Specific Targeting of Human Inflamed Endothelium and In Situ Vascular Tissue Transfection by the Use of Ultrasound Contrast Agents

ObjectivesWe used human umbilical cord segments as an ex vivo model to investigate the possible clinical diagnostic and therapeutic applications of microbubbles (MBs).BackgroundMicrobubbles are commonly used in clinical practice as ultrasound contrast agents. Several studies have addressed the in vivo applications of MBs for specific targeting of vascular dysfunction or sonoporation in animal models, but to date no human tissue model has been established.MethodsPrimary venular endothelial cell monolayers were targeted with MBs conjugated to an antibody against a highly expressed endothelial marker (tetraspanin CD9), and binding was assessed under increasing flow rates (0.5 to 5 dynes/cm2). Furthermore, CD9-coupled MB endothelial targeting was measured under flow conditions by contrast-enhanced ultrasound analysis in an ex vivo human macrovascular model (umbilical cord vein), and the same tissue model was used for the detection of inflamed vasculature with anti-intercellular adhesion molecule (ICAM)-1–coated MBs. Finally, plasmids encoding fluorescent proteins were sonoporated into umbilical cord vessels.ResultsSpecific endothelial targeting in the in vitro and ex vivo models described previously was achieved by the use of MBs covered with an anti-CD9. Furthermore, we managed to induce inflammation in umbilical cord veins and detect it with real-time echography imaging using anti–ICAM-1–coupled MBs. Moreover, expression and correct localization of green fluorescent protein and green fluorescent protein-tagged ICAM-1 were assessed in this human ex vivo model without causing vascular damage.ConclusionsIn the absence of clinical trials to test the benefits and possible applications of ultrasound contrast agents for molecular imaging and therapy, we have developed a novel ex vivo human model using umbilical cords that is valid for the detection of inflammation and for exogenous expression of proteins by sonoporation

CD81 controls sustained T cell activation signaling and defines the maturation stages of cognate immunological synapses

In this study, we investigated the dynamics of the molecular interactions of tetraspanin CD81 in T lymphocytes, and we show that CD81 controls the organization of the immune synapse (IS) and T cell activation. Using quantitative microscopy, including fluorescence recovery after photobleaching (FRAP), phasor fluorescence lifetime imaging microscopy-Föster resonance energy transfer (phasorFLIM-FRET), and total internal reflection fluorescence microscopy (TIRFM), we demonstrate that CD81 interacts with ICAM-1 and CD3 during conjugation between T cells and antigen-presenting cells (APCs). CD81 and ICAM-1 exhibit distinct mobilities in central and peripheral areas of early and late T cell-APC contacts. Moreover, CD81-ICAM-1 and CD81- CD3 dynamic interactions increase over the time course of IS formation, as these molecules redistribute throughout the contact area. Therefore, CD81 associations unexpectedly define novel sequential steps of IS maturation. Our results indicate that CD81 controls the temporal progression of the IS and the permanence of CD3 in the membrane contact area, contributing to sustained T cell receptor (TCR)-CD3-mediated signaling. Accordingly, we find that CD81 is required for proper T cell activation, regulating CD3ζ, ZAP-70, LAT, and extracellular signal-regulated kinase (ERK) phosphorylation; CD69 surface expression; and interleukin- 2 (IL-2) secretion. Our data demonstrate the important role of CD81 in the molecular organization and dynamics of the IS architecture that sets the signaling threshold in T cell activationThis work was supported by SAF2011-25834 from the Spanish Ministry of Science and Innovation, INDISNET-S2011/BMD-2332 from the Comunidad de Madrid, Cardiovascular Network RD12-0042-0056 from the Instituto Salud Carlos III, and ERC-2011-AdG 294340-GENTRI

Endothelial adhesion receptors are recruited to adherent leukocytes by inclusion in preformed tetraspanin nanoplatforms

VCAM-1 and ICAM-1, receptors for leukocyte integrins, are recruited to cell–cell contact sites on the apical membrane of activated endothelial cells. In this study, we show that this recruitment is independent of ligand engagement, actin cytoskeleton anchorage, and heterodimer formation. Instead, VCAM-1 and ICAM-1 are recruited by inclusion within specialized preformed tetraspanin-enriched microdomains, which act as endothelial adhesive platforms (EAPs). Using advanced analytical fluorescence techniques, we have characterized the diffusion properties at the single-molecule level, nanoscale organization, and specific intradomain molecular interactions of EAPs in living primary endothelial cells. This study provides compelling evidence for the existence of EAPs as physical entities at the plasma membrane, distinct from lipid rafts. Scanning electron microscopy of immunogold-labeled samples treated with a specific tetraspanin-blocking peptide identify nanoclustering of VCAM-1 and ICAM-1 within EAPs as a novel mechanism for supramolecular organization that regulates the leukocyte integrin–binding capacity of both endothelial receptors during extravasation

RICORS2040 : The need for collaborative research in chronic kidney disease

Chronic kidney disease (CKD) is a silent and poorly known killer. The current concept of CKD is relatively young and uptake by the public, physicians and health authorities is not widespread. Physicians still confuse CKD with chronic kidney insufficiency or failure. For the wider public and health authorities, CKD evokes kidney replacement therapy (KRT). In Spain, the prevalence of KRT is 0.13%. Thus health authorities may consider CKD a non-issue: very few persons eventually need KRT and, for those in whom kidneys fail, the problem is 'solved' by dialysis or kidney transplantation. However, KRT is the tip of the iceberg in the burden of CKD. The main burden of CKD is accelerated ageing and premature death. The cut-off points for kidney function and kidney damage indexes that define CKD also mark an increased risk for all-cause premature death. CKD is the most prevalent risk factor for lethal coronavirus disease 2019 (COVID-19) and the factor that most increases the risk of death in COVID-19, after old age. Men and women undergoing KRT still have an annual mortality that is 10- to 100-fold higher than similar-age peers, and life expectancy is shortened by ~40 years for young persons on dialysis and by 15 years for young persons with a functioning kidney graft. CKD is expected to become the fifth greatest global cause of death by 2040 and the second greatest cause of death in Spain before the end of the century, a time when one in four Spaniards will have CKD. However, by 2022, CKD will become the only top-15 global predicted cause of death that is not supported by a dedicated well-funded Centres for Biomedical Research (CIBER) network structure in Spain. Realizing the underestimation of the CKD burden of disease by health authorities, the Decade of the Kidney initiative for 2020-2030 was launched by the American Association of Kidney Patients and the European Kidney Health Alliance. Leading Spanish kidney researchers grouped in the kidney collaborative research network Red de Investigación Renal have now applied for the Redes de Investigación Cooperativa Orientadas a Resultados en Salud (RICORS) call for collaborative research in Spain with the support of the Spanish Society of Nephrology, Federación Nacional de Asociaciones para la Lucha Contra las Enfermedades del Riñón and ONT: RICORS2040 aims to prevent the dire predictions for the global 2040 burden of CKD from becoming true

CD81 regula la migración celular a través de su asociación con la GTPasa Rac

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid. Facultad de Medicina, Departamento de Bioquímica. Fecha de lectura: 15 de Febrero de 201

Recent studies on antifouling systems to artificial structures in marine ecosystem

Any artificial structure in contact which serves as a base for macro-organisms to grow on. It is known the biofouling phenomenon, as well as the negative consequences that it means for the artificial structures in contact with seawater in form of structural defects and of additional expenses for the companies which develop their work in the marine scope due to the processes of cleaning and prevention, the evolution in the world of the technology of antifouling paintings, once we analysed the serious environmental problems caused by an indiscriminate use of biocides of high toxicity in its composition as they are the organic derivatives of tin compounds made up and of the uncontrolled emission of volatile organic compounds (VOC) to the atmosphere, according to the present environmental norm, has as only aim to develop environmentally innocuous coverings based on water in which extracts of the very same marine world are used as biocides compound

Decision-making on an explicit risk-taking task in children and adolescents with high intellectual abilities: a neuropsychological perspective

Objective: Two processing pathways have been described in explicit risk decision-making tasks: an emotional and a cognitive feedback pathway. The objective of the study was to examine decision-making on an explicit risk-taking task in children and adolescents with high intellectual abilities compared with a control group typical development and to determine whether their execution is similar or different. Methods: This study explores differences in quality of decision making between gifted (n = 28) and average intellectual ability (n = 37) students of two different age groups (children vs. adolescents). Groups were compared using the scores obtained in the Cambridge Gambling Task (CGT). Results: Results show that gifted students displayed better decision making as evidenced by higher cognitive self-control to postpone immediate rewards and quality of decision when compared to the control group. Deliberation time in gifted was faster in the adolescent group and slower in the child group. Conclusion: This finding suggests developmental influences that need to be considered to explain the effects of the G factor in decision making skills. Procedures help to reflect upon the contribution of controlled cognitive tasks in elucidating abilities related to general intelligence. Neuropsychological basis of decision-making is briefly discussed.Depto. de Psicobiología y Metodología en Ciencias del ComportamientoFac. de EducaciónTRUEpu

Estrategia didáctica para la formación del valor responsabilidad

El artículo tiene como objetivo presentar la propuesta de una estrategia didáctica para la formación del valor responsabilidad en los estudiantes de la licenciatura en Educación Física y Deporte en la Universidad Autónoma del Carmen, México. En la investigación que da origen a este trabajo se aplicaron diversas técnicas y métodos en el diagnóstico inicial del estado de la formación del valor responsabilidad, la elaboración del marco teórico, el desarrollo de la estrategia didáctica y su aplicación en la citada profesión. Los resultados señalan la viabilidad de aplicar los elementos teóricos y prácticos que constituyen las aportaciones del estudio, con sus correspondientes adecuaciones, a otros contextos universitarios, así como en el proceso formativo de posgrado

Analysis of the confidence in the prediction of the protein folding by artificial intelligence

6 p.-4 fig.-1 tab.The determination of protein structure has been facilitated using deep learning models, which can predict protein folding from protein sequences. In some cases, the predicted structure can be compared to the already-known distribution if there is information from classic methods such as nuclear magnetic resonance (NMR) spectroscopy, X-ray crystallography, or electron microscopy (EM). However, challenges arise when the proteins are not abundant, their structure is heterogeneous, and protein sample preparation is difficult. To determine the level of confidence that supports the prediction, different metrics are provided. These values are important in two ways: they offer information about the strength of the result and can supply an overall picture of the structure when different models are combined. This work provides an overview of the different deep-learning methods used to predict protein folding and the metrics that support their outputs. The confidence of the model is evaluated in detail using two proteins that contain four domains of unknown function.This work is a result of the project "Data-driven drug repositioning applying graph neural networks (3DR-GNN)", that is being developed under grant "PID2021-122659OB-I00" from the Spanish Ministerio de Ciencia e Innovación. This work was funded partially by Knowledge Spaces project (Grant PID2020-118274RB-I00 funded by MCIN/AEI/10.13039/501100011033)Peer reviewe

Analysis of the confidence in the prediction of the protein folding by artificial intelligence

6 p.-4 fig.The determination of protein structure has been facilitated using deep learning models, which can predict protein folding from protein sequences. In some cases, the predicted structure can be compared to the already-known distribution if there is information from classic methods such as nuclear magnetic resonance (NMR) spectroscopy, X-ray crystallography, or electron microscopy (EM). However, challenges arise when the proteins are not abundant, their structure is heterogeneous, and protein sample preparation is difficult. To determine the level of confidence that supports the prediction, different metrics are provided. These values are important in two ways: they offer information about the strength of the result and can supply an overall picture of the structure when different models are combined. This work provides an overview of the different deep-learning methods used to predict protein folding and the metrics that support their outputs. The confidence of the model is evaluated in detail using two proteins that contain four domains of unknown function.This work is a result of the project "Data-driven drug repositioning applying graph neural networks (3DR-GNN)", that is being developed under grant "PID2021-122659OB-I00" from the Spanish Ministerio de Ciencia e Innovación. This work was funded partially by Knowledge Spaces project (Grant PID2020-118274RB-I00 funded by MCIN/AEI/10.13039/501100011033)Peer reviewe