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The prediction of protein-ligand complexes (PLC), using both experimental and predicted structures, is an active and important area of research, underscored by the inclusion of the Protein-Ligand Interaction category in the latest round of the Critical Assessment of Protein Structure Prediction experiment CASP15. The prediction task in CASP15 consisted of predicting both the 3-dimensional structure of the receptor protein as well as the position and conformation of the ligand. This paper addresses the challenges and proposed solutions for devising automated benchmarking techniques for PLC prediction. The reliability of experimentally solved PLC as ground truth reference structures is assessed using various validation criteria. Similarity of PLC to previously released complexes are employed to judge the novelty and difficulty of a PLC as a prediction target. We show that the commonly used PDBBind time-split test-set is inappropriate for comprehensive PLC evaluation. Finally, we introduce a fully automated pipeline that predicts PLC and evaluates the accuracy of the protein structure, ligand pose, and protein-ligand interactions.

Prediction categories in the Critical Assessment of Structure Prediction (CASP) experiments change with the need to address specific problems in structure modeling. In CASP15, four new prediction categories were introduced: RNA structure, ligand-protein complexes, accuracy of oligomeric structures and their interfaces, and ensembles of alternative conformations. This paper lists technical specifications for these categories and describes their integration in the CASP data management system.

The Continuous Automated Model EvaluatiOn (CAMEO) platform complements the biennial CASP experiment by conducting fully automated blind evaluations of three-dimensional protein prediction servers based on the weekly prerelease of sequences of those structures, which are going to be published in the upcoming release of the Protein Data Bank. While in CASP14, significant success was observed in predicting the structures of individual protein chains with high accuracy, significant challenges remain in correctly predicting the structures of complexes. By implementing fully automated evaluation of predictions for protein-protein complexes, as well as for proteins in complex with ligands, peptides, nucleic acids, or proteins containing noncanonical amino acid residues, CAMEO will assist new developments in those challenging areas of active research.

Wetlands, especially marshes, support many services such as carbon catchment control or water purification led by primary producers such as phytoplankton and microphytobenthos (PB). The impact of the sedimentary compartment, as source and sink of essential nutrients for the water column, is often neglected in the study of their dynamics and water purification capacity of the systems. This work compared monthly (between February 2020 and April 2021) the benthic and pelagic primary producers' dynamics in two anthropised freshwater marshes (Marans and Genouillé), with the simultaneous follow-up of physico-chemical parameters of the water column and nutrient fluxes at the sediment-water (SWI) interface. It was suggested a strong contribution of phytoplankton (pumping) and the benthic compartment (denitrification) to the water purification of these two nitrates (NO

The Continuous Automated Model EvaluatiOn (CAMEO) platform complements the biennial CASP experiment by conducting fully automated blind evaluations of 3D protein prediction servers based on the weekly pre‐release of sequences of those structures, which are going to be published in the upcoming release of the Protein Data Bank (PDB). While in CASP14 significant success was observed in predicting the structures of individual protein chains with high accuracy, significant challenges remain in correctly predicting the structures of complexes. By implementing fully automated evaluation of predictions for protein-protein complexes, as well as for proteins in complex with ligands, peptides, nucleic acids, or proteins containing non-canonical amino acid residues, CAMEO will assist new developments in those challenging areas of active research.

Activating PIK3CA mutations are known ‘drivers’ of human cancer and developmental overgrowth syndromes. We recently demonstrated that the ‘hotspot’ PIK3CAH1047R variant exerts unexpected allele dose-dependent effects on stemness in human pluripotent stem cells (hPSCs). In this study, we combine high-depth transcriptomics, total proteomics and reverse-phase protein arrays to reveal potentially disease-related alterations in heterozygous cells, and to assess the contribution of activated TGFβ signalling to the stemness phenotype of homozygous PIK3CAH1047R cells. We demonstrate signalling rewiring as a function of oncogenic PI3K signalling strength, and provide experimental evidence that self-sustained stemness is causally related to enhanced autocrine NODAL/TGFβ signalling. A significant transcriptomic signature of TGFβ pathway activation in heterozygous PIK3CAH1047R was observed but was modest and was not associated with the stemness phenotype seen in homozygous mutants. Notably, the stemness gene expression in homozygous PIK3CAH1047R hPSCs was reversed by pharmacological inhibition of NODAL/TGFβ signalling, but not by pharmacological PI3Kα pathway inhibition. Altogether, this provides the first in-depth analysis of PI3K signalling in hPSCs and directly links strong PI3K activation to developmental NODAL/TGFβ signalling. This work illustrates the importance of allele dosage and expression when artificial systems are used to model human genetic disease caused by activating PIK3CA mutations. This article has an associated First Person interview with the first author of the paper., Summary: Transcriptomic and proteomic analyses of iPSCs with allele-dose dependent expression of the PIK3CAH1047R oncogene confirm network rewiring in homozygous mutants, with self-sustained stemness likely driven by constitutive TGFβ/NODAL pathway activation.

It is well known that the development of drug resistance in cancer cells can lead to changes in cell morphology. Here, we describe the use of deep neural networks to analyze this relationship, demonstrating that complex cell morphologies can encode states of signaling networks and unravel cellular mechanisms hidden to conventional approaches. We perform high-content screening of 17 cancer cell lines, generating more than 500 billion data points from similar to 850 million cells. We analyze these data using a deep learning model, resulting in the identification of a continuous 27-dimension space describing all of the observed cell morphologies. From its morphology alone, we could thus predict whether a cell was resistant to ErbB-family drugs, with an accuracy of 74%, and predict the potential mechanism of resistance, subsequently validating the role of MET and insulin-like growth factor 1 receptor (IGF1R) as drivers of cetuximab resistance in in vitro models of lung and head/neck cancer.

International audience; In freshwater systems, sediment can be an important source for the internal loading of phosphate (PO4). The limiting character of this element in such system leads to consider this phenomenon in terms of eutrophication risks and water quality stakes. A four-months follow-up (January, March, April and May 2019) was carried out in a strong PO4 limited secondary channel from an artificial irrigation system of Charente Maritime (France) to link the mobilization of remineralization products in the upper 6 cm layer of sediment (conventional core slicing/centrifugation and DET probes) and the phytoplankton biomass dynamics in the water column. Results showed congruent patterns between the temporal succession of the organic matter mineralization processes in the sediment and the primary biomass dynamics in the water column. In January and March (considered in winter), PO4 proved to be retained by adsorption onto iron oxides in anoxic sediment since pore water nitrate inhibited for about a month the respiration of metal oxides in the first cm of sediment, thus limiting PO4 availability and the phytoplankton growth. In April and May (early spring), after exhaustion of pore water nitrate, the dissolutive reduction of iron oxides released PO4 into pore water generated a significant diffusive outgoing flux from the sediment to the water column with a maximum in April (-1.10E-04±2.81E-05 nmol cm-2 s-1). This release coincided with the nanophytoplankton bloom (5.50 µg Chla L-1) and a potential increase of PO4 concentration in the water column. This work provides some insight on the importance of benthic-pelagic coupling in anthropogenic systems. This conceptual model has to be deployed on other sites of interest where internal loading of P takes precedence over external inputs and nitrate mitigation drives its benthic recycling and ultimately its bioavailability. This is to be essential to characterize the aquatic environment quality in order to limit eutrophication risks.

A PI3Kα-selective inhibitor has recently been approved for use in breast tumours harbouring mutations inPIK3CA, the gene encoding PI3Kα. Preclinical studies have suggested that the PI3K/AKT/mTORC1 signalling pathway influences stemness, a dedifferentiation-related cellular phenotype associated with aggressive cancer. No direct evidence for such a correlation has been demonstrated to date in human tumours. In two independent human breast cancer cohorts, encompassing nearly 3,000 tumour samples, transcriptional footprint-based analysis uncovered a positive linear association between transcriptionally-inferred PI3K signalling scores and stemness scores. Unexpectedly, stratification of tumours according toPIK3CAgenotype revealed a “biphasic” relationship of mutantPIK3CAallele dosage with these scores. Relative to tumour samples withoutPIK3CAmutations, the presence of a single copy of a hotspotPIK3CAvariant was associated with lower PI3K signalling and stemness scores, whereas tumours with multiple copies ofPIK3CAhotspot mutations showed higher PI3K signalling and stemness scores. This observation was recapitulated in a human cell model of heterozygous and homozygousPIK3CAH1047Rexpression. Collectively, our analysis provides evidence for a signalling strength-dependent PI3K-stemness relationship in human breast cancer, which may aid future patient stratification for PI3K-targeted therapies.

International audience; The increase in extreme events such as storms is one of the major threats that coastal ecosystems will have to face in the near future. In such a context, both maturation and ecological successions processes remain at the core of ecology to better anticipate the changes to ecosystem biodiversity and functions facing environmental stressors. However, these concepts are mainly approached through closed experimental studies that oversimplify the mechanisms. A survey was carried out on a ‘natural’ and open ecosystem subjected to an acute disturbance, i.e. a marine submersion of freshwater drained marshes, occurring after a storm. Plankton biomass, production and taxonomic/functional phytoplankton diversity were followed weekly at four stations over 2 months. Most of the stations were disrupted by this acute disturbance and displayed gradual growth and development, as described in the classical maturation process. The main differences between stations were attributed to the heterogeneity of the communities before the storm, the intensity of the disturbance and the different human actions performed to recover the freshwater environment. The concept of ‘ecological resilience’ was thus better suited than ‘engineering resilience’ for such open systems facing constant fluctuations in environmental drivers. With regard to ecological succession, the more impacted stations were marked by a significant change in taxonomic beta-diversity, with numerous stochastic processes, due to taxa dispersion. They first exhibited a convergence in functional traits due to the increase in nutrient availability drained from the catchment basin and then an increase in divergence when nutrients became limited.

International audience; Lectins, and related receptors such as adhesins and toxins, are glycan-binding proteins from all origins that decipher the glycocode, i.e. the structural information encoded in the conformation of complex carbohydrates present on the surface of all cells. Lectins are still poorly classified and annotated, but since their functions are based on ligand recognition, their 3D-structures provide a solid foundation for characterization. UniLectin3D is a curated database that classifies lectins on origin and fold, with cross-links to literature, other databases in glycosciences and functional data such as known specificity. The database provides detailed information on lectins, their bound glycan ligands, and features their interactions using the Protein-Ligand Interaction Profiler (PLIP) server. Special care was devoted to the description of the bound glycan ligands with the use of simple graphical representation and numerical format for cross-linking to other databases in glyco-science. We conceived the design of the database architecture and the navigation tools to account for all organisms, as well as to search for oligosaccharide epitopes complexed within specified binding sites. UniLectin3D is accessible at https://www.unilectin. eu/unilectin3D.

Activating PIK3CA mutations are known “drivers” of human cancer and developmental overgrowth syndromes. We recently demonstrated that the “hotspot” PIK3CAH1047R variant exerts unexpected allele dose-dependent effects on stemness in human pluripotent stem cells (hPSCs). In the present study, we combine high-depth transcriptomics, total proteomics and reverse-phase protein arrays to reveal potentially disease-related alterations in heterozygous cells, and to assess the contribution of activated TGFβ signalling to the stemness phenotype of PIK3CAH1047R homozygous cells. We demonstrate signalling rewiring as a function of oncogenic PI3K signalling dose, and provide experimental evidence that self-sustained stemness is causally related to enhanced autocrine NODAL/TGFβ signalling. A significant transcriptomic signature of TGFβ pathway activation in PIK3CAH1047R heterozygous was observed but was modest and was not associated with the stemness phenotype seen in homozygous mutants. Notably, the stemness gene expression in PIK3CAH1047R homozygous iPSCs was reversed by pharmacological inhibition of TGFβ signalling, but not by pharmacological PI3Kα pathway inhibition. Altogether, this provides the first in-depth analysis of PI3K signalling in human pluripotent stem cells and directly links dose-dependent PI3K activation to developmental NODAL/TGFβ signalling.

We describe a novel Bayesian method for estimating protein concentration and phosphorylation site occupancy ratios from mass spectrometry experiments. Our variance model assigns standard deviations to all quantitative ratios, even when only a single peptide is observed, increasing the number of quantifiable observations in a sample compared to conventional methods. We further demonstrate the application of this method using a dataset investigating the impact of the PRKAR1A-RET gene fusion in immortalized thyroid cells.

Proteomics has allowed the discovery and validation of a massive number of biomarkers. However most of them suffer from insufficient specificity and sensitivity and therefore didn't translate to clinical practice. Combining biomarkers with different properties into panels can be an efficient way to bypass these limitations and facilitate the translation of biomarkers into clinical practice.

Proteomics has allowed the discovery and validation of a massive number of biomarkers. However most of them suffer from insufficient specificity and sensitivity and therefore didn't translate to clinical practice. Combining biomarkers with different properties into panels can be an efficient way to bypass these limitations and facilitate the translation of biomarkers into clinical practice.

The functional diversity of two planktonic functional compartments, the nano-microphytoplankton and the mesozooplankton was used in order to better understand i) the drained marshes functioning and their related ecological functions, ii) the impacts of human control (replenishment) and human activities on the catchment basin (urbanization and catchment basin size). It was based on a monthly seasonal survey on 7 freshwater drained marshes. Both nano-microphyto- and mesozooplankton displayed high seasonal variations linked to the environmental fluctuations and human control on sea lock gates. Winter presented the lower biomasses of both compartments. Winter that is characterized by low water temperature, low light availability and high flood is actually related to the dominance of tychopelagic phytoplankton and K-strategists zooplankton. Spring and summer were characterized by i) the succession of pelagic large cells, small cells and then taxa with alternatives food strategies due to nitrogen limitation and phosphorous desorption from the sediment leading to eutrophication processes and ii) the dominance of r-strategists for mesozooplankton. The artificial summer replenishment acts positively on water quality by decreasing the eutrophication processes since the nitrogen inputs limit the proliferation of phytoplankton mixotrophs and diazotrophs and increase the ecological efficiency during the warm period. Both small and large catchment basins may lead to summer eutrophication processes in drained marshes since the largest ones imply higher hydrodynamic features at the root of large inputs of nitrogen nutrient favoring the phytoplankton development while the smallest ones exhibit hypoxia problems due to high proliferation of macrophytes. Urbanized marshes are less subjected to eutrophication during summer than non urbanized marshes due to more recurrent nutrient inputs from urban waste. However they exhibited a lower ecological efficiency. The results suggest that a better management of the hydrodynamics of such anthropogenic systems can avoid eutrophication risks on coastal areas.

It is well known that the development of drug resistance in cancer cells can lead to a change in cell morphology. We reasoned that machine-learning techniques could thus be used to elucidate far greater insight into the relationship between cell shape and signaling. To test this hypothesis we performed a large high content screen on drug sensitive and drug resistance cancer cells, and analysed the shape of these cells using a deep neural network. Our model identified a continuous 27-dimension space describing all of the observed cell morphologies from which we were able to predict drug resistance with an accuracy of 74%. In addition, analyzing changes in cell morphology identified signaling networks that, when perturbed, caused the death of drug resistant cells. These findings suggests that complex morphologies can decode states of signaling networks seemingly unrelated to cell shape, and that analysis of this information can unravel cellular mechanisms hidden to conventional measurements.

Cell migration is a central biological process that requires fine coordination of molecular events in time and space. A deregulation of the migratory phenotype is also associated with pathological conditions including cancer where cell motility has a causal role in tumor spreading and metastasis formation. Thus cell migration is of critical and strategic importance across the complex disease spectrum as well as for the basic understanding of cell phenotype. Experimental studies of the migration of cells in monolayers are often conducted with 'wound healing' assays. Analysis of these assays has traditionally relied on how the wound area changes over time. However this method does not take into account the shape of the wound. Given the many options for creating a wound healing assay and the fact that wound shape invariably changes as cells migrate this is a significant flaw. Here we present a novel software package for analyzing concerted cell velocity in wound healing assays. Our method encompasses a wound detection algorithm based on cell confluency thresholding and employs a Bayesian approach in order to estimate concerted cell velocity with an associated likelihood. We have applied this method to study the effect of siRNA knockdown on the migration of a breast cancer cell line and demonstrate that cell velocity can track wound healing independently of wound shape and provides a more robust quantification with significantly higher signal to noise ratios than conventional analyses of wound area. The software presented here will enable other researchers in any field of cell biology to quantitatively analyze and track live cell migratory processes and is therefore expected to have a significant impact on the study of cell migration, including cancer relevant processes. Installation instructions, documentation and source code can be found at http://bowhead.lindinglab.science licensed under GPLv3.

Sweat is one of the less employed biofluids for discovery of markers in spite of its increased application in medicine for detection of drugs or for diagnostic of cystic fibrosis. In this research, human sweat was used as clinical sample to develop a screening tool for lung cancer, which is the carcinogenic disease with the highest mortality rate owing to the advanced stage at which it is usually detected. In this context, a method based on the metabolite analysis of sweat to discriminate between patients with lung cancer versus smokers as control individuals is proposed. The capability of the metabolites identified in sweat to discriminate between both groups of individuals was studied and, among them, a trisaccharide phosphate presented the best independent performance in terms of the specificity/sensitivity pair (80 and 72.7%, respectively). Additionally, two panels of metabolites were configured using the PanelomiX tool as an attempt to reduce false negatives (at least 80% specificity) and false positives (at least 80% sensitivity). The first panel (80% specificity and 69% sensitivity) was composed by suberic acid, a tetrahexose, and a trihexose, while the second panel (69% specificity and 80% sensitivity) included nonanedioic acid, a trihexose, and the monoglyceride MG(22:2). Thus, the combination of the five metabolites led to a single panel providing 80% specificity and 79% sensitivity, reducing the false positive and negative rates to almost 20%. The method was validated by estimation of within-day and between-days variability of the quantitative analysis of the five metabolites.

Network medicine aims at unraveling cell signaling networks to propose personalized treatments for patients suffering from complex diseases. In this short review, we show the relevance of network medicine to cancer treatment by outlining the potential convergence points of the most recent technological and scientific developments in both drug design and signaling network analysis. Clinical Pharmacology & Therapeutics (2013); 94 6, 646–650. doi:10.1038/clpt.2013.171

International audience; The degradation of water quality and the multiple conflicts of interest between users make marsh restoration very important. A Water Quality Evaluation System (WQES) was developed for river systems by the European Water Framework Directive (WFD). Some form of biologically-based, habitat-specific reference standard seems absolutely essential for wise management and stewardship of marsh ecosystems. The goal of this study was to develop a statistical method to define and to characterize a water body typology for drained marshes of the Charente-Maritime wetlands on the French Atlantic coast, placing particular emphasis on environmental factors as hydraulic functioning, human activities and pedological substratum. The Charente-Maritime marshes represent a good field study because of his high diversity of types of marshes and of anthropogenic activities in a restrictive area thus erasing spatial climatic effect (latitude effect). The statistical method developed here had permitted to define and characterize 12 different water bodies, 7 in freshwater (F1 to F7) and 5 in salt water marshes for the Charente-Maritime area. This typology demonstrated an important link between the size catchment area, nitrate concentrations, and leaching of precipitation from cultured soils. Even though the Charente-Maritime marshes are strongly impacted by humans, they may still retain the ability to remove nitrate. The increasing gradient of water renewal in the freshwater marshes from F1 to F7 explained the decreasing gradient of eutrophication. A better management of the hydrodynamic of the marshes can avoid eutrophication risk on the coastal sea area. Reliance on the WFD parameter set necessarily placed limits on the kinds of interpretations that could be made and on the study's potential contribution to the basic science of marshes. Ecologically-based insights regarding both external flows (links between ecosystems, meta-ecosystem theory) and internal flows (structure of the planktonic food web) seem an essential prerequisite for further advances in the study of marsh ecosystems.

OBJECTIVES A critical step before treatment of human African trypanosomiasis (HAT) is the correct staging of the disease. As late stage is established when trypanosomes cross the blood-brain barrier and invade the central nervous system, we hypothesized that matrix metalloproteinases and cell adhesion molecules could indicate, alone or in combination, the disease progression from the first to the second stage of HAT. METHODS We measured the levels of MMP-2, MMP-9, ICAM-1, VCAM-1 and E-selectin in the cerebrospinal fluid (CSF) of 63 Trypanosoma brucei gambiense-infected patients (15 stage 1 and 48 stage 2). Staging was based on counting of white blood cells (WBC) and/or parasite detection in CSF. Concentrations were obtained either by ELISA or multiplex bead suspension assays, and results were compared with three known HAT staging markers (CXCL10, CXCL8 and H-FABP). RESULTS ICAM-1 and MMP-9 accurately discriminated between stage 1 and stage 2 patients with HAT with 95% sensitivity (SE) for 100% specificity (SP), which was better than CXCL10 (93% SE for 100% SP), one of the most promising known markers. Combination of ICAM-1 and MMP-9 with H-FABP provided a panel that resulted in 100% of SE and SP for staging HAT. CONCLUSIONS ICAM-1 and MMP-9, alone or in combination, appeared as powerful CSF staging markers of HAT. Final validation of all newly discovered staging markers on a large multi-centric cohort including both forms of the disease as well as patients with others infections should be performed.

PURPOSE: Accurate early anticipation of long-term irreversible brain damage during the acute phase of patients with aneurysmal subarachnoid hemorrhage (aSAH) remains difficult. Using a combination of clinical scores together with brain injury-related biomarkers (H-FABP, NDKA, UFD1 and S100beta), this study aimed at developing a multiparameter prognostic panel to facilitate early outcome prediction following aSAH. METHODS: Blood samples of 141 aSAH patients from two separated cohorts (sets of 28 and 113 patients) were prospectively enrolled and analyzed with 14 months of delay. Patients were admitted within 48 h following aSAH onset. A venous blood sample was withdrawn within 12 h after admission. H-FABP, NDKA, UFD1, S100beta and troponin I levels were determined using classical immunoassays. The World Federation of Neurological Surgeons (WFNS) at admission and the Glasgow Outcome Score (GOS) at 6 months were evaluated. RESULTS: In the two cohorts, blood concentration of H-FABP, S100beta and troponin I at admission significantly predicted unfavorable outcome (GOS 1-2-3). A multivariate analysis identified a six-parameter panel, including WFNS, H-FABP, S100beta, troponin I, NDKA and UFD-1; when at least three of these parameters were simultaneously above cutoff values, prediction of unfavorable outcome reached around 70% sensitivity in both cohorts for 100% specificity. CONCLUSION: The use of this panel, including four brain injury-related proteins, one cardiac marker and a clinical score, could be a valuable tool to identify aSAH patients at risk of poor outcome.

We conducted a weekly survey at two stations of a French coastal marsh during the transition from winter to spring, when the sea lock gates were closed. Field measurements and laboratory experiments were combined in order to describe the structure and dynamics of planktonic food webs. Physico-chemical parameters were measured, and food web typology was described for the first time in the marsh using plankton biomass and internal flux assessment. Both stations changed from a “biological winter” to food webs identified as “multivorous” and passed through to a herbivorous food web. However, food web structure differed significantly between the two stations at the end of the study. Station A remained as a multivorous food web, while station B changed to a strong multivorous food web. After the sea lock gates closing (end of March), an increase in phosphorus concentrations in the water column at station B may have controlled bacterial and phytoplankton development and could explain, at least in part, the differences between the two stations. Our study suggests moreover that differences in water renewal between the two stations could have been responsible for the differences observed. Sea lock gates closing seems to be responsible for the rapid changes observed in food web structure, suggesting that the effects of human hydraulic management on ecosystem functioning in marshes is not yet well understood.

Background & Aims Algorithms for diagnosis of malignant common bile duct (CBD) stenoses are complex and lack accuracy. Malignant tumors secrete large numbers of extracellular vesicles (EVs) into surrounding fluids; EVs might therefore serve as biomarkers for diagnosis. We investigated whether concentrations of EVs in bile could discriminate malignant from nonmalignant CBD stenoses. Methods We collected bile and blood samples from 50 patients undergoing therapeutic endoscopic retrograde cholangiopancreatography at university hospitals in Europe for CBD stenosis of malignant (pancreatic cancer, n = 20 or cholangiocarcinoma, n = 5) or nonmalignant (chronic pancreatitis [CP], n = 15) origin. Ten patients with CBD obstruction due to biliary stones were included as controls. EV concentrations in samples were determined by nanoparticle tracking analyses. The discovery cohort comprised the first 10 patients with a diagnosis of pancreatic cancer, based on tissue analysis, and 10 consecutive controls. Using samples from these subjects, we identified a threshold concentration of bile EVs that could best discriminate between patients with pancreatic cancer from controls. We verified the diagnostic performance of bile EV concentration by analyzing samples from the 30 consecutive patients with a diagnosis of malignant (pancreatic cancer or cholangiocarcinoma, n = 15) or nonmalignant (CP, n = 15) CBD stenosis. Samples were compared using the Mann-Whitney test and nonparametric Spearman correlation analysis. Receiver operating characteristic area under the curve was used to determine diagnostic accuracy. Results In both cohorts, the median concentration of EVs was significantly higher in bile samples from patients with malignant CBD stenoses than controls or nonmalignant CBD stenoses (2.41 × 10 15 vs 1.60 × 10 14 nanoparticles/L in the discovery cohort; P 15 vs 1.26 × 10 14 nanoparticles/L in the verification cohort; P 14 nanoparticles/L in bile best distinguished patients with malignant CBD from controls in the discovery cohort. In the verification cohort, this threshold discriminated malignant from nonmalignant CBD stenoses with 100% accuracy. Serum concentration of EVs distinguished patients with malignant vs patients with nonmalignant CBD stenoses with 63.3% diagnostic accuracy. Conclusions Concentration of EVs in bile samples discriminates between patients with malignant vs nonmalignant CBD stenosis with 100% accuracy. Further studies are needed to confirm these findings. Clinical Trial registration no: ISRCTN66835592.

The outcome after severe traumatic brain injury (TBI) is largely unfavorable, with approximately two thirds of patients suffering from severe disabilities or dying during the first 6 months. Existing predictive models displayed only limited utility for outcome prediction in individual patients. Time courses of heart-fatty acidic binding protein (H-FABP) and their association with outcome were investigated and compared with S100b. Forty-nine consecutive patients with severe TBI (sTBI; Head component of the Abbreviated Injury Scale [HAIS]3) with mono and multiple trauma were enrolled in this study. Enzyme-linked immunosorbent assay measured blood concentrations of H-FABP and S100b at 6, 12, 24, and 48 h after TBI. Outcome measures were conscious state at 14 days (Glasgow Coma Scale), disability (Glasgow Outcome Scale Extended; GOSE), and mortality at 3 months. Univariate logistic regression analysis and receiver operating characteristic curves analysis were carried out. Maximal H-FABP and S100b concentrations were observed at 6 h after TBI (34.4±34.0 and 0.64±0.99 ng/mL, respectively). Patients with multi-trauma had significantly higher H-FABP concentrations at 24 and 48 h (22.6±25.6 and 12.4±18.2 ng/mL, respectively), compared to patients with mono trauma (6.9±5.1 and 3.7±4.2 ng/mL, respectively). In the first 48 h, H-FABP and S100b were inversely correlated with the GOSE at 3 months; H-FABP at 48 h predicted mortality with 75% sensitivity and 93% specificity. Early blood levels of H-FABP after sTBI have prognostic significance for survival and disability.

International audience; Accurate stage determination is crucial in the choice of treatment for patients suffering from sleeping sickness, also known as human African trypanosomiasis (HAT). Current staging methods, based on the counting of white blood cells (WBC) and the detection of parasites in the cerebrospinal fluid (CSF) have limited accuracy. We hypothesized that immune mediators reliable for staging T. b. gambiense HAT could also be used to stratify T. b. rhodesiense patients, the less common form of HAT.A population comprising 85 T. b. rhodesiense patients, 14 stage 1 (S1) and 71 stage 2 (S2) enrolled in Malawi and Uganda, was investigated. The CSF levels of IgM, MMP-9, CXCL13, CXCL10, ICAM-1, VCAM-1, neopterin and B2MG were measured and their staging performances evaluated using receiver operating characteristic (ROC) analyses.IgM, MMP-9 and CXCL13 were the most accurate markers for stage determination (partial AUC 88%, 86% and 85%, respectively). The combination in panels of three molecules comprising CXCL13-CXCL10-MMP-9 or CXCL13-CXCL10-IgM significantly increased their staging ability to partial AUC 94% (p value < 0.01).The present study highlighted new potential markers for stage determination of T. b. rhodesiense patients. Further investigations are needed to better evaluate these molecules, alone or in panels, as alternatives to WBC to make reliable choice of treatment.

Background Post-therapeutic follow-up is essential to confirm cure and to detect early treatment failures in patients affected by sleeping sickness (HAT). Current methods, based on finding of parasites in blood and cerebrospinal fluid (CSF) and counting of white blood cells (WBC) in CSF, are imperfect. New markers for treatment outcome evaluation are needed. We hypothesized that alternative CSF markers, able to diagnose the meningo-encephalitic stage of the disease, could also be useful for the evaluation of treatment outcome. Methodology/Principal findings Cerebrospinal fluid from patients affected by Trypanosoma brucei gambiense HAT and followed for two years after treatment was investigated. The population comprised stage 2 (S2) patients either cured or experiencing treatment failure during the follow-up. IgM, neopterin, B2MG, MMP-9, ICAM-1, VCAM-1, CXCL10 and CXCL13 were first screened on a small number of HAT patients (n = 97). Neopterin and CXCL13 showed the highest accuracy in discriminating between S2 cured and S2 relapsed patients (AUC 99% and 94%, respectively). When verified on a larger cohort (n = 242), neopterin resulted to be the most efficient predictor of outcome. High levels of this molecule before treatment were already associated with an increased risk of treatment failure. At six months after treatment, neopterin discriminated between cured and relapsed S2 patients with 87% specificity and 92% sensitivity, showing a higher accuracy than white blood cell numbers. Conclusions/Significance In the present study, neopterin was highlighted as a useful marker for the evaluation of the post-therapeutic outcome in patients suffering from sleeping sickness. Detectable levels of this marker in the CSF have the potential to shorten the follow-up for HAT patients to six months after the end of the treatment., Author Summary The reduction of the number of lumbar punctures performed during the follow-up of patients affected by sleeping sickness (HAT) is considered a research priority. Follow-up, consisting of the examination of cerebrospinal fluid (CSF) for presence of parasites and for the number of leukocytes, is necessary to assess treatment outcome. However, diagnosis of treatment failure is still imperfect and WHO encourages improvements in defining criteria. Many studies have attempted to standardize actual methods and to define a cut-off for the number of white blood cells in CSF to define relapses, while only few have proposed alternatives to current practice. Here we show that neopterin, already proven to be a powerful marker for staging T. b. gambiense HAT, is also useful in evaluating post-therapeutic outcome. The measurement of neopterin concentration in CSF during the follow-up may allow reduction in the number of lumbar punctures from five to three for the majority of cured patients.

High throughput protein identification and quantification analysis based on mass spectrometry are fundamental steps in most proteomics projects. Here, we present EasyProt (available at http://easyprot.unige.ch), a new platform for mass spectrometry data processing, protein identification, quantification and unexpected post-translational modification characterization. EasyProt provides a fully integrated graphical experience to perform a large part of the proteomic data analysis workflow. Our goal was to develop a software platform that would fulfill the needs of scientists in the field, while emphasizing ease-of-use for non-bioinformatician users. Protein identification is based on OLAV scoring schemes and protein quantification is implemented for both, isobaric labeling and label-free methods. Additional features are available, such as peak list processing, isotopic correction, spectra filtering, charge-state deconvolution and spectra merging. To illustrate the EasyProt platform, we present two identification and quantification workflows based on isobaric tagging and label-free methods.

International audience; BACKGROUND: Sleeping sickness, or human African trypanosomiasis (HAT), is a protozoan disease that affects rural communities in sub-Saharan Africa. Determination of the disease stage, essential for correct treatment, represents a key issue in the management of patients. In the present study we evaluated the potential of CXCL10, CXCL13, ICAM-1, VCAM-1, MMP-9, B2MG, neopterin and IgM to complement current methods for staging Trypanosoma brucei gambiense patients. METHODS AND FINDINGS: Five hundred and twelve T. b. gambiense HAT patients originated from Angola, Chad and the Democratic Republic of the Congo (D.R.C.). Their classification as stage 2 (S2) was based on the number of white blood cells (WBC) (>5/µL) or presence of parasites in the cerebrospinal fluid (CSF). The CSF concentration of the eight markers was first measured on a training cohort encompassing 100 patients (44 S1 and 56 S2). IgM and neopterin were the best in discriminating between the two stages of disease with 86.4% and 84.1% specificity respectively, at 100% sensitivity. When a validation cohort (412 patients) was tested, neopterin (14.3 nmol/L) correctly classified 88% of S1 and S2 patients, confirming its high staging power. On this second cohort, neopterin also predicted both the presence of parasites, and of neurological signs, with the same ability as IgM and WBC, the current reference for staging. CONCLUSIONS: This study has demonstrated that neopterin is an excellent biomarker for staging T. b. gambiense HAT patients. A rapid diagnostic test for detecting this metabolite in CSF could help in more accurate stage determination.

BACKGROUND: Ability to accurately determine time of stroke onset remains challenging. We hypothesized that an early biomarker characterized by a rapid increase in blood after stroke onset may help defining better the time window during which an acute stroke patient may be candidate for intravenous thrombolysis or other intravascular procedures. METHODS: The blood level of 29 proteins was measured by immunoassays on a prospective cohort of stroke patients (N = 103) and controls (N = 132). Mann-Whitney U tests, ROC curves and diagnostic odds ratios were applied to evaluate their clinical performances. RESULTS: Among the 29 molecules tested, GST-π concentration was the most significantly elevated marker in the blood of stroke patients (p3 h after onset). According to goal-oriented distinct cut-offs (sensitivity(Se)-oriented: 17.7 or specificity(Sp)-oriented: 65.2 ug/L), the GST-π test obtained 91%Se/50%Sp and 50%Se/91%Sp, respectively. Moreover, GST-π showed also the highest AUC (0.83) and performances for detecting patients treated with tPA (N = 12) compared to ineligible patients (N = 103). CONCLUSIONS: This study demonstrates that GST-π can accurately predict the time of stroke onset in over 50% of early stroke patients. The GST-π test could therefore complement current guidelines for tPA administration and potentially increase the number of patients accessing thrombolysis.