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Periodontopathogenic Tannerella forsythia uniquely secretes six peptidases of disparate catalytic classes and families that operate as virulence factors during infection of the gums, the KLIKK-peptidases. Their coding genes are immediately downstream of novel ORFs encoding the 98–132 residue potempins (Pot) A, B1, B2, C, D and E. These are outer-membrane-anchored lipoproteins that specifically and potently inhibit the respective downstream peptidase through stable complexes that protect the outer membrane of T. forsythia, as shown in vivo. Remarkably, PotA also contributes to bacterial fitness in vivo and specifically inhibits matrix metallopeptidase (MMP) 12, a major defence component of oral macrophages, thus featuring a novel and highly-specific physiological MMP inhibitor. Information from 11 structures and high-confidence homology models showed that the potempins are distinct β-barrels with either a five-stranded OB-fold (PotA, PotC and PotD) or an eight-stranded up-and-down fold (PotE, PotB1 and PotB2), which are novel for peptidase inhibitors. Particular loops insert like wedges into the active-site cleft of the genetically-linked peptidases to specifically block them either via a new “bilobal” or the classic “standard” mechanism of inhibition. These results discover a unique, tightly-regulated proteolytic armamentarium for virulence and competence, the KLIKK-peptidase/potempin system., This study was supported in part by grants from Polish (National Science Centre and Ministry of Science and Higher Education), US (NIH/NIDR), Spanish, Danish and Catalan public and private bodies (grant/fellowship references PID2019-107725RG-I00 and PDC2022-133344-I00 by MICIN/AEI/10.13039/501100011033, 2017SGR3, 2016/21/B/NZ1/00292, 1306/MOB/IV/2015/0, 2019/35/B/NZ1/03118, DE026280, Fundació “La Marató de TV3” 201815, and Novo Nordisk Foundation grant NNF18OC0032724).

Beta‐microseminoproteins (MSMBs) are small disulfide‐rich proteins that are conserved among vertebrates. These proteins exhibit diverse biological activities and were mainly reported to play a role in male fertility, immunity, and embryogenesis. In this work, we focused on the chicken MSMB3 protein that was previously depicted as an egg antibacterial protein. We report that MSMB3 protein is exclusively expressed in the reproductive tissues of laying hens (in contrast to chicken MSMB1 and MSMB2 paralogs), to be incorporated in the egg white during the process of egg formation. We also showed that chicken MSMB3 possesses highly conserved orthologs in bird species, including Neognathae and Palaeognathae. Chicken MSMB3 was purified from egg white using heparin affinity chromatography and was analyzed by top‐down and bottom‐up proteomics. Several proteoforms could be characterized, and a homodimer was further evidenced by NMR spectroscopy. The X‐ray structure of chicken MSMB3 was solved for the first time, revealing that this protein adopts a novel dimeric arrangement. The highly cationic MSMB3 protein exhibits a distinct electrostatic distribution compared with chicken MSMB1 and MSMB2 structural models, and with published mammalian MSMB structures. The specific incorporation of MSMB3 paralog in the egg, and its phylogenetic conservation in birds together with its peculiar homodimer arrangement and physicochemical properties, suggests that the MSMB3 protein has evolved to play a critical role during the embryonic development of avian species. These new data are likely to stimulate research to elucidate the structure/function relationships of MSMB paralogs and orthologs in the animal kingdom., Beta‐microseminoproteins (MSMBs) are small proteins conserved among vertebrates. The chicken genome contains three MSMB paralogs, which exhibit distinct tissue expression profiles, with chicken beta‐MSMB 3 (MSMB3) protein being egg‐specific. Collectively, results from protein sequence analysis, mass spectrometry analysis, and 3D structure data highlight that chicken MSMB3 possesses specific features that may be related to its presumed role in avian reproduction. ​

L’association Cyclamed a cree une filiere de prise en charge des medicaments non utilises qui federe l’ensemble des acteurs des medicaments a usage humain en ville : les industriels, les grossistes repartiteurs et les officines de pharmacie. L’eco-organisme affiche des resultats quantitatifs performants grâce a la mobilisation des citoyens, sensibilises par une communication associant actions de proximite et campagne multicanale.

This article describes the Versatile Tensor Accelerator (VTA), a programmable DL architecture designed to be extensible in the face of evolving workloads. VTA achieves “flexible specialization” via a parameterizable architecture, two-level Instruction Set Architecture (ISA), and a Just in Time (JIT) compiler.

As a result of the increasing demand for deep neural network (DNN)-based services, efforts to develop hardware accelerators for DNNs are growing rapidly. However, while highly efficient accelerators on convolutional DNNs (Conv-DNNs) have been developed, less progress has been made with regards to fully-connected DNNs. Based on analysis of bit-level SRAM errors, we propose memory adaptive training with in-situ canaries (MATIC), a methodology that enables aggressive voltage scaling of accelerator weight memories to improve the energy-efficiency of DNN accelerators. To enable accurate operation with voltage overscaling, MATIC combines characteristics of SRAM bit failures with the error resilience of neural networks in a memory-adaptive training (MAT) process. Furthermore, PVT-related voltage margins are eliminated using bit-cells from synaptic weights as in-situ canaries to track runtime environmental variation. Demonstrated on a low-power DNN accelerator fabricated in 65 nm CMOS, MATIC enables up to $3.3\times $ energy reduction versus the nominal voltage, or $18.6\times $ application error reduction. We also perform a simulation study that extends MAT to Conv-DNNs, and characterize the accuracy impact of bit failure statistics. Finally, we develop a weight refinement algorithm to improve the performance of MAT, and show that it improves absolute accuracy by 0.8–1.3% or reduces training time by 5– $10\times $ .

The protease activities are tightly regulated by inhibitors and dysregulation contribute to pathological processes such as cancer and inflammatory disorders. Tissue factor pathway inhibitor 2 (TFPI-2) is a serine proteases inhibitor, that mainly inhibits plasmin. This protease activated matrix metalloproteases (MMPs) and degraded extracellular matrix. Other serine proteases are implicated in these mechanisms like kallikreins (KLKs). In this study, we identified for the first time that TFPI-2 is a potent inhibitor of KLK5 and 12. Computer modeling showed that the first Kunitz domain of TFPI-2 could interact with residues of KLK12 near the catalytic triad. Furthermore, like plasmin, KLK12 was able to activate proMMP-1 and -3, with no effect on proMMP-9. Thus, the inhibition of KLK12 by TFPI-2 greatly reduced the cascade activation of these MMPs and the cleavage of cysteine-rich 61, a matrix signaling protein. Moreover, when TFPI-2 bound to extracellular matrix, its classical localisation, the KLK12 inhibition was retained. Finally, TFPI-2 was downregulated in human non-small-cell lung tumour tissue as compared with non-affected lung tissue. These data suggest that TFPI-2 is a potent inhibitor of KLK12 and could regulate matrix remodeling and cancer progression mediated by KLK12.

The control of ovulation helps guarantee the success of reproduction and as such, contributes to the fitness of a species. In mammals, two types of ovulation are observed: induced and spontaneous ovulation. Recent work on camelids, that are induced ovulators, highlighted the role of a factor present in seminal plasma, beta Nerve Growth Factor (β-NGF), as the factor that triggers ovulation in a GnRH dependent manner. In the present work, we characterized alpaca β-NGF (aβ-NGF) and its 3D structure and compared it with human recombinant β-NGF (hβ-NGF). We showed that the β-NGF enriched fraction of alpaca semen and the human recombinant protein, both stimulated spontaneous electrical activity of primary GnRH neurons derived from mouse embryonic olfactory placodes. This effect was dose-dependent and mediated by p75 receptor signaling. P75 receptors were found expressed in vitro by olfactory ensheathing cells (OEC) in close association with GnRH neurons and in vivo by tanycytes in close vicinity to GnRH fibers in adult mouse. Altogether, these results suggested that β-NGF induced ovulation through an increase in GnRH secretion provoked by a glial dependent P75 mediated mechanism.

When a computational task tolerates a relaxation of its specification or when an algorithm tolerates the effects of noise in its execution, hardware, system software, and programming language compilers or their runtime systems can trade deviations from correct behavior for lower resource usage. We present, for the first time, a synthesis of research results on computing systems that only make as many errors as their end-to-end applications can tolerate. The results span the disciplines of computer-aided design of circuits, digital system design, computer architecture, programming languages, operating systems, and information theory. Rather than over-provisioning the resources controlled by each of these layers of abstraction to avoid errors, it can be more efficient to exploit the masking of errors occurring at one layer and thereby prevent those errors from propagating to a higher layer., We demonstrate the potential benefits of end-to-end approaches using two illustrative examples. We introduce a formalization of terminology that allows us to present a coherent view across the techniques traditionally used by different research communities in their individual layer of focus. Using this formalization, we survey tradeoffs for individual layers of computing systems at the circuit, architecture, operating system, and programming language levels as well as fundamental information-theoretic limits to tradeoffs between resource usage and correctness.

Approximate computing is the idea that systems can gain performance and energy efficiency if they expend less effort on producing a “perfect” answer. Approximate computing techniques propose various ways of exposing and exploiting accuracy–efficiency tradeoffs. We present a taxonomy that classifies approximate computing techniques according to salient features: visibility, determinism, and coarseness. These axes allow us to address questions about the correctability, reproducibility, and control over accuracy–efficiency tradeoffs of different techniques. We use this taxonomy to inform research challenges in approximate architectures, compilers, and applications.

Macrophage elastase, or MMP-12, is mainly produced by alveolar macrophages and is believed to play a major role in the development of chronic obstructive pulmonary disease (COPD). The catalytic domain of MMP-12 is unique among MMPs in that it is very highly active on numerous substrates including elastin. However, measuring MMP-12 activity in biological fluids has been hampered by the lack of highly selective substrates. We therefore synthesized four series of fluorogenic peptide substrates based on the sequences of MMP-12 cleavage sites in its known substrates. Human MMP-12 efficiently cleaved peptide substrates containing a Pro at P3 in the sequence Pro-X-X↓Leu but lacked selectivity towards these substrates compared to other MMPs, including MMP-2, MMP-7, MMP-9 and MMP-13. On the contrary, the substrate Abz-RNALAVERTAS-EDDnp derived from the CXCR5 chemokine was the most selective substrate for MMP-12 ever reported. All substrates were cleaved more efficiently by full-length MMP-12 than by its catalytic domain alone, indicating that the C-terminal hemopexin domain influences substrate binding and/or catalysis. Docking experiments revealed unexpected interactions between the peptide substrate Abz-RNALAVERTAS-EDDn and MMP-12 residues. Most of our substrates were poorly cleaved by murine MMP-12 suggesting that human and murine MMP-12 have different substrate specificities despite their structural similarity.

We present a full-stack design to accelerate deep learning inference with FPGAs. Our contribution is two-fold. At the software layer, we leverage and extend TVM, the end-to-end deep learning optimizing compiler, in order to harness FPGA-based acceleration. At the the hardware layer, we present the Versatile Tensor Accelerator (VTA) which presents a generic, modular, and customizable architecture for TPU-like accelerators. Our results take a ResNet-18 description in MxNet and compiles it down to perform 8-bit inference on a 256-PE accelerator implemented on a low-cost Xilinx Zynq FPGA, clocked at 100MHz. Our full hardware acceleration stack will be made available for the community to reproduce, and build upon at http://github.com/uwsaml/vta.

Discussion is centered around the following questions:* How do we facilitate tech transfer between academia and industry in a quickly evolving research landscape?* How do we incentivize companies and academic researchers to release more artifacts and open source projects as portable, customizable and reusable components which can be collaboratively optimized by the community across diverse models, data sets and platforms from the cloud to edge?* How do we ensure reproducible evaluation and fair comparison of diverse AI/ML frameworks, libraries, techniques and tools?* What other workloads (AI, ML, quantum) and exciting research challenges should ReQuEST attempt to solve in its future iterations with the help of the multi-disciplinary community: reducing training time and costs, comparing specialized hardware (TPU/FPGA/DSP), distributing learning across edge devices, ...

Phosphorylated kininogen and some of its fragments containing serine phosphorylated bradykinin ([pS(6)]-Bk) were identified in human serum and plasma by a phosphoproteomic approach. We report the kininogenase ability of human tissue and plasma kallikreins and tryptase to generate [pS(6)]-Bk or Lys-[pS(6)]-Bk having as substrate the synthetic human kininogen fluorescent fragment Abz-MISLMKRPPGF[pS(386)]PFRSSRI-NH2. The pharmacological assays of [pS(6)]-Bk showed it as a full B2 bradykinin receptor agonist in smooth muscle, it produces a portal liver hypertensive response in rat and mouse paw edema that lasts longer than Bk. The rat hypotensive response to infusions of Bk is greater than that of [pS(6)]Bk, both if injected through femoral vein or aorta. [pS(6)]-Bk was more resistant than Bk to kininase digestion performed with angiotensin converting enzyme, neprilysin, thimet oligopeptidase, aminopeptidase P and carboxypeptidase M. (1)H-NMR experiments indicated that [pS(6)]-Bk has lower flexibility, with the pS(6)-P(7) bond restricted to the trans conformation, and can explain [pS(6)]-Bk resistance to hydrolysis. In conclusion, [pS(6)]-Bk presenting lower activity than Bk, with longer lasting effects and being slowly released by kininogenases from synthetic Abz-MISLMKRPPGF[pS(386)]PFRSSRI-NH2, suggests that phosphorylation of the kininogens can be an efficient kallikrein-kinin system regulator.

Approximate systems can reclaim energy that's currently lost to the "correctness tax" imposed by traditional safety margins designed to prevent worst-case scenarios. Researchers at the University of Washington have co-designed programming language extensions, a compiler, and a hardware co-processor to support approximate acceleration. Their end-to-end system includes two building blocks. First, a new programmer-guided compiler framework transforms programs to use approximation in a controlled way. An Approximate C Compiler for Energy and Performance Tradeoffs (Accept) uses programmer annotations, static analysis, and dynamic profiling to find parts of a program that are amenable to approximation. Second, the compiler targets a system on a chip (SoC) augmented with a co-processor that can efficiently evaluate coarse regions of approximate code. A Systolic Neural Network Accelerator in Programmable logic (Snnap) is a hardware accelerator prototype that can efficiently evaluate approximate regions of code in a general-purpose program.

In randomized clinical trials where the times to event of two treatment groups are compared under a proportional hazards assumption, it has been established that omitting prognostic factors from the model entails an underestimation of the hazards ratio. Heterogeneity due to unobserved covariates in cancer patient populations is a concern since genomic investigations have revealed molecular and clinical heterogeneity in these populations. In HIV prevention trials, heterogeneity is unavoidable and has been shown to decrease the treatment effect over time. This article assesses the influence of trial duration on the bias of the estimated hazards ratio resulting from omitting covariates from the Cox analysis. The true model is defined by including an unobserved random frailty term in the individual hazard that reflects the omitted covariate. Three frailty distributions are investigated: gamma, log-normal, and binary, and the asymptotic bias of the hazards ratio estimator is calculated. We show that the attenuation of the treatment effect resulting from unobserved heterogeneity strongly increases with trial duration, especially for continuous frailties that are likely to reflect omitted covariates, as they are often encountered in practice. The possibility of interpreting the long-term decrease in treatment effects as a bias induced by heterogeneity and trial duration is illustrated by a trial in oncology where adjuvant chemotherapy in stage 1B NSCLC was investigated.

Elafin is a serine protease inhibitor produced by epithelial and immune cells with anti-inflammatory properties. Research has shown that dysregulated protease activity may elicit proteolytic cleavage of elafin, thereby impairing the innate immune function of the protein. The aim of this study was to generate variants of elafin (GG- and QQ-elafin) that exhibit increased protease resistance while retaining the biological properties of wild-type (WT) elafin. Similar to WT-elafin, GG- and QQ-elafin variants retained antiprotease activity and susceptibility to transglutaminase-mediated fibronectin cross-linking. However, in contrast to WT-elafin, GG- and QQ-elafin displayed significantly enhanced resistance to degradation when incubated with bronchoalveolar lavage fluid from patients with cystic fibrosis. Intriguingly, both variants, particularly GG-elafin, demonstrated improved lipopolysaccharide (LPS) neutralization properties in vitro. In addition, GG-elafin showed improved anti-inflammatory activity in a mouse model of LPS-induced acute lung inflammation. Inflammatory cell infiltration into the lung was reduced in lungs of mice treated with GG-elafin, predominantly neutrophilic infiltration. A reduction in MCP-1 levels in GG-elafin treated mice compared to the LPS alone treatment group was also demonstrated. GG-elafin showed increased functionality when compared to WT-elafin and may be of future therapeutic relevance in the treatment of lung diseases characterized by a protease burden.

Approximate computing aims to expose and exploit quality vs. efficiency tradeoffs to enable ever-more demanding applications on energy-constrained devices such as smartphones, or IoT devices. This paper makes the case for arbitrary quantization as a compelling approximation technique that exposes quality vs. energy tradeoffs and provides practical error guarantees. We present QAPPA (Quality Autotuner for Precision Programmable Accelerators), an autotuning framework for C/C++ programs that automatically minimizes the precision of each arithmetic and memory operation to meet user defined application level quality guarantees. QAPPA integrates energy models of precision scaling mechanisms to produce bandwidth and energy savings estimates for precision scalable accelerator designs. We show that QAPPA can exploit precision scaling mechanisms to meet arbitrary user-provided quality targets on the PERFECT benchmark suite to achieve significant energy savings and memory bandwidth reduction.

Twenty-seven serpins belonging to clade A, B, C, D, E, F, G, H and I serpins are currently referenced in chicken genome databases. Phylogenetic analysis of chicken serpins revealed that ovalbumin (Serpinb14) and its paralogs ovalbumin-related protein Y (Serpinb14b) and ovalbumin-related protein X (Serpinb14c) are found in bird species. These clade B serpins are specifically expressed in reproductive tissues and exported in the egg where they constitute major protein components. These data suggest that these three paralogs have probably appeared in birds to face new environments and ensure the extra-uterine development of an embryo in a shell egg. Twelve other serpins have been identified in the newly produced egg, some of them having a specific distribution in the respective egg structures (eggshell, egg white, vitelline membrane and egg yolk). The physiological role of these egg serpins remain largely unexplored, but there is increasing evidence in literature or by homologies with their mammalian counterparts, that some of them participate in cell proliferation, tissue remodeling and/or angiogenesis associated with folliculogenesis and development of extraembryonic structures, eggshell biomineralization, egg defense and nutrition of the embryo. A better knowledge of the phylogenetic evolution of these 15 serpins in other oviparous species, on their egg distribution, on their regulation during embryonic development (activation/degradation/transfer) and on their functional specificity, is needed to better appreciate their role and their bird-specificity. These review shed light on the multiple possibilities that offer the avian egg model to study the role of serpins in reproduction and developmental biology.

Cameras are the defacto sensor. The growing demand for real-time and low-power computer vision, coupled with trends towards high-efficiency heterogeneous systems, has given rise to a wide range of image processing acceleration techniques at the camera node and in the cloud. In this paper, we characterize two novel camera systems that use acceleration techniques to push the extremes of energy and performance scaling, and explore the computation-communication tradeoffs in their design. The first case study targets a camera system designed to detect and authenticate individual faces, running solely on energy harvested from RFID readers. We design a multi-accelerator SoC design operating in the sub-mW range, and evaluate it with real-world workloads to show performance and energy efficiency improvements over a general purpose microprocessor. The second camera system supports a 16-camera rig processing over 32 Gb/s of data to produce real-time 3D-360 degree virtual reality video. We design a multi-FPGA processing pipeline that outperforms CPU and GPU configurations by up to 10x in computation time, producing panoramic stereo video directly from the camera rig at 30 frames per second. We find that an early data reduction step, either before complex processing or offloading, is the most critical optimization for in-camera systems.

As a result of the increasing demand for deep neural network (DNN)-based services, efforts to develop dedicated hardware accelerators for DNNs are growing rapidly. However,while accelerators with high performance and efficiency on convolutional deep neural networks (Conv-DNNs) have been developed, less progress has been made with regards to fully-connected DNNs (FC-DNNs). In this paper, we propose MATIC (Memory Adaptive Training with In-situ Canaries), a methodology that enables aggressive voltage scaling of accelerator weight memories to improve the energy-efficiency of DNN accelerators. To enable accurate operation with voltage overscaling, MATIC combines the characteristics of destructive SRAM reads with the error resilience of neural networks in a memory-adaptive training process. Furthermore, PVT-related voltage margins are eliminated using bit-cells from synaptic weights as in-situ canaries to track runtime environmental variation. Demonstrated on a low-power DNN accelerator that we fabricate in 65 nm CMOS, MATIC enables up to 60-80 mV of voltage overscaling (3.3x total energy reduction versus the nominal voltage), or 18.6x application error reduction., Comment: 6 pages, 12 figures, 3 tables. Published at Design, Automation and Test in Europe Conference and Exhibition (DATE) 2018

The disruption of the circadian timing system (CTS), which rhythmically controls cellular metabolism and proliferation, accelerated experimental cancer progression. A measure of CTS function in cancer patients could thus provide novel prediction information for outcomes, and help to identify novel specific therapies. The rest-activity circadian rhythm is a reliable and non-invasive CTS biomarker, which was monitored using a wrist watch accelerometer for 2 days in 436 patients with metastatic colorectal cancer. The relative percentage of activity in-bed versus out-of-bed (I

The robustness of the circadian timing system (CTS) was correlated to quality of life and predicted for improved survival in cancer patients. However, chemotherapy disrupted the CTS according to dose and circadian timing in mice. A continuous and repeated measures longitudinal design was implemented here to characterize CTS dynamics in patients receiving a fixed circadian-based chemotherapy protocol. The rest-activity rhythm of 49 patients with advanced cancer was monitored using a wrist actigraph for 13 days split into four consecutive spans of 3-4 days each, i.e., before, during, right after and late after a fixed chronotherapy course. The relative amount of activity in bed vs. out of bed (I

OBJECTIVE HIV-1 has been classified into four groups: M, N, O and P. The aim of this study was to revisit the cross-group neutralization using a highly diverse panel of primary isolates. DESIGN The panel of viruses included nine HIV-1 group O primary isolates, one recombinant M/O primary isolate, one group N primary isolates, one group P primary isolate, two group M (subtype B) primary isolates and the HIV-1 group M adapted strain MN. METHODS All the viruses were tested for neutralization in TZM-bl cells, using sera issued from patients infected by viruses of group M (n = 11), O (n = 12) and P (n = 1), and a panel of nine human monoclonal broadly neutralizing antibodies (HuMo bNAbs). RESULTS Although the primary isolates displayed a wide spectrum of sensitivity to neutralization by the human sera, cross-group neutralization was clearly observed. In contrast, the bNAbs did not show any cross-group neutralization, except PG9 and PG16. Interestingly, the group N prototype strain YBF30 was highly sensitive to neutralization by PG9 (IC50: 0.28 μg/ml) and PG16 (IC50

BACKGROUND: Chemotherapy-induced neutropenia has been associated with prolonged survival selectively in patients on a conventional schedule (combined 5-fluorouracil, leucovorin, and oxaliplatin [FOLFOX2]) but not on a chronomodulated schedule of the same drugs administered at specific circadian times (chronoFLO4). The authors hypothesized that the early occurrence of chemotherapyinduced symptoms correlated with circadian disruption would selectively hinder the efficacy of chronotherapy. METHODS: Fatigue and weight loss (FWL) were considered to be associated with circadian disruption based on previous data. Patients with metastatic colorectal cancer (n 5543) from an international phase 3 trial comparing FOLFOX2 with chronoFLO4 were categorized into 4 subgroups according to the occurrence of FWL or other clinically relevant toxicities during the initial 2 courses of chemotherapy. Multivariate Cox models were used to assess the role of toxicity on the time to progression (TTP) and overall survival (OS). RESULTS: The proportions of patients in the 4 subgroups were comparable in both treatment arms (P 5.77). No toxicity was associated with TTP or OS on FOLFOX2. The median OS on FOLFOX2 ranged from 16.4 (95% confidence limits [CL], 7.2-25.6 months) to 19.8 months (95% CL, 17.722.0 months) according to toxicity subgroup (P 5.45). Conversely, FWL, but no other toxicity, independently predicted for significantly shorter TTP (P

BACKGROUND: Molecular circadian clocks can modify cancer chemotherapy effects, with a possible moderation according to sex differences. We investigated whether sex determine the optimal delivery schedule of chemotherapy for metastatic colorectal cancer. PATIENTS AND METHODS: A meta-analysis was performed using individual data from three international Phase III trials comparing 5-fluorouracil, leucovorin and oxaliplatin administered in chronomodulated (chronoFLO) or conventional (CONV) infusions. The data from 345 females and 497 males were updated at 9 years. The main end point was survival. RESULTS: Overall survival was improved in males on chronoFLO when compared with CONV (P = 0.009), with respective median values of 20.8 (95% CL, 18.7 to 22.9) and 17.5 months (16.1 to 18.8). Conversely, median survival was 16.6 months (13.9 to 19.3) on chronoFLO and 18.4 months (16.6 to 20.2) on CONV in females (P = 0.012). The sex versus schedule interaction was a strong predictive factor of optimal treatment schedule, with a hazard ratio of 1.59 (1.30 to 1.75) for overall survival (P = 0.002) in multivariate analysis. CONCLUSIONS: Males lived significantly longer on chronomodulated chemotherapy rather than on conventional chemotherapy. The current chronoFLO schedule deserves prospective assessment as a safe and more effective first-line treatment option than conventional delivery for male patients.

International audience; L'évolution paysagère de 3 lacs urbains d'Ile-De-France, a été caractérisée par photo-interprétation pour 3 périodes, entre 1950 et 2014. Les résultats montrent que l'environnement lacustre a été profondément modifié (sauf pour Enghien) entre 1950 et 1990 : sans surprise, les espaces dédiés à l'agriculture on reculé au profit de l'urbanisation et, pour Créteil et Saint-Quentin, des espaces verts ont été aménagés en périphérie du milieu aquatique. Ces parcs de nature anthropisée, accessibles aux citadins, assurent à la fois les fonctions sociale, récréative et esthétique dans l'environnement hyper-urbanisé d'Ile-de-France.

International audience; Trappin-2 is a serine protease inhibitor with a very narrow inhibitory spectrum and has significant anti-microbial activities. It is a 10 kDa cationic protein composed of two distinct domains. The N-terminal domain (38 residues) named cementoin is known to be intrinsically disordered when it is not linked to the elafin. The C-terminal domain (57 residues), corresponding to elafin, is a cysteine-rich domain stabilized by four disulfide bridges and is characterized by a flat core and a flexible N-terminal part. To our knowledge, there is no structural data available on trappin-2. We report here the complete 1H, 15N and 13C resonance assignment of the recombinant trappin-2 and the 1H assignments of cementoin and elafin, under the same experimental conditions. This is the first step towards the 3D structure determination of the trappin-2.