Modeling hypoxia-induced radiation resistance and the impact of radiation sources

Hypoxia contributes significantly to resistance in radiotherapy. Our research rigorously examines the influence of microvascular morphology on radiotherapy outcome, specifically focusing on how microvasculature shapes hypoxia within the microenvironment and affects resistance to a standard treatment regimen (30×2GyRBE). Our computational modeling extends to the effects of different radiation sources. For photons and protons, our analysis establishes a clear correlation between hypoxic volume distribution and treatment effectiveness, with vascular density and regularity playing a crucial role in treatment success. On the contrary, carbon ions exhibit distinct effectiveness, even in areas of intense hypoxia and poor vascularization. This finding points to the potential of carbon-based hadron therapy in overcoming hypoxia-induced resistance to RT. Considering that the spatial scale analyzed in this study is closely aligned with that of imaging data voxels, we also address the implications of these findings in a clinical context envisioning the possibility of detecting subvoxel hypoxia.

Sensitivity analysis of a multi-physics model for the vascular microenvironment

The vascular microenvironment is the scale at which microvascular transport, interstitial tissue properties and cell metabolism interact. The vascular microenvironment has been widely studied by means of quantitative approaches, including multi-physics mathematical models as it is a central system for the pathophysiology of many diseases, such as cancer. The microvascular architecture is a key factor for fluid balance and mass transfer in the vascular microenvironment, together with the physical parameters characterizing the vascular wall and the interstitial tissue. The scientific literature of this field has witnessed a long debate about which factor of this multifaceted system is the most relevant. The purpose of this work is to combine the interpretative power of an advanced multi-physics model of the vascular microenvironment with state of the art and robust sensitivity analysis methods, in order to determine the factors that most significantly impact quantities of interest, related in particular to cancer treatment. We are particularly interested in comparing the factors related to the microvascular architecture with the ones affecting the physics of microvascular transport. Ultimately, this work will provide further insight into how the vascular microenvironment affects cancer therapies, such as chemotherapy, radiotherapy or immunotherapy.

The Microvascular Network Density and Morphology Affect the Radiotherapy Outcome at the Microscale Level: A Computational Analysis

PURPOSE/OBJECTIVE(S)

Half of the cancer patients are treated with radiotherapy to obtain tumor control while minimizing radiation toxicity. In this context, hypoxia is known to determine treatment resistance, driving tumor relapse after treatment. Therefore, we investigated the role of microvasculature density and morphology in shaping the tissue oxygen distribution and consequently affecting the treatment outcome.

MATERIALS/METHODS

We developed an advanced computational model to describe oxygen delivery in the vascular network and the surrounding tissue. A peculiar aspect of the model is its mesoscale mixed-dimensional approach, which allows the explicit inclusion of vascular network geometry and the description of the red blood cells' effect. The oxygen delivery is modeled considering both diffusive and convective phenomena. A 30 × 2GyRBE treatment is delivered in silico simulating photons, protons, and carbon ions. First, we estimated the surviving fraction by the classical linear quadratic model modified to account for the oxygen effect. Then, leveraging the 3D description of the surviving fraction at the microenvironment scale, we compute the local tumor control probability (LTCP) in different oxygenation states (reference, acute hypoxia, high oxygen consumption).

RESULTS

We report correlations between the LTCP and the hypoxic volume fractions (with pO2 lower than 1 mmHg) starting with photons. These hypoxic regions are present locally, even in highly vascularized tissue, if the network is not uniformly distributed, as it might be in cancer. They are also present in tissue with low microvascular density, even with regular morphology. Interestingly, the domain considered is comparable to or smaller than the clinical imaging standard voxel dimension, and the average oxygen partial pressure in the tissue region fails to spot treatments with low LTCP, questioning whether these hypoxia areas are visible clinically via imaging. Protons have a similar effect, highlighting a similar behavior across the oxygenation levels at the microscale level. Finally, carbon ions seem more effective than photons and protons in the presence of hypoxia due to the lower oxygen effect at high LET. For this reason, the treatment with carbon ions results in high LTCPs, whatever vascular network is considered (density and morphology differences).

CONCLUSION

These results show the effect of microvascular density and regularity on the radiotherapy outcome and they help us understand how the microvascular network morphology affects tumor oxygenation and the radiotherapy outcome.

Supplementation of honey bee production colonies with a native beneficial microbe mixture

Honey bee colonies form a complex superorganism, with individual and social immune defences that control overall colony health. Sometimes these defences are not enough to overcome infections by parasites and pathogens. For that reason, several studies have been conducted to evaluate different strategies to improve honey bee health. A novel alternative that is being studied is the use of beneficial microbes. In a previous study, we isolated and characterised bacterial strains from the native gut microbiota of honey bees. Four Apilactobacillus kunkeei strains were mixed and administered in laboratory models to evaluate their potential beneficial effect on larvae and adult bees. This beneficial microbe mixture was safe; it did not affect the expression of immune-related genes, and it was able to decrease the mortality caused by Paenibacillus larvae infection in larvae and reduced the Nosema ceranae spore number in infected adult honey bees. In the present study, we aimed to delve into the impact of the administration of this beneficial microbe mixture on honey bee colonies, under field conditions. The mixture was administered in sugar syrup using lyophilised bacterial cells or fresh cultures, by aspersion or sprayed and feeder, once a week for three consecutive weeks, in autumn or spring 2015, 2017 and 2019. Colony strength parameters were estimated before the administration, and one and three months later. Simultaneously different samples were collected to evaluate the infection levels of parasites and pathogens. The results showed that administering the beneficial microbe mixture decreased or stabilised the infection by N. ceranae or Varroa destructor in some trials but not in others. However, it failed to improve the colony's strength parameters or honey production. Therefore, field studies can be a game-changer when beneficial microbes for honey bees are tested, and meticulous studies should be performed to test their effectiveness.

A three-dimensional method for morphological analysis and flow velocity estimation in microvasculature on-a-chip

Three-dimensional (3D) imaging techniques (e.g., confocal microscopy) are commonly used to visualize in vitro models, especially microvasculature on-a-chip. Conversely, 3D analysis is not the standard method to extract quantitative information from those models. We developed the μVES algorithm to analyze vascularized in vitro models leveraging 3D data. It computes morphological parameters (geometry, diameter, length, tortuosity, eccentricity) and intravascular flow velocity. μVES application to microfluidic vascularized in vitro models shows that they successfully replicate functional features of the microvasculature in vivo in terms of intravascular fluid flow velocity. However, wall shear stress is lower compared to in vivo references. The morphological analysis also highlights the model's physiological similarities (vessel length and tortuosity) and shortcomings (vessel radius and surface-over-volume ratio). The addition of the third dimension in our analysis produced significant differences in the metrics assessed compared to 2D estimations. It enabled the computation of new indices, such as vessel eccentricity. These μVES capabilities can find application in analyses of different in vitro vascular models, as well as in vivo and ex vivo microvasculature.

Approximation bounds for convolutional neural networks in operator learning

Recently, deep Convolutional Neural Networks (CNNs) have proven to be successful when employed in areas such as reduced order modeling of parametrized PDEs. Despite their accuracy and efficiency, the approaches available in the literature still lack a rigorous justification on their mathematical foundations. Motivated by this fact, in this paper we derive rigorous error bounds for the approximation of nonlinear operators by means of CNN models. More precisely, we address the case in which an operator maps a finite dimensional input μ∈R^p onto a functional output u_μ:[0,1]^d→R, and a neural network model is used to approximate a discretized version of the input-to-output map. The resulting error estimates provide a clear interpretation of the hyperparameters defining the neural network architecture. All the proofs are constructive, and they ultimately reveal a deep connection between CNNs and the Fourier transform. Finally, we complement the derived error bounds by numerical experiments that illustrate their application.

Prediction of myocardial blood flow under stress conditions by means of a computational model

PURPOSE

Quantification of myocardial blood flow (MBF) and functional assessment of coronary artery disease (CAD) can be achieved through stress myocardial computed tomography perfusion (stress-CTP). This requires an additional scan after the resting coronary computed tomography angiography (cCTA) and administration of an intravenous stressor. This complex protocol has limited reproducibility and non-negligible side effects for the patient. We aim to mitigate these drawbacks by proposing a computational model able to reproduce MBF maps.

METHODS

A computational perfusion model was used to reproduce MBF maps. The model parameters were estimated by using information from cCTA and MBF measured from stress-CTP (MBF_CTP) maps. The relative error between the computational MBF under stress conditions (MBF_COMP) and MBF_CTP was evaluated to assess the accuracy of the proposed computational model.

RESULTS

Applying our method to 9 patients (4 control subjects without ischemia vs 5 patients with myocardial ischemia), we found an excellent agreement between the values of MBF_COMP and MBF_CTP. In all patients, the relative error was below 8% over all the myocardium, with an average-in-space value below 4%.

CONCLUSION

The results of this pilot work demonstrate the accuracy and reliability of the proposed computational model in reproducing MBF under stress conditions. This consistency test is a preliminary step in the framework of a more ambitious project which is currently under investigation, i.e., the construction of a computational tool able to predict MBF avoiding the stress protocol and potential side effects while reducing radiation exposure.

Relevance of iron metabolic genes in biofilm and infection in uropathogenic Proteus mirabilis

The microorganisms are found in the environment, forming sessile communities embedded in an extracellular matrix of their own production, called biofilm. These communities have a great relevance in the clinical context, since they are associated with infections caused by biofilm in medical implants, such as urinary catheters. The development of biofilms is a complex process where a great diversity of genes participate. The present work is based on the study of genes related to iron metabolism and its implication in the development of P. mirabilis biofilms and pathogenicity. For this study, two mutant strains defective in biofilm formation were selected, generated by the interruption of genes that encoded non-heme ferritin and TonB-dependent receptor. The mutations influence on the development of the biofilm was evaluated by different approaches. The complexity of the biofilm was analyzed using Confocal Laser Microscopy and image analysis. The mutants infectivity potential was assessed in two experimental mice models of urinary tract infection. The results obtained in the present work show us the role of the ferritin and a TonB-associated porin protein over the initial and later stages of biofilm development. Moreover, in the ascending UTI mouse model, both mutants failed to colonize the urinary tract. In CAUTI models, ferritin mutant damaged the bladder similarly to wild type but the Ton-B mutant was unable to generate infection in the urinary tract. The results obtained in the present work confirm the relevant role that iron metabolism genes have in P. mirabilis biofilm development and for infection in the urinary tract.

Development of a method for generating SNP interaction-aware polygenic risk scores for radiotherapy toxicity

AIM

To identify the effect of single nucleotide polymorphism (SNP) interactions on the risk of toxicity following radiotherapy (RT) for prostate cancer (PCa) and propose a new method for polygenic risk score incorporating SNP-SNP interactions (PRSi).

MATERIALS AND METHODS

Analysis included the REQUITE PCa cohort that received external beam RT and was followed for 2 years. Late toxicity endpoints were: rectal bleeding, urinary frequency, haematuria, nocturia, decreased urinary stream. Among 43 literature-identified SNPs, the 30% most strongly associated with each toxicity were tested. SNP-SNP combinations (named SNP-allele sets) seen in ≥10% of the cohort were condensed into risk (RS) and protection (PS) scores, respectively indicating increased or decreased toxicity risk. Performance of RS and PS was evaluated by logistic regression. RS and PS were then combined into a single PRSi evaluated by area under the receiver operating characteristic curve (AUC).

RESULTS

Among 1,387 analysed patients, toxicity rates were 11.7% (rectal bleeding), 4.0% (urinary frequency), 5.5% (haematuria), 7.8% (nocturia) and 17.1% (decreased urinary stream). RS and PS combined 8 to 15 different SNP-allele sets, depending on the toxicity endpoint. Distributions of PRSi differed significantly in patients with/without toxicity with AUCs ranging from 0.61 to 0.78. PRSi was better than the classical summed PRS, particularly for the urinary frequency, haematuria and decreased urinary stream endpoints.

CONCLUSIONS

Our method incorporates SNP-SNP interactions when calculating PRS for radiotherapy toxicity. Our approach is better than classical summation in discriminating patients with toxicity and should enable incorporating genetic information to improve normal tissue complication probability models.

A surrogate model for plaque modeling in carotids based on Robin conditions calibrated by cine MRI data

We propose a surrogate model for the fluid-structure interaction (FSI) problem for the study of blood dynamics in carotid arteries in presence of plaque. This is based on the integration of a numerical model with subject-specific data and clinical imaging. We propose to model the plaque as part of the tissues surrounding the vessel wall through the application of an elastic support boundary condition. In order to characterize the plaque and other surrounding tissues, such as the close-by jugular vein, the elastic parameters of the boundary condition were spatially differentiated and their values were estimated by minimizing the discrepancies between computed vessel displacements and reference values obtained from CINE Magnetic Resonance Imaging data. We applied the model to three subjects with a degree of stenosis greater than 70%. We found that accounting for both plaque and jugular vein in the estimation of the elastic parameters increases the accuracy. In particular, in all patients, mismatches between computed and in vivo measured wall displacements were one to two orders of magnitude lower than the spatial resolution of the original MRI data. These results confirmed the validity of the proposed surrogate plaque model. We also compared fluid-dynamics results with those obtained in a fixed wall setting and in a full FSI model, used as gold standard, highlighting the better accordance of our results in comparison to the rigid ones.

Modeling the cardiac response to hemodynamic changes associated with COVID-19: a computational study

Emerging studies address how COVID-19 infection can impact the human cardiovascular system. This relates particularly to the development of myocardial injury, acute coronary syndrome, myocarditis, arrhythmia, and heart failure. Prospective treatment approach is advised for these patients. To study the interplay between local changes (reduced contractility), global variables (peripheral resistances, heart rate) and the cardiac function, we considered a lumped parameters computational model of the cardiovascular system and a three-dimensional multiphysics model of cardiac electromechanics. Our mathematical model allows to simulate the systemic and pulmonary circulations, the four cardiac valves and the four heart chambers, through equations describing the underlying physical processes. By the assessment of conventionally relevant parameters of cardiac function obtained through our numerical simulations, we propose a computational model to effectively reveal the interactions between the cardiac and pulmonary functions in virtual subjects with normal and impaired cardiac function at baseline affected by mild or severe COVID-19.

Impact of Nutritional Stress on Honeybee Gut Microbiota, Immunity, and Nosema ceranae Infection

Honeybees are important pollinators, having an essential role in the ecology of natural and agricultural environments. Honeybee colony losses episodes reported worldwide and have been associated with different pests and pathogens, pesticide exposure, and nutritional stress. This nutritional stress is related to the increase in monoculture areas which leads to a reduction of pollen availability and diversity. In this study, we examined whether nutritional stress affects honeybee gut microbiota, bee immunity, and infection by Nosema ceranae, under laboratory conditions. Consumption of Eucalyptus grandis pollen was used as a nutritionally poor-quality diet to study nutritional stress, in contraposition to the consumption of polyfloral pollen. Honeybees feed with Eucalyptus grandis pollen showed a lower abundance of Lactobacillus mellifer and Lactobacillus apis (Firm-4 and Firm-5, respectively) and Bifidobacterium spp. and a higher abundance of Bartonella apis, than honeybees fed with polyfloral pollen. Besides the impact of nutritional stress on honeybee microbiota, it also decreased the expression levels of vitellogenin and genes associated to immunity (glucose oxidase, hymenoptaecin and lysozyme). Finally, Eucalyptus grandis pollen favored the multiplication of Nosema ceranae. These results show that nutritional stress impacts the honeybee gut microbiota, having consequences on honeybee immunity and pathogen development. Those results may be useful to understand the influence of modern agriculture on honeybee health.

A Deep Learning Approach Validates Genetic Risk Factors for Late Toxicity After Prostate Cancer Radiotherapy in a REQUITE Multi-National Cohort

Background: REQUITE (validating pREdictive models and biomarkers of radiotherapy toxicity to reduce side effects and improve QUalITy of lifE in cancer survivors) is an international prospective cohort study. The purpose of this project was to analyse a cohort of patients recruited into REQUITE using a deep learning algorithm to identify patient-specific features associated with the development of toxicity, and test the approach by attempting to validate previously published genetic risk factors. Methods: The study involved REQUITE prostate cancer patients treated with external beam radiotherapy who had complete 2-year follow-up. We used five separate late toxicity endpoints: ≥grade 1 late rectal bleeding, ≥grade 2 urinary frequency, ≥grade 1 haematuria, ≥ grade 2 nocturia, ≥ grade 1 decreased urinary stream. Forty-three single nucleotide polymorphisms (SNPs) already reported in the literature to be associated with the toxicity endpoints were included in the analysis. No SNP had been studied before in the REQUITE cohort. Deep Sparse AutoEncoders (DSAE) were trained to recognize features (SNPs) identifying patients with no toxicity and tested on a different independent mixed population including patients without and with toxicity. Results: One thousand, four hundred and one patients were included, and toxicity rates were: rectal bleeding 11.7%, urinary frequency 4%, haematuria 5.5%, nocturia 7.8%, decreased urinary stream 17.1%. Twenty-four of the 43 SNPs that were associated with the toxicity endpoints were validated as identifying patients with toxicity. Twenty of the 24 SNPs were associated with the same toxicity endpoint as reported in the literature: 9 SNPs for urinary symptoms and 11 SNPs for overall toxicity. The other 4 SNPs were associated with a different endpoint. Conclusion: Deep learning algorithms can validate SNPs associated with toxicity after radiotherapy for prostate cancer. The method should be studied further to identify polygenic SNP risk signatures for radiotherapy toxicity. The signatures could then be included in integrated normal tissue complication probability models and tested for their ability to personalize radiotherapy treatment planning.

Effect of the administration of Lactobacillus spp. strains on neonatal diarrhoea, immune parameters and pathogen abundance in pre-weaned calves

Neonatal calf diarrhoea is one of the challenges faced by intensive farming, and probiotics are considered a promising approach to improve calves' health. The objective of this study was to evaluate the effect of potential probiotic lactobacilli on new-born dairy calves' growth, diarrhoea incidence, faecal score, cytokine expression in blood cells, immunoglobulin A (IgA) levels in plasma and faeces, and pathogen abundance in faeces. Two in vivo assays were conducted at the same farm in two annual calving seasons. Treated calves received one daily dose of the selected lactobacilli (Lactobacillus reuteri TP1.3B or Lactobacillus johnsonii TP1.6) for 10 consecutive days. A faecal score was recorded daily, average daily gain (ADG) was calculated, and blood and faeces samples were collected. Pathogen abundance was analysed by absolute qPCR in faeces using primers directed at Salmonella enterica, rotavirus, coronavirus, Cryptosporidium parvum and three Escherichia coli virulence genes (eae, clpG and Stx1). The faecal score was positively affected by the administration of both lactobacilli strains, and diarrhoea incidence was significantly lower in treated calves. No differences were found regarding ADG, cytokine expression, IgA levels and pathogen abundance. Our findings showed that oral administration of these strains could improve gastrointestinal health, but results could vary depending on the calving season, which may be related to pathogen seasonality and other environmental effects.

Application of Transmural Flow Across In Vitro Microvasculature Enables Direct Sampling of Interstitial Therapeutic Molecule Distribution

In vitro prediction of physiologically relevant transport of therapeutic molecules across the microcirculation represents an intriguing opportunity to predict efficacy in human populations. On-chip microvascular networks (MVNs) show physiologically relevant values of molecular permeability, yet like most systems, they lack an important contribution to transport: the ever-present fluid convection through the endothelium. Quantification of transport through the MVNs by current methods also requires confocal imaging and advanced analytical techniques, which can be a bottleneck in industry and academic laboratories. Here, it is shown that by recapitulating physiological transmural flow across the MVNs, the concentration of small and large molecule therapeutics can be directly sampled in the interstitial fluid and analyzed using standard analytical techniques. The magnitudes of transport measured in MVNs reveal trends with molecular size and type (protein versus nonprotein) that are expected in vivo, supporting the use of the MVNs platform as an in vitro tool to predict distribution of therapeutics in vivo.

Impact of nutritional stress on the honeybee colony health

Honeybees Apis mellifera are important pollinators of wild plants and commercial crops. For more than a decade, high percentages of honeybee colony losses have been reported worldwide. Nutritional stress due to habitat depletion, infection by different pests and pathogens and pesticide exposure has been proposed as the major causes. In this study we analyzed how nutritional stress affects colony strength and health. Two groups of colonies were set in a Eucalyptus grandis plantation at the beginning of the flowering period (autumn), replicating a natural scenario with a nutritionally poor food source. While both groups of colonies had access to the pollen available in this plantation, one was supplemented with a polyfloral pollen patty during the entire flowering period. In the short-term, colonies under nutritional stress (which consumed mainly E. grandis pollen) showed higher infection level with Nosema spp. and lower brood and adult bee population, compared to supplemented colonies. On the other hand, these supplemented colonies showed higher infection level with RNA viruses although infection levels were low compared to countries were viral infections have negative impacts. Nutritional stress also had long-term colony effects, because bee population did not recover in spring, as in supplemented colonies did. In conclusion, nutritional stress and Nosema spp. infection had a severe impact on colony strength with consequences in both short and long-term.

A computational model for microcirculation including Fahraeus-Lindqvist effect, plasma skimming and fluid exchange with the tissue interstitium

We present a two-phase model for microcirculation that describes the interaction of plasma with red blood cells. The model takes into account of typical effects characterizing the microcirculation, such as the Fahraeus-Lindqvist effect and plasma skimming. Besides these features, the model describes the interaction of capillaries with the surrounding tissue. More precisely, the model accounts for the interaction of capillary transmural flow with the surrounding interstitial pressure. Furthermore, the capillaries are represented as one-dimensional channels with arbitrary, possibly curved configuration. The latter two features rely on the unique ability of the model to account for variations of flow rate and pressure along the axis of the capillary, according to a local differential formulation of mass and momentum conservation. Indeed, the model stands on a solid mathematical foundation, which is also addressed in this work. In particular, we present the model derivation, the variational formulation, and its approximation using the finite element method. Finally, we conclude the work with a comparative computational study of the importance of the Fahraeus-Lindqvist, plasma skimming, and capillary leakage effects on the distribution of flow in a microvascular network.

Numerical simulations of the microvascular fluid balance with a non-linear model of the lymphatic system

Fluid homeostasis is required for life. Processes involved in fluid balance are strongly related to exchanges at the microvascular level. Computational models have been presented in the literature to analyze the microvascular-interstitial interactions. As far as we know, none of those models consider a physiological description for the lymphatic drainage-interstitial pressure relation. We develop a computational model that consists of a network of straight cylindrical vessels and an isotropic porous media with a uniformly distributed sink term acting as the lymphatic system. In order to describe the lymphatic flow rate, a non-linear function of the interstitial pressure is defined, based on literature data on the lymphatic system. The proposed model of lymphatic drainage is compared to a linear one, as is typically used in computational models. To evaluate the response of the model, the two are compared with reference to both physiological and pathological conditions. Differences in the local fluid dynamic description have been observed using the non-linear model. In particular, the distribution of interstitial pressure is heterogeneous in all the cases analyzed. The resulting averaged values of the interstitial pressure are also different, and they agree with literature data when using the non-linear model. This work highlights the key role of lymphatic drainage and its modeling when studying the fluid balance in microcirculation for both to physiological and pathological conditions, e.g. uremia.

Probiotic properties of native Lactobacillus spp. strains for dairy calves

The use of native microorganisms with probiotic capacity is an alternative tool for the treatment and prevention of several diseases that affect animals, such as neonatal calf diarrhoea. The selection of probiotic strains within a collection is based on different in vitro and in vivo assays, which predict their potential. The aim of this study was to characterise a group of native Lactobacillus spp. strains isolated from faeces of healthy calves using an in vitro approach and to assess their ability to colonise the gastrointestinal tract (GIT) of calves. Native Lactobacillus spp. strains were evaluated on their capacity to survive low pH conditions and bile salts presence, biofilm formation and adhesion to both mucus and Caco-2 cells. Based on the in vitro characterisation, four strains (Lactobacillus johnsonii TP1.1, Lactobacillus reuteri TP1.3B, L. johnsonii TP1.6 and Lactobacillus amylovorus TP8.7) were selected to evaluate their capacity to colonise and persist in the GIT of calves. The assessment of enteric persistence involved an in vivo assay with oral administration of probiotics and quantification in faeces of the administered bacterial species with real-time quantitative PCR (qPCR). The study was conducted using 15 calves (1-month-old) which were divided into five groups of three animals, four of which were treated with four different selected strains and one was the control group. Strains TP1.3B and TP1.6 managed to persist in treated animals until ten days after the end of the administration period, indicating that they could be promising candidates for the design of probiotics for calves.

Design and validation of an osteochondral bioreactor for the screening of treatments for osteoarthritis

Bioreactors are systems that can be used to monitor the response of tissues and cells to candidate drugs. Building on the experience developed in the creation of an osteochondral bioreactor, we have designed a new 3D printed system, which allows optical access to the cells throughout testing for in line monitoring. Because of the use of 3D printing, the fluidics could be developed in the third dimension, thus maintaining the footprint of a single well of a typical 96 well plate. This new design was optimized to achieve the maximum fluid transport through the central chamber, which corresponds to optimal nutrient or drug exposure. This optimization was achieved by altering each dimension of the bioreactor fluid path. A physical model for optimized drug exposure was then created and tested.

Lactobacillus kunkeei strains decreased the infection by honey bee pathogens Paenibacillus larvae and Nosema ceranae

Due to their social behaviour, honey bees can be infected by a wide range of pathogens including the microsporidia Nosema ceranae and the bacteria Paenibacillus larvae. The use of probiotics as food additives for the control or prevention of infectious diseases is a widely used approach to improve human and animal health. In this work, we generated a mixture of four Lactobacillus kunkeei strains isolated from the gut microbial community of bees, and evaluated its potential beneficial effect on larvae and adult bees. Its administration in controlled laboratory models was safe for larvae and bees; it did not affect the expression of immune-related genes and it was able to decrease the mortality associated to P. larvae infection in larvae and the counts of N. ceranae spores from adult honey bees. These promising results suggest that this beneficial microorganism's mixture may be an attractive strategy to improve bee health. Field studies are being carried out to evaluate its effect in naturally infected colonies.

Characterization of Nosema ceranae Genetic Variants from Different Geographic Origins

In recent years, large-scale colony losses of honey bees (Apis mellifera) have been reported and the infection with the microsporidia Nosema ceranae has been involved. However, the effect of N. ceranae at the colony level and its role in colony losses vary in different geographic areas. This difference may be related to the presence of multiple N. ceranae genetic variants resulting in different biological consequences. In this study, we analyzed the genetic diversity of 75 N. ceranae samples obtained from 13 countries and Hawaii through inter-sequence single repetition (ISSR) and evaluated if two of these genetic variants triggered different immune responses when infecting Apis mellifera iberiensis. The genetic diversity analysis showed that 41% of the samples had the same DNA amplification pattern, including samples from most European countries except Spain, while the remaining samples showed high variability. Infection assays were performed to analyze the infection levels and the immune response of bees infected with N. ceranae from Spain and Uruguay. The infected bees presented similar infection levels, and both isolates downregulated the expression of abaecin, confirming the ability of the microsporidia to depress the immune response. Only N. ceranae from Uruguay downregulated the expression level of imd compared to control bees. On the other hand, both genetic variants triggered different expression levels of lysozyme. As imd and lysozyme play important roles in the response to pathogens, these results could reflect differences in the biological consequences of N. ceranae variants in A. mellifera infection.

Distributed and Lumped Parameter Models for the Characterization of High Throughput Bioreactors

Next generation bioreactors are being developed to generate multiple human cell-based tissue analogs within the same fluidic system, to better recapitulate the complexity and interconnection of human physiology [1, 2]. The effective development of these devices requires a solid understanding of their interconnected fluidics, to predict the transport of nutrients and waste through the constructs and improve the design accordingly. In this work, we focus on a specific model of bioreactor, with multiple input/outputs, aimed at generating osteochondral constructs, i.e., a biphasic construct in which one side is cartilaginous in nature, while the other is osseous. We next develop a general computational approach to model the microfluidics of a multi-chamber, interconnected system that may be applied to human-on-chip devices. This objective requires overcoming several challenges at the level of computational modeling. The main one consists of addressing the multi-physics nature of the problem that combines free flow in channels with hindered flow in porous media. Fluid dynamics is also coupled with advection-diffusion-reaction equations that model the transport of biomolecules throughout the system and their interaction with living tissues and C constructs. Ultimately, we aim at providing a predictive approach useful for the general organ-on-chip community. To this end, we have developed a lumped parameter approach that allows us to analyze the behavior of multi-unit bioreactor systems with modest computational effort, provided that the behavior of a single unit can be fully characterized.

A computational study of cancer hyperthermia based on vascular magnetic nanoconstructs

The application of hyperthermia to cancer treatment is studied using a novel model arising from the fundamental principles of flow, mass and heat transport in biological tissues. The model is defined at the scale of the tumour microenvironment and an advanced computational scheme called the embedded multiscale method is adopted to solve the governing equations. More precisely, this approach involves modelling capillaries as one-dimensional channels carrying flow, and special mathematical operators are used to model their interaction with the surrounding tissue. The proposed computational scheme is used to analyse hyperthermic treatment of cancer based on systemically injected vascular magnetic nanoconstructs carrying super-paramagnetic iron oxide nanoparticles. An alternating magnetic field is used to excite the nanoconstructs and generate localized heat within the tissue. The proposed model is particularly adequate for this application, since it has a unique capability of incorporating microvasculature configurations based on physiological data combined with coupled capillary flow, interstitial filtration and heat transfer. A virtual tumour model is initialized and the spatio-temporal distribution of nanoconstructs in the vascular network is analysed. In particular, for a reference iron oxide concentration, temperature maps of several different hypothesized treatments are generated in the virtual tumour model. The observations of the current study might in future guide the design of more efficient treatments for cancer hyperthermia.

Theory and application of arterial tissue in-host remodelling

A central therapeutic goal in many applications of modern Biomedicine is the reconstruction of the diseased arterial sections via robust and viable tissue equivalents. In-host remodelling is an emerging technology that exploits the remodelling ability of the host to regenerate tissue. We develop a general theoretical framework of growth and remodeling of arterial tissue starting from a synthetic, degradable, acellularized graft and we demonstrate the potential of mechanistic models to guide the development and assisting in the design of arterial tissue engineered constructs.

Modelling mass and heat transfer in nano-based cancer hyperthermia

We derive a sophisticated mathematical model for coupled heat and mass transport in the tumour microenvironment and we apply it to study nanoparticle delivery and hyperthermic treatment of cancer. The model has the unique ability of combining the following features: (i) realistic vasculature; (ii) coupled capillary and interstitial flow; (iii) coupled capillary and interstitial mass transfer applied to nanoparticles; and (iv) coupled capillary and interstitial heat transfer, which are the fundamental mechanisms governing nano-based hyperthermic treatment. This is an improvement with respect to previous modelling approaches, where the effect of blood perfusion on heat transfer is modelled in a spatially averaged form. We analyse the time evolution and the spatial distribution of particles and temperature in a tumour mass treated with superparamagnetic nanoparticles excited by an alternating magnetic field. By means of numerical experiments, we synthesize scaling laws that illustrate how nano-based hyperthermia depends on tumour size and vascularity. In particular, we identify two distinct mechanisms that regulate the distribution of particle and temperature, which are characterized by perfusion and diffusion, respectively.

A computational model of drug delivery through microcirculation to compare different tumor treatments

Starting from the fundamental laws of filtration and transport in biological tissues, we develop a computational model to capture the interplay between blood perfusion, fluid exchange with the interstitial volume, mass transport in the capillary bed, through the capillary walls and into the surrounding tissue. These phenomena are accounted at the microscale level, where capillaries and interstitial volume are viewed as two separate regions. The capillaries are described as a network of vessels carrying blood flow. We apply the model to study drug delivery to tumors. The model can be adapted to compare various treatment options. In particular, we consider delivery using drug bolus injection and nanoparticle injection into the blood stream. The computational approach is suitable for a systematic quantification of the treatment performance, enabling the analysis of interstitial drug concentration levels, metabolization rates and cell surviving fractions. Our study suggests that for the treatment based on bolus injection, the drug dose is not optimally delivered to the tumor interstitial volume. Using nanoparticles as intermediate drug carriers overrides the shortcomings of the previous delivery approach. This work shows that the proposed theoretical and computational framework represents a promising tool to compare the efficacy of different cancer treatments.

Simulation of oxygen transfer in stented arteries and correlation with in-stent restenosis

Computational models are used to study the combined effect of biomechanical and biochemical factors on coronary in-stent restenosis, which is a postoperative remodeling and regrowth pathology of the stented arteries. More precisely, we address numerical simulations, on the basis of Navier-Stokes and mass transport equations, to study the role of perturbed wall shear stresses and reduced oxygen concentration in a geometrical model reconstructed from a real porcine artery treated with a stent. Joining in vivo and in silico tools of investigation has multiple benefits in this case. On one hand, the geometry of the arterial wall and of the stent closely correspond to a real implanted configuration. On the other hand, the inspection of histological tissue samples informs us on the location and intensity of in-stent restenosis. As a result, we are able to correlate geometrical factors, such as the axial variation of the artery diameter and its curvature; the numerical quantification of biochemical stimuli, such as wall shear stresses; and the availability of oxygen to the inner layers of the artery, with the appearance of in-stent restenosis. This study shows that the perturbation of the vessel curvature could induce hemodynamic conditions that stimulate undesired arterial remodeling.

Numerical treatment of boundary conditions to replace lateral branches in hemodynamics

In this paper, we discuss a technique for weakly enforcing flow rate conditions in computational hemodynamics. In particular, we study the effectiveness of cutting lateral branches from the computational domain and replacing them with non-perturbing boundary conditions to simplify the geometrical reconstruction and the numerical simulation. All these features are investigated both in the case of rigid and compliant walls. Several numerical results are presented to discuss the reliability of the proposed method.

Development of 3D architecture of uropathogenic Proteus mirabilis batch culture biofilms-A quantitative confocal microscopy approach

This work studies the development of the 3D architecture of batch culture P. mirabilis biofilms on the basis of morpho-topological descriptors calculated from confocal laser scanning microscopy (CLSM) stacks with image processing routines. A precise architectonical understanding of biofilm organization on a morpho-topological level is necessary to understand emergent interactions with the environment and the appearance of functionally different progeny swarmer cells. P. mirabilis biofilms were grown on glass coverslips for seven days on LB broth and subjected to in situ immunofluorescence. Confocal image stacks were deconvolved prior to segmentation of regions of interest (ROI) that identify individual bacteria and extracellular material, followed by 3D reconstruction and calculation of different morpho-topological key descriptors. Results showed that P. mirabilis biofilm formation followed a five stage process: (i) reversible adhesion to the surface characterized by slow growth, presence of elongated bacteria, and absence of extracellular material, (ii) irreversible bacterial adhesion concomitant to decreasing elongation, and the beginning of extracellular polymer production, (iii) accelerated bacterial growth concomitant to continuously decreasing elongation and halting of extracellular polymer production, (iv) maturation of biofilm defined by maximum bacterial density, volume, minimum elongation, maximum extracellular material, and highest compaction, and (v) decreased bacterial density and extracellular material through detachment and dispersion. Swarmer cells do not play a role in P. mirabilis biofilm formation under the applied conditions. Our approach sets the basis for future studies of 3D biofilm architecture using dynamic in vivo models and different environmental conditions that assess clinical impacts of P. mirabilis biofilm.

Changes in the aerobic vaginal bacterial mucous load after treatment with intravaginal sponges in anoestrous ewes: effect of medroxiprogesterone acetate and antibiotic treatment use

Intravaginal sponges (IS) impregnated with progestagens are widely used for oestrous synchronization in ewes. As progestogens depress the immuno response, the first aim was to determine whether medroxiprogesterone acetate (MAP) content affects the vaginal bacteria number (VBN) in IS-treated anoestrous ewes. The second aim was to compare the effectiveness of different antibiotic treatments to control the VBN increase caused by IS. In both experiments, IS were inserted during 14 days in anoestrous ewes. In the first, 11 ewes received commercial sponges (50 mg MAP), and 10 ewes received placebo sponges. For the second experiment, IS were inserted in three groups (n = 12/group), containing oxytetracycline im (20 mg/kg); injected into the sponge (0.02 mg), or control (no antibiotic). At sponge withdrawal, all ewes received 300 UI eCG. Mucous samples were collected from the vagina before sponge insertion, at sponge withdrawal, 24, 48 and 72 h later, and the VBN (colony-forming units per ml; CFU/ml) was counted after 48-h incubation. Medroxiprogesterone content did not affect VBN (log CFU/ml: 4.3 ± 0.2 vs 4.4 ± 0.2 with and without MAP, respectively). Bacterial number increased from 3.5 ± 0.2 at sponge insertion to 6.9 ± 0.1 at sponge withdrawal (p < 0.0001) and decreased the following day to 4.3 ± 0.2 (p < 0.0001). In the second experiment, VBN increased at sponge withdrawal (p < 0.0001) in all groups and decreased the following day (p < 0.0001). The CFU/ml at sponge withdrawal was lower in ewes treated with antibiotics (p < 0.0001), being even lower when local rather than systemic antibiotic was administered (log CFU/ml: 3.3 ± 1.8 vs 7.2 ± 1.8). The day of oestrous VBN was similar for all treatments and similar to that observed before sponge insertion. We concluded that MAP does not influence the increase in VBN, as the main effect is provoked by the sponge device itself, and local antibiotic treatment resulted in a lower bacterial growth than systemic treatments.

Trends in biomedical engineering: focus on Patient Specific Modeling and Life Support Systems

Over the last twenty years major advancements have taken place in the design of medical devices and personalized therapies. They have paralleled the impressive evolution of three-dimensional, non invasive, medical imaging techniques and have been continuously fuelled by increasing computing power and the emergence of novel and sophisticated software tools. This paper aims to showcase a number of major contributions to the advancements of modeling of surgical and interventional procedures and to the design of life support systems. The selected examples will span from pediatric cardiac surgery procedures to valve and ventricle repair techniques, from stent design and endovascular procedures to life support systems and innovative ventilation techniques.

Expansion and drug elution model of a coronary stent

The present study illustrates a possible methodology to investigate drug elution from an expanded coronary stent. Models based on finite element method have been built including the presence of the atherosclerotic plaque, the artery and the coronary stent. These models take into account the mechanical effects of the stent expansion as well as the effect of drug transport from the expanded stent into the arterial wall. Results allow to quantify the stress field in the vascular wall, the tissue prolapse within the stent struts, as well as the drug concentration at any location and time inside the arterial wall, together with several related quantities as the drug dose and the drug residence times.