Confined cell migration and asymmetric hydraulic environments to evaluate the metastatic potential of cancer cells

Metastasis, a hallmark of cancer development, is also the leading reason for most cancer-related deaths. Furthermore, cancer cells are highly adaptable to microenvironments and can migrate along pre-existing channel-like tracks of anatomical structures. However, more representative three-dimensional models are required to reproduce the heterogeneity of metastatic cell migration in vivo to further understand the metastasis mechanism and develop novel therapeutic strategies against it. Here, we designed and fabricated different microfluidic-based devices that recreate confined migration and diverse environments with asymmetric hydraulic resistances. Our results show different migratory potential between metastatic and nonmetastatic cancer cells in confined environments. Moreover, although nonmetastatic cells have not been tested against barotaxis due to their low migration capacity, metastatic cells present an enhanced preference to migrate through the lowest resistance path, being sensitive to barotaxis. This device, approaching the study of metastasis capability based on confined cell migration and barotactic cell decisions, may pave the way for the implementation of such technology to determine and screen the metastatic potential of certain cancer cells

Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: insights from the AIRA identification algorithm

This study analyzed the sensitivity of atmospheric rivers (ARs) to aerosol treatment in regional climate simulations. Three experiments covering the Iberian Peninsula for the period from 1991 to 2010 were examined: (1) an experiment including prescribed aerosols (BASE); (2) an experiment including direct and semi-direct aerosol effects (ARI); and (3) an experiment including direct, semi-direct, and indirect aerosol effects (ARCI). A new regional-scale AR identification algorithm, AIRA, was developed and used to identify around 250 ARs in each experiment. The results showed that spring and autumn ARs were the most frequent, intense, and long-lasting and that ARs could explain up to 30 % of the total accumulated precipitation. The inclusion of aerosols was found to redistribute precipitation, with increases in the areas of AR occurrence. The analysis of common AR events showed that the differences between simulations were minimal in the most intense cases and that a negative correlation existed between mean direction and mean latitude differences. This implies that more zonal ARs in ARI or ARCI with respect to BASE could also be linked to northward deviations. The joint analysis and classification of dust and sea salt aerosol distributions allowed for the common events to be clustered into eight main aerosol configurations in ARI and ARCI. The sensitivity of ARs to different aerosol treatments was observed to be relevant, inducing spatial deviations and integrated water vapor transport (IVT) magnitude reinforcements/attenuations with respect to the BASE simulation depending on the aerosol configuration. Thus, the correct inclusion of aerosol effects is important for the simulation of AR behavior at both global and regional scales, which is essential for meteorological predictions and climate change projections.</p

P-Stereogenic Phosphines for the Stabilisation of Metal Nanoparticles. A Surface State Study

Palladium and ruthenium nanoparticles have been prepared following the organometallic precursor decomposition methodology, under dihydrogen pressure and in the presence of borane protected P-stereogenic phosphines. NMR (Nuclear Magnetic Resonance) monitoring of the corresponding syntheses has permitted to determine the optimal metal/ligand ratio for leading to small and well-dispersed nanoparticles. Exchange ligand reactions of the as-prepared materials have proven the strong interaction of the phosphines with the metal surface; only oxidative treatment using hydrogen peroxide could release the phosphine-based stabiliser from the metal surface. Pd and Ru nanoparticles have been evaluated in hydrogenation reactions, confirming the robustness of the stabilisers, which selectively permitted the hydrogenation of exocyclic C=C bonds, preventing the coordination of the aromatic rings and as a result, their hydrogenation

Linaclotide utilization and potential for off-label use and misuse in three European countries

INTRODUCTION Linaclotide is approved for adults with moderate-to-severe irritable bowel syndrome (IBS) with constipation (IBS-C). Linaclotide is not indicated for weight loss or for patients with inflammatory bowel disease (IBD); it is contraindicated in patients with mechanical bowel obstruction (MBO). Some patients with obesity or eating disorders (ED) may use linaclotide off-label for weight loss or as a laxative. OBJECTIVES To describe the use of linaclotide in clinical practice, including patients with potential for off-label use or misuse. METHODS Post-authorization safety study conducted in three databases from the linaclotide launch date to 2017: the Clinical Practice Research Datalink in the United Kingdom (UK), the Information System for Research in Primary Care database in Spain and the linked Patient, Prescription and Causes of Death Registries in Sweden. Cohorts of patients were identified as having IBS using diagnostic and treatment codes; IBS subtypes were identified using symptoms and treatment codes; patients with obesity, ED, MBO, and IBD were identified using diagnostic codes or body mass index. RESULTS There were 1319, 1981, and 5081 linaclotide users from the United Kingdom, Spain, and Sweden with a median age of 45, 57, and 51 years, respectively; most were females. In the United Kingdom, Spain, and Sweden, respectively: 59.0%, 60.3%, and 31.3% of linaclotide users had an IBS diagnosis recorded, and among those, 68.8%, 61.3%, and 92.7% were classified as IBS-C. The proportions of linaclotide users considered at risk for potential off-label use for weight loss or as a laxative were 17.1%, 29.7%, and 1.7%, and the proportions of users considered at risk of misuse due to a history of MBO or IBD were 3.5%, 4.6%, and 5.7% in the United Kingdom, Spain, and Sweden, respectively. CONCLUSIONS Potential linaclotide off-label use and misuse appears limited, as evidenced by the small sizes of the patient subgroups at risk for off-label use and misuse

A multiscale orchestrated computational framework to reveal emergent phenomena in neuroblastoma

Neuroblastoma is a complex and aggressive type of cancer that affects children. Current treatments involve a combination of surgery, chemotherapy, radiotherapy, and stem cell transplantation. However, treatment outcomes vary due to the heterogeneous nature of the disease. Computational models have been used to analyse data, simulate biological processes, and predict disease progression and treatment outcomes. While continuum cancer models capture the overall behaviour of tumours, and agent-based models represent the complex behaviour of individual cells, multiscale models represent interactions at different organisational levels, providing a more comprehensive understanding of the system. In 2018, the PRIMAGE consortium was formed to build a cloud-based decision support system for neuroblastoma, including a multi-scale model for patient-specific simulations of disease progression. In this work we have developed this multi-scale model that includes data such as patient's tumour geometry, cellularity, vascularization, genetics and type of chemotherapy treatment, and integrated it into an online platform that runs the simulations on a high-performance computation cluster using Onedata and Kubernetes technologies. This infrastructure will allow clinicians to optimise treatment regimens and reduce the number of costly and time-consuming clinical trials. This manuscript outlines the challenging framework's model architecture, data workflow, hypothesis, and resources employed in its development

Tumour growth: An approach to calibrate parameters of a multiphase porous media model based on in vitro observations of Neuroblastoma spheroid growth in a hydrogel microenvironment

To unravel processes that lead to the growth of solid tumours, it is necessary to link knowledge of cancer biology with the physical properties of the tumour and its interaction with the surrounding microenvironment. Our understanding of the underlying mechanisms is however still imprecise. We therefore developed computational physics-based models, which incorporate the interaction of the tumour with its surroundings based on the theory of porous media. However, the experimental validation of such models represents a challenge to its clinical use as a prognostic tool. This study combines a physics-based model with in vitro experiments based on microfluidic devices used to mimic a three-dimensional tumour microenvironment. By conducting a global sensitivity analysis, we identify the most influential input parameters and infer their posterior distribution based on Bayesian calibration. The resulting probability density is in agreement with the scattering of the experimental data and thus validates the proposed workflow. This study demonstrates the huge challenges associated with determining precise parameters with usually only limited data for such complex processes and models, but also demonstrates in general how to indirectly characterise the mechanical properties of neuroblastoma spheroids that cannot feasibly be measured experimentally

A multiscale orchestrated computational framework to reveal emergent phenomena in neuroblastoma

Neuroblastoma is a complex and aggressive type of cancer that affects children. Current treatments involve a combination of surgery, chemotherapy, radiotherapy, and stem cell transplantation. However, treatment outcomes vary due to the heterogeneous nature of the disease. Computational models have been used to analyse data, simulate biological processes, and predict disease progression and treatment outcomes. While continuum cancer models capture the overall behaviour of tumours, and agent-based models represent the complex behaviour of individual cells, multiscale models represent interactions at different organisational levels, providing a more comprehensive understanding of the system. In 2018, the PRIMAGE consortium was formed to build a cloud-based decision support system for neuroblastoma, including a multi-scale model for patient-specific simulations of disease progression. In this work we have developed this multi-scale model that includes data such as patient's tumour geometry, cellularity, vascularization, genetics and type of chemotherapy treatment, and integrated it into an online platform that runs the simulations on a high-performance computation cluster using Onedata and Kubernetes technologies. This infrastructure will allow clinicians to optimise treatment regimens and reduce the number of costly and time-consuming clinical trials. This manuscript outlines the challenging framework's model architecture, data workflow, hypothesis, and resources employed in its development

Validation of the SF-36 in patients with endometriosis.

OBJECTIVES: Endometriosis presents with significant pain as the most common symptom. Generic health measures can allow comparisons across diseases or populations. However, the Medical Outcomes Study Short Form 36 (SF-36) has not been validated for this disease. The goal of this study was to validate the SF-36 (version 2) for endometriosis. METHODS: Using data from two clinical trials (N = 252 and 198) of treatment for endometriosis, a full complement of psychometric analyses was performed. Additional instruments included a pain visual analog scale (VAS); a physician-completed questionnaire based on patient interview (modified Biberoglu and Behrman--B&B); clinical global impression of change (CGI-C); and patient satisfaction with treatment. RESULTS: Bodily pain (BP) and the Physical Component Summary Score (PCS) were correlated with the pain VAS at baseline and over time and the B&B at baseline and end of study. In addition, those who had the greatest change in BP and PCS also reported the greatest change on CGI-C and patient satisfaction with treatment. Other subscales showed smaller, but significant, correlations with change in the pain VAS, CGI-C, and patient satisfaction with treatment. CONCLUSIONS: The SF-36--particularly BP and the PCS--appears to be a valid and responsive measure for endometriosis and its treatment