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Circadian clocks exist in all types of organisms and coordinate key biological processes, e.g. photosynthesis in phytoplankton (microalgae) and land plants. We asked whether a circadian rhythm sustains in phytoplankton when living under constant illumination without environmental cues. Here, we report the first transcriptomic architecture of persistent oscillatory gene expression in the model marine diatom, Phaeodactylum tricornutum living under constant illumination and temperature without environmental cues. We show that cyclic expression of a considerable number of genes involved in light harvesting and carbon fixation sustained after 24 h of constant illumination (free-running), which could pose additional constraints on cell growth under constant light conditions. Over long-term adaptation to constant illumination, the majority of the rhythmic genes identified under diel light conditions lose their oscillatory expression in the absence of external entrainers, and the genes potentially controlled by persistent circadian clocks are primarily involved in transcriptional regulation and cell division. We find constant illumination leads to an increased average expression of transcription factors and cell division genes, while genes involved in the Calvin-Benson cycle and pigment biosynthesis are kept at low expression levels, which plays a role in the down-regulation of photosynthetic efficiency. By manipulation of the dark rest period, we confirm a fine-tuned light/dark cycle could dramatically improve photosynthetic efficiency in microalgae. Our results unveil a novel persistent circadian rhythm on photosynthetic regulation in marine phytoplankton and provide critical insights into the interaction between environmental signals and inheritable internal circadian clocks in diatoms., (© The Author(s) 2024. Published by Oxford University Press on behalf of National Academy of Sciences.)

Articular cartilage degeneration poses a significant public health challenge; techniques such as 3D bioprinting are being explored for its regeneration in vitro. Gelatin-based hydrogels represent one of the most promising biopolymers used in cartilage tissue engineering, especially for its collagen composition and tunable mechanical properties. However, there are no standard protocols that define process parameters such as the crosslinking method to apply. To this aim, a reproducible study was conducted for exploring the influence of different crosslinking methods on 3D bioprinted gelatin structures. This study assessed mechanical properties and cell viability in relation to various crosslinking techniques, revealing promising results particularly for dual (photo + ionic) crosslinking methods, which achieved high cell viability and tunable stiffness. These findings offer new insights into the effects of crosslinking methods on 3D bioprinted gelatin for cartilage applications. For example, ionic and photo-crosslinking methods provide softer materials, with photo-crosslinking supporting cell stretching and diffusion, while ionic crosslinking preserves a spherical stem cell morphology. On the other hand, dual crosslinking provides a stiffer, optimized solution for creating stable cartilage-like constructs. The results of this study offer a new perspective on the standardization of gelatin for cartilage bioprinting, bridging the gap between research and clinical applications.

Recently, gravity-driven membrane (GDM) filtration has been adopted as an alternative solution for decentralized wastewater treatment due to easy installation and maintenance, reduced energy and operation cost, and low global warming impact. This study investigated the influence of microplastic size (0.5-0.8 μm and 40-48 μm) and amount (0.1 and 0.2 g/L) on the membrane performance and microbial community in GDM systems for primary municipal wastewater treatment. The results showed that dosing microplastics in the GDM systems led to 9-54% lower permeate flux than that in the control. This was attributed to more cake formation (up to 6.4-fold) with more deposition of extracellular polymeric substances (EPS, up to 1.5-fold) and divalent cations (up to 2.1-fold) in the presence of microplastics, especially with increasing microplastic amount or size. However, the dosed microplastics promoted formation of heterogeneous cake layers with more porous nature, possibly because microplastics created void space in the cake and also tended to bind with divalent cations to reduce EPS-divalent cations interactions. In the biofilm of the GDM systems, the presence of microplastics could lower the number of total species, but it greatly enhanced the abundance of certain dominant prokaryotes (Phenylobacterium haematophilum, Planctomycetota bacterium, and Flavobacteriales bacterium), eukaryotes (Stylonychia lemnae, Halteria grandinella, and Paramicrosporidium saccamoebae), and virus (phylum Nucleocytoviricota), as well as amino acid and lipid metabolic functions. Especially, the small-size microplastics at a higher dosed amount led to more variations of microbial community structure and microbial metabolic functions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Prosthetic foot stiffness, which is typically invariable for commercially available prosthetic feet, needs to be considered when prescribing a prosthetic foot. While a biological foot adapts its function according to the movement task, an individual with lower limb amputation may be limited during more functionally demanding gait tasks by their conventional energy storing and return prosthetic foot., Research Question: How do changes in prosthetic foot stiffness during incline walking affect biomechanical measures as well as perception of participants., Methods: Kinetic and kinematic data were collected during incline walking, for five participants with trans-tibial amputation. A mixed model analysis of variance was used to analyse the effects of changing the stiffness during incline walking, using a novel variable-stiffness unit built on a commercially available prosthetic foot. Biomechanical results were also analysed on an individual level alongside the participant feedback, for a better understanding of the various strategies and perceptions exhibited during incline walking., Results: Statistically significant effects were only observed on the biomechanical parameters directly related to prosthetic ankle kinematics and kinetics (i.e., peak prosthetic ankle dorsiflexion, peak prosthetic ankle power, dynamic joint stiffness during controlled dorsiflexion). Participant perception during walking was affected by changes in stiffness. Individual analyses revealed varied perceptions and varied biomechanical responses among participants., Significance: While changes in prosthesis mechanical properties influenced the amputee's experience, minimal immediate effects were found with the overall gait pattern. The reported inter-participant variability may be due to the person's physical characteristics or habitual gait pattern, which may influence prosthesis function. The ability to vary prosthetic foot stiffness during the assessment phase of setting up a prosthesis could provide useful information to guide selection of the appropriate prosthetic device for acceptable performance across a range of activities., Competing Interests: Declaration of Competing Interest Two of the authors are employees of Össur, Research and Development., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Acute Respiratory Distress Syndrome (ARDS) is a condition that endangers the lives of many Intensive Care Unit patients through gradual reduction of lung function. Due to its heterogeneity, this condition has been difficult to diagnose and treat, although it has been the subject of continuous research, leading to the development of several tools for modeling disease progression on the one hand, and guidelines for diagnosis on the other, mainly the "Berlin Definition". This paper describes the development of a deep learning-based surrogate model of one such tool for modeling ARDS onset in a virtual patient: the Nottingham Physiology Simulator. The model-development process takes advantage of current machine learning and data-analysis techniques, as well as efficient hyperparameter-tuning methods, within a high-performance computing-enabled data science platform. The lightweight models developed through this process present comparable accuracy to the original simulator (per-parameter R 2 > 0.90). The experimental process described herein serves as a proof of concept for the rapid development and dissemination of specialised diagnosis support systems based on pre-existing generalised mechanistic models, making use of supercomputing infrastructure for the development and testing processes and supported by open-source software for streamlined implementation in clinical routines.

The COVID-19 pandemic shed light on the need for quick diagnosis tools in healthcare, leading to the development of several algorithmic models for disease detection. Though these models are relatively easy to build, their training requires a lot of data, storage, and resources, which may not be available for use by medical institutions or could be beyond the skillset of the people who most need these tools. This paper describes a data analysis and machine learning platform that takes advantage of high-performance computing infrastructure for medical diagnosis support applications. This platform is validated by re-training a previously published deep learning model (COVID-Net) on new data, where it is shown that the performance of the model is improved through large-scale hyperparameter optimisation that uncovered optimal training parameter combinations. The per-class accuracy of the model, especially for COVID-19 and pneumonia, is higher when using the tuned hyperparameters (healthy: 96.5%; pneumonia: 61.5%; COVID-19: 78.9%) as opposed to parameters chosen through traditional methods (healthy: 93.6%; pneumonia: 46.1%; COVID-19: 76.3%). Furthermore, training speed-up analysis shows a major decrease in training time as resources increase, from 207 min using 1 node to 54 min when distributed over 32 nodes, but highlights the presence of a cut-off point where the communication overhead begins to affect performance. The developed platform is intended to provide the medical field with a technical environment for developing novel portable artificial-intelligence-based tools for diagnosis support.

In this study, two lava stone biocarrier facilitated gravity-driven membrane (GDM) reactors were operated at ~8 °C and ~22 °C in parallel for treating primary wastewater effluent. Although the biocarrier reactor at 8 °C displayed less efficient removals of biodegradable organics than that at 22 °C, both GDM systems (without cleaning) showed comparable fouling resistance distribution patterns, accompanying with similar cake filtration constants and pore constriction constants by modelling simulation. Compared to the GDM at 8 °C, more foulants were accumulated on the GDM at 22 °C, but they presented similar soluble organics/inorganics contents and specific cake resistances. This indicated the cake layers at 22 °C may contain greater-sized foulants due to proliferation of both prokaryotes and eukaryotes, leading to a relatively less-porous nature. In the presence of periodic cleaning (at 50 °C), the cleaning effectiveness followed a sequence as ultrasonication-enhanced physical cleaning > two-phase flow cleaning > chemical-enhanced physical cleaning > physical cleaning, regardless of GDM operation temperature. However, significantly higher cake resistances were observed in the GDM system at 22 °C than those at 8 °C, because shear force tended to remove loosely-attached foulant layers and may compress the residual dense cake layer. The presence of periodic cleaning led to dissimilar dominant prokaryotic and eukaryotic communities in the cake layers as those without cleaning and in the lava stone biocarriers. Nevertheless, operation temperature did not influence GDM permeate quality, which met EU discharge standards., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Adaptation of lower limb function to different gait tasks is inherently not as effective among individuals with lower limb amputation as compared to able-bodied individuals. Varying stiffness of a prosthetic foot may be a way of facilitating gait tasks that require larger ankle joint range of motion., Methods: Three stiffness settings of a novel prosthetic foot design were tested for level walking at three speeds as well as for 7,5° incline and decline walking. Outcome measures, describing ankle range of motion and ankle dynamic joint stiffness were contrasted across the three stiffness settings. Standardized mechanical tests were done for the hindfoot and forefoot., Findings: Dorsiflexion angle was incrementally increased with a softer foot and a faster walking speed / higher degree of slope. The concurrent dynamic joint stiffness exhibited a less systematic change, especially during INCLINE and DECLINE walking. The small difference seen between the stiffness settings for hindfoot loading limits analysis for the effects of stiffness during weight acceptance, however, a stiffer foot significantly restricted plantarflexion during DECLINE., Interpretations: Varying stiffness settings within a prosthetic foot does have an effect on prosthetic foot dynamics, and differences are task dependent, specifically in parameters involving kinetic attributes. When considering the need for increased ankle range of motion while performing more demanding gait tasks, a foot that allows the users themselves to adjust stiffness according to the task at hand may be of benefit for active individuals, possibly enhancing the user's satisfaction and comfort during various daily activities., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

The Tröllaskagi Peninsula in northern Iceland hosts more than a hundred small glaciers that have left a rich terrestrial record of Holocene climatic fluctuations in their forelands. Traditionally, it has been assumed that most of the Tröllaskagi glaciers reached their Late Holocene maximum extent during the Little Ice Age (LIA). However, there is evidence of slightly more advanced pre-LIA positions. LIA moraines from Iceland have been primary dated mostly through lichenometric dating, but the limitations of this technique do not allow dating of glacial advances prior to the 18th or 19th centuries. The application of 36 Cl Cosmic-Ray Exposure (CRE) dating to Tungnahryggsjökull moraine sequences in Vesturdalur and Austurdalur (central Tröllaskagi) has revealed a number of pre-LIA glacial advances at ~400 and ~700 CE, and a number of LIA advances in the 15 th and 17 th centuries, the earliest LIA advances dated so far in Tröllaskagi. This technique hence shows that the LIA chronology in Tröllaskagi agrees with that of other European areas such as the Alps or the Mediterranean mountains. The combined use of lichenometric dating, aerial photographs, satellite images and fieldwork shows that the regional colonization lag of the commonly used lichen species Rhizocarpon geographicum is longer than previously assumed. For exploratory purposes, an alternative lichen species (Porpidia soredizodes) has been tested for lichenometric dating, estimating a tentative growth rate of 0.737 mm yr -1 ., (Copyright © 2019 Elsevier B.V. All rights reserved.)

To convert waste CO 2 from flue gases of power plants into value-added products, bio-mitigation technologies show promise. In this study, we cultivated a fast-growing species of green microalgae, Chlorella vulgaris, in different sizes of photobioreactors (PBRs) and developed a strategy using small doses of sugars for enhancing CO 2 sequestration under light-emitting diode illumination. Glucose supplementation at low levels resulted in an increase of photoautotrophic growth-driven biomass generation as well as CO 2 capture by 10% and its enhancement corresponded to an increase of supplied photon flux. The utilization of urea instead of nitrate as the sole nitrogen source increased photoautotrophic growth by 14%, but change of nitrogen source didn't compromise glucose-induced enhancement of photoautotrophic growth. The optimized biomass productivity achieved was 30.4% higher than the initial productivity of purely photoautotrophic culture. The major pigments in the obtained algal biomass were found comparable to its photoautotrophic counterpart and a high neutral lipids productivity of 516.6 mg/(L·day) was achieved after optimization. A techno-economic model was also developed, indicating that LED-based PBRs represent a feasible strategy for converting CO 2 into value-added algal biomass., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The data presented in this article are related to the research article entitled "Sugar-stimulated CO 2 sequestration by the green microalga Chlorella vulgaris " (Fu et al., 2019) [1]. The data describe a rational design and scale-up of LED-based photobioreactors for producing value-added algal biomass while removing waste CO 2 from flu gases from power plants. The dataset were created from growth rate experiments for biomass production including direct biomass productivity data, PBR size and setup parameters, medium composition as well as indirect energy cost and overhead in Iceland. A complete economic analysis is formed through a cost breakdown as well as PBR scalability predictions.

The temperature dependence of biological processes has been studied at the levels of individual biochemical reactions and organism physiology ( e.g. basal metabolic rates) but has not been examined at the metabolic network level. Here, we used a systems biology approach to characterize the temperature dependence of the human red blood cell (RBC) metabolic network between 4 and 37 °C through absolutely quantified exo- and endometabolomics data. We used an Arrhenius-type model ( Q 10 ) to describe how the rate of a biochemical process changes with every 10 °C change in temperature. Multivariate statistical analysis of the metabolomics data revealed that the same metabolic network-level trends previously reported for RBCs at 4 °C were conserved but accelerated with increasing temperature. We calculated a median Q 10 coefficient of 2.89 ± 1.03, within the expected range of 2-3 for biological processes, for 48 individual metabolite concentrations. We then integrated these metabolomics measurements into a cell-scale metabolic model to study pathway usage, calculating a median Q 10 coefficient of 2.73 ± 0.75 for 35 reaction fluxes. The relative fluxes through glycolysis and nucleotide metabolism pathways were consistent across the studied temperature range despite the non-uniform distributions of Q 10 coefficients of individual metabolites and reaction fluxes. Together, these results indicate that the rate of change of network-level responses to temperature differences in RBC metabolism is consistent between 4 and 37 °C. More broadly, we provide a baseline characterization of a biochemical network given no transcriptional or translational regulation that can be used to explore the temperature dependence of metabolism., (© 2017 by The American Society for Biochemistry and Molecular Biology, Inc.)

Background: Alternate sugar metabolism during red blood cell (RBC) storage is not well understood. Here we report fructose and mannose metabolism in RBCs during cold storage in SAGM and the impact that these monosaccharides have on metabolic biomarkers of RBC storage lesion., Study Design and Methods: RBCs were stored in SAGM containing uniformly labeled 13 C-fructose or 13 C-mannose at 9 or 18 mmol/L concentration for 25 days. RBCs and media were sampled at 14 time points during storage and analyzed using ultraperformance liquid chromatography-mass spectrometry. Blood banking quality assurance measurements were performed., Results: Red blood cells incorporated fructose and mannose during cold storage in the presence of glucose. Mannose was metabolized in preference to glucose via glycolysis. Fructose lowered adenosine triphosphate (ATP) levels and contributed little to ATP maintenance when added to SAGM. Both monosaccharides form the advanced glycation end product glycerate. Mannose activates enzymes in the RBC that take part in glycan synthesis., Conclusions: Fructose or mannose addition to RBC SAGM concentrates may not offset the shift in metabolism of RBCs that occurs after 10 days of storage. Fructose and mannose metabolism at 4°C in SAGM reflects their metabolism at physiologic temperature. Glycerate excretion is a measure of protein deglycosylation activity in stored RBCs. No cytoprotective effect was observed upon the addition of either fructose or mannose to SAGM., (© 2017 AABB.)

Motivation: A genome-scale reconstruction of human metabolism, Recon 2, is available but no interface exists to interactively visualize its content integrated with omics data and simulation results., Results: We manually drew a comprehensive map, ReconMap 2.0, that is consistent with the content of Recon 2. We present it within a web interface that allows content query, visualization of custom datasets and submission of feedback to manual curators., Availability and Implementation: ReconMap can be accessed via http://vmh.uni.lu , with network export in a Systems Biology Graphical Notation compliant format released under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. A Constraint-Based Reconstruction and Analysis (COBRA) Toolbox extension to interact with ReconMap is available via https://github.com/opencobra/cobratoolbox ., Contact: ronan.mt.fleming@gmail.com., (© The Author 2016. Published by Oxford University Press.)

As a major primary producer in marine environments, diatoms have been considered as promising feedstocks for their applications in functional foods, bioactive pharmaceuticals, and cosmetics. This review focuses on the biotechnology potential of diatoms for value-added products like carotenoids. The impact of abiotic environmental stresses, such as intensity and quality of incident light, nutrient deficiency and silicon depletion, on diatoms has been examined to determine key factors that affect the growth performance and the accumulation of valuable compounds. Previous studies suggested that adaptive evolution could be an efficient method to improve the diatom productivity of valuable compounds. Light emitting diode (LED)-based photobioreactors were introduced and proposed as a promising new technology for producing quality products from diatoms. Currently available molecular biology tools were also summarized and discussed in relation to their application in the production of carotenoids and other valuable products. Taken together, systems biology and synthetic biology approaches have the potential to address the challenges faced while working toward the industrial application of diatoms., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Background: Platelet concentrates (PCs) can be prepared using three methods: platelet (PLT)-rich plasma, apheresis, and buffy coat. The aim of this study was to obtain a comprehensive data set that describes metabolism of buffy coat-derived PLTs during storage and to compare it with a previously published parallel data set obtained for apheresis-derived PLTs., Study Design and Methods: During storage we measured more than 150 variables in 8 PLT units, prepared by the buffy coat method. Samples were collected at seven different time points resulting in a data set containing more than 8000 measurements. This data set was obtained by combining a series of standard quality control assays to monitor the quality of stored PLTs and a deep coverage metabolomics study using liquid chromatography coupled with mass spectrometry., Results: Stored PLTs showed a distinct metabolic transition occurring 4 days after their collection. The transition was evident in PLT produced by both production methods. Apheresis-derived PLTs showed a clearer phenotype of PLT activation during early days of storage. The activated phenotype of apheresis PLTs was accompanied by a higher metabolic activity, especially related to glycolysis and the tricarboxylic acid cycle. Moreover, the extent of the activation differed between bags resulting in interbag variability in the storage lesion of apheresis-prepared PLTs. This may be related to donor-related polymorphism., Conclusion: This study demonstrated two discrete metabolic phenotypes in stored PLTs prepared with both apheresis and buffy coat methods. PLT activation occurs during the first metabolic phenotype and might lead to a low reproducibility of the apheresis PCs., (© 2014 AABB.)

Background: Platelet (PLT) concentrates are routinely stored for 5 to 7 days. During storage they exhibit what has been termed PLT storage lesion (PSL), which is evident by a loss of hemostatic function when transfused into patients. The overall goal of this study was to obtain a comprehensive data set describing PLT metabolism during storage., Study Design and Methods: The experimental approach adopted to achieve this goal combined a series of standard assays to monitor the quality of stored PLTs and a deep-coverage metabolomics study using liquid chromatography coupled with mass spectrometry performed on both the extracellular and the intracellular environments. During storage we measured 174 different variables in 6 PLT units, collected by apheresis. Samples were collected at eight different time points resulting in a data set containing more than 8000 measurements., Results: Stored PLTs did not undergo a monotonic decay, but experienced systematic changes in metabolism reflected in three discrete metabolic phenotypes: The first (Days 0-3) was associated with active glycolysis, pentose phosphate pathway, and glutathione metabolism and down regulation of tricarboxylic acid (TCA) cycle. The second (Days 4-6) was associated with a more active TCA cycle as well as increased purine metabolism. A third metabolic phenotype of less clinical relevance (Days 7-10) was associated with a faster decay of cellular metabolism., Conclusion: PSL is not associated with a linear decay of metabolism, but rather with successive metabolic shifts. These findings may give new insight into the mechanisms underlying PSL and encourage the deployment of systems biology methods to PSL., (© 2014 AABB.)

We recently evaluated the relationship between abiotic environmental stresses and lutein biosynthesis in the green microalga Dunaliella salina and suggested a rational design of stress-driven adaptive evolution experiments for carotenoids production in microalgae. Here, we summarize our recent findings regarding the biotechnological production of carotenoids from microalgae and outline emerging technology in this field. Carotenoid metabolic pathways are characterized in several representative algal species as they pave the way for biotechnology development. The adaptive evolution strategy is highlighted in connection with enhanced growth rate and carotenoid metabolism. In addition, available genetic modification tools are described, with emphasis on model species. A brief discussion on the role of lights as limiting factors in carotenoid production in microalgae is also included. Overall, our analysis suggests that light-driven metabolism and the photosynthetic efficiency of microalgae in photobioreactors are the main bottlenecks in enhancing biotechnological potential of carotenoid production from microalgae.

Background: Recent years have witnessed a rising trend in exploring microalgae for valuable carotenoid products as the demand for lutein and many other carotenoids in global markets has increased significantly. In green microalgae lutein is a major carotenoid protecting cellular components from damage incurred by reactive oxygen species under stress conditions. In this study, we investigated the effects of abiotic stressors on lutein accumulation in a strain of the marine microalga D. salina which had been selected for growth under stress conditions of combined blue and red lights by adaptive laboratory evolution., Results: Nitrate concentration, salinity and light quality were selected as three representative influencing factors and their impact on lutein production in batch cultures of D. salina was evaluated using response surface analysis. D. salina was found to be more tolerant to hyper-osmotic stress than to hypo-osmotic stress which caused serious cell damage and death in a high proportion of cells while hyper-osmotic stress increased the average cell size of D. salina only slightly. Two models were developed to explain how lutein productivity depends on the stress factors and for predicting the optimal conditions for lutein productivity. Among the three stress variables for lutein production, stronger interactions were found between nitrate concentration and salinity than between light quality and the other two. The predicted optimal conditions for lutein production were close to the original conditions used for adaptive evolution of D. salina. This suggests that the conditions imposed during adaptive evolution may have selected for the growth optima arrived at., Conclusions: This study shows that systematic evaluation of the relationship between abiotic environmental stresses and lutein biosynthesis can help to decipher the key parameters in obtaining high levels of lutein productivity in D. salina. This study may benefit future stress-driven adaptive laboratory evolution experiments and a strategy of applying stress in a step-wise manner can be suggested for a rational design of experiments.

There is a particularly high interest to derive carotenoids such as β-carotene and lutein from higher plants and algae for the global market. It is well known that β-carotene can be overproduced in the green microalga Dunaliella salina in response to stressful light conditions. However, little is known about the effects of light quality on carotenoid metabolism, e.g., narrow spectrum red light. In this study, we present UPLC-UV-MS data from D. salina consistent with the pathway proposed for carotenoid metabolism in the green microalga Chlamydomonas reinhardtii. We have studied the effect of red light-emitting diode (LED) lighting on growth rate and biomass yield and identified the optimal photon flux for D. salina growth. We found that the major carotenoids changed in parallel to the chlorophyll b content and that red light photon stress alone at high level was not capable of upregulating carotenoid accumulation presumably due to serious photodamage. We have found that combining red LED (75 %) with blue LED (25 %) allowed growth at a higher total photon flux. Additional blue light instead of red light led to increased β-carotene and lutein accumulation, and the application of long-term iterative stress (adaptive laboratory evolution) yielded strains of D. salina with increased accumulation of carotenoids under combined blue and red light.

The aim of the present study is to compare the results from subject-specific finite element analysis (FEA) of a human femur to experimental measurements, using two different methods for assigning material properties to the FE models. A modified material mapping strategy allowing for spatial variation of material properties within the elements and Young's modulus surface corrections is presented and compared to a more conventional strategy, whereby constant material properties are assigned to each element. The accuracy of the superficial stress-strain predictions was evaluated against experimental results from 13 strain gauges and five different load cases. Both methods predicted stresses with acceptable accuracy (R(2) = 0.92, root mean square error, RMSE < 10%), with the conventional method performing slightly better. The modified method performed better in strain prediction (R(2) = 0.85, RMSE = 23% versus R(2) = 0.79, RMSE = 31%).

Background: In many published studies, elastic properties of bone are correlated to the bone density, in order to derive an empirical elasticity-density relationship. The most common use of these relationships is the prediction of the bone local properties from medical imaging data in subject-specific numerical simulation studies. The proposed relationships are substantially different one from the other. It is unclear whether such differences in elasticity-density relationships can be entirely explained in terms of methodological discrepancies among studies., Methods: All relevant literature was reviewed. Only elasticity-density relationships derived from similarly controlled experiments were included and properly normalized. The resulting relationships were grouped according to the most important methodological differences: type of end support during testing, specimen geometry, and anatomical sampling location., Findings: Even after normalization with respect to strain rate and densitometric measurement unit, substantial inter-study differences do exist, and they can only be partially explained by the methodological differences between studies., Interpretation: Some recommendations are made for the application of elasticity-density relationships to subject-specific finite element studies. The importance of defining a standardized mechanical testing methodology for bone specimens is stressed, and some guidelines that emerged from the literature are proposed. To identify density-elasticity relationships suitable for use in subject-specific FE studies, the development of a benchmark study is also proposed, where the elasticity-density relationship is taken as the variable under study, and a numerical model of known numerical accuracy predicts experimental strain measurements.

Pushout tests can be used to estimate the shear strength of the bone implant interface. Numerous such experimental studies have been published in the literature. Despite this researchers are still some way off with respect to the development of accurate numerical models to simulate implant stability. In the present work a specific experimental pushout study from the literature was simulated using two different bones implant interface models. The implant was a porous coated Ti-6Al-4V retrieved 4 weeks postoperatively from a dog model. The purpose was to find out which of the interface models could replicate the experimental results using physically meaningful input parameters. The results showed that a model based on partial bone ingrowth (ingrowth stability) is superior to an interface model based on friction and prestressing due to press fit (initial stability). Even though the present study is limited to a single experimental setup, the authors suggest that the presented methodology can be used to investigate implant stability from other experimental pushout models. This would eventually enhance the much needed understanding of the mechanical response of the bone implant interface and help to quantify how implant stability evolves with time.