by Keyword: Modeling
Calvo, Mireia, González, Rubèn, Seijas, Núria, Vela, Emili, Hernández, Carme, Batiste, Guillem, Miralles, Felip, Roca, Josep, Cano, Isaac, Jané, Raimon, (2020). Health outcomes from home hospitalization: Multisource predictive modeling Journal of Medical Internet Research 22, (10), e21367
Background: Home hospitalization is widely accepted as a cost-effective alternative to conventional hospitalization for selected patients. A recent analysis of the home hospitalization and early discharge (HH/ED) program at Hospital Clínic de Barcelona over a 10-year period demonstrated high levels of acceptance by patients and professionals, as well as health value-based generation at the provider and health-system levels. However, health risk assessment was identified as an unmet need with the potential to enhance clinical decision making. Objective: The objective of this study is to generate and assess predictive models of mortality and in-hospital admission at entry and at HH/ED discharge. Methods: Predictive modeling of mortality and in-hospital admission was done in 2 different scenarios: at entry into the HH/ED program and at discharge, from January 2009 to December 2015. Multisource predictive variables, including standard clinical data, patients’ functional features, and population health risk assessment, were considered. Results: We studied 1925 HH/ED patients by applying a random forest classifier, as it showed the best performance. Average results of the area under the receiver operating characteristic curve (AUROC; sensitivity/specificity) for the prediction of mortality were 0.88 (0.81/0.76) and 0.89 (0.81/0.81) at entry and at home hospitalization discharge, respectively; the AUROC (sensitivity/specificity) values for in-hospital admission were 0.71 (0.67/0.64) and 0.70 (0.71/0.61) at entry and at home hospitalization discharge, respectively. Conclusions: The results showed potential for feeding clinical decision support systems aimed at supporting health professionals for inclusion of candidates into the HH/ED program, and have the capacity to guide transitions toward community-based care at HH discharge.
Keywords: Home hospitalization, Health risk assessment, Predictive modeling, Chronic care, Integrated care, Modeling, Hospitalization, Health risk, Prediction, Mortality, Clinical decision support
Solà-Soler, J., Giraldo, B. F., Jané, R., (2019). Linear mixed effects modelling of oxygen desaturation after sleep apneas and hypopneas: A pilot study Engineering in Medicine and Biology Society (EMBC) 41st Annual International Conference of the IEEE , IEEE (Berlín, Germany) , 5731-5734
Obstructive Sleep Apnea severity is commonly determined after a sleep polysomnographic study by the Apnea-Hypopnea Index (AHI). This index does not contain information about the duration of events, and weights apneas and hypopneas alike. Significant differences in disease severity have been reported in patients with the same AHI. The aim of this work was to study the effect of obstructive event type and duration on the subsequent oxygen desaturation (SaO2) by mixed-effects models. These models allow continuous and categorical independent variables and can model within-subject variability through random effects. The desaturation depth dSaO2, desaturation duration dtSaO2 and desaturation area dSaO2A were analyzed in the 2022 apneas and hypopneas of eight severe patients. A mixed-effects model was defined to account for the influence of event duration (AD), event type, and their interaction on SaO2 parameters. A two-step backward model reduction process was applied for random and fixed effects optimization. The optimum model obtained for dtSaO2 suggests an almost subject-independent proportion increase with AD, which did not significantly change in apneas as compared to hypopneas. The optimum model for dSaO2 reveals a significantly higher increase as a function of AD in apneas than hypopneas. Dependence of on event type and duration was different in every subject, and a subject-specific model could be obtained. The optimum model for SaO2A combines the effects of the other two. In conclusion, the proposed mixed-effects models for SaO2 parameters allow to study the effect of respiratory event duration and type, and to include repeated events within each subject. This simple model can be easily extended to include the contribution of other important factors such as patient severity, sleep stage, sleeping position, or the presence of arousals.
Keywords: Biological system modeling, Sleep apnea, Mathematical model, Indexes, Reduced order systems, Optimization
Magdaleno, Fernando, Schierwagen, R., Uschner, Frank E., Trebicka, J., (2018). “Tipping” extracellular matrix remodeling towards regression of liver fibrosis: novel concepts Minerva Gastroenterologica e Dietologica , 64, (1), 51-61
Fibrosis development was initially conceived as an incessant progressive condition. Nowadays, it has become evident that fibrotic tissue undergoes a continuous two-way process: fibrogenesis and fibrinolysis, characterizing the remodeling of extracellular matrix (ECM). However, in established fibrosis, this two-way process is tipped towards fibrogenesis and this leads to a self-perpetuating accumulation of ECM, a distinct metabolic unit, together with other cells and processes promoting fibrosis deposition. Several mechanisms promote fibrosis regression, such as degradation of ECM, infiltration of restorative macrophages, prevention of the epithelial-mesenchymal transition of hepatocytes, restoration of the liver sinusoidal endothelial cells’ differentiation phenotype, and reversion to quiescence, apoptosis and senescence of hepatic stellate cells (HSC). Hence, fibrosis is the result of an unbalanced two-way process of matrix remodeling. At the late stage of the disease, antifibrotic interventions could become necessary to reverse self-perpetuating fibrogenesis and accelerate regression of fibrosis even if cause and cofactors of hepatic injury have been eliminated. This review outlines some of the important mechanisms leading towards regression of liver fibrosis.
Keywords: Hepatic stellate cells, Extracellular matrix, remodeling, Rho-associated kinases, Janus kinases
González-García, C., Cantini, M., Ballester-Beltrán, J., Altankov, G., Salmerón-Sánchez, M., (2018). The strength of the protein-material interaction determines cell fate Acta Biomaterialia 77, 74-84
Extracellular matrix (ECM) proteins are key mediators of cell/material interactions. The surface density and conformation of these proteins adsorbed on the material surface influence cell adhesion and the cellular response. We have previously shown that subtle variations in surface chemistry lead to drastic changes in the conformation of adsorbed fibronectin (FN). On poly(ethyl acrylate) (PEA), FN unfolds and displays domains for cell adhesion and FN-FN interaction, whereas on poly(methyl acrylate) (PMA) â€“ with only one methyl group less â€“ FN remains globular as it is in solution. The effect of the strength of the protein/material interaction in cell response, and its relation to protein density and conformation, has received limited attention so far. In this work, we used FN-functionalized AFM cantilevers to evaluate, via force spectroscopy, the strength of interaction between fibronectin and the underlying polymer which controls FN conformation (PEA and PMA). We found that the strength of FN/PEA interaction is significantly higher than FN/PMA, which limits the mobility of FN layer on PEA, reduces the ability of cells to mechanically reorganize FN and then leads to enhanced proteolysis and degradation of the surrounding matrix with compromised cell viability. By contrast, both PEA and PMA support cell adhesion when FN density is increased and also in the presence of serum or other serum proteins, including vitronectin (VN) and bovine serum albumin (BSA), which provide a higher degree of mobility to the matrix. Statement of Significance: The identification of parameters influencing cell response is of paramount importance for the design of biomaterials that will act as synthetic scaffolds for cells to anchor, grow and, eventually, become specialised tissues. Cells interact with materials through an intermediate layer of proteins adsorbed on the material surface. It is known that the density and conformation of these proteins determine cell behaviour. Here we show that the strength of protein/material interactions, which has received very limited attention so far, is key to understand the cellular response to biomaterials. Very strong protein/material interactions reduce the ability of cells to mechanically reorganize proteins at the material interface which results in enhanced matrix degradation, leading ultimately to compromised cell viability.
Keywords: Fibronectin adsorption, Fibronectin remodeling, Protein mobility, Protein-material interaction strength
Torras, N., García-Díaz, M., Fernández-Majada, V., Martínez, Elena, (2018). Mimicking epithelial tissues in three-dimensional cell culture models Frontiers in Bioengineering and Biotechnology 6, Article 197
Epithelial tissues are composed of layers of tightly connected cells shaped into complex three-dimensional (3D) structures such as cysts, tubules, or invaginations. These complex 3D structures are important for organ-specific functions and often create biochemical gradients that guide cell positioning and compartmentalization within the organ. One of the main functions of epithelia is to act as physical barriers that protect the underlying tissues from external insults. In vitro, epithelial barriers are usually mimicked by oversimplified models based on cell lines grown as monolayers on flat surfaces. While useful to answer certain questions, these models cannot fully capture the in vivo organ physiology and often yield poor predictions. In order to progress further in basic and translational research, disease modeling, drug discovery, and regenerative medicine, it is essential to advance the development of new in vitro predictive models of epithelial tissues that are capable of representing the in vivo-like structures and organ functionality more accurately. Here, we review current strategies for obtaining biomimetic systems in the form of advanced in vitro models that allow for more reliable and safer preclinical tests. The current state of the art and potential applications of self-organized cell-based systems, organ-on-a-chip devices that incorporate sensors and monitoring capabilities, as well as microfabrication techniques including bioprinting and photolithography, are discussed. These techniques could be combined to help provide highly predictive drug tests for patient-specific conditions in the near future.
Keywords: 3D cell culture models, Biofabrication, Disease modeling, Drug screening, Epithelial barriers, Microengineered tissues, Organ-on-a-chip, Organoids
Garreta, E., González, F., Montserrat, N., (2018). Studying kidney disease using tissue and genome engineering in human pluripotent stem cells Nephron 138, 48-59
Kidney morphogenesis and patterning have been extensively studied in animal models such as the mouse and zebrafish. These seminal studies have been key to define the molecular mechanisms underlying this complex multistep process. Based on this knowledge, the last 3 years have witnessed the development of a cohort of protocols allowing efficient differentiation of human pluripotent stem cells (hPSCs) towards defined kidney progenitor populations using two-dimensional (2D) culture systems or through generating organoids. Kidney organoids are three-dimensional (3D) kidney-like tissues, which are able to partially recapitulate kidney structure and function in vitro. The current possibility to combine state-of-the art tissue engineering with clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated systems 9 (Cas9)-mediated genome engineering provides an unprecedented opportunity for studying kidney disease with hPSCs. Recently, hPSCs with genetic mutations introduced through CRISPR/Cas9-mediated genome engineering have shown to produce kidney organoids able to recapitulate phenotypes of polycystic kidney disease and glomerulopathies. This mini review provides an overview of the most recent advances in differentiation of hPSCs into kidney lineages, and the latest implementation of the CRISPR/Cas9 technology in the organoid setting, as promising platforms to study human kidney development and disease.
Keywords: Clustered regularly interspaced short palindromic repeats/CRISPR-associated systems 9, Disease modeling, Gene editing, Human pluripotent stem cells, Kidney genetics, Tissue engineering
Garreta, Elena, Marco, Andrés, Eguizábal, Cristina, Tarantino, Carolina, Samitier, Mireia, Badiola, Maider, Gutiérrez, Joaquín, Samitier, Josep, Montserrat, Nuria, (2017). Pluripotent stem cells and skeletal muscle differentiation: Challenges and immediate applications The Plasticity of Skeletal Muscle: From Molecular Mechanism to Clinical Applications (ed. Sakuma, Kunihiro), Springer Singapore (Singapore, Singapore) 2018, 1-35
Recent advances in the generation of skeletal muscle derivatives from pluripotent stem cells (PSCs) provide innovative tools for muscle development, disease modeling, and cell replacement therapies. Here, we revise major relevant findings that have contributed to these advances in the field, by the revision of how early findings using mouse embryonic stem cells (ESCs) set the bases for the derivation of skeletal muscle cells from human pluripotent stem cells (hPSCs) and patient-derived human-induced pluripotent stem cells (hiPSCs) to the use of genome editing platforms allowing for disease modeling in the petri dish.
Keywords: Pluripotent stem cells, Differentiation, Genome editing, Disease modeling
González, F., (2016). CRISPR/Cas9 genome editing in human pluripotent stem cells: Harnessing human genetics in a dish Developmental Dynamics , 245, (7), 788-806
Abstract: Because of their extraordinary differentiation potential, human pluripotent stem cells (hPSCs) can differentiate into virtually any cell type of the human body, providing a powerful platform not only for generating relevant cell types useful for cell replacement therapies, but also for modeling human development and disease. Expanding this potential, structures resembling human organs, termed organoids, have been recently obtained from hPSCs through tissue engineering. Organoids exhibit multiple cell types self-organizing into structures recapitulating in part the physiology and the cellular interactions observed in the organ in vivo, offering unprecedented opportunities for human disease modeling. To fulfill this promise, tissue engineering in hPSCs needs to be supported by robust and scalable genome editing technologies. With the advent of the CRISPR/Cas9 technology, manipulating the genome of hPSCs has now become an easy task, allowing modifying their genome with superior precision, speed, and throughput. Here we review current and potential applications of the CRISPR/Cas9 technology in hPSCs and how they contribute to establish hPSCs as a model of choice for studying human genetics.
Keywords: CRISPR/Cas9, Disease modeling, Human genetics, Human pluripotent stem cells, Tissue and genome engineering
Coelho, N. M., Llopis-Hernández, V., Salmerón-Sánchez, M., Altankov, G., (2016). Dynamic reorganization and enzymatic remodeling of type IV collagen at cell–biomaterial interface Advances in Protein Chemistry and Structural Biology (ed. Christo, Z. Christov), Academic Press (San Diego, USA) 105, 81-104
Abstract Vascular basement membrane remodeling involves assembly and degradation of its main constituents, type IV collagen (Col IV) and laminin, which is critical during development, angiogenesis, and tissue repair. Remodeling can also occur at cellâ€“biomaterials interface altering significantly the biocompatibility of implants. Here we describe the fate of adsorbed Col IV in contact with endothelial cells adhering on positively charged NH2 or hydrophobic CH3 substrata, both based on self-assembly monolayers (SAMs) and studied alone or mixed in different proportions. AFM studies revealed distinct pattern of adsorbed Col IV, varying from single molecular deposition on pure NH2 to network-like assembly on mixed SAMs, turning to big globular aggregates on bare CH3. Human umbilical endothelial cells (HUVECs) interact better with Col IV adsorbed as single molecules on NH2 surface and readily rearrange it in fibril-like pattern that coincide with secreted fibronectin fibrils. The cells show flattened morphology and well-developed focal adhesion complexes that are rich on phosphorylated FAK while expressing markedly low pericellular proteolytic activity. Conversely, on hydrophobic CH3 substrata HUVECs showed abrogated spreading and FAK phosphorylation, combined with less reorganization of the aggregated Col IV and significantly increased proteolytic activity. The later involves both MMP-2 and MMP-9, as measured by zymography and FITC-Col IV release. The mixed SAMs support intermediate remodeling activity. Taken together these results show that chemical functionalization combined with Col IV preadsorption provides a tool for guiding the endothelial cells behavior and pericellular proteolytic activity, events that strongly affect the fate of cardiovascular implants.
Keywords: Type IV collagen, Adsorption, Remodeling, Pericellular proteolysis, Reorganization, Substratum chemistry, CH3 and NH2 groups, Self-assembly monolayers
Pérez-Amodio, Soledad, Engel, Elisabeth, (2014). Bone biology and Regeneration Bio-Ceramics with Clinical Applications (ed. Vallet-Regí, M.), John Wiley & Sons, Ltd (Chichester, UK) , 315-342
Each bone of the skeleton constantly undergoes modeling during life to help it to adapt to changing biomechanical forces as well as remodeling to remove old bone and replace it with new, mechanically stronger bone to help preserve bone strength. Bone remodeling involves the removal of mineralized bone by osteoclasts, followed by the formation of bone matrix through the osteoblasts that subsequently become mineralized. All these assets make bone a suitable model for regeneration. Bone tissue can be grossly divided into inorganic mineral material (mostly HA), and organic material from cells and the extracellular matrix. This chapter outlines some of the bone diseases such as osteoporosis and Paget's disease. Bone can be considered as a biphasic composite material, with two phases: one the mineral and the other collagen. This combination confers better mechanical properties on the tissue than each component itself.
Keywords: Bone biology, Bone cells, Bone diseases, Bone extracellular matrix, Bone mechanics, Bone remodeling, Bone tissue regeneration, Skeleton
Barreto, S., Clausen, C. H., Perrault, C. M., Fletcher, D. A., Lacroix, D., (2013). A multi-structural single cell model of force-induced interactions of cytoskeletal components Biomaterials 34, (26), 6119-6126
Several computational models based on experimental techniques and theories have been proposed to describe cytoskeleton (CSK) mechanics. Tensegrity is a prominent model for force generation, but it cannot predict mechanics of individual CSK components, nor explain the discrepancies from the different single cell stimulating techniques studies combined with cytoskeleton-disruptors. A new numerical concept that defines a multi-structural 3D finite element (FE) model of a single-adherent cell is proposed to investigate the biophysical and biochemical differences of the mechanical role of each cytoskeleton component under loading. The model includes prestressed actin bundles and microtubule within cytoplasm and nucleus surrounded by the actin cortex. We performed numerical simulations of atomic force microscopy (AFM) experiments by subjecting the cell model to compressive loads. The numerical role of the CSK components was corroborated with AFM force measurements on U2OS-osteosarcoma cells and NIH-3T3 fibroblasts exposed to different cytoskeleton-disrupting drugs. Computational simulation showed that actin cortex and microtubules are the major components targeted in resisting compression. This is a new numerical tool that explains the specific role of the cortex and overcomes the difficulty of isolating this component from other networks invitro. This illustrates that a combination ofcytoskeletal structures with their own properties is necessary for a complete description of cellular mechanics.
Keywords: Actin bundles, Actin cortex, AFM (atomic force microscopy), Cytoskeleton, Finite element modeling, Microtubules
Giraldo, B. F., Chaparro, J. A., Caminal, P., Benito, S., (2013). Characterization of the respiratory pattern variability of patients with different pressure support levels Engineering in Medicine and Biology Society (EMBC) 35th Annual International Conference of the IEEE , IEEE (Osaka, Japan) , 3849-3852
One of the most challenging problems in intensive care is still the process of discontinuing mechanical ventilation, called weaning process. Both an unnecessary delay in the discontinuation process and a weaning trial that is undertaken too early are undesirable. In this study, we analyzed respiratory pattern variability using the respiratory volume signal of patients submitted to two different levels of pressure support ventilation (PSV), prior to withdrawal of the mechanical ventilation. In order to characterize the respiratory pattern, we analyzed the following time series: inspiratory time, expiratory time, breath duration, tidal volume, fractional inspiratory time, mean inspiratory flow and rapid shallow breathing. Several autoregressive modeling techniques were considered: autoregressive models (AR), autoregressive moving average models (ARMA), and autoregressive models with exogenous input (ARX). The following classification methods were used: logistic regression (LR), linear discriminant analysis (LDA) and support vector machines (SVM). 20 patients on weaning trials from mechanical ventilation were analyzed. The patients, submitted to two different levels of PSV, were classified as low PSV and high PSV. The variability of the respiratory patterns of these patients were analyzed. The most relevant parameters were extracted using the classifiers methods. The best results were obtained with the interquartile range and the final prediction errors of AR, ARMA and ARX models. An accuracy of 95% (93% sensitivity and 90% specificity) was obtained when the interquartile range of the expiratory time and the breath duration time series were used a LDA model. All classifiers showed a good compromise between sensitivity and specificity.
Keywords: autoregressive moving average processes, feature extraction, medical signal processing, patient care, pneumodynamics, signal classification, support vector machines, time series, ARX, autoregressive modeling techniques, autoregressive models with exogenous input, autoregressive moving average model, breath duration time series, classification method, classifier method, discontinuing mechanical ventilation, expiratory time, feature extraction, final prediction errors, fractional inspiratory time, intensive care, interquartile range, linear discriminant analysis, logistic regression analysis, mean inspiratory flow, patient respiratory volume signal, pressure support level, pressure support ventilation, rapid shallow breathing, respiratory pattern variability characterization, support vector machines, tidal volume, weaning trial, Analytical models, Autoregressive processes, Biological system modeling, Estimation, Support vector machines, Time series analysis, Ventilation
Jané, R., Lazaro, J., Ruiz, P., Gil, E., Navajas, D., Farre, R., Laguna, P., (2013). Obstructive Sleep Apnea in a rat model: Effects of anesthesia on autonomic evaluation from heart rate variability measures CinC 2013 Computing in Cardiology Conference (CinC) , IEEE (Zaragoza, Spain) , 1011-1014
Rat model of Obstructive Sleep Apnea (OSA) is a realistic approach for studying physiological mechanisms involved in sleep. Rats are usually anesthetized and autonomic nervous system (ANS) could be blocked. This study aimed to assess the effect of anesthesia on ANS activity during OSA episodes. Seven male Sprague-Dawley rats were anesthetized intraperitoneally with urethane (1g/kg). The experiments were conducted applying airway obstructions, simulating 15s-apnea episodes for 15 minutes. Five signals were acquired: respiratory pressure and flow, SaO2, ECG and photoplethysmography (PPG). In total, 210 apnea episodes were studied. Normalized power spectrum of Pulse Rate Variability (PRV) was analyzed in the Low Frequency (LF) and High Frequency (HF) bands, for each episode in consecutive 15s intervals (before, during and after the apnea). All episodes showed changes in respiratory flow and SaO2 signal. Conversely, decreases in the amplitude fluctuations of PPG (DAP) were not observed. Normalized LF presented extremely low values during breathing (median=7,67%), suggesting inhibition of sympathetic system due to anesthetic effect. Subtle increases of LF were observed during apnea. HRV and PPG analysis during apnea could be an indirect tool to assess the effect and deep of anesthesia.
Keywords: electrocardiography, fluctuations, medical disorders, medical signal detection, medical signal processing, neurophysiology, photoplethysmography, pneumodynamics, sleep, ECG, SaO2 flow, SaO2 signal, airway obstructions, amplitude fluctuations, anesthesia effects, anesthetized nervous system, autonomic evaluation, autonomic nervous system, breathing, heart rate variability, high-frequency bands, low-frequency bands, male Sprague-Dawley rats, normalized power spectrum, obstructive sleep apnea, photoplethysmography, physiological mechanisms, pulse rate variability, rat model, respiratory flow, respiratory pressure, signal acquisition, sympathetic system inhibition, time 15 min, time 15 s, Abstracts, Atmospheric modeling, Computational modeling, Electrocardiography, Rats, Resonant frequency
Sánchez-Danés, A., Richaud-Patin, Y., Carballo-Carbajal, I., Jiménez-Delgado, S., Caig, C., Mora, S., Di Guglielmo, C., Ezquerra, M., Patel, B., Giralt, A., Canals, J. M., Memo, M., Alberch, J., López-Barneo, J., Vila, M., Cuervo, A. M., Tolosa, E., Consiglio, A., Raya, A., (2012). Disease-specific phenotypes in dopamine neurons from human iPS-based models of genetic and sporadic Parkinson's disease EMBO Molecular Medicine 4, (5), 380-395
Induced pluripotent stem cells (iPSC) offer an unprecedented opportunity to model human disease in relevant cell types, but it is unclear whether they could successfully model age-related diseases such as Parkinson's disease (PD). Here, we generated iPSC lines from seven patients with idiopathic PD (ID-PD), four patients with familial PD associated to the G2019S mutation in the Leucine-Rich Repeat Kinase 2 (LRRK2) gene (LRRK2-PD) and four age- and sex-matched healthy individuals (Ctrl). Over long-time culture, dopaminergic neurons (DAn) differentiated from either ID-PD- or LRRK2-PD-iPSC showed morphological alterations, including reduced numbers of neurites and neurite arborization, as well as accumulation of autophagic vacuoles, which were not evident in DAn differentiated from Ctrl-iPSC. Further induction of autophagy and/or inhibition of lysosomal proteolysis greatly exacerbated the DAn morphological alterations, indicating autophagic compromise in DAn from ID-PD- and LRRK2-PD-iPSC, which we demonstrate occurs at the level of autophagosome clearance. Our study provides an iPSC-based in vitro model that captures the patients' genetic complexity and allows investigation of the pathogenesis of both sporadic and familial PD cases in a disease-relevant cell type.
Keywords: Autophagy, Disease modeling, LRRK2 mutation, Neurodegeneration, Pluripotent stem cells
Giraldo, B.F., Gaspar, B.W., Caminal, P., Benito, S., (2012). Analysis of roots in ARMA model for the classification of patients on weaning trials Engineering in Medicine and Biology Society (EMBC) 34th Annual International Conference of the IEEE , IEEE (San Diego, USA) , 698-701
One objective of mechanical ventilation is the recovery of spontaneous breathing as soon as possible. Remove the mechanical ventilation is sometimes more difficult that maintain it. This paper proposes the study of respiratory flow signal of patients on weaning trials process by autoregressive moving average model (ARMA), through the location of poles and zeros of the model. A total of 151 patients under extubation process (T-tube test) were analyzed: 91 patients with successful weaning (GS), 39 patients that failed to maintain spontaneous breathing and were reconnected (GF), and 21 patients extubated after the test but before 48 hours were reintubated (GR). The optimal model was obtained with order 8, and statistical significant differences were obtained considering the values of angles of the first four poles and the first zero. The best classification was obtained between GF and GR, with an accuracy of 75.3% on the mean value of the angle of the first pole.
Keywords: Analytical models, Biological system modeling, Computational modeling, Estimation, Hospitals, Poles and zeros, Ventilation, Autoregressive moving average processes, Patient care, Patient monitoring, Pneumodynamics, Poles and zeros, Ventilation, ARMA model, T-tube test, Autoregressive moving average model, Extubation process, Mechanical ventilation, Optimal model, Patient classification, Respiratory flow signal, Roots, Spontaneous breathing, Weaning trials
Sandino, C., Checa, S., Prendergast, P. J., Lacroix, D., (2010). Simulation of angiogenesis and cell differentiation in a CaP scaffold subjected to compressive strains using a lattice modeling approach Biomaterials 31, (8), 2446-2452
Mechanical stimuli are one of the factors that influence tissue differentiation. In the development of biomaterials for bone tissue engineering, mechanical stimuli and formation of a vascular network that transport oxygen to cells within the pores of the scaffolds are essential. Angiogenesis and cell differentiation have been simulated in scaffolds of regular porosity; however, the dynamics of differentiation can be different when the porosity is not uniform. The objective of this study was to investigate the effect of the mechanical stimuli and the capillary network formation on cell differentiation within a scaffold of irregular morphology. A porous scaffold of calcium phosphate based glass was used. The pores and the solid phase were discretized using micro computed tomography images. Cell activity was simulated within the interconnected pore domain of the scaffold using a lattice modeling approach. Compressive strains of 0.5 and 1% of total deformation were applied and two cases of mesenchymal stem cells initialization (in vitro seeding and in vivo) were simulated. Similar capillary networks were formed independently of the cell initialization mode and the magnitude of the mechanical strain applied. Most of vessels grew in the pores at the periphery of the scaffolds and were blocked by the walls of the scaffold. When 0.5% of strain was applied, 70% of the pore volume was affected by mechano-regulatory stimuli corresponding to bone formation; however, because of the lack of oxygen, only 40% of the volume was filled with osteoblasts. 40% of volume was filled with chondrocytes and 3% with fibroblasts. When the mechanical strain was increased to 1%, 11% of the pore volume was filled with osteoblasts, 59% with chondrocytes, and 8% with fibroblasts. This study has shown the dynamics of the correlation between mechanical load, angiogenesis and tissue differentiation within a scaffold with irregular morphology.
Keywords: Tissue engineering, Calcium phosphates, Mechanoregulation, Micro computer tomography, Finite element modeling
Park, C. Y., Tambe, D., Alencar, A. M., Trepat, X., Zhou, E. H., Millet, E., Butler, J. P., Fredberg, J. J., (2010). Mapping the cytoskeletal prestress The American Journal of Physiology - Cell Physiology , 298, (5), C1245-C1252
Park CY, Tambe D, Alencar AM, Trepat X, Zhou EH, Millet E, Butler JP, Fredberg JJ. Mapping the cytoskeletal prestress. Am J Physiol Cell Physiol 298: C1245-C1252, 2010. First published February 17, 2010; doi: 10.1152/ajpcell.00417.2009.-Cell mechanical properties on a whole cell basis have been widely studied, whereas local intracellular variations have been less well characterized and are poorly understood. To fill this gap, here we provide detailed intracellular maps of regional cytoskeleton (CSK) stiffness, loss tangent, and rate of structural rearrangements, as well as their relationships to the underlying regional F-actin density and the local cytoskeletal prestress. In the human airway smooth muscle cell, we used micropatterning to minimize geometric variation. We measured the local cell stiffness and loss tangent with optical magnetic twisting cytometry and the local rate of CSK remodeling with spontaneous displacements of a CSK-bound bead. We also measured traction distributions with traction microscopy and cell geometry with atomic force microscopy. On the basis of these experimental observations, we used finite element methods to map for the first time the regional distribution of intracellular prestress. Compared with the cell center or edges, cell corners were systematically stiffer and more fluidlike and supported higher traction forces, and at the same time had slower remodeling dynamics. Local remodeling dynamics had a close inverse relationship with local cell stiffness. The principal finding, however, is that systematic regional variations of CSK stiffness correlated only poorly with regional F-actin density but strongly and linearly with the regional prestress. Taken together, these findings in the intact cell comprise the most comprehensive characterization to date of regional variations of cytoskeletal mechanical properties and their determinants.
Keywords: Cell mechanics, Stiffness, Remodeling, Heterogeneity
Garde, A., Sörnmo, L., Jané, R., Giraldo, B., (2010). Breathing pattern characterization in chronic heart failure patients using the respiratory flow signal Annals of Biomedical Engineering , 38, (12), 3572-3580
This study proposes a method for the characterization of respiratory patterns in chronic heart failure (CHF) patients with periodic breathing (PB) and nonperiodic breathing (nPB), using the flow signal. Autoregressive modeling of the envelope of the respiratory flow signal is the starting point for the pattern characterization. Spectral parameters extracted from the discriminant frequency band (DB) are used to characterize the respiratory patterns. For each classification problem, the most discriminant parameter subset is selected using the leave-one-out cross-validation technique. The power in the right DB provides an accuracy of 84.6% when classifying PB vs. nPB patterns in CHF patients, whereas the power of the DB provides an accuracy of 85.5% when classifying the whole group of CHF patients vs. healthy subjects, and 85.2% when classifying nPB patients vs. healthy subjects.
Keywords: Chronic heart failure, AR modeling, Respiratory pattern, Discriminant band, Periodic and nonperiodic breathing
Garde, A., Sörnmo, L., Jané, R., Giraldo, B. F., (2010). Correntropy-based spectral characterization of respiratory patterns in patients with chronic heart failure IEEE Transactions on Biomedical Engineering 57, (8), 1964-1972
A correntropy-based technique is proposed for the characterization and classification of respiratory flow signals in chronic heart failure (CHF) patients with periodic or nonperiodic breathing (PB or nPB, respectively) and healthy subjects. The correntropy is a recently introduced, generalized correlation measure whose properties lend themselves to the definition of a correntropy-based spectral density (CSD). Using this technique, both respiratory and modulation frequencies can be reliably detected at their original positions in the spectrum without prior demodulation of the flow signal. Single-parameter classification of respiratory patterns is investigated for three different parameters extracted from the respiratory and modulation frequency bands of the CSD, and one parameter defined by the correntropy mean. The results show that the ratio between the powers in the modulation and respiratory frequency bands provides the best result when classifying CHF patients with either PB or nPB, yielding an accuracy of 88.9%. The correntropy mean offers excellent performance when classifying CHF patients versus healthy subjects, yielding an accuracy of 95.2% and discriminating nPB patients from healthy subjects with an accuracy of 94.4%.
Keywords: Autoregressive (AR) modeling, Chronic heart failure (CHF), Correntropy spectral density (CSD), Linear classification, Periodic breathing (PB)
Prendergast, P. J., Checa, S., Lacroix, D., (2010). Computational models of tissue differentiation Computational Modeling in Biomechanics (ed. Suvranu De, Farshid Guilak, Mohammad R. K. Mofrad), Springer-Verlag Berlin (Berlin) 3, 353-372
Readers of this chapter will learn about our approach to computer simulation of tissue differentiation in response to mechanical forces. It involves defining algorithms for mechanoregulation of each of following cell activities: proliferation, apoptosis, migration, and differentiation using a stimulus based on a combination of strain and fluid flow (Prendergast et al., J. Biomech., 1997) - algorithms are based on a lattice-modelling which also facilitates building algorithms for complex processes such as angiogenesis. The algorithms are designed to be collaboratable individually. They can be combined to create a computational simulation method for tissue differentiation, using finite element analysis to compute the mechanical stimuli in even quite complex biomechanical environments. Examples are presented of the simulation method in use.
Keywords: Mechanobiology, Lattice modeling, Differentiation, Tissue engineering, Finite element modeling, Scaffolds
Udina, S., Carmona, M., Carles, G., Santander, J., Fonseca, L., Marco, S., (2008). A micromachined thermoelectric sensor for natural gas analysis: Thermal model and experimental results Sensors and Actuators B: Chemical 134, (2), 551-558
Natural gas may show significant changes in its chemical composition depending on its origin. Typically, natural gas analysis is carried out using process gas chromatography. However, other methods based on the evaluation of physical properties have recently been reported. Thermal conductivity sensors are currently used in the analysis of binary mixtures of dissimilar gases. In contrast, natural gas is a complex mixture of mainly hydrocarbons, plus other residual gases as carbon dioxide and nitrogen. In this work, the response of a micromachined sensor integrating a heater and a thermopile is studied, regarding its potential use for natural gas analysis. A finite element thermal model of the device is described, and thermal operation simulations as well as a preliminary sensitivity analysis are reported. Experimental data has been collected and compared with simulated data, showing very good agreement. Results show that small variations in the gas mixture composition can be clearly detected. The sensor appears as a good candidate to be included in low-cost natural gas property analysis and quality control systems.
Keywords: Natural gas, Thermopile, MEMS, Thermal conductivity, Modeling, FEM simulation