A rule-based multiscale model of hepatic stellate cell plasticity: Critical role of the inactivation loop in fibrosis progression.

Hepatic stellate cells (HSC) are the source of extracellular matrix (ECM) whose overproduction leads to fibrosis, a condition that impairs liver functions in chronic liver diseases. Understanding the dynamics of HSCs will provide insights needed to develop new therapeutic approaches. Few models of hepatic fibrosis have been proposed, and none of them include the heterogeneity of HSC phenotypes recently highlighted by single-cell RNA sequencing analyses.

Globe-LFMC 2.0, an enhanced and updated dataset for live fuel moisture content research.

Globe-LFMC 2.0, an updated version of Globe-LFMC, is a comprehensive dataset of over 280,000 Live Fuel Moisture Content (LFMC) measurements. These measurements were gathered through field campaigns conducted in 15 countries spanning 47 years.

Multi-scale datasets for monitoring Mediterranean oak forests from optical remote sensing during the SENTHYMED/MEDOAK experiment in the north of Montpellier (France).

Mediterranean forests represent critical areas that are increasingly affected by the frequency of droughts and fires, anthropic activities and land use changes. Optical remote sensing data give access to several essential biodiversity variables, such as species traits (related to vegetation biophysical and biochemical composition), which can help to better understand the structure and functioning of these forests. However, their reliability highly depends on the scale of observation and the spectral configuration of the sensor.

The Spectral Species Concept in Living Color.

Biodiversity monitoring is an almost inconceivable challenge at the scale of the entire Earth. The current (and soon to be flown) generation of spaceborne and airborne optical sensors (i.e.

Retrieval of aboveground crop nitrogen content with a hybrid machine learning method.

Hyperspectral acquisitions have proven to be the most informative Earth observation data source for the estimation of nitrogen (N) content, which is the main limiting nutrient for plant growth and thus agricultural production. In the past, empirical algorithms have been widely employed to retrieve information on this biochemical plant component from canopy reflectance. However, these approaches do not seek for a cause-effect relationship based on physical laws.

Crop nitrogen monitoring: Recent progress and principal developments in the context of imaging spectroscopy missions.

Nitrogen (N) is considered as one of the most important plant macronutrients and proper management of N therefore is a pre-requisite for modern agriculture. Continuous satellite-based monitoring of this key plant trait would help to understand individual crop N use efficiency and thus would enable site-specific N management. Since hyperspectral imaging sensors could provide detailed measurements of spectral signatures corresponding to the optical activity of chemical constituents, they have a theoretical advantage over multi-spectral sensing for the detection of crop N.

Exploring the potential of PROCOSINE and close-range hyperspectral imaging to study the effects of fungal diseases on leaf physiology.

The detection of plant diseases, including fungi, is a major challenge for reducing yield gaps of crops across the world. We explored the potential of the PROCOSINE radiative transfer model to assess the effect of the fungus Pseudocercospora fijiensis on leaf tissues using laboratory-acquired submillimetre-scale hyperspectral images in the visible and near-infrared spectral range. The objectives were (i) to assess the dynamics of leaf biochemical and biophysical parameters estimated using PROCOSINE inversion as a function of the disease stages, and (ii) to discriminate the disease stages by using a Linear Discriminant Analysis model built from the inversion results.

Local Traces: An Over-Approximation of the Behavior of the Proteins in Rule-Based Models.

Thanks to rule-based modelling languages, we can assemble large sets of mechanistic protein-protein interactions within integrated models. Our goal would be to understand how the behavior of these systems emerges from these low-level interactions. Yet, this is a quite long term challenge and it is desirable to offer intermediary levels of abstraction, so as to get a better understanding of the models and to increase our confidence within our mechanistic assumptions.

The Kappa platform for rule-based modeling.

Motivation: We present an overview of the Kappa platform, an integrated suite of analysis and visualization techniques for building and interactively exploring rule-based models. The main components of the platform are the Kappa Simulator, the Kappa Static Analyzer and the Kappa Story Extractor. In addition to these components, we describe the Kappa User Interface, which includes a range of interactive visualization tools for rule-based models needed to make sense of the complexity of biological systems.

Formal derivation of qualitative dynamical models from biochemical networks.

As technological advances allow a better identification of cellular networks, large-scale molecular data are swiftly produced, allowing the construction of large and detailed molecular interaction maps. One approach to unravel the dynamical properties of such complex systems consists in deriving coarse-grained dynamical models from these maps, which would make the salient properties emerge. We present here a method to automatically derive such models, relying on the abstract interpretation framework to formally relate model behaviour at different levels of description.

Landscape-scale variation in plant community composition of an African savanna from airborne species mapping.

Information on landscape-scale patterns in species distributions and community types is vital for ecological science and effective conservation assessment and planning. However, detailed maps of plant community structure at landscape scales seldom exist due to the inability of field-based inventories to map a sufficient number of individuals over large areas. The Carnegie Airborne Observatory (CAO) collected hyperspectral and lidar data over Kruger National Park, South Africa, and these data were used to remotely identify > 500 000 tree and shrub crowns over a 144-km2 landscape using stacked support vector machines.

Microtopographic controls on lowland Amazonian canopy diversity from imaging spectroscopy.

Microtopographic variation is ubiquitous throughout lowland Amazonia, and it may impart patterns of species richness and abundance, and perhaps community compositional changes. To date, no studies have determined the degree to which lowland microtopography influences forest canopy diversity. We developed the first high-resolution maps of forest canopy diversity in Amazonia, focusing on four landscapes on two river systems in Peru.

Mapping tropical forest canopy diversity using high‐fidelity imaging spectroscopy.

There is a growing need for operational biodiversity mapping methods to quantify and to assess the impact of climate change, habitat alteration, and human activity on ecosystem composition and function. Here, we present an original method for the estimation of α- and β-diversity of tropical forests based on high-fidelity imaging spectroscopy. We acquired imagery over high-diversity Amazonian tropical forest landscapes in Peru with the Carnegie Airborne Observatory and developed an unsupervised method to estimate the Shannon index (H′) and variations in species composition using Bray-Curtis dissimilarity (BC) and nonmetric multidimensional scaling (NMDS).

Predicting leaf gravimetric water content from foliar reflectance across a range of plant species using continuous wavelet analysis.

Leaf water content is an important variable for understanding plant physiological properties. This study evaluates a spectral analysis approach, continuous wavelet analysis (CWA), for the spectroscopic estimation of leaf gravimetric water content (GWC, %) and determines robust spectral indicators of GWC across a wide range of plant species from different ecosystems. CWA is both applied to the Leaf Optical Properties Experiment (LOPEX) data set and a synthetic data set consisting of leaf reflectance spectra simulated using the leaf optical properties spectra (PROSPECT) model.

Combinatorial complexity and compositional drift in protein interaction networks.

The assembly of molecular machines and transient signaling complexes does not typically occur under circumstances in which the appropriate proteins are isolated from all others present in the cell. Rather, assembly must proceed in the context of large-scale protein-protein interaction (PPI) networks that are characterized both by conflict and combinatorial complexity. Conflict refers to the fact that protein interfaces can often bind many different partners in a mutually exclusive way, while combinatorial complexity refers to the explosion in the number of distinct complexes that can be formed by a network of binding possibilities.

Intrinsic information carriers in combinatorial dynamical systems.

Many proteins are composed of structural and chemical features--"sites" for short--characterized by definite interaction capabilities, such as noncovalent binding or covalent modification of other proteins. This modularity allows for varying degrees of independence, as the behavior of a site might be controlled by the state of some but not all sites of the ambient protein. Independence quickly generates a startling combinatorial complexity that shapes most biological networks, such as mammalian signaling systems, and effectively prevents their study in terms of kinetic equations-unless the complexity is radically trimmed.

Internal coarse-graining of molecular systems.

Modelers of molecular signaling networks must cope with the combinatorial explosion of protein states generated by posttranslational modifications and complex formation. Rule-based models provide a powerful alternative to approaches that require explicit enumeration of all possible molecular species of a system. Such models consist of formal rules stipulating the (partial) contexts wherein specific protein-protein interactions occur.

Prevention of deep vein thrombosis after total hip replacement. The effect of low-molecular-weight heparin with spinal and general anaesthesia.

Enoxaparin, a low-molecular-weight heparin, has been used together with spinal or general anaesthesia in a prospective, randomised study of 188 consecutive elective hip replacements. Bilateral venography was performed on all patients on day 13 after operation. Group I (65 patients) received spinal anaesthesia and no immediate injection of enoxaparin.

Efficacy and safety of a perioperative enoxaparin regimen in total hip replacement under various anesthesias.

Four trials in which enoxaparin, a low-molecular-weight heparin, was used in patients having hip surgery are reported. In the first two trials, enoxaparin was given before general anesthesia. The protocol consisted of 40 mg of enoxaparin, 4,000 anti-factor Xa IU, subcutaneously 12 hours before surgery, followed by the same dose 12 hours after surgery and then once daily.

Once-daily dosing of enoxaparin (a low molecular weight heparin) in prevention of deep vein thrombosis after total hip replacement.

The main results of three successive prospective clinical trials which represent the successive steps in the definition of once-daily dosing of enoxaparin in elective hip surgery are demonstrated. In the first trial, a dose of 40 mg/day (4000 anti-Factor Xa IU), in one or two subcutaneous injections, was preferred to a dose of 60 mg because it gave the same efficacy with a better tolerance. In a second, randomized double-blind trial, the two modes of administration of a dose of 40 mg, in one or two injections daily, were found to be equivalent with regard to tolerance and efficacy.

[Acute ischemia of the lower limbs in nephrotic syndrome in a young woman].

A thirty-year-old woman, who had onset of nephrotic syndrome during the last part of her pregnancy, experienced recurrent acute ischemia of both lower limbs, leading to three conservative surgical procedures one month after delivery. Investigations disclosed no cause of embolism and were suggestive of thrombosis. The arteriography showed a diffuse reduction in diameter of the aorta and iliac vessels without localised stenosis or other vascular lesions.