Showing papers in "Journal of the Royal Society Interface in 2018"

Opportunities and obstacles for deep learning in biology and medicine.

Abstract: Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood. Hence, deep learning techniques may be particularly well suited to solve problems of these fields. We examine applications of deep learning to a variety of biomedical problems-patient classification, fundamental biological processes and treatment of patients-and discuss whether deep learning will be able to transform these tasks or if the biomedical sphere poses unique challenges. Following from an extensive literature review, we find that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art. Even though improvements over previous baselines have been modest in general, the recent progress indicates that deep learning methods will provide valuable means for speeding up or aiding human investigation. Though progress has been made linking a specific neural network's prediction to input features, understanding how users should interpret these models to make testable hypotheses about the system under study remains an open challenge. Furthermore, the limited amount of labelled data for training presents problems in some domains, as do legal and privacy constraints on work with sensitive health records. Nonetheless, we foresee deep learning enabling changes at both bench and bedside with the potential to transform several areas of biology and medicine.

A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis

Abstract: Structural finite-element analysis (FEA) has been widely used to study the biomechanics of human tissues and organs, as well as tissue-medical device interactions, and treatment strategies. However, patient-specific FEA models usually require complex procedures to set up and long computing times to obtain final simulation results, preventing prompt feedback to clinicians in time-sensitive clinical applications. In this study, by using machine learning techniques, we developed a deep learning (DL) model to directly estimate the stress distributions of the aorta. The DL model was designed and trained to take the input of FEA and directly output the aortic wall stress distributions, bypassing the FEA calculation process. The trained DL model is capable of predicting the stress distributions with average errors of 0.492% and 0.891% in the Von Mises stress distribution and peak Von Mises stress, respectively. This study marks, to our knowledge, the first study that demonstrates the feasibility and great potential of using the DL technique as a fast and accurate surrogate of FEA for stress analysis.

The Markov blankets of life: autonomy, active inference and the free energy principle.

Abstract: This work addresses the autonomous organization of biological systems. It does so by considering the boundaries of biological systems, from individual cells to Home sapiens, in terms of the presence of Markov blankets under the active inference scheme-a corollary of the free energy principle. A Markov blanket defines the boundaries of a system in a statistical sense. Here we consider how a collective of Markov blankets can self-assemble into a global system that itself has a Markov blanket; thereby providing an illustration of how autonomous systems can be understood as having layers of nested and self-sustaining boundaries. This allows us to show that: (i) any living system is a Markov blanketed system and (ii) the boundaries of such systems need not be co-extensive with the biophysical boundaries of a living organism. In other words, autonomous systems are hierarchically composed of Markov blankets of Markov blankets-all the way down to individual cells, all the way up to you and me, and all the way out to include elements of the local environment.

Physico-chemical characteristics of evaporating respiratory fluid droplets

Abstract: The detailed physico-chemical characteristics of respiratory droplets in ambient air, where they are subject to evaporation, are poorly understood. Changes in the concentration and phase of major components in a droplet-salt (NaCl), protein (mucin) and surfactant (dipalmitoylphosphatidylcholine)-may affect the viability of any pathogens contained within it and thus may affect the efficiency of transmission of infectious disease by droplets and aerosols. The objective of this study is to investigate the effect of relative humidity (RH) on the physico-chemical characteristics of evaporating droplets of model respiratory fluids. We labelled these components in model respiratory fluids and observed evaporating droplets suspended on a superhydrophobic surface using optical and fluorescence microscopy. When exposed to continuously decreasing RH, droplets of different model respiratory fluids assumed different morphologies. Loss of water induced phase separation as well as indication of a decrease in pH. The presence of surfactant inhibited the rapid rehydration of the non-volatile components. An enveloped virus, ϕ6, that has been proposed as a surrogate for influenza virus appeared to be homogeneously distributed throughout the dried droplet. We hypothesize that the increasing acidity and salinity in evaporating respiratory droplets may affect the structure of the virus, although at low enough RH, crystallization of the droplet components may eliminate their harmful effects.

Control of human gait stability through foot placement

Abstract: During human walking, the centre of mass (CoM) is outside the base of support for most of the time, which poses a challenge to stabilizing the gait pattern. Nevertheless, most of us are able to walk without substantial problems. In this review, we aim to provide an integrative overview of how humans cope with an underactuated gait pattern. A central idea that emerges from the literature is that foot placement is crucial in maintaining a stable gait pattern. In this review, we explore this idea; we first describe mechanical models and concepts that have been used to predict how foot placement can be used to control gait stability. These concepts, such as for instance the extrapolated CoM concept, the foot placement estimator concept and the capture point concept, provide explicit predictions on where to place the foot relative to the body at each step, such that gait is stabilized. Next, we describe empirical findings on foot placement during human gait in unperturbed and perturbed conditions. We conclude that humans show behaviour that is largely in accordance with the aforementioned concepts, with foot placement being actively coordinated to body CoM kinematics during the preceding step. In this section, we also address the requirements for such control in terms of the sensory information and the motor strategies that can implement such control, as well as the parts of the central nervous system that may be involved. We show that visual, vestibular and proprioceptive information contribute to estimation of the state of the CoM. Foot placement is adjusted to variations in CoM state mainly by modulation of hip abductor muscle activity during the swing phase of gait, and this process appears to be under spinal and supraspinal, including cortical, control. We conclude with a description of how control of foot placement can be impaired in humans, using ageing as a primary example and with some reference to pathology, and we address alternative strategies available to stabilize gait, which include modulation of ankle moments in the stance leg and changes in body angular momentum, such as rapid trunk tilts. Finally, for future research, we believe that especially the integration of consideration of environmental constraints on foot placement with balance control deserves attention.

Computational techniques for ECG analysis and interpretation in light of their contribution to medical advances

Abstract: Widely developed for clinical screening, electrocardiogram (ECG) recordings capture the cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first step to help diagnose, understand and predict cardiovascular disorders responsible for 30% of deaths worldwide. Computational techniques, and more specifically machine learning techniques and computational modelling are powerful tools for classification, clustering and simulation, and they have recently been applied to address the analysis of medical data, especially ECG data. This review describes the computational methods in use for ECG analysis, with a focus on machine learning and 3D computer simulations, as well as their accuracy, clinical implications and contributions to medical advances. The first section focuses on heartbeat classification and the techniques developed to extract and classify abnormal from regular beats. The second section focuses on patient diagnosis from whole recordings, applied to different diseases. The third section presents real-time diagnosis and applications to wearable devices. The fourth section highlights the recent field of personalized ECG computer simulations and their interpretation. Finally, the discussion section outlines the challenges of ECG analysis and provides a critical assessment of the methods presented. The computational methods reported in this review are a strong asset for medical discoveries and their translation to the clinical world may lead to promising advances.

Keeping the home fires burning: AMP-activated protein kinase.

Abstract: Living cells obtain energy either by oxidizing reduced compounds of organic or mineral origin or by absorbing light. Whichever energy source is used, some of the energy released is conserved by converting adenosine diphosphate (ADP) to adenosine triphosphate (ATP), which are analogous to the chemicals in a rechargeable battery. The energy released by the conversion of ATP back to ADP is used to drive most energy-requiring processes, including cell growth, cell division, communication and movement. It is clearly essential to life that the production and consumption of ATP are always maintained in balance, and the AMP-activated protein kinase (AMPK) is one of the key cellular regulatory systems that ensures this. In eukaryotic cells (cells with nuclei and other internal membrane-bound structures, including human cells), most ATP is produced in mitochondria, which are thought to have been derived by the engulfment of oxidative bacteria by a host cell not previously able to use molecular oxygen. AMPK is activated by increasing AMP or ADP (AMP being generated from ADP whenever ADP rises) coupled with falling ATP. Relatives of AMPK are found in essentially all eukaryotes, and it may have evolved to allow the host cell to monitor the output of the newly acquired mitochondria and step their ATP production up or down according to the demand. Structural studies have illuminated how AMPK achieves the task of detecting small changes in AMP and ADP, despite the presence of much higher concentrations of ATP. Recently, it has been shown that AMPK can also sense the availability of glucose, the primary carbon source for most eukaryotic cells, via a mechanism independent of changes in AMP or ADP. Once activated by energy imbalance or glucose lack, AMPK modifies many target proteins by transferring phosphate groups to them from ATP. By this means, numerous ATP-producing processes are switched on (including the production of new mitochondria) and ATP-consuming processes are switched off, thus restoring energy homeostasis. Drugs that modulate AMPK have great potential in the treatment of metabolic disorders such as obesity and Type 2 diabetes, and even cancer. Indeed, some existing drugs such as metformin and aspirin, which were derived from traditional herbal remedies, appear to work, in part, by activating AMPK.

A variational approach to niche construction

Abstract: In evolutionary biology, niche construction is sometimes described as a genuine evolutionary process whereby organisms, through their activities and regulatory mechanisms, modify their environment such as to steer their own evolutionary trajectory, and that of other species. There is ongoing debate, however, on the extent to which niche construction ought to be considered a bona fide evolutionary force, on a par with natural selection. Recent formulations of the variational free-energy principle as applied to the life sciences describe the properties of living systems, and their selection in evolution, in terms of variational inference. We argue that niche construction can be described using a variational approach. We propose new arguments to support the niche construction perspective, and to extend the variational approach to niche construction to current perspectives in various scientific fields.

The future of quantum biology

Abstract: Biological systems are dynamical, constantly exchanging energy and matter with the environment in order to maintain the non-equilibrium state synonymous with living. Developments in observational techniques have allowed us to study biological dynamics on increasingly small scales. Such studies have revealed evidence of quantum mechanical effects, which cannot be accounted for by classical physics, in a range of biological processes. Quantum biology is the study of such processes, and here we provide an outline of the current state of the field, as well as insights into future directions.

Conformational dynamics and enzyme evolution.

Abstract: Enzymes are dynamic entities, and their dynamic properties are clearly linked to their biological function. It follows that dynamics ought to play an essential role in enzyme evolution. Indeed, a link between conformational diversity and the emergence of new enzyme functionalities has been recognized for many years. However, it is only recently that state-of-the-art computational and experimental approaches are revealing the crucial molecular details of this link. Specifically, evolutionary trajectories leading to functional optimization for a given host environment or to the emergence of a new function typically involve enriching catalytically competent conformations and/or the freezing out of non-competent conformations of an enzyme. In some cases, these evolutionary changes are achieved through distant mutations that shift the protein ensemble towards productive conformations. Multifunctional intermediates in evolutionary trajectories are probably multi-conformational, i.e. able to switch between different overall conformations, each competent for a given function. Conformational diversity can assist the emergence of a completely new active site through a single mutation by facilitating transition-state binding. We propose that this mechanism may have played a role in the emergence of enzymes at the primordial, progenote stage, where it was plausibly promoted by high environmental temperatures and the possibility of additional phenotypic mutations.

Habitat fragmentation, biodiversity loss and the risk of novel infectious disease emergence

Abstract: The number of microbes on Earth may be 1030, exceeding all other diversity. A small number of these can infect people and cause disease. The diversity of parasitic organisms likely correlates with ...

Long-range proton-coupled electron transfer in biological energy conversion: towards mechanistic understanding of respiratory complex I

Abstract: Biological energy conversion is driven by efficient enzymes that capture, store and transfer protons and electrons across large distances. Recent advances in structural biology have provided atomic-scale blueprints of these types of remarkable molecular machinery, which together with biochemical, biophysical and computational experiments allow us to derive detailed energy transduction mechanisms for the first time. Here, I present one of the most intricate and least understood types of biological energy conversion machinery, the respiratory complex I, and how its redox-driven proton-pump catalyses charge transfer across approximately 300 A distances. After discussing the functional elements of complex I, a putative mechanistic model for its action-at-a-distance effect is presented, and functional parallels are drawn to other redox- and light-driven ion pumps.

Systems protobiology: origin of life in lipid catalytic networks.

Abstract: Life is that which replicates and evolves, but there is no consensus on how life emerged. We advocate a systems protobiology view, whereby the first replicators were assemblies of spontaneously accreting, heterogeneous and mostly non-canonical amphiphiles. This view is substantiated by rigorous chemical kinetics simulations of the graded autocatalysis replication domain (GARD) model, based on the notion that the replication or reproduction of compositional information predated that of sequence information. GARD reveals the emergence of privileged non-equilibrium assemblies (composomes), which portray catalysis-based homeostatic (concentration-preserving) growth. Such a process, along with occasional assembly fission, embodies cell-like reproduction. GARD pre-RNA evolution is evidenced in the selection of different composomes within a sparse fitness landscape, in response to environmental chemical changes. These observations refute claims that GARD assemblies (or other mutually catalytic networks in the metabolism first scenario) cannot evolve. Composomes represent both a genotype and a selectable phenotype, anteceding present-day biology in which the two are mostly separated. Detailed GARD analyses show attractor-like transitions from random assemblies to self-organized composomes, with negative entropy change, thus establishing composomes as dissipative systems-hallmarks of life. We show a preliminary new version of our model, metabolic GARD (M-GARD), in which lipid covalent modifications are orchestrated by non-enzymatic lipid catalysts, themselves compositionally reproduced. M-GARD fills the gap of the lack of true metabolism in basic GARD, and is rewardingly supported by a published experimental instance of a lipid-based mutually catalytic network. Anticipating near-future far-reaching progress of molecular dynamics, M-GARD is slated to quantitatively depict elaborate protocells, with orchestrated reproduction of both lipid bilayer and lumenal content. Finally, a GARD analysis in a whole-planet context offers the potential for estimating the probability of life's emergence. The invigorated GARD scrutiny presented in this review enhances the validity of autocatalytic sets as a bona fide early evolution scenario and provides essential infrastructure for a paradigm shift towards a systems protobiology view of life's origin.

Realizing 'integral control' in living cells: how to overcome leaky integration due to dilution?

Abstract: A major problem in the design of synthetic genetic circuits is robustness to perturbations and uncertainty. Because of this, there have been significant efforts in recent years in finding approaches to implement integral control in genetic circuits. Integral controllers have the unique ability to make the output of a process adapt perfectly to disturbances. However, implementing an integral controller is challenging in living cells. This is because a key aspect of any integral controller is a 'memory' element that stores the accumulation (integral) of the error between the output and its desired set-point. The ability to realize such a memory element in living cells is fundamentally challenged by the fact that all biomolecules dilute as cells grow, resulting in a 'leaky' memory that gradually fades away. As a consequence, the adaptation property is lost. Here, we propose a general principle for designing integral controllers such that the performance is practically unaffected by dilution. In particular, we mathematically prove that if the reactions implementing the integral controller are all much faster than dilution, then the adaptation error due to integration leakiness becomes negligible. We exemplify this design principle with two synthetic genetic circuits aimed at reaching adaptation of gene expression to fluctuations in cellular resources. Our results provide concrete guidance on the biomolecular processes that are most appropriate for implementing integral controllers in living cells.

Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues

Abstract: A main goal of mathematical and computational oncology is to develop quantitative tools to determine the most effective therapies for each individual patient. This involves predicting the right drug to be administered at the right time and at the right dose. Such an approach is known as precision medicine. Mathematical modelling can play an invaluable role in the development of such therapeutic strategies, since it allows for relatively fast, efficient and inexpensive simulations of a large number of treatment schedules in order to find the most effective. This review is a survey of mathematical models that explicitly take into account the spatial architecture of three-dimensional tumours and address tumour development, progression and response to treatments. In particular, we discuss models of epithelial acini, multicellular spheroids, normal and tumour spheroids and organoids, and multi-component tissues. Our intent is to showcase how these in silico models can be applied to patient-specific data to assess which therapeutic strategies will be the most efficient. We also present the concept of virtual clinical trials that integrate standard-of-care patient data, medical imaging, organ-on-chip experiments and computational models to determine personalized medical treatment strategies.

Designing stem cell niches for differentiation and self-renewal

Abstract: Mesenchymal stem cells, characterized by their ability to differentiate into skeletal tissues and self-renew, hold great promise for both regenerative medicine and novel therapeutic discovery However, their regenerative capacity is retained only when in contact with their specialized microenvironment, termed the stem cell niche Niches provide structural and functional cues that are both biochemical and biophysical, stem cells integrate this complex array of signals with intrinsic regulatory networks to meet physiological demands Although, some of these regulatory mechanisms remain poorly understood or difficult to harness with traditional culture systems Biomaterial strategies are being developed that aim to recapitulate stem cell niches, by engineering microenvironments with physiological-like niche properties that aim to elucidate stem cell-regulatory mechanisms, and to harness their regenerative capacity in vitro In the future, engineered niches will prove important tools for both regenerative medicine and therapeutic discoveries

Shark skin-inspired designs that improve aerodynamic performance

Abstract: There have been significant efforts recently aimed at improving the aerodynamic performance of aerofoils through the modification of their surfaces. Inspired by the drag-reducing properties of the tooth-like denticles that cover the skin of sharks, we describe here experimental and simulation-based investigations into the aerodynamic effects of novel denticle-inspired designs placed along the suction side of an aerofoil. Through parametric modelling to query a wide range of different designs, we discovered a set of denticle-inspired surface structures that achieve simultaneous drag reduction and lift generation on an aerofoil, resulting in lift-to-drag ratio improvements comparable to the best-reported for traditional low-profile vortex generators and even outperforming these existing designs at low angles of attack with improvements of up to 323%. Such behaviour is enabled by two concurrent mechanisms: (i) a separation bubble in the denticle's wake altering the flow pressure distribution of the aerofoil to enhance suction and (ii) streamwise vortices that replenish momentum loss in the boundary layer due to skin friction. Our findings not only open new avenues for improved aerodynamic design, but also provide new perspective on the role of the complex and potentially multifunctional morphology of shark denticles for increased swimming efficiency.

Accounting for residence-time in blood rheology models: do we really need non-Newtonian blood flow modelling in large arteries?

Abstract: Patient-specific computational fluid dynamics (CFD) is a promising tool that provides highly resolved haemodynamics information. The choice of blood rheology is an assumption in CFD models that has been subject to extensive debate. Blood is known to exhibit shear-thinning behaviour, and non-Newtonian modelling has been recommended for aneurysmal flows. Current non-Newtonian models ignore rouleaux formation, which is the key player in blood's shear-thinning behaviour. Experimental data suggest that red blood cell aggregation and rouleaux formation require notable red blood cell residence-time (RT) in a low shear rate regime. This study proposes a novel hybrid Newtonian and non-Newtonian rheology model where the shear-thinning behaviour is activated in high RT regions based on experimental data. Image-based abdominal aortic and cerebral aneurysm models are considered and highly resolved CFD simulations are performed using a minimally dissipative solver. Lagrangian particle tracking is used to define a backward particle RT measure and detect stagnant regions with increased rouleaux formation likelihood. Our novel RT-based non-Newtonian model shows a significant reduction in shear-thinning effects and provides haemodynamic results qualitatively identical and quantitatively close to the Newtonian model. Our results have important implications in patient-specific CFD modelling and suggest that non-Newtonian models should be revisited in large artery flows.

Scalable co-optimization of morphology and control in embodied machines

Abstract: Evolution sculpts both the body plans and nervous systems of agents together over time. By contrast, in artificial intelligence and robotics, a robot's body plan is usually designed by hand, and control policies are then optimized for that fixed design. The task of simultaneously co-optimizing the morphology and controller of an embodied robot has remained a challenge. In psychology, the theory of embodied cognition posits that behaviour arises from a close coupling between body plan and sensorimotor control, which suggests why co-optimizing these two subsystems is so difficult: most evolutionary changes to morphology tend to adversely impact sensorimotor control, leading to an overall decrease in behavioural performance. Here, we further examine this hypothesis and demonstrate a technique for 'morphological innovation protection', which temporarily reduces selection pressure on recently morphologically changed individuals, thus enabling evolution some time to 'readapt' to the new morphology with subsequent control policy mutations. We show the potential for this method to avoid local optima and converge to similar highly fit morphologies across widely varying initial conditions, while sustaining fitness improvements further into optimization. While this technique is admittedly only the first of many steps that must be taken to achieve scalable optimization of embodied machines, we hope that theoretical insight into the cause of evolutionary stagnation in current methods will help to enable the automation of robot design and behavioural training-while simultaneously providing a test bed to investigate the theory of embodied cognition.

Lessons from pressure denaturation of proteins.

Abstract: Although it is now relatively well understood how sequence defines and impacts global protein stability in specific structural contexts, the question of how sequence modulates the configurational landscape of proteins remains to be defined. Protein configurational equilibria are generally characterized by using various chemical denaturants or by changing temperature or pH. Another thermodynamic parameter which is less often used in such studies is high hydrostatic pressure. This review discusses the basis for pressure effects on protein structure and stability, and describes how the unique mechanisms of pressure-induced unfolding can provide unique insights into protein conformational landscapes.

Understanding the ontogeny of foraging behaviour: insights from combining marine predator bio-logging with satellite-derived oceanography in hidden Markov models.

Abstract: The development of foraging strategies that enable juveniles to efficiently identify and exploit predictable habitat features is critical for survival and long-term fitness. In the marine environme...

Antithetic proportional-integral feedback for reduced variance and improved control performance of stochastic reaction networks

Abstract: The ability of a cell to regulate and adapt its internal state in response to unpredictable environmental changes is called homeostasis and this ability is crucial for the cell's survival and proper functioning. Understanding how cells can achieve homeostasis, despite the intrinsic noise or randomness in their dynamics, is fundamentally important for both systems and synthetic biology. In this context, a significant development is the proposed antithetic integral feedback (AIF) motif, which is found in natural systems, and is known to ensure robust perfect adaptation for the mean dynamics of a given molecular species involved in a complex stochastic biomolecular reaction network. From the standpoint of applications, one drawback of this motif is that it often leads to an increased cell-to-cell heterogeneity or variance when compared to a constitutive (i.e. open-loop) control strategy. Our goal in this paper is to show that this performance deterioration can be countered by combining the AIF motif and a negative feedback strategy. Using a tailored moment closure method, we derive approximate expressions for the stationary variance for the controlled network that demonstrate that increasing the strength of the negative feedback can indeed decrease the variance, sometimes even below its constitutive level. Numerical results verify the accuracy of these results and we illustrate them by considering three biomolecular networks with two types of negative feedback strategies. Our computational analysis indicates that there is a trade-off between the speed of the settling-time of the mean trajectories and the stationary variance of the controlled species; i.e. smaller variance is associated with larger settling-time.

Understanding/unravelling carotenoid excited singlet states

Abstract: Carotenoids are essential light-harvesting pigments in natural photosynthesis. They absorb in the blue-green region of the solar spectrum and transfer the absorbed energy to (bacterio-)chlorophylls, and thus expand the wavelength range of light that is able to drive photosynthesis. This process is an example of singlet-singlet excitation energy transfer, and carotenoids serve to enhance the overall efficiency of photosynthetic light reactions. The photochemistry and photophysics of carotenoids have often been interpreted by referring to those of simple polyene molecules that do not possess any functional groups. However, this may not always be wise because carotenoids usually have a number of functional groups that induce the variety of photochemical behaviours in them. These differences can also make the interpretation of the singlet excited states of carotenoids very complicated. In this article, we review the properties of the singlet excited states of carotenoids with the aim of producing as coherent a picture as possible of what is currently known and what needs to be learned.

Hydrogel biomaterials and their therapeutic potential for muscle injuries and muscular dystrophies.

Abstract: Muscular diseases such as muscular dystrophies and muscle injuries constitute a large group of ailments that manifest as muscle weakness, atrophy or fibrosis. Although cell therapy is a promising treatment option, the delivery and retention of cells in the muscle is difficult and prevents sustained regeneration needed for adequate functional improvements. Various types of biomaterials with different physical and chemical properties have been developed to improve the delivery of cells and/or growth factors for treating muscle injuries. Hydrogels are a family of materials with distinct advantages for use as cell delivery systems in muscle injuries and ailments, including their mild processing conditions, their similarities to natural tissue extracellular matrix, and their ability to be delivered with less invasive approaches. Moreover, hydrogels can be made to completely degrade in the body, leaving behind their biological payload in a process that can enhance the therapeutic process. For these reasons, hydrogels have shown great potential as cell delivery matrices. This paper reviews a few of the hydrogel systems currently being applied together with cell therapy and/or growth factor delivery to promote the therapeutic repair of muscle injuries and muscle wasting diseases such as muscular dystrophies.

Multiscale impact of researcher mobility

Abstract: International mobility facilitates the exchange of scientific, institutional and cultural knowledge. Yet whether globalization and advances in virtual communication technologies have altered the impact of researcher mobility is a relevant and open question that we address by analysing a broad international set of 26 170 physicists from 1980 to 2009, focusing on the 10-year period centred around each mobility event to assess the impact of mobility on research outcomes. We account for secular globalization trends by splitting the analysis into three periods, measuring for each period the effect of mobility on researchers' citation impact, research topic diversity, collaboration networks and geographical coordination. In order to identify causal effects we leverage statistical matching methods that pair mobile researchers with non-mobile researchers that are similar in research profile attributes prior the mobility event. We find that mobile researchers gain up to a 17% increase in citations relative to their non-mobile counterparts, which can be explained by the simultaneous increase in their diversity of co-authors, topics and geographical coordination in the period immediately following migration. Nevertheless, we also observe that researcher's completely curtail prior collaborations with their source country in 11% of the cross-border mobility events. As such, these individual-level perturbations fuel multiscale churning in scientific networks, e.g. rewiring the connectivity of individuals and ideas and affecting international integration. Together these results provide additional clarity on the complex relationship between human capital mobility and the dynamics of social capital investment, with implications for immigration and national innovation system policy.

Orderliness predicts academic performance: behavioural analysis on campus lifestyle.

Abstract: Quantitative understanding of relationships between students9 behavioural patterns and academic performances is a significant step towards personalized education. In contrast to previous studies that were mainly based on questionnaire surveys, recent literature suggests that unobtrusive digital data bring us unprecedented opportunities to study students9 lifestyles in the campus. In this paper, we collect behavioural records from undergraduate students9 ( N = 18 960) smart cards and propose two high-level behavioural characters, orderliness and diligence. The former is a novel entropy-based metric that measures the regularity of campus daily life, which is estimated here based on temporal records of taking showers and having meals. Empirical analyses on such large-scale unobtrusive behavioural data demonstrate that academic performance (GPA) is significantly correlated with orderliness. Furthermore, we show that orderliness is an important feature to predict academic performance, which improves the prediction accuracy even in the presence of students9 diligence. Based on these analyses, education administrators could quantitatively understand the major factors leading to excellent or poor performance, detect undesirable abnormal behaviours in time and thus implement effective interventions to better guide students9 campus lives at an early stage when necessary.

In vivo atomic force microscopy-infrared spectroscopy of bacteria.

Abstract: A new experimental platform for probing nanoscale molecular changes in living bacteria using atomic force microscopy-infrared (AFM-IR) spectroscopy is demonstrated. This near-field technique is eminently suited to the study of single bacterial cells. Here, we report its application to monitor dynamical changes occurring in the cell wall during cell division in Staphylococcus aureus using AFM to demonstrate the division of the cell and AFM-IR to record spectra showing the thickening of the septum. This work was followed by an investigation into single cells, with particular emphasis on cell-wall signatures, in several bacterial species. Specifically, mainly cell wall components from S. aureus and Escherichia coli containing complex carbohydrate and phosphodiester groups, including peptidoglycans and teichoic acid, could be identified and mapped at nanometre spatial resolution. Principal component analysis of AFM-IR spectra of six living bacterial species enabled the discrimination of Gram-positive from Gram-negative bacteria based on spectral bands originating mainly from the cell wall components. The ability to monitor in vivo molecular changes during cellular processes in bacteria at the nanoscale opens a new platform to study environmental influences and other factors that affect bacterial chemistry.

Flat and microstructured polymeric membranes in organs-on-chips

Abstract: In recent years, organs-on-chips (OOCs) have been developed to meet the desire for more realistic in vitro cell culture models. These systems introduce microfluidics, mechanical stretch and other physiological stimuli to in vitro models, thereby significantly enhancing their descriptive power. In most OOCs, porous polymeric membranes are used as substrates for cell culture. The polymeric material, morphology and shape of these membranes are often suboptimal, despite their importance for achieving ideal cell functionality such as cell-cell interaction and differentiation. The currently used membranes are flat and thus do not account for the shape and surface morphology of a tissue. Moreover, the polymers used for fabrication of these membranes often lack relevant characteristics, such as mechanical properties matching the tissue to be developed and/or cytocompatibility. Recently, innovative techniques have been reported for fabrication of porous membranes with suitable porosity, shape and surface morphology matching the requirements of OOCs. In this paper, we review the state of the art for developing these membranes and discuss their application in OOCs.

A discrete fibre dispersion method for excluding fibres under compression in the modelling of fibrous tissues.

Abstract: Recently, micro-sphere-based methods derived from the angular integration approach have been used for excluding fibres under compression in the modelling of soft biological tissues. However, recent studies have revealed that many of the widely used numerical integration schemes over the unit sphere are inaccurate for large deformation problems even without excluding fibres under compression. Thus, in this study, we propose a discrete fibre dispersion model based on a systematic method for discretizing a unit hemisphere into a finite number of elementary areas, such as spherical triangles. Over each elementary area, we define a representative fibre direction and a discrete fibre density. Then, the strain energy of all the fibres distributed over each elementary area is approximated based on the deformation of the representative fibre direction weighted by the corresponding discrete fibre density. A summation of fibre contributions over all elementary areas then yields the resultant fibre strain energy. This treatment allows us to exclude fibres under compression in a discrete manner by evaluating the tension–compression status of the representative fibre directions only. We have implemented this model in a finite-element programme and illustrate it with three representative examples, including simple tension and simple shear of a unit cube, and non-homogeneous uniaxial extension of a rectangular strip. The results of all three examples are consistent and accurate compared with the previously developed continuous fibre dispersion model, and that is achieved with a substantial reduction of computational cost.

Influence of the windlass mechanism on arch-spring mechanics during dynamic foot arch deformation

Abstract: The function of the human foot is described dichotomously as a compliant structure during mid-stance and a stiff lever during push-off. The arch-spring and the windlass mechanisms, respectively, describe each of these behaviours; however, their interaction has not been quantified to date. We hypothesized that by engaging the windlass mechanism with metatarsophalangeal joint (MTPJ) dorsiflexion, we would observe stiffening of the arch and reduced energy absorption and dissipation during dynamic compressions of the foot. Using a custom apparatus, the MTPJ angle was fixed at 30 degrees of plantarflexion, neutral or 30 degrees of dorsiflexion for nine participants, with the shank positioned similarly to the end of mid-stance. The arch was compressed at two speeds, with the faster speed comparable to walking around 1.5 m s-1 Six cameras captured the compression and elongation of the arch, along with other kinematic variables, synchronously with the ground reaction force. Combining these measures, we computed the energy absorbed, returned and dissipated in the arch. Contrary to our hypothesis, when the windlass mechanism was engaged, the arch elongated more, and absorbed and dissipated more energy than when it was not engaged. This engagement of the windlass altered the rotational axis of the mid-foot, which probably oriented the arch-spanning structures closer to their resting length, increasing their compliance. This study provides novel evidence for an interplay between the windlass and arch-spring mechanisms that aids in regulation of energy storage within the foot.