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Catchment travel time distributions (TTDs) are an efficient concept for summarizing the time-varying 3D transport of water and solutes towards an outlet in a single function of a water age and for estimating catchment storage by leveraging information contained in tracer data (e.g., deuterium 2H and tritium 3H). It is argued that the preferential use of the stable isotopes of O and H as tracers, compared to tritium, has truncated our vision of streamflow TTDs, meaning that the long tails of the distribution associated with old water tend to be neglected. However, the reasons for the truncation of the TTD tails are still obscured by methodological and data limitations. In this study, we went beyond these limitations and evaluated the differences between streamflow TTDs calculated using only deuterium (2H) or only tritium (3H). We also compared mobile catchment storage (derived from the TTDs) associated with each tracer. For this, we additionally constrained a model that successfully simulated high-frequency stream deuterium measurements with 24 stream tritium measurements over the same period (2015–2017). We used data from the forested headwater Weierbach catchment (42 ha) in Luxembourg. Time-varying streamflow TTDs were estimated by consistently using both tracers within a framework based on StorAge Selection (SAS) functions. We found similar TTDs and similar mobile storage between the 2H- and 3H-derived estimates, despite statistically significant differences for certain measures of TTDs and storage. The streamflow mean travel time was estimated at 2.90±0.54 years, using 2H, and 3.12±0.59 years, using 3H (mean ± 1 SD – standard deviation). Both tracers consistently suggested that less than 10 % of the stream water in the Weierbach catchment is older than 5 years. The travel time differences between the tracers were small compared to previous studies in other catchments, and contrary to prior expectations, we found that these differences were more pronounced for young water than for old water. The found differences could be explained by the calculation uncertainties and by a limited sampling frequency for tritium. We conclude that stable isotopes do not seem to systematically underestimate travel times or storage compared to tritium. Using both stable and radioactive isotopes of H as tracers reduced the travel time and storage calculation uncertainties. Tritium and stable isotopes both had the ability to reveal short travel times in streamflow. Using both tracers together better exploited the more specific information about longer travel times that 3H inherently contains due to its radioactive decay. The two tracers thus had different information contents overall. Tritium was slightly more informative than stable isotopes for travel time analysis, despite a lower number of tracer samples. In the future, it would be useful to similarly test the consistency of travel time estimates and the potential differences in travel time information contents between those tracers in catchments with other characteristics, or with a considerable fraction of stream water older than 5 years, since this could emphasize the role of the radioactive decay of tritium in discriminating younger water from older water.

Patients with severe coronavirus disease (COVID-19) may have COVID-19-associated invasive mold infection (CAIMI) develop. We report 16 cases of CAIMI among 146 nonimmunocompromised patients with severe COVID-19 at an academic hospital in Santiago, Chile. These rates correspond to a CAIMI incidence of 11%; the mortality rate for these patients was 31.2%.

Triacylglycerols (TG) are synthesized at the endoplasmic reticulum (ER) bilayer and packaged into organelles called lipid droplets (LDs). LDs are covered by a single phospholipid monolayer contiguous with the ER bilayer. This connection is used by several monotopic integral membrane proteins, with hydrophobic membrane association domains (HDs), to diffuse between the organelles. However, how proteins partition between ER and LDs is not understood. Here, we employed synthetic model systems and found that HD-containing proteins strongly prefer monolayers and returning to the bilayer is unfavorable. This preference for monolayers is due to a higher affinity of HDs for TG over membrane phospholipids. Protein distribution is regulated by PC/PE ratio via alterations in monolayer packing and HD-TG interaction. Thus, HD-containing proteins appear to non-specifically accumulate to the LD surface. In cells, protein editing mechanisms at the ER membrane would be necessary to prevent unspecific relocation of HD-containing proteins to LDs. Triacylglycerols (TG) are synthesized at the endoplasmic reticulum (ER) bilayer and packaged into monolayer lipid droplets (LDs), but how proteins partition between ER and LDs is poorly understood. Here authors use synthetic model systems and find that proteins containing hydrophobic membrane association domains strongly prefer monolayers and that returning to the bilayer is unfavorable.

Living cells sense the rigidity of their environment and adapt their activity to it. In particular, cells cultured on elastic substrates align their shape and their traction forces along the direction of highest stiffness and preferably migrate towards stiffer regions. Although numerous studies investigated the role of adhesion complexes in rigidity sensing, less is known about the specific contribution of acto-myosin based contractility. Here we used a custom-made single-cell technique to measure the traction force as well as the speed of shortening of isolated myoblasts deflecting microplates of variable stiffness. The rate of force generation increased with increasing stiffness and followed a Hill force-velocity relationship. Hence, cell response to stiffness was similar to muscle adaptation to load, reflecting the force-dependent kinetics of myosin binding to actin. These results reveal an unexpected mechanism of rigidity sensing, whereby the contractile acto-myosin units themselves can act as sensors. This mechanism may translate anisotropy in substrate rigidity into anisotropy in cytoskeletal tension, and could thus coordinate local activity of adhesion complexes and guide cell migration along rigidity gradients.

Background Computing accurate nucleic acid melting temperatures has become a crucial step for the efficiency and the optimisation of numerous molecular biology techniques such as in situ hybridization, PCR, antigene targeting, and microarrays. MELTING is a free open source software which computes the enthalpy, entropy and melting temperature of nucleic acids. MELTING 4.2 was able to handle several types of hybridization such as DNA/DNA, RNA/RNA, DNA/RNA and provided corrections to melting temperatures due to the presence of sodium. The program can use either an approximative approach or a more accurate Nearest-Neighbor approach. Results Two new versions of the MELTING software have been released. MELTING 4.3 is a direct update of version 4.2, integrating newly available thermodynamic parameters for inosine, a modified adenine base with an universal base capacity, and incorporates a correction for magnesium. MELTING 5 is a complete reimplementation which allows much greater flexibility and extensibility. It incorporates all the thermodynamic parameters and corrections provided in MELTING 4.x and introduces a large set of thermodynamic formulae and parameters, to facilitate the calculation of melting temperatures for perfectly matching sequences, mismatches, bulge loops, CNG repeats, dangling ends, inosines, locked nucleic acids, 2-hydroxyadenines and azobenzenes. It also includes temperature corrections for monovalent ions (sodium, potassium, Tris), magnesium ions and commonly used denaturing agents such as formamide and DMSO. Conclusions MELTING is a useful and very flexible tool for predicting melting temperatures using approximative formulae or Nearest-Neighbor approaches, where one can select different sets of Nearest-Neighbor parameters, corrections and formulae. Both versions are freely available at http://sourceforge.net/projects/melting/ and at http://www.ebi.ac.uk/compneur-srv/melting/ under the terms of the GPL license.

Background Quantitative models of biochemical and cellular systems are used to answer a variety of questions in the biological sciences. The number of published quantitative models is growing steadily thanks to increasing interest in the use of models as well as the development of improved software systems and the availability of better, cheaper computer hardware. To maximise the benefits of this growing body of models, the field needs centralised model repositories that will encourage, facilitate and promote model dissemination and reuse. Ideally, the models stored in these repositories should be extensively tested and encoded in community-supported and standardised formats. In addition, the models and their components should be cross-referenced with other resources in order to allow their unambiguous identification. Description BioModels Database http://www.ebi.ac.uk/biomodels/ is aimed at addressing exactly these needs. It is a freely-accessible online resource for storing, viewing, retrieving, and analysing published, peer-reviewed quantitative models of biochemical and cellular systems. The structure and behaviour of each simulation model distributed by BioModels Database are thoroughly checked; in addition, model elements are annotated with terms from controlled vocabularies as well as linked to relevant data resources. Models can be examined online or downloaded in various formats. Reaction network diagrams generated from the models are also available in several formats. BioModels Database also provides features such as online simulation and the extraction of components from large scale models into smaller submodels. Finally, the system provides a range of web services that external software systems can use to access up-to-date data from the database. Conclusions BioModels Database has become a recognised reference resource for systems biology. It is being used by the community in a variety of ways; for example, it is used to benchmark different simulation systems, and to study the clustering of models based upon their annotations. Model deposition to the database today is advised by several publishers of scientific journals. The models in BioModels Database are freely distributed and reusable; the underlying software infrastructure is also available from SourceForge https://sourceforge.net/projects/biomodels/ under the GNU General Public License.

During the second third of last century, the Orinoco Crocodile ( Crocodylus intermedius ) underwent a hunting process driven by the demand from the North American, European, and Japanese leather industry, resulting in a sharp decline of its populations. Currently, only two known remaining populations of this Critically Endangered species persist in the Colombian Orinoquía: in the Guayabero-Duda-Lozada and the Cravo Norte-Ele-Lipa River Systems. The latter has been the only population subject of study, including recent surveys and local conservation initiatives such as egg and hatchling ranching. Despite suggestions for population recovery based on the observed increase in clutches in the area, information regarding its genetic status has been pending assessment. This research aims to provide a genetic characterization of this remaining population and to evaluate the diversity recovered during a period of the egg ranching initiative. For this purpose, we utilized variable molecular markers, specifically 17 microsatellite loci, nuclear DNA. Despite revealing intermediate levels of genetic diversity, we identified an effective population size of 11.5–17, well below the minimum values proposed for short-term subsistence. While no evidence of inbreeding was found, it is acknowledged as a potential risk based on the population’s history. Additionally, we detected a historical bottleneck possibly influenced by arid periods affecting the region since the Pleistocene. While the evaluated population presents a unique opportunity for C . intermedius conservation, it also exposes a high risk of entering the extinction vortex. The primary action to be taken is to support the egg and hatchling ranching program, which successfully recovered most of the genetic diversity present in the population.

The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously. Ontologies are one of the tools frequently used for this purpose. We describe here three ontologies created specifically to address the needs of the systems biology community. The Systems Biology Ontology (SBO) provides semantic information about the model components. The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of systems biology models, their characterization and interrelationships. The Terminology for the Description of Dynamics (TEDDY) categorizes dynamical features of the simulation results and general systems behavior. The provision of semantic information extends a model's longevity and facilitates its reuse. It provides useful insight into the biology of modeled processes, and may be used to make informed decisions on subsequent simulation experiments. The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. This Perspective discusses the development and use of ontologies that are designed to add semantic information to computational models and simulations.

The severity of SARS-CoV-2 infection has been related to uncontrolled inflammatory innate responses and impaired adaptive immune responses mostly due to exhausted T lymphocytes and lymphopenia. In this work we have characterized the nature of the lymphopenia and demonstrate a set of factors that hinder the effective control of virus infection and the activation and arming of effector cytotoxic T CD8 cells and showing signatures defining a high-risk population. We performed immune profiling of the T helper (Th) CD4+ and T CD8+ cell compartments in peripheral blood of 144 COVID-19 patients using multiparametric flow cytometry analysis. On the one hand, there was a consistent lymphopenia with an overrepresentation of non-functional T cells, with an increased percentage of naive Th cells (CD45RA+, CXCR3-, CCR4-, CCR6-, CCR10-) and persistently low frequency of markers associated with Th1, Th17, and Th1/Th17 memory-effector T cells compared to healthy donors. On the other hand, the most profound alteration affected the Th1 subset, which may explain the poor T cells responses and the persistent blood virus load. Finally, the decrease in Th1 cells may also explain the low frequency of CD4+ and CD8+ T cells that express the HLA-DR and CD38 activation markers observed in numerous patients who showed minimal or no lymphocyte activation response. We also identified the percentage of HLA-DR+CD4+ T cells, PD-1+CD+4/CD8+ T cells in blood, and the neutrophil/lymphocyte ratio as useful factors for predicting critical illness and fatal outcome in patients with confirmed COVID-19.

Background Systems biology projects and omics technologies have led to a growing number of biochemical pathway models and reconstructions. However, the majority of these models are still created de novo , based on literature mining and the manual processing of pathway data. Results To increase the efficiency of model creation, the Path2Models project has automatically generated mathematical models from pathway representations using a suite of freely available software. Data sources include KEGG, BioCarta, MetaCyc and SABIO-RK. Depending on the source data, three types of models are provided: kinetic, logical and constraint-based. Models from over 2 600 organisms are encoded consistently in SBML, and are made freely available through BioModels Database at http://www.ebi.ac.uk/biomodels-main/path2models . Each model contains the list of participants, their interactions, the relevant mathematical constructs, and initial parameter values. Most models are also available as easy-to-understand graphical SBGN maps. Conclusions To date, the project has resulted in more than 140 000 freely available models. Such a resource can tremendously accelerate the development of mathematical models by providing initial starting models for simulation and analysis, which can be subsequently curated and further parameterized.