine the reliability criteria and the number of necessary reliable measurements for 2D-SWE. METHODS: 788 patients with chronic liver disease underwent liver biopsy and 2D-SWE examination in three centers. The 4277 2D-SWE measurements performed were 2:1 randomly divided into derivation (n = 2851) and validation (n = 1426) sets. Reliability criteria for a 2D-SWE measurement were defined in the derivation set from the intrinsic characteristics given by the device (mean liver stiffness, standard deviation, diameter of the region of interest), with further evaluation in the validation set. RESULTS: In the whole population of 4277 measurements, AUROC for bridging fibrosis was 0.825 ± 0.006 and AUROC for cirrhosis was 0.880 ± 0.006. Mean stiffness and coefficient of variation (CV) were independent predictors of bridging fibrosis or cirrhosis. From these two parameters, new criteria were derived to define a reliable 2D-SWE measurement: stiffness <8.8 kPa, or stiffness between 8.8-11.9 kPa with CV <0.25, or stiffness ≥12.0 kPa with CV <0.10. In the validation set, AUROC for bridging fibrosis was 0.830 ± 0.013 in reliable measurements vs 0.667 ± 0.031 in unreliable measurements (P < .001). AUROC for cirrhosis was 0.918±0.014 vs 0.714 ± 0.027, respectively (P < .001). The best diagnostic accuracy for a 2D-SWE examination was achieved from three reliable measurements. CONCLUSIONS: Reliability of a 2D-SWE measurement relies on the coefficient of variation and the liver stiffness level. A 2D-SWE examination should include three reliable measurements according to our new criteria.

Cross-linkage between bacterial taxonomy and gene functions: a study of metagenome-assembled genomes of gut microbiota in adult non-alcoholic fatty liver disease.

BACKGROUND: The reconstruction of metagenome-assembled genomes (MAGs) has emerged as a powerful approach for combining the taxonomic and functional content of microbial populations. AIM: To use this new approach to highlight mechanisms linking gut microbiota to NAFLD severity METHODS: Stool samples were collected from 96 NAFLD patients on the day of liver biopsy. Shotgun DNA sequencing of the gut microbiota was performed on an Illumina HiSeq3000 system. Contigs were binned into MAGs according to their co-abundances and tetranucleotide frequencies using Metabat v.0.32.4. Predicted protein-coding genes were clustered in orthologous groups (OGs) with DIAMOND against the EggNOG v4.5 database. Liver biopsies were read in accordance with the NASH CRN classification. RESULTS: Fifty-four patients had NASH and 44 had significant fibrosis (F ≥ 2). Sequencing of DNA extracted from stools resulted in 13.8 + 3.2 million paired-end reads per sample. Of the 4,000 reconstructed MAGs, 220 in NASH patients, 192 in non-NASH patients, 203 in F ≥ 2 patients and 230 in F0-1 patients had > 70% completeness and < 5% contamination. Within these MAGs, 28 OGs were associated with NASH, 33 with significant fibrosis, and seven with both NASH and significant fibrosis. The study of MAGs showed associations between NAFLD severity and some gut bacteria with microbiota functions related to hydrogen sulfide production, citrate transport, hemicellulose degradation, aldehyde production and vitamin B12 synthesis. CONCLUSION: Using new metagenomics methods, our study unveils potential mechanisms by which certain bacteria from the gut microbiota could protect or contribute to the development of NASH and liver fibrosis in NAFLD.

A Computation Method Based on the Combination of Chlorophyll Fluorescence Parameters to Improve the Discrimination of Visually Similar Phenotypes Induced by Bacterial Virulence Factors.

Phenotyping biotic stresses in plant-pathogen interactions studies is often hindered by phenotypes that can hardly be discriminated by visual assessment. Particularly, single gene mutants in virulence factors could lack visible phenotypes. Chlorophyll fluorescence (CF) imaging is a valuable tool to monitor plant-pathogen interactions. However, while numerous CF parameters can be measured, studies on plant-pathogen interactions often focus on a restricted number of parameters. It could result in limited abilities to discriminate visually similar phenotypes. In this study, we assess the ability of the combination of multiple CF parameters to improve the discrimination of such phenotypes. Such an approach could be of interest for screening and discriminating the impact of bacterial virulence factors without prior knowledge. A computation method was developed, based on the combination of multiple CF parameters, without any parameter selection. It involves histogram Bhattacharyya distance calculations and hierarchical clustering, with a normalization approach to take into account the inter-leaves and intra-phenotypes heterogeneities. To assess the efficiency of the method, two datasets were analyzed the same way. The first dataset featured single gene mutants of a Xanthomonas strain which differed only by their abilities to secrete bacterial virulence proteins. This dataset displayed expected phenotypes at 6 days post-inoculation and was used as ground truth dataset to setup the method. The efficiency of the computation method was demonstrated by the relevant discrimination of phenotypes at 3 days post-inoculation. A second dataset was composed of transient expression (agrotransformation) of Type 3 Effectors. This second dataset displayed phenotypes that cannot be discriminated by visual assessment and no prior knowledge can be made on the respective impact of each Type 3 Effectors on leaf tissues. Using the computation method resulted in clustering the leaf samples according to the Type 3 Effectors, thereby demonstrating an improvement of the discrimination of the visually similar phenotypes. The relevant discrimination of visually similar phenotypes induced by bacterial strains differing only by one virulence factor illustrated the importance of using a combination of CF parameters to monitor plant-pathogen interactions. It opens a perspective for the identification of specific signatures of biotic stresses.

Simple blood fibrosis tests reduce unnecessary referrals for specialized evaluations of liver fibrosis in NAFLD and ALD patients.

BACKGROUND: Liver fibrosis evaluation is mandatory in non-alcoholic fatty liver disease (NAFLD) and alcoholic liver disease (ALD) to decide the patient management. Patients with these diseases are usually under the care of non-liver specialists who refer them to specialized centers where the most accurate fibrosis tests are available. We aimed to evaluate whether simple blood fibrosis tests available to all physicians help to reduce the rate of unnecessary referral of NAFLD and ALD patients without advanced fibrosis. METHODS: NAFLD and/or ALD patients newly referred to our center for a non-invasive evaluation of liver fibrosis were retrospectively included. The FibroMeterVCTE (FMVCTE, combination of blood markers and Fibroscan results) was defined as the reference test for specialized evaluation of liver fibrosis. A FMVCTE result <0.384 indicated the absence of advanced fibrosis and thus an "unnecessary referral". RESULTS: 558 patients were included (NAFLD: 283, ALD: 156, mixed NAFLD+ALD: 119). FMVCTE was <0.384 (unnecessary referral) in 58.8% of patients. FIB4 was <1.30 in 45.2% and eLIFT <8 in 47.7% of the patients. 84.9% of patients with FIB4 <1.30 and 85.3% of patients with eLIFT <8 had also FMVCTE <0.384. Therefore, using FIB4 or eLIFT as first-line evaluation of liver fibrosis decreased by three-fold the rate of unnecessary referral. The negative predictive value of FIB4 and eLIFT was >80% whatever the underlying cause of chronic liver disease. CONCLUSION: The use of eLIFT by non-liver specialists for NAFLD and ALD patients can improve the relevance of referrals for specialized evaluation of liver fibrosis.

New sequential combinations of non-invasive fibrosis tests provide an accurate diagnosis of advanced fibrosis in NAFLD.

BACKGROUND & AIMS: Advanced liver fibrosis is an important diagnostic target in non-alcoholic fatty liver disease (NAFLD) as it defines the subgroup of patients with impaired prognosis. The non-invasive diagnosis of advanced fibrosis is currently limited by the suboptimal positive predictive value and the grey zone (representing indeterminate diagnosis) of fibrosis tests. Here, we aimed to determine the best combination of non-invasive tests for the diagnosis of advanced fibrosis in NAFLD. METHODS: A total of 938 patients with biopsy-proven NAFLD were randomized 2:1 into derivation and validation sets. All patients underwent liver stiffness measurement with vibration controlled transient elastography (VCTE) and blood fibrosis tests (NAFLD fibrosis score, Fibrosis-4 [FIB4], Fibrotest, Hepascore, FibroMeter). FibroMeterVCTE, which combines VCTE results and FibroMeter markers in a single test, was also calculated in all patients. RESULTS: For the diagnosis of advanced fibrosis, VCTE was significantly more accurate than the blood tests (area under the receiver operating characteristic curve [AUROC]: 0.840 ±â€¯0.013, p ≤0.005). FibroMeter was the most accurate blood test (AUROC: 0.793 ±â€¯0.015, p ≤0.017). The combinatory test FibroMeterVCTE outperformed VCTE and blood tests (AUROC: 0.866 ±â€¯0.012, p ≤0.005). The sequential combination of FIB4 then FibroMeterVCTE (FIB4-FMVCTE algorithm) or VCTE then FibroMeterVCTE (VCTE-FMVCTE algorithm) provided an excellent diagnostic accuracy of 90% for advanced fibrosis, with liver biopsy only required to confirm the diagnosis in 20% of cases. The FIB4-FMVCTE and VCTE-FMVCTE algorithms were significantly more accurate than the pragmatic algorithms currently proposed. CONCLUSION: The sequential combination of fibrosis tests in the FIB4-FMVCTE and VCTE-FMVCTE algorithms provides a highly accurate solution for the diagnosis of advanced fibrosis in NAFLD. These algorithms should now be validated for the diagnosis of advanced liver fibrosis in diabetology or primary care settings. LAY SUMMARY: The evaluation of liver fibrosis is mandatory in non-alcoholic fatty liver disease (NAFLD), as advanced fibrosis identifies the subgroup of patients with impaired prognosis. FibroMeterVCTE is a new fibrosis test combining blood markers and the result of vibration controlled transient elastography (VCTE) into a single diagnostic test. Our results show that FibroMeterVCTE outperforms other blood fibrosis tests and VCTE alone for the diagnosis of advanced fibrosis in a large multi-centric cohort of 938 patients with biopsy-proven NAFLD. Sequential algorithms using a simple blood test or VCTE as a first-line procedure, then FibroMeterVCTE as a second-line test accurately classified 90% of patients.

Liver Stiffness Measurement With FibroScan: Use the Right Probe in the Right Conditions!

INTRODUCTION: FibroScan's M and XL probes give significantly different results, which could lead to misevaluation of liver fibrosis if the correct probe is not chosen. According to the manufacturer, the M probe should be used when the skin-liver capsule distance (SCD) is <25 mm, and the XL probe should be used when SCD is ≥25 mm. We aimed at validating this recommendation and defining the conditions of use for FibroScan probes in clinical practice. METHODS: Four hundred thirty-nine patients with biopsy-proven chronic liver disease were included. Of them, 382 had successful examinations with both M and XL probes. Advanced fibrosis was defined as Nonalcoholic Steatohepatitis Clinical Research Network (NASH CRN) F ≥3 or Metavir F ≥2. RESULTS: In a same patient, XL probe results were significantly lower than M probe results: 7.9 (5.6-11.7) vs 9.5 (6.7-14.6) kPa, respectively (P < 0.001). After matching for age, sex, liver fibrosis, and serum transaminases, M probe results in patients with SCD <25 mm and XL probe results in those with SCD ≥25 mm did not significantly differ: 8.8 (6.0-12.0) vs 9.1 (6.7-12.8) kPa, respectively (P = 0.175). Of note, 81.4% of patients with body mass index (BMI) <32 kg/m had SCD <25 mm, and 77.7% of patients with BMI ≥32 kg/m had SCD ≥25 mm. A practical algorithm using BMI first and then the FibroScan Automatic Probe Selection tool was proposed to help physicians accurately choose which probe to use in clinical practice. CONCLUSIONS: There is no significant difference in results between M and XL probes when they are used in the right conditions. In clinical practice, the probe should be selected according to the BMI and the Automatic Probe Selection tool.

Criteria to Determine Reliability of Noninvasive Assessment of Liver Fibrosis With Virtual Touch Quantification.

BACKGROUND & AIMS: Virtual Touch Quantification (VTQ) evaluates liver fibrosis in patients with chronic liver diseases by measuring shear wave speed in the liver. We aimed to determine the reliability criteria of VTQ examination. METHODS: We performed a prospective study of 1094 patients with chronic liver disease from November 2009 through October 2016 at Angers University Hospital, and between April 2010 and May 2015 at Bordeaux University Hospital, in France. All patients underwent liver biopsy analysis (reference standard), and VTQ examination was made by experienced operators on the same day, or no more than 3 months before or afterward. Advanced liver fibrosis was defined as fibrosis stage F ≥ 3 according to the scoring system of the Nonalcoholic Steatohepatitis Clinical Research Network, or fibrosis stage F ≥ 2 according to the Metavir scoring system. The diagnostic accuracy of VTQ in detection of advanced fibrosis or cirrhosis was assessed using the area under the receiver operating characteristic (AUROC) and the rate of correctly classified patients. Reliability criteria were defined from the intrinsic characteristics of VTQ examination, which were shown to influence the diagnostic accuracy. RESULTS: VTQ identified patients with advanced fibrosis with an AUROC of 0.773 ± 0.014 and correctly classified 72.0% of patients using a diagnostic cut-off value of 1.37 m/s. VTQ identified patients with cirrhosis with an AUROC value of 0.839 ± 0.014 and correctly classified 78.4% of patients using a cut-off value of 1.87 m/s. The reliability of VTQ decreased with an increasing ratio of interquartile range/median (IQR/M) in patients with intermediate-high VTQ results. We defined 3 reliability categories for VTQ: unreliable (IQR/M ≥0.35 with VTQ result ≥1.37 m/s), reliable (IQR/M ≥0.35 with VTQ result <1.37 m/s or IQR/M 0.15-0.34), and very reliable (IQR/M <0.15). For advanced fibrosis, VTQ correctly classified 57.8% of patients in the unreliable group, 73.7% of patients in the reliable group, and 80.9% of patients in the very reliable group (P < .001); for cirrhosis, these values were 50.0%, 83.4%, and 92.6%, respectively (P < .001). Of the VTQ examinations made, 21.4% were unreliable, 55.0% were reliable, and 23.6% were very reliable. The skin-liver capsule distance was independently associated with an unreliable VTQ examination, which occurred in 52.7% of patients with a distance of 30 mm or more. CONCLUSIONS: In a study to determine the reliability of VTQ findings, compared with results from biopsy analysis, we assigned VTQ examinations to 3 categories (unreliable, reliable, and very reliable). VTQ examinations with IQR/M ≥0.35 and ≥1.37 m/s had very low diagnostic accuracy. Our reliability criteria for liver fibrosis assessment with VTQ will help physicians to accurately evaluate the severity of chronic liver diseases and monitor their progression.

Dataset's chemical diversity limits the generalizability of machine learning predictions.

The QM9 dataset has become the golden standard for Machine Learning (ML) predictions of various chemical properties. QM9 is based on the GDB, which is a combinatorial exploration of the chemical space. ML molecular predictions have been recently published with an accuracy on par with Density Functional Theory calculations. Such ML models need to be tested and generalized on real data. PC9, a new QM9 equivalent dataset (only H, C, N, O and F and up to 9 "heavy" atoms) of the PubChemQC project is presented in this article. A statistical study of bonding distances and chemical functions shows that this new dataset encompasses more chemical diversity. Kernel Ridge Regression, Elastic Net and the Neural Network model provided by SchNet have been used on both datasets. The overall accuracy in energy prediction is higher for the QM9 subset. However, a model trained on PC9 shows a stronger ability to predict energies of the other dataset.

Estimation of soil organic carbon stocks of two cities, New York City and Paris.

In cities, the strong heterogeneity of soils, added to the lack of standardized assessment methods, serves as a barrier to the estimation of their soil organic carbon content (SOC), soil organic carbon stocks (SOCS; kgC m-2) and soil organic carbon citywide totals (SOCCT; kgC). Are urban soils, even the subsoils and sealed soils, contributing to the global stock of C? To address this question, the SOCS and SOCCT of two cities, New York City (NYC) and Paris, were compared. In NYC, soil samples were collected with a pedological standardized method to 1 m depth. The bulk density (Db) was measured; SOC and SOCS were calculated for 0-30 cm and 30-100 cm depths in open (unsealed) soils and sealed soils. In Paris, the samples were collected for 0-30 cm depth in open soils and sealed soils by different sampling methods. If SOC was measured, Db had to be estimated using pedotransfer functions (PTFs) refitted from the literature on NYC data; hence, SOCS was estimated. Globally, SOCS for open soils were not significantly different between both cities (11.3 ±â€¯11.5 kgC m-2 in NYC; 9.9 ±â€¯3.9 kgC m-2 in Paris). Nevertheless, SOCS was lower in sealed soils (2.9 ±â€¯2.6 kgC m-2 in NYC and 3.4 ±â€¯1.2 kgC m-2 in Paris). The SOCCT was similar between both cities for 0-30 cm (3.8 TgC in NYC and 3.5 TgC in Paris) and was also significant for the 30-100 cm layer in NYC (5.8 TgC). A comparison with estimated SOCCT in agricultural and forest soils demonstrated that the city's open soils represent important pools of organic carbon (respectively 110.4% and 44.5% more C in NYC and Paris than in agricultural soils, for 0-30 cm depth). That was mainly observable for the 1 m depth (146.6% more C in NYC than in agricultural soils). The methodology to assess urban SOCS was also discussed.

A single blood test adjusted for different liver fibrosis targets improves fibrosis staging and especially cirrhosis diagnosis.

Fibrosis blood tests are usually developed using significant fibrosis, which is a unique diagnostic target; however, these tests are employed for other diagnostic targets, such as cirrhosis. We aimed to improve fibrosis staging accuracy by simultaneously targeting biomarkers for several diagnostic targets. A total of 3,809 patients were included, comprising 1,012 individuals with chronic hepatitis C (CHC) into a derivation population and 2,797 individuals into validation populations of different etiologies (CHC, chronic hepatitis B, human immunodeficiency virus/CHC, nonalcoholic fatty liver disease, alcohol) using Metavir fibrosis stages as reference. FibroMeter biomarkers were targeted for different fibrosis-stage combinations into classical scores by logistic regression. Independent scores were combined into a single score reflecting Metavir stages by linear regression and called Multi-FibroMeter Version Second Generation (V2G). The primary objective was to combine the advantages of a test targeted for significant fibrosis (FibroMeterV2G) with those of a test targeted for cirrhosis (CirrhoMeterV2G). In the derivation CHC population, we first compared Multi-FibroMeterV2G to FibroMeterV2G and observed significant increases in the cirrhosis area under the receiver operating characteristic curve (AUROC), Obuchowski index (reflecting all fibrosis-stage AUROCs), and classification metric (six classes expressed as a correctly classified percentage) and a nonsignificant increase in significant fibrosis AUROC. Thereafter, we compared it to CirroMeterV2G and observed a nonsignificant increase in the cirrhosis AUROC. In all 3,809 patients, respective accuracies for Multi-FibroMeterV2G and FibroMeterV2G were the following: cirrhosis AUROC, 0.906 versus 0.878 (P < 0.001; versus CirroMeterV2G, 0.897, P = 0.014); Obuchowski index, 0.795 versus 0.791 (P = 0.059); classification, 86.0% versus 82.1% (P < 0.001); significant fibrosis AUROC, 0.833 versus 0.832 (P = 0.366). Multi-FibroMeterV2G had the highest correlation with the area of portoseptal fibrosis and the highest reproducibility over time. Correct classification rates of Multi-FibroMeter with hyaluronate (V2G, 86.0%) or without (V3G, 86.1%) did not differ (P = 0.938). Conclusion: Multitargeting biomarkers significantly improves fibrosis staging and especially cirrhosis diagnosis compared to classical single-targeted blood tests. (Hepatology Communications 2018;2:455-466).

sHSPdb: a database for the analysis of small Heat Shock Proteins.

BACKGROUND: small Heat Shock Proteins (sHSP) is a wide proteins family. SHSP are found in all kingdoms and they play critical roles in plant stress tolerance mechanisms (as well as in pathogenic microorganisms and are implicated in human diseases). RESULTS: sHSPdb (small Heat Shock Proteins database) is an integrated resource containing non-redundant, full-length and curated sequences of sHSP, classified on the basis of amino acids motifs and physico-chemical properties. sHSPdb gathers data about sHSP defined by various databases (Uniprot, PFAM, CDD, InterPro). It provides a browser interface for retrieving information from the whole database and a search interface using various criteria for retrieving a refined subset of entries. Physicochemical properties, amino acid composition and combinations are calculated for each entry. sHSPdb provides automatic statistical analysis of all sHSP properties. Among various possibilities, sHSPdb allows BLAST searches, alignment of selected sequences and submission of sequences. CONCLUSIONS: sHSPdb is a new database containing information about sHSP from all kingdoms. sHSPdb provides a classification of sHSP, as well as tools and data for the analysis of the structure - function relationships of sHSP. Data are mainly related to various physico-chemical properties of the amino acids sequences of sHSP. sHSPdb is accessible at http://forge.info.univ-angers.fr/~gh/Shspdb/index.php .

Differences in stability of seed-associated microbial assemblages in response to invasion by phytopathogenic microorganisms.

Seeds are involved in the vertical transmission of microorganisms from one plant generation to another and consequently act as reservoirs for the plant microbiota. However, little is known about the structure of seed-associated microbial assemblages and the regulators of assemblage structure. In this work, we have assessed the response of seed-associated microbial assemblages of Raphanus sativus to invading phytopathogenic agents, the bacterial strain Xanthomonas campestris pv. campestris (Xcc) 8004 and the fungal strain Alternaria brassicicola Abra43. According to the indicators of bacterial (16S rRNA gene and gyrB sequences) and fungal (ITS1) diversity employed in this study, seed transmission of the bacterial strain Xcc 8004 did not change the overall composition of resident microbial assemblages. In contrast seed transmission of Abra43 strongly modified the richness and structure of fungal assemblages without affecting bacterial assemblages. The sensitivity of seed-associated fungal assemblage to Abra43 is mostly related to changes in relative abundance of closely related fungal species that belong to the Alternaria genus. Variation in stability of the seed microbiota in response to Xcc and Abra43 invasions could be explained by differences in seed transmission pathways employed by these micro-organisms, which ultimately results in divergence in spatio-temporal colonization of the seed habitat.

The severity of nonalcoholic fatty liver disease is associated with gut dysbiosis and shift in the metabolic function of the gut microbiota.

UNLABELLED: Several animal studies have emphasized the role of gut microbiota in nonalcoholic fatty liver disease (NAFLD). However, data about gut dysbiosis in human NAFLD remain scarce in the literature, especially studies including the whole spectrum of NAFLD lesions. We aimed to evaluate the association between gut dysbiosis and severe NAFLD lesions, that is, nonalcoholic steatohepatitis (NASH) and fibrosis, in a well-characterized population of adult NAFLD. Fifty-seven patients with biopsy-proven NAFLD were enrolled. Taxonomic composition of gut microbiota was determined using 16S ribosomal RNA gene sequencing of stool samples. Thirty patients had F0/F1 fibrosis stage at liver biopsy (10 with NASH), and 27 patients had significant F≥2 fibrosis (25 with NASH). Bacteroides abundance was significantly increased in NASH and F≥2 patients, whereas Prevotella abundance was decreased. Ruminococcus abundance was significantly higher in F≥2 patients. By multivariate analysis, Bacteroides abundance was independently associated with NASH and Ruminococcus with F≥2 fibrosis. Stratification according to the abundance of these two bacteria generated three patient subgroups with increasing severity of NAFLD lesions. Based on imputed metagenomic profiles, Kyoto Encyclopedia of Genes and Genomes pathways significantly related to NASH and fibrosis F≥2 were mostly related to carbohydrate, lipid, and amino acid metabolism. CONCLUSION: NAFLD severity associates with gut dysbiosis and a shift in metabolic function of the gut microbiota. We identified Bacteroides as independently associated with NASH and Ruminococcus with significant fibrosis. Thus, gut microbiota analysis adds information to classical predictors of NAFLD severity and suggests novel metabolic targets for pre-/probiotics therapies.

Automated morphometry provides accurate and reproducible virtual staging of liver fibrosis in chronic hepatitis C.

BACKGROUND: Liver fibrosis staging provides prognostic value, although hampered by observer variability. We used digital analysis to develop diagnostic morphometric scores for significant fibrosis, cirrhosis and fibrosis staging in chronic hepatitis C. MATERIALS AND METHODS: We automated the measurement of 44 classical and new morphometric descriptors. The reference was histological METAVIR fibrosis (F) staging (F0 to F4) on liver biopsies. The derivation population included 416 patients and liver biopsies ≥20 mm-length. Two validation population included 438 patients. RESULTS: In the derivation population, the area under the receiver operating characteristic (AUROC) for clinically significant fibrosis (F stage ≥2) of a logistic score combining 5 new descriptors (stellar fibrosis area, edge linearity, bridge thickness, bridge number, nodularity) was 0.957. The AUROC for cirrhosis of 6 new descriptors (edge linearity, nodularity, portal stellar fibrosis area, portal distance, granularity, fragmentation) was 0.994. Predicted METAVIR F staging combining 8 morphometric descriptors agreed well with METAVIR F staging by pathologists: κ = 0.868. Morphometric score of clinically significant fibrosis had a higher correlation with porto-septal fibrosis area (r s = 0.835) than METAVIR F staging (r s = 0.756, P < 0.001) and the same correlations with fibrosis biomarkers, e.g., serum hyaluronate: r s = 0.484 versus r s = 0.476 for METAVIR F (P = 0.862). In the validation population, the AUROCs of clinically significant fibrosis and cirrhosis scores were, respectively: 0.893 and 0.993 in 153 patients (biopsy < 20 mm); 0.955 and 0.994 in 285 patients (biopsy ≥ 20 mm). The three morphometric diagnoses agreed with consensus expert reference as well as or better than diagnoses by first-line pathologists in 285 patients, respectively: significant fibrosis: 0.733 versus 0.733 (κ), cirrhosis: 0.900 versus 0.827, METAVIR F: 0.881 versus 0.865. CONCLUSION: The new automated morphometric scores provide reproducible and accurate diagnoses of fibrosis stages via "virtual expert pathologist."

Phenoplant: a web resource for the exploration of large chlorophyll fluorescence image datasets.

BACKGROUND: Image analysis is increasingly used in plant phenotyping. Among the various imaging techniques that can be used in plant phenotyping, chlorophyll fluorescence imaging allows imaging of the impact of biotic or abiotic stresses on leaves. Numerous chlorophyll fluorescence parameters may be measured or calculated, but only a few can produce a contrast in a given condition. Therefore, automated procedures that help screening chlorophyll fluorescence image datasets are needed, especially in the perspective of high-throughput plant phenotyping. RESULTS: We developed an automatic procedure aiming at facilitating the identification of chlorophyll fluorescence parameters impacted on leaves by a stress. First, for each chlorophyll fluorescence parameter, the procedure provides an overview of the data by automatically creating contact sheets of images and/or histograms. Such contact sheets enable a fast comparison of the impact on leaves of various treatments, or of the contrast dynamics during the experiments. Second, based on the global intensity of each chlorophyll fluorescence parameter, the procedure automatically produces radial plots and box plots allowing the user to identify chlorophyll fluorescence parameters that discriminate between treatments. Moreover, basic statistical analysis is automatically generated. Third, for each chlorophyll fluorescence parameter the procedure automatically performs a clustering analysis based on the histograms. This analysis clusters images of plants according to their health status. We applied this procedure to monitor the impact of the inoculation of the root parasitic plant Phelipanche ramosa on Arabidopsis thaliana ecotypes Col-0 and Ler. CONCLUSIONS: Using this automatic procedure, we identified eight chlorophyll fluorescence parameters discriminating between the two ecotypes of A. thaliana, and five impacted by the infection of Arabidopsis thaliana by P. ramosa. More generally, this procedure may help to identify chlorophyll fluorescence parameters impacted by various types of stresses. We implemented this procedure at http://www.phenoplant.org freely accessible to users of the plant phenotyping community.

Ex vivo thrombin generation patterns in septic patients with and without disseminated intravascular coagulation.

INTRODUCTION: The thrombin generation test (TGT) describes the ability of the plasma to generate thrombin. Its usefulness in septic patients has yet to be assessed. METHODS: Patients admitted for severe sepsis in a medical intensive care unit were sampled for TGT on day 0, 3, 6, and 10. TGT data were compared to "classical" hemostastic tests and to outcome parameters, notably disseminated intravascular coagulation (DIC) according to International Society for Thrombosis and Hemostasis criteria as well as survival. RESULTS: A total of 102 patients were recruited of whom 11 received therapeutic anticoagulation and showed profoundly-altered TGT parameters. In comparison to healthy subjects, the 67 septic patients without DIC exhibited longer Lag times, higher Rate Indices, no change in peak or amount of thrombin generated, although the return to baseline was prolonged. In the 24 DIC patients, Lag time and Rate Index did not differ from healthy subjects (Rate Index being significantly lower than in Sepsis patients). The decreases in peak and amount of thrombin generated were not significant. Return to baseline was prolonged comparatively to Sepsis patients. Due to a large overlap of TGT values between groups, the ability of TGT parameters to diagnose DIC or predict survival was respectively poor or absent. CONCLUSION: The thrombin Generation Test displayed particular patterns in septic patients and in septic DIC patients. The wide overlap between patients in TGT values prevents the usefulness of this test in clinical practice.

Emergence shapes the structure of the seed microbiota.

Seeds carry complex microbial communities, which may exert beneficial or deleterious effects on plant growth and plant health. To date, the composition of microbial communities associated with seeds has been explored mainly through culture-based diversity studies and therefore remains largely unknown. In this work, we analyzed the structures of the seed microbiotas of different plants from the family Brassicaceae and their dynamics during germination and emergence through sequencing of three molecular markers: the ITS1 region of the fungal internal transcribed spacer, the V4 region of 16S rRNA gene, and a species-specific bacterial marker based on a fragment of gyrB. Sequence analyses revealed important variations in microbial community composition between seed samples. Moreover, we found that emergence strongly influences the structure of the microbiota, with a marked reduction of bacterial and fungal diversity. This shift in the microbial community composition is mostly due to an increase in the relative abundance of some bacterial and fungal taxa possessing fast-growing abilities. Altogether, our results provide an estimation of the role of the seed as a source of inoculum for the seedling, which is crucial for practical applications in developing new strategies of inoculation for disease prevention.

Comparison of amino acids physico-chemical properties and usage of late embryogenesis abundant proteins, hydrophilins and WHy domain.

Late Embryogenesis Abundant proteins (LEAPs) comprise several diverse protein families and are mostly involved in stress tolerance. Most of LEAPs are intrinsically disordered and thus poorly functionally characterized. LEAPs have been classified and a large number of their physico-chemical properties have been statistically analyzed. LEAPs were previously proposed to be a subset of a very wide family of proteins called hydrophilins, while a domain called WHy (Water stress and Hypersensitive response) was found in LEAP class 8 (according to our previous classification). Since little is known about hydrophilins and WHy domain, the cross-analysis of their amino acids physico-chemical properties and amino acids usage together with those of LEAPs helps to describe some of their structural features and to make hypothesis about their function. Physico-chemical properties of hydrophilins and WHy domain strongly suggest their role in dehydration tolerance, probably by interacting with water and small polar molecules. The computational analysis reveals that LEAP class 8 and hydrophilins are distinct protein families and that not all LEAPs are a protein subset of hydrophilins family as proposed earlier. Hydrophilins seem related to LEAP class 2 (also called dehydrins) and to Heat Shock Proteins 12 (HSP12). Hydrophilins are likely unstructured proteins while WHy domain is structured. LEAP class 2, hydrophilins and WHy domain are thus proposed to share a common physiological role by interacting with water or other polar/charged small molecules, hence contributing to dehydration tolerance.

Improved fibrosis staging by elastometry and blood test in chronic hepatitis C.

AIMS: Our main objective was to improve non-invasive fibrosis staging accuracy by resolving the limits of previous methods via new test combinations. Our secondary objectives were to improve staging precision, by developing a detailed fibrosis classification, and reliability (personalized accuracy) determination. METHODS: All patients (729) included in the derivation population had chronic hepatitis C, liver biopsy, 6 blood tests and Fibroscan. Validation populations included 1584 patients. RESULTS: The most accurate combination was provided by using most markers of FibroMeter and Fibroscan results targeted for significant fibrosis, i.e. 'E-FibroMeter'. Its classification accuracy (91.7%) and precision (assessed by F difference with Metavir: 0.62 ± 0.57) were better than those of FibroMeter (84.1%, P < 0.001; 0.72 ± 0.57, P < 0.001), Fibroscan (88.2%, P = 0.011; 0.68 ± 0.57, P = 0.020), and a previous CSF-SF classification of FibroMeter + Fibroscan (86.7%, P < 0.001; 0.65 ± 0.57, P = 0.044). The accuracy for fibrosis absence (F0) was increased, e.g. from 16.0% with Fibroscan to 75.0% with E-FibroMeter (P < 0.001). Cirrhosis sensitivity was improved, e.g. E-FibroMeter: 92.7% vs. Fibroscan: 83.3%, P = 0.004. The combination improved reliability by deleting unreliable results (accuracy <50%) observed with a single test (1.2% of patients) and increasing optimal reliability (accuracy ≥85%) from 80.4% of patients with Fibroscan (accuracy: 90.9%) to 94.2% of patients with E-FibroMeter (accuracy: 92.9%), P < 0.001. The patient rate with 100% predictive values for cirrhosis by the best combination was twice (36.2%) that of the best single test (FibroMeter: 16.2%, P < 0.001). CONCLUSION: The new test combination increased: accuracy, globally and especially in patients without fibrosis, staging precision, cirrhosis prediction, and even reliability, thus offering improved fibrosis staging.

Computational and statistical analyses of amino acid usage and physico-chemical properties of the twelve late embryogenesis abundant protein classes.

Late Embryogenesis Abundant Proteins (LEAPs) are ubiquitous proteins expected to play major roles in desiccation tolerance. Little is known about their structure - function relationships because of the scarcity of 3-D structures for LEAPs. The previous building of LEAPdb, a database dedicated to LEAPs from plants and other organisms, led to the classification of 710 LEAPs into 12 non-overlapping classes with distinct properties. Using this resource, numerous physico-chemical properties of LEAPs and amino acid usage by LEAPs have been computed and statistically analyzed, revealing distinctive features for each class. This unprecedented analysis allowed a rigorous characterization of the 12 LEAP classes, which differed also in multiple structural and physico-chemical features. Although most LEAPs can be predicted as intrinsically disordered proteins, the analysis indicates that LEAP class 7 (PF03168) and probably LEAP class 11 (PF04927) are natively folded proteins. This study thus provides a detailed description of the structural properties of this protein family opening the path toward further LEAP structure - function analysis. Finally, since each LEAP class can be clearly characterized by a unique set of physico-chemical properties, this will allow development of software to predict proteins as LEAPs.