Publications

Micro/nanomotors (MNMs) have evolved from single self-propelled entities to versatile systems capable of performing one or multiple biomedical tasks. When single MNMs self-assemble into coordinated swarms, either under external control or triggered by chemical reactions, they offer advantages that individual MNMs cannot achieve. These benefits include intelligent multitasking and adaptability to changes in the surrounding environment. Here, we provide our perspective on the evolution of MNMs, beginning with the development of enzymatic MNMs since the first theoretical model was proposed in 2005. These enzymatic MNMs hold immense promise in biomedicine due to their advantages in biocompatibility and fuel availability. Subsequently, we introduce the design and application of single motors in biomedicine, followed by the control of MNM swarms and their biomedical applications. In the end, we propose viable solutions for advancing the development of MNM swarms and anticipate valuable insights into the creation of more intelligent and controllable MNM swarms for biomedical applications.; Micro/nanomotor swarms propelled by diverse mechanisms.

JTD Keywords: Active particles, Actuation, Behaviors, Biocompatibility, Biomedical applications, Coordination reactions, Design and application, Diffusion, External control, Medical applications, Micromotors, Motion, Nanomotors, Powered nanomotors, Propulsion, Self-assemble, Surrounding environment, Theoretical modeling, Versatile system, Viable solutions

Duchenne muscular dystrophy (DMD) is the most prevalent neuromuscular disease diagnosed in childhood. It is a progressive and wasting disease, characterized by a degeneration of skeletal and cardiac muscles caused by the lack of dystrophin protein. The absence of this crucial structural protein leads to sarcolemmal fragility, resulting in muscle fiber damage during contraction. Despite ongoing efforts, there is no cure available for DMD patients. One of the primary challenges is the limited efficacy of current preclinical tools, which fail in modeling the biological complexity of the disease. Human-based three-dimensional (3D) cell culture methods appear as a novel approach to accelerate preclinical research by enhancing the reproduction of pathophysiological processes in skeletal muscle. In this work, we developed a patient-derived functional 3D skeletal muscle model of DMD that reproduces the sarcolemmal damage found in the native DMD muscle. These bioengineered skeletal muscle tissues exhibit contractile functionality, as they responded to electrical pulse stimulation. Sustained contractile regimes induced the loss of myotube integrity, mirroring the pathological myotube breakdown inherent in DMD due to sarcolemmal instability. Moreover, damaged DMD tissues showed disease functional phenotypes, such as tetanic fatigue. We also evaluated the therapeutic effect of utrophin upregulator drug candidates on the functionality of the skeletal muscle tissues, thus providing deeper insight into the real impact of these treatments. Overall, our findings underscore the potential of bioengineered 3D skeletal muscle technology to advance DMD research and facilitate the development of novel therapies for DMD and related neuromuscular disorders.

JTD Keywords: 3d cell culture, disease modeling, drug testing, duchenne muscular dystrophy, sarcolemmal damage, skeletal muscle, 3d cell culture, Animal-models, Disease modeling, Dmso, Drug testing, Duchenne muscular dystrophy, Gene, Humans, Image, Mechanisms, Muscle fibers, skeletal, Muscle, skeletal, Muscular dystrophy, duchenne, Myocardium, Sarcolemmal damage, Skeletal muscle, Tissue engineering, Utrophin

JTD Keywords: 3d cancer modeling, 3d printing, Decellularization, Mammary gland

Gradients of signaling pathways within the intestinal stem cell (ISC) niche are instrumental for cellular compartmentalization and tissue function, yet how are they sensed by the epithelium is still not fully understood. Here a new in vitro model of the small intestine based on primary epithelial cells (i), apically accessible (ii), with native tissue mechanical properties and controlled mesh size (iii), 3D villus-like architecture (iv), and precisely controlled biomolecular gradients of the ISC niche (v) is presented. Biochemical gradients are formed through hydrogel-based scaffolds by free diffusion from a source to a sink chamber. To confirm the establishment of spatiotemporally controlled gradients, light-sheet fluorescence microscopy and in-silico modeling are employed. The ISC niche biochemical gradients coming from the stroma and applied along the villus axis lead to the in vivo-like compartmentalization of the proliferative and differentiated cells, while changing the composition and concentration of the biochemical factors affects the cellular organization along the villus axis. This novel 3D in vitro intestinal model derived from organoids recapitulates both the villus-like architecture and the gradients of ISC biochemical factors, thus opening the possibility to study in vitro the nature of such gradients and the resulting cellular response.© 2022 The Authors. Advanced Healthcare Materials published by Wiley-VCH GmbH.

JTD Keywords: 3d architectures, biomolecular gradients, colon, crypt, engineering organoids, hydrogels, identification, in silico modeling, intestinal stem cell niches, light sheet fluorescence microscopy, niche, permeability, photolithography, regeneration, villus, wnt, 3d architectures, Biomolecular gradients, Engineering organoids, In silico modeling, Intestinal stem cell niches, Light sheet fluorescence microscopy, Photolithography, Stem-cell

The mechanical signals sensed by the alveolar cells through the changes in the local matrix stiffness of the extracellular matrix (ECM) are determinant for regulating cellular functions. Therefore, the study of the mechanical response of lung tissue becomes a fundamental aspect in order to further understand the mechanosensing signals perceived by the cells in the alveoli. This study is focused on the development of a finite element (FE) model of a decellularized rat lung tissue strip, which reproduces accurately the mechanical behaviour observed in the experiments by means of a tensile test. For simulating the complex structure of the lung parenchyma, which consists of a heterogeneous and non-uniform network of thin-walled alveoli, a 3D model based on a Voronoi tessellation is developed. This Voronoi-based model is considered very suitable for recreating the geometry of cellular materials with randomly distributed polygons like in the lung tissue. The material model used in the mechanical simulations of the lung tissue was characterized experimentally by means of AFM tests in order to evaluate the lung tissue stiffness on the micro scale. Thus, in this study, the micro (AFM test) and the macro scale (tensile test) mechanical behaviour are linked through the mechanical simulation with the 3D FE model based on Voronoi tessellation. Finally, a micro-mechanical FE-based model is generated from the Voronoi diagram for studying the stiffness sensed by the alveolar cells in function of two independent factors: the stretch level of the lung tissue and the geometrical position of the cells on the extracellular matrix (ECM), distinguishing between pneumocyte type I and type II. We conclude that the position of the cells within the alveolus has a great influence on the local stiffness perceived by the cells. Alveolar cells located at the corners of the alveolus, mainly type II pneumocytes, perceive a much higher stiffness than those located in the flat areas of the alveoli, which correspond to type I pneumocytes. However, the high stiffness, due to the macroscopic lung tissue stretch, affects both cells in a very similar form, thus no significant differences between them have been observed. © 2021 The Authors

JTD Keywords: rat, scaffolds, stiffness, Afm, Animal cell, Animal experiment, Animal model, Animal tissue, Article, Biological organs, Cell function, Cells, Computational geometry, Cytology, Extracellular matrices, Extracellular matrix, Extracellular-matrix, Geometry, High stiffness, Human, Lung alveolus cell type 1, Lung alveolus cell type 2, Lung parenchyma, Lung tissue, Male, Mechanical behavior, Mechanical modeling, Mechanical simulations, Mechanosensing, Model-based opc, Nonhuman, Physical model, Rat, Rigidity, Stiffness, Stiffness matrix, Tensile testing, Thin walled structures, Three dimensional finite element analysis, Tissue, Type ii, Voronoi tessellations

Drug development is an ever-growing field, increasingly requesting reliable in vitro tools to speed up early screening phases, reducing the need for animal experiments. In oral delivery, understanding the absorption pattern of a new drug in the small intestine is paramount. Classical two-dimensional (2D) in vitro models are generally too simplistic and do not accurately represent native tissues. The main goal of this work was to develop an advanced three-dimensional (3D) in vitro intestinal model to test absorption in a more reliable manner, by better mimicking the native environment. The 3D model is composed of a collagen-based stromal layer with embedded fibroblasts mimicking the intestinal lamina propria and providing support for the epithelium, composed of enterocytes and mucus-secreting cells. An endothelial layer, surrogating the absorptive capillary network, is also present. The cellular crosstalk between the different cells present in the model is unveiled, disclosing key players, namely those involved in the contraction of collagen by fibroblasts. The developed 3D model presents lower levels of P-glycoprotein (P-gp) and Multidrug Resistance Protein 2 (MRP2) efflux transporters, which are normally overexpressed in traditional Caco-2 models, and are paramount in the absorption of many compounds. This, allied with transepithelial electrical resistance (TEER) values closer to physiological ranges, leads to improved and more reliable permeability outcomes, which are observed when comparing our results with in vivo data.

JTD Keywords: 3d intestinal model, drug absorption, drug development, endothelium, hydrogel, 3d intestinal model, 3d modeling, 3d models, 3d-modeling, Alkaline-phosphatase, Animal experiments, Biopharmaceutics classification, Caco-2 cells, Cell culture, Collagen, Collagen gel, Drug absorption, Drug development, Endothelium, Fibroblasts, Glycoproteins, Hydrogel, In-vitro, Matrix metalloproteinases, Membrane-permeability, Paracellular transport, Permeability, Single-pass vs., Speed up

The generation of kidney organoids from human pluripotent stem cells (hPSCs) has represented a relevant scientific achievement in the organoid field. Importantly, hPSC-derived kidney organoids contain multiple nephron-like structures that exhibit some renal functional characteristics and have the capacity to respond to nephrotoxic agents. In this review, we first discuss how bioengineering approaches can help overcome current kidney organoid challenges. Next, we focus on recent works exploiting kidney organoids for drug screening and disease modeling applications. Finally, we provide a state of the art on current research toward the potential application of kidney organoids and renal cells derived from hPSCs for future renal replacement therapies.

JTD Keywords: Bioengineering, Converting enzyme-ii, Crispr/cas9 gene editing, Disease, Disease modeling, Extracellular-matrix, Generation, Human pluripotent stem cells, Kidney organoids, Kidney regeneration, Model, Mouse, Reveals, Scaffold, Transplantation

CCBY Intermittent hypoxia (IH) produces autonomic dysfunction that promotes the development of arrhythmia and hypertension in patients with obstructive sleep apnea (OSA). This paper investigated different heart rate variability (HRV) indices in the context of IH using a rat model for OSA. Linear and non-linear HRV parameters were assessed from ultra-short (15-s segments) and short-term (5 min) analyses of heartbeat time-series. Transient changes observed from pre-apnea segments to hypoxia episodes were evaluated, besides the relative and global impact of IH, as a function of its severity. Results showed an overall increase in ultra-short HRV markers as immediate response to hypoxia: standard deviation of normal RR intervals, SDNN=1.2 ms (IQR: 1.1-2.1) vs 1.4 ms (IQR: 1.2-2.2), p=0.015; root mean square of the successive differences, RMSSD=1.7 ms (IQR: 1.5-2.2) vs 1.9 ms (IQR: 1.6-2.4), p=0.031. The power in the very low frequency (VLF) band also showed a significant increase: 0.09 ms2 (IQR: 0.05-0.20) vs 0.16 ms2 (IQR: 0.12-0.23), p=0.016, probably associated with the potentiation of the carotid body chemo-sensory response to hypoxia. Moreover, a clear link between severity of IH and short-term HRV measures was found in VLF and LF power, besides their progressive increase seen throughout the experiment after each apnea sequence. However, only those markers quantifying fragmentation levels in RR series were significantly affected when the experiment ended, as compared to baseline measures: percentage of inflection points, PIP=49% (IQR: 45-51) vs 53% (IQR: 47-53), p=0.031; percentage of short (≥3 RR intervals) accelerated/decelerated segments, PSS=75% (IQR: 51-81) vs 87% (IQR: 51-90), p=0.046. These findings suggest a significant deterioration of cardiac rhythm with a more erratic behavior beyond the normal sinus arrhythmia, that may lead to a future cardiac condition.

JTD Keywords: artificial intelligence, atmospheric modeling, electrocardiography, heart rate variability, hypoxia rat model, intermittent hypoxia, obstructive apneas, protocols, radio access technologies, Artificial intelligence, Atmospheric modeling, Electrocardiography, Heart rate variability, Hypoxia rat model, Intermittent hypoxia, Obstructive apneas, Protocols, Radio access technologies, Rats

Patient-derived cancer 3D models are a promising tool that will revolutionize personalized cancer therapy but that require previous knowledge of optimal cell growth conditions and the most advantageous parameters to evaluate biomimetic relevance and monitor therapy efficacy. This study aims to establish general guidelines on 3D model characterization phenomena, focusing on neuroblastoma. We generated gelatin-based scaffolds with different stiffness and performed SK-N-BE(2) and SH-SY5Y aggressive neuroblastoma cell cultures, also performing co-cultures with mouse stromal Schwann cell line (SW10). Model characterization by digital image analysis at different time points revealed that cell proliferation, vitronectin production, and migration-related gene expression depend on growing conditions and are specific to the tumor cell line. Morphometric data show that 3D in vitro models can help generate optimal patient-derived cancer models, by creating, identifying, and choosing patterns of clinically relevant artificial microenvironments to predict patient tumor cell behavior and therapeutic responses.

JTD Keywords: 3D cancer modeling, DOCK8, KANK1, Ki67, Preclinical therapeutic studies, Vitronectin

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.

JTD Keywords: Home hospitalization, Health risk assessment, Predictive modeling, Chronic care, Integrated care, Modeling, Hospitalization, Health risk, Prediction, Mortality, Clinical decision support

Declining life expectancy and increasing all-cause mortality in the United States have been associated with unhealthy behaviors, socioecological factors, and preventable disease. A growing body of basic science, clinical research, and population health evidence points to the benefits of healthy behaviors, environments and policies to maintain health and prevent, treat, and reverse the root causes of common chronic diseases. Similarly, innovations in research methodologies, standards of evidence, emergence of unique study cohorts, and breakthroughs in data analytics and modeling create new possibilities for producing biomedical knowledge and clinical translation. To understand these advances and inform future directions research, The Lifestyle Medicine Research Summit was convened at the University of Pittsburgh on December 4–5, 2019. The Summit's goal was to review current status and define research priorities in the six core areas of lifestyle medicine: plant-predominant nutrition, physical activity, sleep, stress, addictive behaviors, and positive psychology/social connection. Forty invited subject matter experts (1) reviewed existing knowledge and gaps relating lifestyle behaviors to common chronic diseases, such as cardiovascular disease, diabetes, many cancers, inflammatory- and immune-related disorders and other conditions; and (2) discussed the potential for applying cutting-edge molecular, cellular, epigenetic and emerging science knowledge and computational methodologies, research designs, and study cohorts to accelerate clinical applications across all six domains of lifestyle medicine. Notably, federal health agencies, such as the Department of Defense and Veterans Administration have begun to adopt “whole-person health and performance” models that address these lifestyle and environmental root causes of chronic disease and associated morbidity, mortality, and cost. Recommendations strongly support leveraging emerging research methodologies, systems biology, and computational modeling in order to accelerate effective clinical and population solutions to improve health and reduce societal costs. New and alternative hierarchies of evidence are also be needed in order to assess the quality of evidence and develop evidence-based guidelines on lifestyle medicine. Children and underserved populations were identified as prioritized groups to study. The COVID-19 pandemic, which disproportionately impacts people with chronic diseases that are amenable to effective lifestyle medicine interventions, makes the Summit's findings and recommendations for future research particularly timely and relevant.

JTD Keywords: Chronic disease, Epigenetics, In silico modeling, Inflammation, Lifestyle medicine, Nutrition, Physical activity, Research methodologies

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.

JTD Keywords: Biological system modeling, Sleep apnea, Mathematical model, Indexes, Reduced order systems, Optimization

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.

JTD Keywords: Hepatic stellate cells, Extracellular matrix, remodeling, Rho-associated kinases, Janus kinases

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) – with only one methyl group less – 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.

JTD Keywords: Fibronectin adsorption, Fibronectin remodeling, Protein mobility, Protein-material interaction strength

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.

JTD Keywords: 3D cell culture models, Biofabrication, Disease modeling, Drug screening, Epithelial barriers, Microengineered tissues, Organ-on-a-chip, Organoids

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.

JTD Keywords: Clustered regularly interspaced short palindromic repeats/CRISPR-associated systems 9, Disease modeling, Gene editing, Human pluripotent stem cells, Kidney genetics, Tissue engineering

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.

JTD Keywords: Pluripotent stem cells, Differentiation, Genome editing, Disease modeling

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.

JTD Keywords: CRISPR/Cas9, Disease modeling, Human genetics, Human pluripotent stem cells, Tissue and genome engineering

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 cell–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.

JTD Keywords: Type IV collagen, Adsorption, Remodeling, Pericellular proteolysis, Reorganization, Substratum chemistry, CH3 and NH2 groups, Self-assembly monolayers

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.

JTD Keywords: Bone biology, Bone cells, Bone diseases, Bone extracellular matrix, Bone mechanics, Bone remodeling, Bone tissue regeneration, Skeleton

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.

JTD Keywords: Actin bundles, Actin cortex, AFM (atomic force microscopy), Cytoskeleton, Finite element modeling, Microtubules

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.

JTD 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

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.

JTD 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

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.

JTD Keywords: Autophagy, Disease modeling, LRRK2 mutation, Neurodegeneration, Pluripotent stem cells

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.

JTD 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

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.

JTD Keywords: Tissue engineering, Calcium phosphates, Mechanoregulation, Micro computer tomography, Finite element modeling

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.

JTD Keywords: Cell mechanics, Stiffness, Remodeling, Heterogeneity

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.

JTD Keywords: Chronic heart failure, AR modeling, Respiratory pattern, Discriminant band, Periodic and nonperiodic breathing

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%.

JTD Keywords: Autoregressive (AR) modeling, Chronic heart failure (CHF), Correntropy spectral density (CSD), Linear classification, Periodic breathing (PB)

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.

JTD Keywords: Mechanobiology, Lattice modeling, Differentiation, Tissue engineering, Finite element modeling, Scaffolds

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.

JTD Keywords: Natural gas, Thermopile, MEMS, Thermal conductivity, Modeling, FEM simulation