Explore the vast range of titles available.

Lubricated surfaces have shown promise in numerous applications where impinging foreign droplets must be removed easily; however, before they can be widely adopted, the problem of lubricant depletion, which eventually leads to decreased performance, must be solved. Despite recent progress, a quantitative mechanistic explanation for lubricant depletion is still lacking. Here, we first explain the shape of a droplet on a lubricated surface by balancing the Laplace pressures across interfaces. We then show that the lubricant film thicknesses beneath, behind, and wrapping around a moving droplet change dynamically with the droplet’s speed—analogous to the classical Landau-Levich-Derjaguin problem. The interconnected lubricant dynamics results in the growth of the wetting ridge around the droplet, which is the dominant source of lubricant depletion. We then develop an analytic expression for the maximum amount of lubricant that can be depleted by a single droplet. Counterintuitively, faster-moving droplets subjected to higher driving forces deplete less lubricant than their slower-moving counterparts. The insights developed in this work will inform future work and the design of longer-lasting lubricated surfaces.

ABO-incompatible allogeneic hematopoietic stem cell transplantation (HSCT) can be complicated by poor red cell engraftment and hemolysis, both mediated by isoagglutinins. Anecdotally, isoagglutinins indicates an activation of donor’s immunity or even relapse. Consequently, the routine monitoring of isoagglutinins could help physicians to predict the risk of complications. The purpose of this study is to investigate the time to disappearance and appearance of isoagglutinins after ABO-incompatible allogeneic HSCT. In a one-year follow-up, data of 136 ABO-incompatible hematopoietic stem cell (HSC) allogeneic transplanted patients were studied, of which 60 had major, 61 minor and 15 bidirectional incompatibility. Survival analyses were conducted and association with hematological diseases, HLA-compatibility and transplantation strategy was investigated. We observed a disappearance of isoagglutinin A in 82.0% of cases at one year with a median and 75th percentile of 38.4 and 138.6 days, respectively. For isoagglutinin B, these same values were 96.4%, 15.9 and 29.1 days, respectively. The appearance of isoagglutinin A occurred in 10.7% of cases. Disappearance of isoagglutinin A was significantly slower in patients with myeloid diseases compared to other diseases. The results of this study provide useful values to detect early risks of preventable immunohematological complications and possibly, in exceptional cases, relapse.

Objectives. To determine the ferritin inter-assay differences between three “Conformité Européenne” (CE) marked tests, the impact on reference intervals (RI), and the proportion of individuals with iron deficiency (ID), we used plasma and serum from healthy blood donors (HBD) recruited in three different Switzerland regions. Design and Methods. Heparinized plasma and serum from HBD were obtained from three different transfusion centers in Switzerland (Fribourg, Geneva, and Neuchatel). One hundred forty samples were recruited per center and per matrix, with a gender ratio of 50%, for a total of 420 HBD samples available per matrix. On both matrices, ferritin concentrations were quantified by three different laboratories using electrochemiluminescence (ECL), latex immunoturbidimetric assay (LIA), and luminescent oxygen channeling immunoassay (LOCI) assays, respectively. The degree of agreement between matrices and between the three sites/methods was assessed by Passing–Bablok and we evaluated the proportion of individuals deemed to have ID per method. Results. Overall, no difference between serum and heparinized plasma ferritin values was observed according to Passing–Bablok analyses (proportional bias range: 1.0–3.0%; maximum constant bias: 1.84 µg/L). Significant median ferritin differences (p < 0.001 according to Kruskal–Wallis test) were observed between the three methods (i.e., 83.6 µg/L, 103.5 µg/L, and 62.1 µg/L for ECL, LIA, and LOCI in heparinized plasma, respectively), with proportional bias varying significantly between ±16% and ±32% on serum and from ±14% to ±35% on plasma with no sign of gender-related differences. Affecting the lower end of RI, the proportion of ID per method substantially varied between 4.76% (20/420) for ECL, 2.86% (12/420) for LIA, and 9.05% (38/420) for LOCI. Conclusions. Serum and heparinized plasma are exchangeable for ferritin assessment. However, the order of magnitude of ferritin differences across methods and HBD recruitment sites could lead to diagnostic errors if uniform RI were considered. Challenging the recently proposed use of uniform ferritin thresholds, our results highlight the importance of method- and region-specific RI for ferritin due to insufficient inter-assay harmonization. Failing to do so significantly impacts ID diagnosis.

This dissertation presents the theoretical, numerical, and experimental results of studies on a varieties of complex polymer systems using a combination of analytical models, numerical simulations, and machine learning methods.We begin with the benchmark of a new hybrid encapsulation membrane that combines an inert fluorinated polymer matrix infused with a dense omniphobic lubricating oil to protect materials with high water sensitivity while simultaneously offering mechanical flexibility, transparency and scalability. We evaluate this new protecting strategy on halide perovskite, a promising material for next-generation solar cells and photoelectronic devices. We conduct an extensive investigation by combining numerical and analytical tools to demonstrate that the lubricant infusion leads to a defect-free membranes where the water transport is dominated by the diffusion of small water cluster through a highly hydrophobic membrane.We extend the use of numerical simulations to temperature-responsive liquid crystal molecules. In particular, we analyze end-on molecules, a particular class of liquid crystals with the ability to form covalent bonds at the extremity of the molecules. Once polymerized, these molecules are experimentally used as a cornerstone to build a new soft robotics platform for bio-inspired muscles and self-powered actuators. We demonstrate that end-on phase behaviors or dominated by thermo-activated alkyl chains conformations that dictates the molecular order. We then use molecular dynamics models to simulate how liquid crystal moieties order themselves when they are polymerized to form liquid crystal elastomers. We demonstrate that the intermolecular pi-pi stacking is the driving force behind liquid crystal mesophases. With this theoretical work, experimentalists are capable of designing temperature-responsive non-monotonic mechanical behaviors with a full mechanistical understanding of the underlying material by controlling the molecular order of end-on LCEs using external magnetic fields. To further bridge the gap between experiments and numerical simulations, we extend an existing diffraction theory to simulate X-ray scattering patterns from molecular dynamics simulations, with a high potential impact for scientists to enhance and test their understanding of materials at the molecular level.Finally, we combine classical computation with modern machine learning tools to evaluate the recent advancement in supervised learning for molecular simulations of liquid crystals. We established an entire pipeline starting from ab-initio molecular simulations and trained our own interatomic ML potentials for bulk liquid crystal simulations. Because the resulting ML-powered MD simulations still maintain a significant computation cost, we then develop an alternative, ultrafast prediction tool using unsupervised learning and polymer theory. We show that neural networks can predict the phase transition of lyotropic liquid crystals by comparing directly with an analytical model. We hope this work will give rise to future research involving advanced predictions of complex molecular systems with ultralow latency.

Soil water content (SWC) sensors are widely used for scientific studies or for the management of agricultural practices. The most common sensing techniques provide an estimate of volumetric soil water content based on sensing of dielectric permittivity. These techniques include frequency domain reflectometry (FDR), time domain reflectometry (TDR), capacitance and even remote-sensing techniques such as ground-penetrating radar (GPR) and microwave-based techniques. Here, we will focus on frequency domain reflectometry (FDR) sensors and more specifically on the questioning of their factory calibration, which does not take into account soil-specific features and therefore possibly leads to inconsistent SWC estimates. We conducted the present study in the southwest of France on two plots that are part of the ICOS ERIC network (Integrated Carbon Observation System, European Research and Infrastructure Consortium), FR-Lam and FR-Aur. We propose a simple protocol for soil-specific calibration, particularly suitable for clayey soil, to improve the accuracy of SWC determination when using commercial FDR sensors. We compared the sensing accuracy after soil-specific calibration versus factory calibration. Our results stress the necessity of performing a thorough soil-specific calibration for very clayey soils. Hence, locally, we found that factory calibration results in a strong overestimation of the actual soil water content. Indeed, we report relative errors as large as +115 % with a factory-calibrated sensor based on the real part of dielectric permittivity and up to + 245 % with a factory-calibrated sensor based on the modulus of dielectric permittivity.

We introduce Proteus, a novel self-designing approximate range filter, which configures itself based on sampled data in order to optimize its false positive rate (FPR) for a given space requirement. Proteus unifies the probabilistic and deterministic design spaces of state-of-the-art range filters to achieve robust performance across a larger variety of use cases. At the core of Proteus lies our Contextual Prefix FPR (CPFPR) model - a formal framework for the FPR of prefix-based filters across their design spaces. We empirically demonstrate the accuracy of our model and Proteus' ability to optimize over both synthetic workloads and real-world datasets. We further evaluate Proteus in RocksDB and show that it is able to improve end-to-end performance by as much as 5.3x over more brittle state-of-the-art methods such as SuRF and Rosetta. Our experiments also indicate that the cost of modeling is not significant compared to the end-to-end performance gains and that Proteus is robust to workload shifts.

Lubricated surfaces have shown promise in numerous applications where impinging foreign droplets must be removed easily; however, before they can be widely adopted, the problem of lubricant depletion, which eventually leads to decreased performance, must be solved. Despite recent progress, a quantitative mechanistic explanation for lubricant depletion is still lacking. Here, we first explained the shape of a droplet on a lubricated surface by balancing the Laplace pressures across interfaces. We then showed that the lubricant film thicknesses beneath, behind, and wrapping around a moving droplet change dynamically with droplet's speed---analogous to the classical Landau-Levich-Derjaguin problem. The interconnected lubricant dynamics results in the growth of the wetting ridge around the droplet, which is the dominant source of lubricant depletion. We then developed an analytic expression for the maximum amount of lubricant that can be depleted by a single droplet. Counter-intuitively, faster moving droplets subjected to higher driving forces deplete less lubricant than their slower moving counterparts. The insights developed in this work will inform future work and the design of longer-lasting lubricated surfaces.

Background Confusion exists over the definition of the care pathway concept and existing conceptual frameworks contain various inadequacies which have led to implementation difficulties. In the current global context of rapidly changing health care systems, there is great need for a standardized definition and integrative framework that can guide implementation. This study aims to propose an accurate and up-to-date definition of care pathway and an integrative conceptual framework. Methods An innovative hybrid method combining systematic review, concept analysis and bibliometric analysis was undertaken to summarize qualitative, quantitative, and mixed-method studies. Databases searched were PubMed, Embase and ABI/Inform. Methodological quality of included studies was then assessed. Results Forty-four studies met the inclusion criteria. Using concept analysis, we developed a fine-grained understanding, an integrative conceptual framework, and an up-to-date definition of patient-centered care pathway by proposing 28 subcategories grouped into seven attributes. This conceptual framework considers both operational and social realities and supports the improvement and sustainable transformation of clinical, administrative, and organizational practices for the benefit of patients and caregivers, while considering professional experience, organizational constraints, and social dynamics. The proposed attributes of a fluid and effective pathway are (i) the centricity of patients and caregivers, (ii) the positioning of professional actors involved in the care pathway, (iii) the operation management through the care delivery process, (iv) the particularities of coordination structures, (v) the structural context of the system and organizations, (vi) the role of the information system and data management and (vii) the advent of the learning system. Antecedents are presented as key success factors of pathway implementation. By using the consequences and empirical referents, such as outcomes and evidence of care pathway interventions, we went beyond the single theoretical aim, proposing the application of the conceptual framework to healthcare management. Conclusions This study has developed an up-to-date definition of patient-centered care pathway and an integrative conceptual framework. Our framework encompasses 28 subcategories grouped into seven attributes that should be considered in complex care pathway intervention. The formulation of these attributes, antecedents as success factors and consequences as potential outcomes, allows the operationalization of this model for any pathway in any context.

Chronic NF-κB activation in inflammation and cancer has long been linked to persistent activation of NF-κB–responsive gene promoters. However, NF-κB factors also massively bind to gene bodies. Here, we demonstrate that recruitment of the NF-κB factor RELA to intragenic regions regulates alternative splicing upon NF-κB activation by the viral oncogene Tax of HTLV-1. Integrative analyses of RNA splicing and chromatin occupancy, combined with chromatin tethering assays, demonstrate that DNA-bound RELA interacts with and recruits the splicing regulator DDX17, in an NF-κB activation-dependent manner. This leads to alternative splicing of target exons due to the RNA helicase activity of DDX17. Similar results were obtained upon Tax-independent NF-κB activation, indicating that Tax likely exacerbates a physiological process where RELA provides splice target specificity. Collectively, our results demonstrate a physical and direct involvement of NF-κB in alternative splicing regulation, which significantly revisits our knowledge of HTLV-1 pathogenesis and other NF-κB-related diseases. The nuclear factors κB (NF-κB) is a transcription factor involved in immune functions, inflammation, and cancer. Here, the authors show that the NF-κB factor RELA regulates splicing of target genes by recruiting DDX17 on chromatin upon expression of the viral oncogene Tax.

Background Nucleotide composition bias plays an important role in the 1D and 3D organization of the human genome. Here, we investigate the potential interplay between nucleotide composition bias and the regulation of exon recognition during splicing. Results By analyzing dozens of RNA-seq datasets, we identify two groups of splicing factors that activate either about 3200 GC-rich exons or about 4000 AT-rich exons. We show that splicing factor–dependent GC-rich exons have predicted RNA secondary structures at 5′ ss and are dependent on U1 snRNP–associated proteins. In contrast, splicing factor–dependent AT-rich exons have a large number of decoy branch points, SF1- or U2AF2-binding sites and are dependent on U2 snRNP–associated proteins. Nucleotide composition bias also influences local chromatin organization, with consequences for exon recognition during splicing. Interestingly, the GC content of exons correlates with that of their hosting genes, isochores, and topologically associated domains. Conclusions We propose that regional nucleotide composition bias over several dozens of kilobase pairs leaves a local footprint at the exon level and induces constraints during splicing that can be alleviated by local chromatin organization at the DNA level and recruitment of specific splicing factors at the RNA level. Therefore, nucleotide composition bias establishes a direct link between genome organization and local regulatory processes, like alternative splicing.