State estimation of a physical system with unknown governing equations.

State estimation is concerned with reconciling noisy observations of a physical system with the mathematical model believed to predict its behaviour for the purpose of inferring unmeasurable states and denoising measurable ones1,2. Traditional state-estimation techniques rely on strong assumptions about the form of uncertainty in mathematical models, typically that it manifests as an additive stochastic perturbation or is parametric in nature3. Here we present a reparametrization trick for stochastic variational inference with Markov Gaussian processes that enables an approximate Bayesian approach for state estimation in which the equations governing how the system evolves over time are partially or completely unknown. In contrast to classical state-estimation techniques, our method learns the missing terms in the mathematical model and a state estimate simultaneously from an approximate Bayesian perspective. This development enables the application of state-estimation methods to problems that have so far proved to be beyond reach. Finally, although we focus on state estimation, the advancements to stochastic variational inference made here are applicable to a broader class of problems in machine learning.

Unlocking Early Cancer Detection: Exploring Biomarkers, Circulating DNA, and Innovative Technological Approaches.

Research and development improvements in early cancer diagnosis have had a significant positive impact on health. In the treatment and prevention of cancer, early detection is essential. In this context, biomarkers are essential because they offer important information on the state of cells at any particular time. Cells go through unique changes when they shift from a healthy condition to a malignant state, changes that appropriate biomarkers may pick up. Recent advancements have been made to identify and characterize circulating cancer-specific mutations in cell-free circulating DNA derived from tumors and tumor cells. A patient's delay between the time they first detect symptoms and the time they contact a doctor has been noted for many cancer forms. The tumor's location and features significantly impact the presentation of symptoms judged appropriate for early diagnosis. Lack of knowledge of the severity of the symptoms may be one cause for this delay. Our review is largely focused on the ongoing developments of early diagnosis in the study of biomarkers, circulating DNA for diagnosis, the biology of early challenges, early symptoms, liquid biopsies, detectable by imaging, established tumor markers, plasma DNA technologies, gender differences, and artificial intelligence (AI) in diagnosis. This review aims to determine and evaluate Indicators for detecting early cancer, assessing medical conditions, and evaluating potential risks. For Individuals with a heightened likelihood of developing cancer or who have already been diagnosed, early identification is crucial for enhancing prognosis and raising the likelihood of effective treatment.

Enhanced inhibition of Pseudomonas aeruginosa virulence factor production and biofilm development by sublethal concentrations of eugenol and phenyllactic acid.

Biofilm development in Pseudomonas aeruginosa is regulated by its quorum sensing (QS) systems. It has three major QS systems: LasI/R, RhlI/R and PQS/MvfR. Previous studies showed that phenyllactic acid (PLA) binds to RhlR and PqsR and inhibits the Rhl and PQS QS; and eugenol at sublethal concentration inhibits Las and PQS QS systems. Here, we have demonstrated that a combination of sublethal doses of eugenol and PLA enhanced the inhibition of the QS mediated production of the virulence factors and biofilm development of this pathogen. A combination of 50 µmol l-1 eugenol and 0·3 mmol l-1 PLA significantly inhibited the pyocyanin production, protease activity, swarming motility and cytotoxic activities of P. aeruginosa strain PAO1, whereas eugenol and PLA when added individually to PAO1 cultures were less effective in inhibiting its virulence factor expression. Biofilm formation of PAO1 was reduced by 32, 19 and 87% on glass surfaces; and 54, 49 and 93% on catheter surfaces when treated using 50 µmol l-1 eugenol or 0·3 mmol l-1 PLA and their combinations, respectively. The in vitro finding in the reduction of biofilm development was further validated in vivo using a catheter associated medaka fish biofilm model. Our results indicate that a combination of QS inhibitors targeting different QS pathways should be selected while designing therapeutic molecules to achieve maximum QS mediated biofilm inhibition and clinical outcome against P. aeruginosa.

A Study on Algae Bloom Pigment in the Eutrophic Lake Using Bio-Optical Modelling: Hyperspectral Remote Sensing Approach.

Inland lake is one of the important sources of freshwater ecosystem and serves as a sentinel to the changing aquatic biodiversity. Chlorophyll-a (Chl-a) is a major biological indicator and essential measure of the eutrophic status of lake water because it is strongly related to algae biomass. In the present research, bio-optical algorithms were developed based on the semi-empirical approach using the spectral wavelengths of 400 to 800 nm from hyperspectral remote sensing measurement and compared with Sentinel-2MSI image for estimation of Chl-a concentration in the lake water. The results show that the bio-optical algorithm can estimate and predict the algae pigment (Chl-a) concentration in the eutrophic lake with good accuracy of R2 of 0.8958, root mean squared error of 13.028, and mean absolute percentage error of 8.44%. The developed algorithm will be suitable and potential for monitoring algae spatial dynamics and assessment in an inland lake.

Ab Initio Molecular Dynamics Simulations of the Interaction between Organic Phosphates and Goethite.

Today's fertilizers rely heavily on mining phosphorus (P) rocks. These rocks are known to become exhausted in near future, and therefore effective P use is crucial to avoid food shortage. A substantial amount of P from fertilizers gets adsorbed onto soil minerals to become unavailable to plants. Understanding P interaction with these minerals would help efforts that improve P efficiency. To this end, we performed a molecular level analysis of the interaction of common organic P compounds (glycerolphosphate (GP) and inositol hexaphosphate (IHP)) with the abundant soil mineral (goethite) in presence of water. Molecular dynamics simulations are performed for goethite-IHP/GP-water complexes using the multiscale quantum mechanics/molecular mechanics method. Results show that GP forms monodentate (M) and bidentate mononuclear (B) motifs with B being more stable than M. IHP interacts through multiple phosphate groups with the 3M motif being most stable. The order of goethite-IHP/GP interaction energies is GP M < GP B < IHP M < IHP 3M. Water is important in these interactions as multiple proton transfers occur and hydrogen bonds are formed between goethite-IHP/GP complexes and water. We also present theoretically calculated infrared spectra which match reasonably well with frequencies reported in literature.

QM/MM simulations of organic phosphorus adsorption at the diaspore-water interface.

Phosphorus (P) immobilization and thus its availability for plants are mainly affected by the strong interaction of phosphates with soil components especially soil mineral surfaces. The related reactions have been studied extensively via sorption experiments especially by carrying out adsorption of ortho-phosphates onto Fe-oxide surfaces. But a molecular-level understanding of the P-binding mechanisms at the mineral-water interface is still lacking, especially for forest eco-systems. Therefore, the current contribution provides an investigation of the molecular binding mechanisms for two abundant phosphates in forest soils, inositol hexaphosphate (IHP) and glycerolphosphate (GP), at the diaspore mineral surface. Here a hybrid electrostatic embedding quantum mechanics/molecular mechanics (QM/MM) based molecular dynamics simulation has been applied to explore the diaspore-IHP/GP-water interactions. The results provide evidence for the formation of different P-diaspore binding motifs involving monodentate (M) and bidentate (B) for GP and two (2M) as well as three (3M) monodentates for IHP. The interaction energy results indicated the abundance of the GP B motif compared to the M one. The IHP 3M motif has a higher total interaction energy compared to its 2M motif, but exhibits a lower interaction energy per bond. Compared to GP, IHP exhibited stronger interaction with the surface as well as with water. Water was found to play an important role in controlling these diaspore-IHP/GP-water interactions. The interfacial water molecules form moderately strong H-bonds (HBs) with GP and IHP as well as with the diaspore surface. For all the diaspore-IHP/GP-water complexes, the interaction of water with the diaspore exceeds that with the studied phosphates. Furthermore, some water molecules form covalent bonds with diaspore Al atoms while others dissociate at the surface to protons and hydroxyl groups leading to proton transfer processes. Finally, the current results confirm the previous experimental conclusions indicating the importance of the number of phosphate groups, HBs, and proton transfers in controlling the P-binding at soil mineral surfaces.

Sparse low-rank separated representation models for learning from data.

We consider the problem of learning a multivariate function from a set of scattered observations using a sparse low-rank separated representation (SSR) model. The model structure considered here is promising for high-dimensional learning problems; however, existing training algorithms based on alternating least-squares (ALS) are known to have convergence difficulties, particularly when the rank of the model is greater than 1. In the present work, we supplement the model structure with sparsity constraints to ensure the well posedness of the approximation problem. We propose two fast training algorithms to estimate the model parameters: (i) a cyclic coordinate descent algorithm and (ii) a block coordinate descent (BCD) algorithm. While the first algorithm is not provably convergent owing to the non-convexity of the optimization problem, the BCD algorithm guarantees convergence to a Nash equilibrium point. The computational cost of the proposed algorithms is shown to scale linearly with respect to all of the parameters in contrast to methods based on ALS. Numerical studies on synthetic and real-world regression datasets indicate that the proposed SSR model structure holds significant potential for machine learning problems.

Impregnation of catheters with anacardic acid from cashew nut shell prevents Staphylococcus aureus biofilm development.

AIM: The effect of anacardic acid impregnation on catheter surfaces for the prevention of Staphylococcus aureus attachments and biofilm formations were evaluated. METHODS AND RESULTS: Silicon catheter tubes were impregnated using different concentrations of anacardic acids (0·002-0·25%). Anacardic acids are antibacterial phenolic lipids from cashew nut (Anacardium occidentale) shell oil. Anacardic acid-impregnated silicon catheters revealed no significant haemolytic activity and were cytocompatible against fibroblast cell line (L929). Sustained release of anacardic acids was observed for 4 days. Anacardic acid-impregnated silicon catheters efficiently inhibited S. aureus colonization and the biofilm formation on its surface. The in vivo antibiofilm activity of anacardic acid-impregnated catheters was tested in an intraperitoneal catheter-associated medaka fish infection model. Significant reduction in S. aureus colonization on anacardic acid-impregnated catheter tubes was observed. CONCLUSIONS: Our data suggest that anacardic acid-impregnated silicon catheters may help in preventing catheter-related staphylococcal infections. SIGNIFICANCE AND IMPACT OF THE STUDY: This study opens new directions for designing antimicrobial phytochemical-coated surfaces with ideal antibiofilm properties and could be of great interest for biomedical research scientists.

Protonated N-benzyl- and N-(1-phenylethyl)tyrosine amides dissociate via ion/neutral complexes.

RATIONALE: The collisional-induced dissociations (CID) of the [M+H]+ ions of molecules having benzyl groups attached to N-atoms have been proposed to involve migration of the benzyl group through the intermediacy of ion/neutral complexes (INCs). We report the investigation of the mechanism of dissociation of protonated N-benzyl- and N-(1-phenylethyl)tyrosine amides by electrospray ionization (ESI) tandem mass spectrometry (MS/MS) and density functional theory (DFT) calculations. METHODS: The amides were synthesized from the corresponding amino acids and amines. The ESI-MS/MS spectra were recorded using an Agilent QTOF 6540 mass spectrometer. The DFT calculations were performed by using Gaussian 09 software. The structures of the [M+H]+ ions, intermediates, products and transition states (TS) were optimized at the B3LYP/6-31G(d,p) level of theory. RESULTS: CID of the [M+H]+ ions of N-benzyltyrosine amide yields two product ions due to rearrangements: (i) the [M+H-74]+ ion (m/z 197) due to benzyl migration to the hydroxyphenyl ring and (ii) the [M+H-45]+ ion (m/z 226) due to benzyl migration to the NH2 group. DFT calculations suggest that the rearrangements occur through an INC in which the benzyl cation is the cation partner. The [M+H]+ ion of N-(1-phenylethyl)tyrosine amide rearranges to an INC of the 1-phenylethyl cation. Subsequent elimination of styrene occurs by transfer of a proton from the 1-phenylethyl cation to the neutral partner. CONCLUSIONS: The [M+H]+ ions of both N-benzyl (1) and N-(1-phenylethyl) (2) tyrosine amide rearrange into INCs. The dissociation of [M+H]+ ion of 1 yields the benzyl cation and [M+H-74]+ and [M+H-45]+ due to benzyl migration to the hydroxyphenyl ring and NH2 group, respectively. However, the formation of the [M+H-74]+ ion is not observed when the aromatic ring is deactivated. The [M+H]+ ion of 2 either dissociates to form the 1-phenylethyl cation or [M+H-styrene]+ . Copyright © 2015 John Wiley & Sons, Ltd.

Structural characterization of alkaline and oxidative stressed degradation products of lurasidone using LC/ESI/QTOF/MS/MS.

A selective, accurate, precise and robust stability indicating liquid chromatography assay method was developed for the monitoring of a novel antipsychotic drug, lurasidone, in the presence of its degradation products (DPs). Also, we investigated degradation behavior of the drug under various stressed conditions such as hydrolytic (acidic, basic and neutral), oxidation, photolytic and thermal. The drug was found to be degraded under base hydrolytic and oxidative conditions, while it was stable in acid and neutral hydrolytic, photolytic and thermal conditions. The method showed adequate separation of lurasidone and its DPs on Xterra C18 (150 mm × 4.6 mm i.d., 3.5 µm) column using 20 mM ammonium formate (pH 3.0): acetonitrile as a mobile phase in gradient elution mode at a flow rate of 0.6 mL/min. This method was extended to liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry (LC/ESI/QTOF/MS/MS) for structural characterization of DPs. A total of five DPs were characterized by LC/ESI/QTOF/MS/MS studies. Most probable mechanisms for the formation of DPs were proposed. The developed method was validated in terms of specificity, linearity, accuracy, precision, and robustness as per International Conference on Harmonization Guideline Q2 (R1).

A comparative evaluation of compressive strength of Portland cement with zinc oxide eugenol and Polymer-reinforced cement: an in vitro analysis.

OBJECTIVE: The purpose of this study is to evaluate the ultimate compressive strength of 50% and 25% Portland cement mixed with Polymer-reinforced zinc oxide eugenol and zinc oxide eugenol cement after 1 hour, 24 hours, and 7 days. MATERIALS AND METHODS: One hundred and eighty samples were selected. The samples were made cylindrical of size 6 × 8 mm and were divided into six groups as follows with each group consisting of 10 samples. Group 1: Polymer-reinforced zinc oxide eugenol with 50% Portland cement (PMZNPC 50%) Group 2: Polymer-reinforced zinc oxide eugenol with 25% Portland cement (PMZNPC 25%) Group 3: Polymer-reinforced zinc oxide eugenol with 0% Portland cement (PMZNPC 0%) Group 4: Zinc oxide eugenol with 50% Portland cement (ZNPC 50%) Group 5: Zinc oxide eugenol with 25% Portland cement (ZNPC 25%) Group 6: Zinc oxide eugenol with 0% Portland cement (ZNPC 0%) These samples were further subdivided based on time interval and were tested at 1 hour, 24 hours and at 7 th day. After each period of time all the specimens were tested by vertical CVR loaded frame with capacity of 5 tones/0473-10kan National Physical laboratory, New Delhi and the results were statistically analyzed using ANOVA and Scheffe test. RESULTS: Polymer-reinforced cement with 50% Portland cement, Zinc oxide with 50% Portland cement, Polymer-reinforced cement with 25% Portland cement and Zinc oxide with 25% Portland cement exhibited higher compressive strength when compared to Zinc oxide with 0% Portland cement and Polymer-reinforced cement with 0% Portland cement, at different periods of time. The difference between these two groups were statistically significant (P < 0.05) and it is suggested that mixture of 50% and 25% Portland cement in Zinc oxide eugenol and Polymer-modified zinc oxide cement can be used as core build up material and permanent filling material. CONCLUSION: It is concluded that 50% and 25% Portland cement in zinc oxide eugenol and polymer-modified zinc oxide eugenol results in higher compressive strength and hence can be used as permanent filling material and core built-up material.

Estrogen oversees the maintenance of the female genetic program in terminally differentiated gonochorists.

The sexual plasticity of the gonads is not retained after the completion of sex differentiation in vertebrates, except in some hermaphroditic species. Here, we report that the depletion of estradiol-17ß (E2) by aromatase inhibitors (AI) for up to six months resulted in a functional female-to-male sex reversal in sexually-mature adults of two gonochoristic fish species, Nile tilapia and medaka. The sex-reversed fish showed a typical male pattern of E2 and androgen levels, secondary sexual characteristics, and male-like sex behavior, producing fertile sperm. Conversely, co-treatment of E2 inhibited AI-induced sex reversal. In situ hybridization of medaka gonads during AI-induced sex reversal indicated that cysts on the dorsal side of the adult ovaries are the origin of germ cells and Sertoli cells in the newly formed testicular tissue. Gonochoristic fish maintain their sexual plasticity until adulthood and E2 plays a critical role in maintaining the female phenotype.

Cu(II)-porphyrin molecular dynamics as seen in a novel EPR/Stochastic Liouville equation study.

Copper porphyrin dissolved in CH2Cl2:toluene as fluid and frozen solution was studied as a function of temperature using X-band electron paramagnetic resonance (EPR). Quantitative interpretation was obtained using a recently developed Stochastic Liouville simulation method. For the first time we address the large spin system that translates into a 400,000 dimensional Liouville equation solved under slow-motion conditions. Using a simple three parameter microscopic model, the temperature dependence of porphyrin rotational correlation time is determined to be in the range 1-10 ns and a fast local motion is in the subpico-second regime with an amplitude increasing with temperature. The methodology provides an important tool for arriving at an accurate set of spin Hamiltonian parameters since determining a unique set of parameters from a frozen solution EPR experiment is often difficult. Thus, the proposed method discriminates between parameters proposed from frozen solution EPR experiments or quantum chemistry calculations. The methodology presented is expected to be valuable in obtaining a molecular dynamics picture of metal proteins using EPR as well as in the study of artificial photosynthetic systems.

Poly (lactic acid)-chitosan-collagen composite nanofibers as substrates for blood outgrowth endothelial cells.

In this work, the attachment, viability and functionality of rat Blood Outgrowth Endothelial Cells (rBOEC) and genetically modified rBOEC (rBOEC/eNOS-GFP), which over express endothelial nitric oxide synthase (eNOS), were investigated on Poly(lactic acid) (PLA)-chitosan and PLA-chitosan-collagen nanofibrous scaffolds. Both the cell types displayed good attachment, remained viable and functional on both scaffolds. Moreover, incorporation of collagen in the scaffold helped in sustaining the rBOEC for upto one week, although collagen was not found necessary for rBOEC/eNOS-GFP. We conclude that PLA-chitosan based nanofibrous scaffolds can be a potential candidate for BOEC based wound healing applications.

Influence of femur size and morphology on load transfer in the resurfaced femoral head: A large scale, multi-subject finite element study.

Femoral resurfacing has become an increasingly popular procedure, especially for young, active patients. The procedure is known to alter load transfer through the proximal femur and this has been linked with the most commonly observed complication, neck fracture. An intriguing observation noted by registry data and clinical studies is an inverse relationship between implant size and revision rate. While computational analysis has become an established part of biomedical engineering, the majority of work uses a single or small set of bone models, with a single implant size, due to the constraints of time and data availability. Therefore, it has been infeasible to run a study incorporating natural inter-patient variability or the performance of smaller implants could not be meaningfully studied. In previous work a statistical model of the whole femur was used to generate large numbers of unique, realistic, FE-ready femur models describing both geometry and material properties. The current study demonstrates a methodology for virtually implanting and performing stress analysis of cemented femoral resurfacing components, with model specific sizing and orientation. Automated analysis of 400 generated femurs, in both implanted and intact configurations showed the strain changes induced by resurfacing. This produced a statistically meaningful number of results and allowed the examination of outliers. Results showed increased femoral neck strain changes potentially increasing the risk of neck fracture, associated with smaller, less dense femurs and smaller implant sizes; agreeing with clinical observations. The study demonstrates a methodology for more comprehensive analyses, based on populations rather than individuals.

Implicit numerical schemes for the stochastic Liouville equation in Langevin form.

We present and numerically test implicit as well as explicit numerical schemes for solving the Stochastic Liouville Equation in Langevin form. It is found that implicit schemes provide significant gain in robustness, for example, when nonsecular Hamiltonian terms cannot be ignored in electron and nuclear spin resonance. Implicit schemes open up several spectroscopic relaxation problems for direct interpretation using the Stochastic Liouville Equation. To illustrate the proposed numerical schemes, studies are presented for an electron paramagnetic resonance problem involving a coordinated copper complex and a fluorescence problem.

Sex differences in aromatase gene expression in the medaka brain.

The brain of teleost fish exhibits a significant degree of sexual plasticity, even in adulthood. This unique feature is almost certainly attributable to a teleost-specific sexual differentiation process of the brain, which remains largely unknown. To dissect the molecular basis of sexual differentiation of the teleost brain, we searched for genes differentially expressed between both sexes in the medaka brain. One gene identified in the screen, cyp19a1b, which encodes the steroidogenic enzyme aromatase, was selected for further analysis. As opposed to the situation in most vertebrates, medaka cyp19a1b is expressed at higher levels in the adult female brain than the male brain. The female-biased expression in the brain is consistent regardless of reproductive or diurnal cycle. Medaka cyp19a1b is expressed throughout the ventricular zones in wide areas of the brain, where, in most regions, females have a greater degree of expression compared to males, with the optic tectum exhibiting the most conspicuous predominance in females. Contrary to what is known in mammals, cyp19a1b expression exhibits neither a transient elevation nor a sex difference in medaka embryos. It is not until just before the onset of puberty that cyp19a1b expression in the medaka brain is sexually differentiated. Finally, cyp19a1b expression in the medaka brain is not under the direct control of sex chromosome genes but relies mostly, if not solely, on oestrogen derived from the gonad. These unique properties of aromatase expression in the brain probably contribute substantially to the less rigid sexual differentiation process, thus ensuring remarkable sexual plasticity in the teleost brain.

Analysis of sexually dimorphic expression of genes at early gonadogenesis of pejerrey Odontesthes bonariensis using a heterologous microarray.

The process of morphological development of a differentiated gonad from an undifferentiated primordium is a very important step of gonadogenesis. Studies on sexually dimorphic gene expression are important to increase our understanding of this process and to investigate how environmental factors such as temperature can regulate gonadal development. The aim of this study was to identify putative genes involved in sex differentiation in pejerrey (Odontesthes bonariensis) reared at male- and female-producing temperatures (MPT and FPT, respectively) using a microarray heterologous from the medaka (Oryzias latipes), a closely phylogenetic species. Genes related to numerous processes presented higher expression at MPT, including those involved in muscular contraction, metabolic pathways, developmental processes, and reproduction. Genes induced by FPT were classified under the gene ontology terms of response to stimulus, transport and proteolysis. From genes selected for validation, at MPT ndrg3 expression was observed in the somatic cells, whereas pen-2 was detected in germ cells in the caudal portion of the gonads, where no apoptotic signals were observed. Finally, hsp90 was highly expressed in somatic cells of the gonads at the FPT. The results suggest that the interplay of pro-apoptotic and anti-apoptotic genes is important during the masculinization process and for the prevention of sterility following exposure to warm temperatures.

Efficient computational method for assessing the effects of implant positioning in cementless total hip replacements.

The present work describes a statistical investigation into the effects of implant positioning on the initial stability of a cementless total hip replacement (THR). Mesh morphing was combined with design of computer experiments to automatically construct Finite Element (FE) meshes for a range of pre-defined femur-implant configurations and to predict implant micromotions under joint contact and muscle loading. Computed micromotions, in turn, are postprocessed using a Bayesian approach to: (a) compute the main effects of implant orientation angles, (b) predict the sensitivities of the considered implant performance metrics with respect to implant ante-retroversion, varus-valgus and antero-posterior orientation angles and (c) identify implant positions that maximise and minimise each metric. It is found that the percentage of implant area with micromotion greater than 50 µm, average and maximum micromotions are all more sensitive to antero-posterior orientation than ante-retroversion and varus-valgus orientation. Sensitivities, combined with the main effect results, suggest that bone is less likely to grow if the implant is increasingly moved from the neutral position towards the anterior part of the femur, where the highest micromotions occur. The computed implant best position leads to a percentage of implant area with micromotion greater than 50 µm of 1.14 when using this metric compared to 14.6 and 5.95 in the worst and neutrally positioned implant cases. In contrast, when the implant average/maximum micromotion is used to assess the THR performance, the implant best position corresponds to average/maximum micromotion of 9 µm/59 µm, compared to 20 µm/114 µm and 13 µm/71 µm in the worst and neutral positions, respectively. The proposed computational framework can be extended further to study the effects of uncertainty and variability in anatomy, bone mechanical properties, loading or bone-implant interface contact conditions.

Statistical modelling of the whole human femur incorporating geometric and material properties.

When analysing the performance of orthopaedic implants the vast majority of computational studies use either a single or limited number of bone models. The results are then extrapolated to the population as a whole, overlooking the inherent and large interpatient variability in bone quality and geometry. This paper describes the creation of a three dimensional, statistical, finite element analysis (FEA) ready model of the femur using principal component analysis. To achieve this a registration scheme based on elastic surface matching and a mesh morphing algorithm has been developed. This method is fully automated enabling registration and generation of high resolution models. The variation in both geometry and material properties was extracted from 46 computer tomography scans and captured by the statistical model. Analysis of mesh quality showed this was maintained throughout the model generation and sampling process. Reconstruction of the training femurs showed 35 eigenmodes were required for accurate reproduction. A set of unique, anatomically realistic femur models were generated using the statistical model, with a variation comparable to that seen in the population. This study illustrates a methodology with the potential to generate femur models incorporating material properties for large scale multi-femur finite element studies.