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The five papers published by Hodgkin and Huxley in 1952 are seminal works in the field of physiology, earning their authors the Nobel Prize in 1963 and ushering in the era of membrane biophysics. The papers present a considerable challenge to the novice student, but this has been partly allayed by recent publications that have updated the reporting of current and voltage to reflect the modern convention and two books that describe the contents of the papers in detail. A disadvantage is that these guides contain hundreds of pages, requiring considerable time and energy on behalf of the reader. We present a concise guide to the Hodgkin and Huxley papers that includes only essential content, with the data presented in a linear and logical manner. We have color-coded figures for ease of understanding and included boxes that summarize key information for easy reference. It is our expectation that this article will act as an accessible introduction for students to the work of Hodgkin and Huxley and hopefully foster an appreciation for a fascinating story that repays in-depth study. NEW & NOTEWORTHY The Hodgkin and Huxley papers continue to inspire and intimidate, 70 years after their publication. The diverse subjects they cover include advanced experimental procedures, complex data analysis, calculus, and modeling, all of which ensure the papers can present a challenging read. We present a concise guide to the papers that includes only essential content depicted in color-coded graphs, allowing tracking of data from recordings to analysis and incorporation into the model to ease understanding. [ABSTRACT FROM AUTHOR]

Abstract In order to make 2nd-generation biofuels more competitive, high solid-matter content has to be reached. To progress towards this target, the mechanism for destructuring lignocellulose fibres in semidilute conditions has to be well understood, as this configuration shows the basic mechanism which limits transfers and efficiency. This study aims to delve deeply into the biophysical and transfer limitations occurring during enzymatic hydrolysis. A specific experimental set-up associating in-situ and ex-situ physical (rheometry, chord length analysis) and biochemical analysis was used to expand the knowledge of hydrolysis of extruded softwood paper pulp over 24 h under different substrate concentrations (1%–3%) and enzyme doses (Accellerase 1500, 5 and 25 FPU/g cellulose). Non-Newtonian behaviour associated with pronounced yield stress stand as the major factors limiting process efficiency. A critical time was deduced from viscosity evolution, and the existence of a unique, dimensionless viscosity-time curve was established, suggesting similar mechanisms for fibre degradation. In addition, chord length distribution allowed for the description of population evolution and was discussed in the light of in-situ viscosity and hydrolysis yield. Physical (viscosity, particle size) and biochemical (substrate) kinetics were modelled (second-order) and coefficients identified. A chronology of the encountered phenomenological limitations demonstrates the necessity of optimising bioprocesses by considering physical parameters. A reference feed rate is proposed in order to reach high solid loading under fed-batch strategy. Highlights • An in- & ex-situ multiscale approach was used to study the paper pulp hydrolysis. • The bio-physical and transfer limitations during hydrolysis were investigated. • A non-Newtonian behaviour was the major factor limiting process efficiency. • A unique dimensionless viscosity-time curve was identified. • A reference feed rate is proposed to reach high solid loading with fed-batch mode. [ABSTRACT FROM AUTHOR]

While mounting evidence indicates that a phylogenetically diverse group of animals detect Earth-strength magnetic fields, a magnetoreceptor has not been identified in any animal. One possible reason that identifying a magnetoreceptor has proven challenging is that, like many research fields, magnetoreception research lacks extensive independent replication. Independent replication is important because a subset of studies undoubtedly contain false positive results and without replication it is difficult to determine whether the outcome of an experiment is a false positive. However, we report here a reanalysis of a well-cited paper on honeybee magnetoreception demonstrating that the original paper represented a false positive finding caused by incorrect estimates of probability. We also point out how good experimental design practices could have revealed the error prior to publication. Hopefully, this reanalysis will serve as a reminder of the importance of good experimental design in order to reduce the likelihood of publishing false positive results. [ABSTRACT FROM AUTHOR]

Understanding active matter has led to new perspectives on biophysics and non-equilibrium dynamics. However, the development of numerical tools for simulating active fluids capable of incorporating non-trivial boundaries or inclusions has lagged behind. Active particle-based methods, which typically excel at this, suffer from large density fluctuations that affect the dynamics of inclusions. To this end, we advance the Active-Nematic Multi-Particle Collision Dynamics algorithm, a particle-based method for simulating active nematics, by addressing the large density fluctuations that arise from activity. This paper introduces three activity formulations that mitigate the coupling between activity and local density. Local density fluctuations are decreased to a level comparable to the passive limit while retaining active nematic phenomenology and increasing the active turbulence regime four-fold in two dimensions. These developments extend the technique into a flexible tool for modeling active systems, including solutes and inclusions, with broad applications for the study of biophysical systems. Particle-based models of soft active matter are known to exhibit large density fluctuations, which may be problematic for considering homogeneous systems. Through considering the coupling of activity to local density, we reduce density fluctuations while retaining active turbulent dynamics. [ABSTRACT FROM AUTHOR]

Definition: This entry paper is an attempt to explain how the discrete nature of light (energy discreteness in the form of photons) constrains the light detection process all along the evolutionary path, in the not-fully-understood photoreceptive systems of unicellular microorganisms (nonimaging systems) and in the complex and well-known visual system of higher organisms (imaging systems). All these systems are perfect examples of the interplay between physics and biology, i.e., they are the perfect topic of research for biophysicists. The paper describes how photoreceptive and visual systems achieve the goal of photon counting, which information is conveyed by a finite number of photons, and which noise factors limit light-detecting processes. [ABSTRACT FROM AUTHOR]

Biophysically detailed simulations of neuronal activity often rely on solving large systems of differential equations; in some models, these systems have tens of thousands of states per cell. Numerically solving these equations is computationally intensive and requires making assumptions about the initial cell states. Additional realism from incorporating more biological detail is achieved at the cost of increasingly more states, more computational resources, and more modeling assumptions. We show that for both a point and morphologically-detailed cell model, the presence and timing of future action potentials is probabilistically well-characterized by the relative timings of a moderate number of recent events alone. Knowledge of initial conditions or full synaptic input history is not required. While model time constants, etc. impact the specifics, we demonstrate that for both individual spikes and sustained cellular activity, the uncertainty in spike response decreases as the number of known input events increases, to the point of approximate determinism. Further, we show cellular model states are reconstructable from ongoing synaptic events, despite unknown initial conditions. We propose that a strictly event-based modeling framework is capable of representing the complexity of cellular dynamics of the differential-equations models with significantly less per-cell state variables, thus offering a pathway toward utilizing modern data-driven modeling to scale up to larger network models while preserving individual cellular biophysics. Author summary: There are 86 billion neurons in the human brain, each of which is a complex cell that responds to synaptic stimuli of other neurons with electrical signals. Neuroscientists have uncovered many of the biophysical mechanisms underlying the neuron's function and utilize them to create detailed simulations of neurons and neural networks. However, due to the complexity of the neuron, these simulations require extensive computational resources. In this paper, we present a new modeling framework that incorporates the discrete synaptic events of neurons with the detailed mechanistic modeling of their biophysics, using a strictly event-based protocol. We investigate the extent to which this new event-based framework behaves like the existing conductance-based modeling approach by measuring how much its future responses vary provided different numbers of past input stimuli. This framework is an entry point for integrating machine learning methods to assist in reducing the computational complexity of detailed neuron modeling. The goal of this work is to enable researchers to better integrate mechanistic understanding of cell biology into broader multiscale studies. [ABSTRACT FROM AUTHOR]

Deep brain stimulation (DBS) in thalamic reticular nucleus (TRN) neuron provides a novel treatment for drug-resistant epilepsy via the induced electrical field (EFs). However, the mechanisms underlying EF effects remain unclear. This paper investigated how EFs regulate low-threshold dendritic Ca2+ (dCa) response and thus contribute to the input–output relationship of TRN cell. Our results showed that EFs modulate firing modes differently in a neuronal state-dependent manner. At the depolarized state, EFs only regulate the spike timing of a somatic stimulus-evoked single action potential (AP) with less contribution in the regulation of dCa response but could induce the transition between a dendritic stimulus-evoked single AP and a tonic burst of APs via the moderate regulation of dCa response. At the hyperpolarized state, EFs have significant effects on the dCa response, which modulate the large dCa response-dependent burst discharge and even cause a transition from this type of burst discharge to a single AP with less dCa response. Moreover, EF effects on stimulation threshold of somatic spiking prominently depend on EF-regulated dCa responses and the onset time differences between the stimulus and EF give rise to the distinct effect in the EF regulation of dCa responses. Finally, the larger neuronal axial resistance tends to result in the dendritic stimulus-evoked dCa response independent of somatic state. Interestingly, in this case, the EF application could reproduce the similar somatic state-dependent dCa response to dendritic stimulus which occurs in the case of lower axial resistance. These results suggest that the influence of EF on neuronal activities depends on neuronal intrinsic properties, which provides insight into understanding how DBS in TRN neuron modulates epilepsy from the point of view of biophysics. [ABSTRACT FROM AUTHOR]

In this paper, a biophysical fractional diffusive cancer model with virotherapy is thoroughly analyzed and analytically simulated. The goal of this biophysical model is to represent both the dynamics of cancer development and the results of virotherapy, which uses viruses to target and destroy cancer cells. The Caputo sense is applied to the fractional derivatives. We look at the governing model's existence and uniqueness. For analytical solutions, the Laplace residual power series approach is used. The study investigates the model's dynamic behavior, shedding light on the development of cancer and the effects of virotherapy. The research advances our knowledge of cancer modeling and treatment options. Numerical simulations show the agreement between the analytical results and the related numerical solutions, proving the usefulness of the analytical solution. [ABSTRACT FROM AUTHOR]

In this paper it is obtained, through variational methods and sub-supersolution arguments, existence and multiplicity of solutions for a nonhomogeneous problem which arise in several branches of science such as chemical reactions, biophysics and plasma physics. Under a general hypothesis it is proved an existence result and multiple solutions are obtained by considering an additional natural condition. [ABSTRACT FROM AUTHOR]

• The pattern formation of morphogens is studied in geometrically-confined microtissues during early embryogenesis. • The microtissue consisted of human stem cells is modeled as a piece of biphasic poroelastic material. • The active contractility is fully-coupled with the reaction-diffusion of the morphogens through the poroelasticity. • Linear stability analysis is performed to determine ranges of parameters that leads to diffusion-induced instability. • A comprehensive parameter study, including the sizes and geometries of the tissues, is carried out in the paper. The reaction-diffusion models have been extensively applied to explain the mechanism of pattern formations in early embryogenesis based on geometrically confined microtissues consisting of human pluripotent stem cells. Mechanical cues, such as the cellular stresses and strains, have been found to dictate the pattern formation in human stem cell differentiation. As a result, the traditional reaction-diffusion models are modified by adding mechanically related terms to consider the role played by the mechanical cues during the very early stage of embryogenesis. However, these models either do not consider the activeness of the cellular tissues or neglect their poroelastic nature that biological tissues are made by both cells and interstitial fluid. Here we propose a modified reaction-diffusion model that couples with the active contraction of cellular tissues. The cellular tissue is modelled as a piece of biphasic poroelastic material, where mechanical forces naturally regulate the transport of chemical cues. Such chemical cues direct cell fate and hence yield certain types of pattern formations observed in previous experiments. [ABSTRACT FROM AUTHOR]

Bacterial swarms are a highly-researched example of natural active matter. In particular, the interplay between biological interactions and the physics underlying the swarming dynamics is of both biological and physical interest. In this paper, we study mixed swarms of Bacillus subtilis and Pseudomonas aeruginosa. We find intricate interactions between the species, showing both cooperation and segregation across different spatial and temporal scales. On one hand, even though axenic colonies grow on disparate time scale, an order of magnitude apart, the two-species swarm together, forming a single, combined colony. However, the rapidly moving populations are locally segregated, with different characteristic speeds and lengths (or cluster sizes) that depend on the ratio between the species. Comparison with controlled mutant strains suggest that both the physical and known biological differences in species characteristics may not be enough to explain the segregation between the species in the mixed swarm. We hypothesize that the heterogeneous spatial distribution is due to some mechanism that enables bacteria to recognize their own kind, whose precise origin we could not identify. [ABSTRACT FROM AUTHOR]

This paper presents the methods that have participated in the SHREC 2022 contest on protein–ligand binding site recognition. The prediction of protein- ligand binding regions is an active research domain in computational biophysics and structural biology and plays a relevant role for molecular docking and drug design. The goal of the contest is to assess the effectiveness of computational methods in recognizing ligand binding sites in a protein based on its geometrical structure. Performances of the segmentation algorithms are analyzed according to two evaluation scores describing the capacity of a putative pocket to contact a ligand and to pinpoint the correct binding region. Despite some methods perform remarkably, we show that simple non-machine-learning approaches remain very competitive against data-driven algorithms. In general, the task of pocket detection remains a challenging learning problem which suffers of intrinsic difficulties due to the lack of negative examples (data imbalance problem). [Display omitted] • A new contest for binding site detection in a protein. • Proteins are provided both as molecular surfaces and in anonymized PQR format. • Analysis of computational methods for recognizing ligand binding sites in a protein. • Analysis of the performances of the methods that participated in SHREC 2022. [ABSTRACT FROM AUTHOR]

We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM's Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM's Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen's early Nobel prize winning experiments by using OpenMM's Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology. Author summary: The cell's most important pieces of machinery are large complexes of proteins often along with nucleic acids. From the ribosome, to CRISPR-Cas9, to transcription factors and DNA-wrangling proteins like the SMC-Kleisins, these complexes allow organisms to replicate and enable cells to respond to environmental cues. Computer simulation is a key technology that can be used to connect physical theories with biological reality. Unfortunately, the time and length scales accessible to molecular simulation have not kept pace with our ambition to study the cell's molecular factories. Many simulation codes also unfortunately remain effectively locked away from the user community who need to modify them as more of the underlying physics is learned. In this paper, we present OpenAWSEM and Open3SPN2, two new easy-to-use and easy to modify implementations of efficient and accurate coarse-grained protein and DNA simulation forcefields that can now be run hundreds of times faster than before, thereby making studies of large biomolecular machines more facile. [ABSTRACT FROM AUTHOR]

Earth system models (ESMs) have been developed to represent the role of terrestrial ecosystems on the energy, water, and carbon cycles. However, many ESMs still lack representation of within-ecosystem heterogeneity and diversity. In this paper, we present the Ecosystem Demography model version 2.2 (ED-2.2). In ED-2.2, the biophysical and physiological processes account for the horizontal and vertical heterogeneity of the ecosystem: the energy, water, and carbon cycles are solved separately for a series of vegetation cohorts (groups of individual plants of similar size and plant functional type) distributed across a series of spatially implicit patches (representing collections of micro-environments that have a similar disturbance history). We define the equations that describe the energy, water, and carbon cycles in terms of total energy, water, and carbon, which simplifies the differential equations and guarantees excellent conservation of these quantities in long-term simulation (< 0.1 % error over 50 years). We also show examples of ED-2.2 simulation results at single sites and across tropical South America. These results demonstrate the model's ability to characterize the variability of ecosystem structure, composition, and functioning both at stand and continental scales. A detailed model evaluation was conducted and is presented in a companion paper. Finally, we highlight some of the ongoing model developments designed to improve the model's accuracy and performance and to include processes hitherto not represented in the model. [ABSTRACT FROM AUTHOR]

First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping researchers promote themselves alongside their papers. Sherman Foo is first author on 'Diacylglycerol at the inner nuclear membrane fuels nuclear envelope expansion in closed mitosis', published in JCS. Sherman conducted the research described in this article while a PhD student in the labs of Snezhana Oliferenko (The Francis Crick Institute, London, UK, and Randall Centre for Cell and Molecular Biophysics, King's College London, UK) and Markus R. Wenk (Singapore Lipidomics Incubator, National University of Singapore). He is now a postdoc in the lab of Buzz Baum at Medical Research Council Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, UK, where he is currently studying cellular organization of hyperthermophilic archaea, with a particular focus on the surface layer and cell cycle of Sulfolobus acidocaldarius. [ABSTRACT FROM AUTHOR]

First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping researchers promote themselves alongside their papers. Lilian Sluimer is first author on 'SKOR1 mediates FER kinase-dependent invasive growth of breast cancer cells', published in JCS. Lilian conducted the research described in this article while working on this research as a first-year master's student and continued working on this project as a research technician for a year in Patrick Derksen's lab atUMCUtrecht, The Netherlands. She is nowa PhD student in the lab of Anna Akhmanova at the Division of Cell Biology, Neurobiology and Biophysics, Utrecht University, The Netherlands, investigating the organization and dynamics of cytoskeletal microtubule networks in different cellular systems. [ABSTRACT FROM AUTHOR]

This paper develops a non-equilibrium thermodynamics approach to oncogenesis, with a particular focus on 'symmetry breaking'. The Onsager phenomenological coefficients are introduced to show the biophysical and thermophysical properties of cellular systems with differences between normal and cancerous cells. Seebeck- and Peltier-like effects are introduced to simplify the description of heat exchange and ion fluxes, in an effort to characterize the distinct role of the cellular electric membrane potential. Our results indicate that oncogenesis leads to changes in: (i) the thermophysical properties of the cell cytoplasm, caused by differences in density and heat capacity, (ii) the interactions with the micro-environment, (iii) geometrical characteristics, both in fractal dimensions and in shape symmetry, and (iv) the constitutive properties of membrane fluxes. This presents a unifying biophysics concept for such diverse characteristics, and it may yield new diagnostic and therapeutic opportunities. [ABSTRACT FROM AUTHOR]

This paper describes the possibilities of supporting the teaching of neural tissue biology and biophysics through experiments with a simple, commonly available electroencephalography headset. Data are transmitted over a Bluetooth virtual serial port and can be analyzed in several ways by students or used solely as a potential motivational factor for teaching otherwise challenging and abstract curriculum about the human brain. [ABSTRACT FROM AUTHOR]

From the molecular interactions between cardiolipin, ceramide, and autophagy proteins to the effects of raft disruptors on membrane fluidity, these studies illuminated the delicate balance within lipid rafts. The four research papers presented in this Special Issue delved into the profound yet intricate relationship between biophysics and cellular functionality, with a particular emphasis on cryopreservation of cells and the lipid behavior in cell membranes. The membrane of a cell, often compared to a dynamic city border, carries out an intricate dance of controlling entry and exit, guarding the valuable life processes occurring inside. [Extracted from the article]

This paper presents a new approach to guiding coastal stakeholders about making informed decisions about Disaster Risk Reduction (DRR) measures and alternatives. As part of the RISC-KIT project and tool box, the paper presents a holistic DRR measure approach including the biophysical environment, governance aspects and practical examples from coastal areas in Europe and elsewhere. The guide (see: www.coastal-management.eu ) is addressed to a wide variety of coastal stakeholders with a different level of knowledge about DRR measures with the aim to provide guidance and information. The paper gives an overview of the overall structure of the guide. [ABSTRACT FROM AUTHOR]

In this paper, we reject commonly accepted views on fundamentality in science, either based on bottom-up construction or top-down reduction to isolate the alleged fundamental entities. We do not introduce any new scientific methodology, but rather describe the current scientific methodology and show how it entails an inherent search for foundations of science. This is achieved by phrasing (minimal sets of) metaphysical assumptions into falsifiable statements and define as fundamental those that survive empirical tests. The ones that are falsified are rejected, and the corresponding philosophical concept is demolished as a prejudice. Furthermore, we show the application of this criterion in concrete examples of the search for fundamentality in quantum physics and biophysics. [ABSTRACT FROM AUTHOR]

Proteins in cellular environments are highly susceptible. Local perturbations to any residue can be sensed by other spatially distal residues in the protein molecule, showing long-range correlations in the native dynamics of proteins. The long-range correlations of proteins contribute to many biological processes such as allostery, catalysis, and transportation. Revealing the structural origin of such long-range correlations is of great significance in understanding the design principle of biologically functional proteins. In this work, based on a large set of globular proteins determined by X-ray crystallography, by conducting normal mode analysis with the elastic network models, we demonstrate that such long-range correlations are encoded in the native topology of the proteins. To understand how native topology defines the structure and the dynamics of the proteins, we conduct scaling analysis on the size dependence of the slowest vibration mode, average path length, and modularity. Our results quantitatively describe how native proteins balance between order and disorder, showing both dense packing and fractal topology. It is suggested that the balance between stability and flexibility acts as an evolutionary constraint for proteins at different sizes. Overall, our result not only gives a new perspective bridging the protein structure and its dynamics but also reveals a universal principle in the evolution of proteins at all different sizes. Author summary: The long-range correlated fluctuations are closely related to many biological processes of the proteins, such as catalysis, ligand binding, biomolecular recognition, and transportation. In this paper, we elucidate the structural origin of the long-range correlation and describe how native contact topology defines the slow-mode dynamics of the native proteins. Our result suggests an evolutionary constraint for proteins at different sizes, which may shed light on solving many biophysical problems such as structure prediction, multi-scale molecular simulations, and the design of molecular machines. Moreover, in statistical physics, as the long-range correlations are notable signs of the critical point, unveiling the origin of such criticality can extend our understanding of the organizing principle of a large variety of complex systems. [ABSTRACT FROM AUTHOR]

Background and Aim Human Serum Albumin (HSA) is one of the most abundant proteins in the blood vascular system which regulates the transportation of many chemical compounds and molecules. The purpose of this study is to review the studies about the effects of three groups of pesticides (Insecticides, herbicides and fungicides) on the molecular structure of HSA protein. Methods & Materials This systematic review covers 35 studies of biophysical studies of the effect of pesticides on HSA protein. These papers were searched in PubMed, Science Direct, Web of Science databases and using Google Scholar search engine among those published from 1980 to 2019. Ethical Considerations In this study, all ethical principles were considered. Results Given the close relationship between biological activities of HSA and its secondary structure, the most of the reviewed articles analyzed the secondary structures of the HSA using various biophysical methods such as Fourier Transform Infrared (FTIR), Circular Dichroism (CD) and computational analysis. In general, HSA-pesticides interactions can cause a reduction in α-helix structure and an increase in other secondary structures including β-sheet, β-anti, and random coils. In the most reports, it has been proven that the pesticides interact with HSA through hydrophobic and electrostatic interactions and hydrogen bonding. These interactions take place in the IIA subdomain (Site 1) of HSA. The binding constants of these interactions were in the range of 10 3 to 10 6 M-1. Conclusion The changes around the single important tryptophan residue of HSA (Trp-214) induce conformational deformity in the IIA subdomain of this protein which causes the loss of its native structure and leads to a decrease in free HSA concentrations which subsequently interrupt the transport of the essential compounds like drugs and hormones in the blood vascular system. [ABSTRACT FROM AUTHOR]

The Ecosystem Demography model version 2.2 (ED-2.2) is a terrestrial biosphere model that simulates the biophysical, ecological, and biogeochemical dynamics of vertically and horizontally heterogeneous terrestrial ecosystems. In a companion paper , we described how the model solves the energy, water, and carbon cycles, and verified the high degree of conservation of these properties in long-term simulations that include long-term (multi-decadal) vegetation dynamics. Here, we present a detailed assessment of the model's ability to represent multiple processes associated with the biophysical and biogeochemical cycles in Amazon forests. We use multiple measurements from eddy covariance towers, forest inventory plots, and regional remote-sensing products to assess the model's ability to represent biophysical, physiological, and ecological processes at multiple timescales, ranging from subdaily to century long. The ED-2.2 model accurately describes the vertical distribution of light, water fluxes, and the storage of water, energy, and carbon in the canopy air space, the regional distribution of biomass in tropical South America, and the variability of biomass as a function of environmental drivers. In addition, ED-2.2 qualitatively captures several emergent properties of the ecosystem found in observations, specifically observed relationships between aboveground biomass, mortality rates, and wood density; however, the slopes of these relationships were not accurately captured. We also identified several limitations, including the model's tendency to overestimate the magnitude and seasonality of heterotrophic respiration and to overestimate growth rates in a nutrient-poor tropical site. The evaluation presented here highlights the potential of incorporating structural and functional heterogeneity within biomes in Earth system models (ESMs) and to realistically represent their impacts on energy, water, and carbon cycles. We also identify several priorities for further model development. [ABSTRACT FROM AUTHOR]

The following paper presents the history of the Climate and Human Health Commission at the International Society of Biometeorology after more than one decade since its creation. A brief history of the origins of the human biometeorology is revealed through some of the main research topics and publications of the founders of the society in this field. Secondly, it is presented as a brief review of the activities of the commission in the last 10 years, based on the reports that have periodically been submitted by members of the commission to the Bulletin of the society. A summary of the topics of interest on human biometeorology and the most frequent research topics are also described. Thirdly, the need of adapting human biometeorology contents, methods and techniques to a changing world is articulated according to some of the new environmental threats in the XXI century. Finally, a list of future actions and research lines collected through a form from members of the commission is presented. The paper concludes with the existence of great challenge for human biometeorology in order to transform biometeorological knowledge into specific services to improve the wellbeing of human beings. [ABSTRACT FROM AUTHOR]

The estimation of soil moisture and crop biomass based on differential interferometry is questioned by the influence of intercepted rain (i.e., plant surface moisture) on repeat-pass observables. The magnitude, the origin of this effect, as well as its dependence on system and crop biophysical parameters have been only marginally addressed so far. This paper intends to investigate these aspects within the frame of a laboratory experiment carried out in a highly controlled electromagnetic environment. The collection of multifrequency and fully polarimetric scatterometer profiles offers a distinctive data set, which helps to understand the variations of the interferometric observables in response to a varying plant surface moisture. These changes are assessed by comparing the predictions of a first-order scattering solution with the impact found in the experimental data. Furthermore, the connection between plant surface moisture and differential interferometric observables (i.e., the magnitude and phase of the interferometric coherence) is empirically tested with the aid of regression techniques. Irrespective of frequency and polarization, intercepted water is found to impact the interferometric coherence in a similar way as changes in soil and/or plant water status, i.e., the increase of the sensor to target optical path. Changes of plant surface moisture might be erroneously mistaken either for soil water content or fresh biomass variations. Therefore, this paper raises the possibility that, in certain circumstances, intercepted water might represent a potential source of bias for the estimation of these two land surface parameters. [ABSTRACT FROM PUBLISHER]

Transient receptor potential (TRP) proteins form Ca2+-permeable, nonselective cation channels, but their role in neuronal Ca2+ homeostasis is elusive. In the present paper, we show that TRPC channels potently regulate synaptic plasticity by changing the presynaptic Ca2+-homeostasis of hippocampal neurons. Specifically, loss of TRPC1/C4/C5 channels decreases basal-evoked secretion, decreases the pool size of readily releasable vesicles, and accelerates synaptic depression during high-frequency stimulation (HFS). In contrast, primary TRPC5 channel-expressing neurons, identified by a novel TRPC5–τ-green fluorescent protein (τGFP) knockin mouse line, show strong short-term enhancement (STE) of synaptic signaling during HFS, indicating a key role of TRPC5 in short-term plasticity. Lentiviral expression of either TRPC1 or TRPC5 turns classic synaptic depression of wild-type neurons into STE, demonstrating that TRPCs are instrumental in regulating synaptic plasticity. Presynaptic Ca2+ imaging shows that TRPC activity strongly boosts synaptic Ca2+ dynamics, showing that TRPC channels provide an additional presynaptic Ca2+ entry pathway, which efficiently regulates synaptic strength and plasticity. [ABSTRACT FROM AUTHOR]

Objective: Systematic Review was used to evaluate the efficacy and safety of Dalfampridine (DAP) in the treatment of Mobility Disability (MS) in patients with Multiple Sclerosis. Methods: Clinical randomized controlled studies about DAP and placebo in the treatment of Mobility Disability in patients with Multiple Sclerosis until March 2019 were explored by searching Embase, PubMed, Cochrane, Web of Knowledge, and ClinicalTrials.gov. Literature screening, data extraction, quality assessment, and statistical analysis were performed by using Stata 14.0. Results: 10 papers were included in the meta-analysis, and the number of patients was 2100. In conclusion, the application of DAP in clinical can significantly improve the Mobility Disability of patients [OR = 2.73, 95%CI (1.66, 4.50), P<0.001, I2 = 74.1%] and boost the mobility speed of patients in Timing 24 Minute Walk Test (T24FW) [SMD = 3,08, 95%CI(1,58, 4.58), P<0.001, I2 = 98.7%]. There are no significant differences of the incidence of adverse events [RR = 1.06, 95%CI (0.99, 1.14), P = 0.928, I2 = 0.0%] and urinary tract infection [RR = 1.21, 95%CI(0.91, 1.60), P = 0.145, I2 = 37.2%] between the DAP test group (Doses≤10 mg) and the placebo control group, and the incidence of adverse events [RR = 1.14, 95%CI(1.02, 1.28), P = 0.793, I2 = 0.0%] and urinary tract infection[RR = 3.05, 95%CI(1.04, 8.99), P = 0.680, I2 = 0.0%] for the DAP test group (Doses>10 mg) is a litter higher than the placebo control group. Conclusion: DAP can effectively improve Mobility Disability in patients with Multiple Sclerosis, which is safe and reliable in specific DAP usage doses. [ABSTRACT FROM AUTHOR]

This paper reports an outdoor-use polymerase chain reaction (PCR) technology in which stability of resistance temperature detectors (RTDs) is remarkably improved. A thin-film RTD made of non-annealed Pt shows accuracy degradation because the resistance of the RTD tends to decrease during the PCR operation. Thus, the annealing process is applied to the Pt RTD to improve the stability, which is a prerequisite to the accurate measurement of the absolute temperature. Both heaters and the RTD are fabricated on a thin quartz substrate whose melting temperature is high enough for annealing. The performances in the PCR time and power consumption are enhanced by reducing the size of the heater chips with no degradation in the temperature uniformity. A spring-loaded electrode is employed to simplify the procedure of electrical connection to the thermal controller and loading/unloading of the PCR chip. The contact area of the electrical connection is so small that the conductive thermal resistance increases; thereby small heat dissipation can be exploited for low-power operation. The stability of the RTD is experimentally confirmed in terms of resistance variation over repeated PCR operations (four times). The least variation of 0.005%, which corresponds to a negligible temperature variation of 0.038 °C for the PCR, is achieved from the RTD annealed for 5 min at 450 °C. The gel-electrophoresis result indicates that the PCR performance of the proposed system using a film-type PCR chip is comparable to that of a conventional system using a vial tube despite its low power consumption. [ABSTRACT FROM AUTHOR]

Human body communication (HBC) has emerged as an alternative to radio wave communication for connecting low power, miniaturized wearable, and implantable devices in, on, and around the human body. HBC uses the human body as the communication channel between on-body devices. Previous studies characterizing the human body channel has reported widely varying channel response much of which has been attributed to the variation in measurement setup. This calls for the development of a unifying bio-physical model of HBC, supported by in-depth analysis and an understanding of the effect of excitation, termination modality on HBC measurements. This paper characterizes the human body channel up to 1 MHz frequency to evaluate it as a medium for the broadband communication. The communication occurs primarily in the electro-quasistatic (EQS) regime at these frequencies through the subcutaneous tissues. A lumped bio-physical model of HBC is developed, supported by experimental validations that provide insight into some of the key discrepancies found in previous studies. Voltage loss measurements are carried out both with an oscilloscope and a miniaturized wearable prototype to capture the effects of non-common ground. Results show that the channel loss is strongly dependent on the termination impedance at the receiver end, with up to 4 dB variation in average loss for different termination in an oscilloscope and an additional 9 dB channel loss with wearable prototype compared to an oscilloscope measurement. The measured channel response with capacitive termination reduces low-frequency loss and allows flat-band transfer function down to 13 KHz, establishing the human body as a broadband communication channel. Analysis of the measured results and the simulation model shows that instruments with 50 Ω input impedance (Vector Network Analyzer, Spectrum Analyzer) provides pessimistic estimation of channel loss at low frequencies. Instead, high impedance and capacitive termination should be used at the receiver end for accurate voltage mode loss measurements of the HBC channel at low frequencies. The experimentally validated bio-physical model shows that capacitive voltage mode termination can improve the low frequency loss by up to 50 dB, which helps broadband communication significantly. [ABSTRACT FROM AUTHOR]

The conduction of electrical signals through cardiac tissue is essential for maintaining the function of the heart, and conduction abnormalities are known to potentially lead to life-threatening arrhythmias. The properties of cardiac conduction have therefore been the topic of intense study for decades, but a number of questions related to the mechanisms of conduction still remain unresolved. In this paper, we demonstrate how the so-called EMI model may be used to study some of these open questions. In the EMI model, the extracellular space, the cell membrane, the intracellular space and the cell connections are all represented as separate parts of the computational domain, and the model therefore allows for study of local properties that are hard to represent in the classical homogenized bidomain or monodomain models commonly used to study cardiac conduction. We conclude that a non-uniform sodium channel distribution increases the conduction velocity and decreases the time delays over gap junctions of reduced coupling in the EMI model simulations. We also present a theoretical optimal cell length with respect to conduction velocity and consider the possibility of ephaptic coupling (i.e. cell-to-cell coupling through the extracellular potential) acting as an alternative or supporting mechanism to gap junction coupling. We conclude that for a non-uniform distribution of sodium channels and a sufficiently small intercellular distance, ephaptic coupling can influence the dynamics of the sodium channels and potentially provide cell-to-cell coupling when the gap junction connection is absent. [ABSTRACT FROM AUTHOR]

When listening to music, humans can easily identify and move to the beat. Numerous experimental studies have identified brain regions that may be involved with beat perception and representation. Several theoretical and algorithmic approaches have been proposed to account for this ability. Related to, but different from the issue of how we perceive a beat, is the question of how we learn to generate and hold a beat. In this paper, we introduce a neuronal framework for a beat generator that is capable of learning isochronous rhythms over a range of frequencies that are relevant to music and speech. Our approach combines ideas from error-correction and entrainment models to investigate the dynamics of how a biophysically-based neuronal network model synchronizes its period and phase to match that of an external stimulus. The model makes novel use of on-going faster gamma rhythms to form a set of discrete clocks that provide estimates, but not exact information, of how well the beat generator spike times match those of a stimulus sequence. The beat generator is endowed with plasticity allowing it to quickly learn and thereby adjust its spike times to achieve synchronization. Our model makes generalizable predictions about the existence of asymmetries in the synchronization process, as well as specific predictions about resynchronization times after changes in stimulus tempo or phase. Analysis of the model demonstrates that accurate rhythmic time keeping can be achieved over a range of frequencies relevant to music, in a manner that is robust to changes in parameters and to the presence of noise. [ABSTRACT FROM AUTHOR]

Abstract We present SIBIA (Scalable Integrated Biophysics-based Image Analysis), a framework for joint image registration and biophysical inversion and we apply it to analyze MR images of glioblastomas (primary brain tumors). We have two applications in mind. The first one is normal-to-abnormal image registration in the presence of tumor-induced topology differences. The second one is biophysical inversion based on single-time patient data. The underlying optimization problem is highly non-linear and non-convex and has not been solved before with a gradient-based approach. Given the segmentation of a normal brain MRI and the segmentation of a cancer patient MRI, we determine tumor growth parameters and a registration map so that if we "grow a tumor" (using our tumor model) in the normal brain and then register it to the patient image, then the registration mismatch is as small as possible. This " coupled problem " two-way couples the biophysical inversion and the registration problem. In the image registration step we solve a large-deformation diffeomorphic registration problem parameterized by an Eulerian velocity field. In the biophysical inversion step we estimate parameters in a reaction–diffusion tumor growth model that is formulated as a partial differential equation (PDE). In SIBIA, we couple these two sub-components in an iterative manner. We first presented the components of SIBIA in "Gholami et al., Framework for Scalable Biophysics-based Image Analysis, IEEE/ACM Proceedings of the SC2017" , in which we derived parallel distributed memory algorithms and software modules for the decoupled registration and biophysical inverse problems. In this paper, our contributions are the introduction of a PDE-constrained optimization formulation of the coupled problem, and the derivation of a Picard iterative solution scheme. We perform extensive tests to experimentally assess the performance of our method on synthetic and clinical datasets. We demonstrate the convergence of the SIBIA optimization solver in different usage scenarios. We demonstrate that using SIBIA, we can accurately solve the coupled problem in three dimensions (25 6 3 resolution) in a few minutes using 11 dual-x86 nodes. [ABSTRACT FROM AUTHOR]

The Ecosystem Demography Model version 2.2 (ED-2.2) is a terrestrial biosphere model that simulates the biophysical and biogeochemical cycles of dynamic ecosystems while considering the role of vertical structure of plant communities and the heterogeneity of such structures across the landscape. In a companion paper, we described in detail how the model solves the energy, water, and carbon cycles, and verified the excellent conservation of such properties in long-term simulation. Here, we present a thorough assessment of the model's ability to represent multiple processes associated with the biophysical and biogeochemical cycles, with focus on the Amazon forest. We used multiple measurements from eddy covariance towers, forest inventory plots and regional remote-sensing products to assess the model's ability to represent biophysical, physiological, and ecological processes at multiple time scales ranging from sub-daily to century-long. The ED-2.2 model accurately describes the vertical distribution of light, water fluxes and the storage of water, energy and carbon in the canopy air space, the regional distribution of biomass in tropical South America, and the variability of biomass as a function of environmental drivers. In addition, ED-2.2 also simulates emerging properties of the ecosystem found in observations, such as the relationship between biomass and mortality rates and wood density, although the relationships predicted by the model were biased. We also identified some of the model limitations, such as the model's tendency to overestimate the magnitude and seasonality of heterotrophic respiration, and to overestimate growth rates in a nutrient-poor tropical site. The evaluation presented here highlights the potential of incorporating structural and functional heterogeneity within biomes in ESMs, to realistically represent the role of forest structure and composition on energy, water, and carbon cycles, as well as the priority areas for further model development. [ABSTRACT FROM AUTHOR]

Earth System Models (ESMs) have been developed to represent the role of terrestrial ecosystems on the energy, water, and carbon cycles. However, many ESMs still lack representation of within-ecosystem heterogeneity and diversity. In this manuscript, we present the Ecosystem Demography Model version 2.2 (ED-2.2). In ED-2.2, the biophysical and physiological cycles account for the horizontal and vertical heterogeneity of the ecosystem: the energy, water, and carbon cycles are solved separately for each group of individual trees of similar size and functional group (cohorts) living in a micro-environment with similar disturbance history (patches). We define the equations that describe the energy, water, and carbon cycles in terms of total energy, water, and carbon, which simplifies the ordinary differential equations and guarantees excellent conservation of these quantities in long-term simulation (< 0.1% error over 50 years). We also show examples of ED-2.2 simulation results at single sites and across tropical South America. These results demonstrate the model's ability to characterize the variability of ecosystem structure, composition and functioning both at stand- and continental-scales. In addition, a detailed model evaluation was carried out and presented in a companion paper. Finally, we highlight some of the ongoing developments in ED-2.2 that aim at reducing the uncertainties identified in this study and the inclusion of processes hitherto not represented in the model. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Ecosystem service accounts are a useful tool to assess changes in the service use. • Spatial models of ecosystem services provide key information for accounting. • Proximity between recreation potential and demand determine the actual flow. • Accounting tables show the monetary value of nature-based recreation. • Linkages between nature-based recreation and components of human wellbeing are shown. Abstract Natural capital accounting aims to measure changes in the stock of natural assets (i.e., soil, air, water and all living things) and to integrate the value of ecosystem services into accounting systems that will contribute to better ecosystems management. This study develops ecosystem services accounts at the European Union level, using nature-based recreation as a case study and following the current international accounting framework: System of Environmental-Economic Accounting – Experimental Ecosystem Accounting (SEEA EEA). We adapt and integrate different biophysical and socio-economic models, illustrating the workflow necessary for ecosystem services accounts: from a biophysical assessment of nature-based recreation to an economic valuation and compilation of the accounting tables. The biophysical assessment of nature-based recreation is based on spatially explicit models for assessing different components of ecosystem services: potential, demand and actual flow. Deriving maps of ecosystem service potential and demand is a key step in quantifying the actual flow of the service used, which is determined by the spatial relationship (i.e., proximity in the case of nature-based recreation) between service potential and demand. The nature-based recreation accounts for 2012 show an actual flow of 40 million potential visits to 'high-quality areas for daily recreation', with a total value of EUR 50 billion. This constitutes an important contribution of ecosystems to people's lives that has increased by 26% since 2000. Practical examples of ecosystem services accounts, as shown in this study, are required to derive recommendations and further develop the conceptual and methodological framework proposed by the SEEA EEA. This paper highlights the importance of using spatially explicit models for ecosystem services accounts. Mapping the different components of ecosystem services allows proper identification of the drivers of changes in the actual service flow derived from ecosystems, socio-economic systems and/or their spatial relationship. This will contribute to achieving one of the main goals of ecosystem accounts, namely measuring changes in natural capital, but it will also support decision-making that targets the enhancement of ecosystems, their services and the benefits they provide. [ABSTRACT FROM AUTHOR]

The logistic coupled map lattices (LCML) have been widely investigated as well as their pattern dynamics. The patterns formation may depend on not only fluctuations of system parameters, but variation of the initial conditions. However, the mathematical discussion is quite few for the effect of initial values so far. The present paper is concerned with the pattern formation for a two-dimensional Logistic coupled map lattice, where any initial value can be linear expressed by corresponding eigenvectors, and patterns formation can be determined by selecting the corresponding eigenvectors. A set of simulations are conducted whose results demonstrate the fact. The method utilized in the present paper could be applied to other discrete systems as well. [ABSTRACT FROM AUTHOR]

Appropriate integration of remote sensing technologies into ecosystem services concepts and practices leads to potential practical benefits for the protection of biodiversity and the promotion of sustainable use of Earth's natural assets. The last decade has seen the rapid development of research efforts on the topic of ecosystem services, which has led to a significant increase in the number of scientific publications. This systematic review aims to identify, evaluate and synthesise the evidence provided in published peer reviewed studies framing their work in the context of spatially explicit remote sensing assessment and valuation of ecosystem services. Initially, a search through indexed scientific databases found 5920 papers making direct and/or indirect reference to the topic of “ecosystem services” between the years of 1960 and 2013. Among these papers, 211 make direct reference to the use of remote sensing. During the search we aimed at selecting papers that were peer-reviewed publications available through indexed bibliographic databases. For this reason, our literature search did not include books, grey literature, extended abstracts and presentations. We quantitatively present the growth of remote sensing applications in ecosystem services’ research, reviewing the literature to produce a summary of the state of available and feasible remote sensing variables used in the assessment and valuation of ecosystem services. The results provide valuable information on how remotely sensed Earth observation data are used currently to produce spatially-explicit assessments and valuation of ecosystem services. Using examples from the literature we produce a concise summary of what has been done, what can be done and what can be improved upon in the future to integrate remote sensing into ecosystem services research. The reason for doing so is to motivate discussion about methodological challenges, solutions and to encourage an uptake of remote sensing technology and data where it has potential practical applications. [ABSTRACT FROM AUTHOR]

This paper summarizes the advances made by the DiFrancesco and Noble (DFN) model of cardiac cellular electrophysiology, which was published in Philosophical Transactions B in 1985. This model was developed at a time when the introduction of new techniques and provision of experimental data had resulted in an explosion of knowledge about the cellular and bio-physical properties of the heart. It advanced the cardiac modelling field from a period when computer models considered only the voltage-dependent channels in the surface membrane. In particular, it included a consideration of changes of both intra- and extracellular ionic concentrations. In this paper, we summarize the most important contributions of the DiFrancesco and Noble paper. We also describe how computer modelling has developed subsequently with the extension from the single cell to the whole heart as well as its use in understanding disease and predicting the effects of pharmaceutical interventions. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society. [ABSTRACT FROM AUTHOR]

Traditional descriptions of the knee suggest that the function of the patella is to facilitate knee extension by increasing the moment arm of the quadriceps muscles. Through modelling and evidence from the literature it is shown in this paper that the presence of the patella makes the ability of the quadriceps to rotate the thigh greater than their ability to rotate the tibia. Furthermore, this difference increases as the knee is flexed, thus demonstrating a pattern that is consistent with many human movements. This paper also shows that the anterior cruciate ligament plays a previously unheralded role in extending the shank and that translation at the tibiofemoral and patellofemoral joints is important in improving the capacity for thigh rotation when the knee is flexed. This study provides new insights as to how the structure of the knee is adapted to its purpose and illustrates how the functional anatomy of the knee contributes to its extension function. [ABSTRACT FROM AUTHOR]

The symmetry breaking observed in nature is fascinating. This symmetry breaking is observed in both human crowds and ant colonies. In such cases, when escaping from a closed space with two symmetrically located exits, one exit is used more often than the other. Group size and density have been reported as having no significant impact on symmetry breaking, and the alignment rule has been used to model symmetry breaking. Density usually plays important roles in collective behavior. However, density is not well-studied in symmetry breaking, which forms the major basis of this paper. The experiment described in this paper on an ant colony displays an increase then decrease of symmetry breaking versus ant density. This result suggests that a Vicsek-like model with an alignment rule may not be the correct model for escaping ants. Based on biological facts that ants use pheromones to communicate, rather than seeing how other individuals move, we propose a simple yet effective alarm pheromone model. The model results agree well with the experimental outcomes. As a measure, this paper redefines symmetry breaking as the collective asymmetry by deducing the random fluctuations. This research indicates that ants deposit and respond to the alarm pheromone, and the accumulation of this biased information sharing leads to symmetry breaking, which suggests true fundamental rules of collective escape behavior in ants. [ABSTRACT FROM AUTHOR]

This paper presents a reassessment of the archaeological record at Leang Burung 2, a key early human occupation site in the Late Pleistocene of Southeast Asia. Excavated originally by Ian Glover in 1975, this limestone rock-shelter in the Maros karsts of Sulawesi, Indonesia, has long held significance in our understanding of early human dispersals into ‘Wallacea’, the vast zone of oceanic islands between continental Asia and Australia. We present new stratigraphic information and dating evidence from Leang Burung 2 collected during the course of our excavations at this site in 2007 and 2011–13. Our findings suggest that the classic Late Pleistocene modern human occupation sequence identified previously at Leang Burung 2, and proposed to span around 31,000 to 19,000 conventional 14C years BP (~35–24 ka cal BP), may actually represent an amalgam of reworked archaeological materials. Sources for cultural materials of mixed ages comprise breccias from the rear wall of the rock-shelter–remnants of older, eroded deposits dated to 35–23 ka cal BP–and cultural remains of early Holocene antiquity. Below the upper levels affected by the mass loss of Late Pleistocene deposits, our deep-trench excavations uncovered evidence for an earlier hominin presence at the site. These findings include fossils of now-extinct proboscideans and other ‘megafauna’ in stratified context, as well as a cobble-based stone artifact technology comparable to that produced by late Middle Pleistocene hominins elsewhere on Sulawesi. [ABSTRACT FROM AUTHOR]

This paper reports the levitation of micro-organisms in the sheath of radio-frequency (RF) plasma. Based on simple force-balance calculations, the required electric field for the levitation of micro-organisms has been estimated. It is predicted that micro-organisms could levitate at the periphery of the sheath. Experimental results demonstrate the levitation of two species of bacillus micro-organisms Escherichia coli (E. coli) and Klebsiella pneumoniae in an RF plasma. The almost monodiverse Klebsiella pneumoniae levitating in the RF plasma formed an ordered state similar to a 2-D Coulomb crystal. Diverse E. coli particles demonstrate the tendency that the levitating height of micro-organisms decreases as the radius of particles increases. Levitating micro-organisms in plasmas can be referred as dusty plasmas. [ABSTRACT FROM AUTHOR]

Solving inverse problems is central in geosciences and remote sensing. The radiative transfer models (RTMs) represent mathematically the physical laws that rule the phenomena in remote sensing applications (forward models). The numerical inversion of the RTM equations is a challenging and computationally demanding problem. For this reason, often the application of a simpler statistical regression is preferred. In general, the regression models predict the biophysical parameter of interest from the corresponding received radiance, learning a mapping from in situ data. However, this approach does not employ the physical information encoded in the RTMs. An alternative strategy, which attempts to include the physical knowledge, consists in learning a regression model trained using simulated data by an RTM code. In this paper, we introduce a nonlinear nonparametric regression model that combines the benefits of the two aforementioned approaches. The inversion is performed considering jointly both real observations and RTMsimulated data. The proposed joint Gaussian process (JGP) provides a solid framework for exploiting the regularities between the two types of data, in order to perform inverse modeling. The JGP automatically detects the relative quality of the simulated and real data, and combines them properly. This occurs by learning an additional hyperparameter with respect to a standard Gaussian process model, so that the novel scheme is at the same time simple and robust, i.e., capable of adapting to different scenarios. The advantages of the JGP method compared with benchmark strategies are shown considering synthetic and real data in different experiments. Specifically, we consider leaf area index retrieval from Landsat data combined with simulated data generated by the PROSAIL model. [ABSTRACT FROM AUTHOR]

Lipids are essential components of biological membranes that present a wide diversity in eukaryotic cells. Recent impressive advances in lipid biochemistry and biophysics have enabled a refocus of our view of lipids as functional units for cellular activity. However, the gap between molecular and cellular processes remains to be bridged. Here, 2 papers meet the burden of proof that choline transporters participate in local lipid composition modifications at the trans-Golgi network, an intracellular compartment that serves as the main sorting station in the cell. Localization of choline transporters to this precise compartment could be a way for plant cells to quickly modify the membrane lipid composition and asymmetry during both the allocation of cargos and the recruitment of trafficking machineries into distinct subcellular pathways. [ABSTRACT FROM AUTHOR]

Objective: In this paper, we explore the dependence of sliding window correlation (SWC) results on different parameters of correlating signals. The SWC is extensively used to explore the dynamics of functional connectivity (FC) networks using resting-state functional MRI (rsfMRI) scans. These scanned signals often contain multiple amplitudes, frequencies, and phases. However, the exact values of these parameters are unknown. Two recent studies explored the relationship of window length and frequencies (minimum/maximum) in the correlating signals. Methods: We extend the findings of these studies by using two deterministic signals with multiple amplitudes, frequencies, and phases. Afterward, we modulate one of the signals to introduce dynamics (nonstationarity) in their relationship. We also explore the relationship of window length and frequency band for real rsfMRI data. Results: For deterministic signals, the spurious fluctuations due to the method itself minimize, and the SWC estimates the stationary correlation when frequencies in the signals have specific relationship. For dynamic relationship also, the undesirable frequencies were removed under specific conditions for the frequencies. For real rsfMRI data, the SWC results varied with frequencies and window length. Conclusion: In the absence of any “ground truth” for different parameters in real rsfMRI signals, the SWC with a constant window size may not be a reliable method to study the dynamics of the FC. Significance: This study reveals the parametric dependencies of the SWC and its limitation as a method to analyze dynamics of FC networks in the absence of any ground truth. [ABSTRACT FROM AUTHOR]

The assessment of Land Uses and Land-use Changes (LULUC) impacts has become increasingly complex. Sophisticated modelling tools such as Life Cycle Assessment (LCA) are employed to capture both direct and indirect damages. However, quantitative assessments are often incomplete, dominated by environmental aspects. Land uses are a multidisciplinary matter and environmental and sustainable development policies intertwine. Yet, LCAs mostly focus on environmental impacts excluding socioeconomic implications of land occupation. This paper investigates the limitations of current LULUC modelling practices in LCA. Common LCA assumptions harbor value choices reflect a post-positivist epistemology that are often non-transparent to e.g. policymakers. They particularly influence the definition of the functional unit, the reference system and system boundaries, among other LCA methodological choices. Consequently, results informing land policies may be biased towards determined development strategies or hide indirect effects and socioeconomic damages caused by large-scale land acquisitions, such as violation of tenure rights, speculation and displacement. Quantitative assessments of LULUC impacts are certainly useful but should holistically encompass both direct and indirect impacts concerning the environmental and the social science dimension of LULUC. An epistemological shift towards a dialectic approach would facilitate the integration of multiple tools and methods and a critical interpretation of results. [ABSTRACT FROM AUTHOR]

Viscoelasticity of soft tissue is often related to pathology, and therefore, has become an important diagnostic indicator in the clinical assessment of suspect tissue. Surgeons, particularly within head and neck subsites, typically use palpation techniques for intra-operative tumor detection. This detection method, however, is highly subjective and often fails to detect small or deep abnormalities. Vibroacoustography (VA) and similar methods have previously been used to distinguish tissue with high-contrast, but a firm understanding of the main contrast mechanism has yet to be verified. The contributions of tissue mechanical properties in VA images have been difficult to verify given the limited literature on viscoelastic properties of various normal and diseased tissue. This paper aims to investigate viscoelasticity theory and present a detailed description of viscoelastic experimental results obtained in tissue-mimicking phantoms (TMPs) and ex vivo tissues to verify the main contrast mechanism in VA and similar imaging modalities. A spherical-tip micro-indentation technique was employed with the Hertzian model to acquire absolute, quantitative, point measurements of the elastic modulus (E), long term shear modulus (η), and time constant (τ) in homogeneous TMPs and ex vivo tissue in rat liver and porcine liver and gallbladder. Viscoelastic differences observed between porcine liver and gallbladder tissue suggest that imaging modalities which utilize the mechanical properties of tissue as a primary contrast mechanism can potentially be used to quantitatively differentiate between proximate organs in a clinical setting. These results may facilitate more accurate tissue modeling and add information not currently available to the field of systems characterization and biomedical research. [ABSTRACT FROM AUTHOR]

Scabies is an infestation of the skin by the mite Sarcoptes scabiei. It manifests with pruritic erythematous papules and excoriations, in addition to the pathognomonic burrows. Multiple drugs can be used for treatment, but resistance to conventional therapy is increasing throughout the years. This paper will review the mechanisms of resistance proposed in the literature and some of the potential solutions to this problem. [ABSTRACT FROM AUTHOR]

Neuron models are available for computational neurodynamics and the main dynamical properties can be reproduced in the numerical scheme for further dynamical analysis. During model setting, some important biophysical factors should be considered and thus reliable neuron models can be approached. In this paper, a neuron model driven by autapse connection is investigated with the effect of electromagnetic induction being considered as well. A digital neuronal circuit is designed by using FPGA, the dynamical response and biological function of autapse connection. It is found that positive feedback in autapse can modulate the oscillating behaviors in the digital circuit, which could be effective for further investigation on digital neuronal network. [ABSTRACT FROM AUTHOR]