Phenotypic, morphological, and metabolic characterization of vascular-spheres from human vascular mesenchymal stem cells

The ability to form spheroids under non-adherent conditions is a well-known property of human mesenchymal stem cells (hMSCs), in addition to stemness and multilineage differentiation features. In the present study, we tested the ability of hMSCs isolated from the vascular wall (hVW-MSCs) to grow as spheres, and provide a characterization of this 3D model. hVW-MSCs were isolated from femoral arteries through enzymatic digestion. Spheres were obtained using ultra-low attachment and hanging drop methods. Immunophenotype and pluripotent genes (SOX-2, OCT-4, NANOG) were analyzed by immunocytochemistry and real-time PCR, respectively. Spheres histological and ultrastructural architecture were examined. Cell viability and proliferative capacity were measured using LIVE/DEATH assay and ki-67 proliferation marker. Metabolomic profile was obtained with liquid chromatography–mass spectrometry. In 2D, hVW-MSCs were spindle-shaped, expressed mesenchymal antigens, and displayed mesengenic potential. 3D cultures of hVW-MSCs were CD44+, CD105low, CD90low, exhibited a low propensity to enter the cell cycle as indicated by low percentage of ki-67 expression and accumulated intermediate metabolites pointing to slowed metabolism. The 3D model of hVW-MSCs exhibits stemness, dormancy and slow metabolism, typically observed in stem cell niches. This culture strategy can represent an accurate model to investigate hMSCs features for future clinical applications in the vascular field

Linguistic analysis of Latinx patients’ responses to a text messaging adjunct during cognitive behavioral therapy for depression

Cognitive behavioral therapy (CBT) is efficacious to treat depression, however more research is needed to understand its functions among Latinxs. This study analyzed qualitative responses that were paired with a mood rating (1–9 scale) from daily ecological momentary assessments via text-messaging of 52 low-income, Spanish-speaking patients to assess the relationship between word use and changes in mood during group CBT. Based on previous research, we chose 11 linguistic dimensions from the Linguistic Inquiry and Word Count text analysis software that conceptually related to core CBT treatment elements and sociocultural factors of depression in Latinxs. Results showed that the use of words from the categories of Friends, Religion, Positive Emotions, and Leisure (proxy for behavioral activation) were significantly associated with a significant increase in mood. The use of Negative Emotions and Health words were significantly associated with a significant decrease in mood. Post-hoc analysis revealed that Certainty (proxy for cognitive inflexibility) words were related to a significant decrease in mood when Negative Emotional words were present. Findings contribute to our understanding of the role of sociocultural factors and core CBT elements in changes in mood among Latinxs. Lastly, this paper demonstrates the potential for analyzing language content during a digital health intervention to better understand user experiences.Fil: Hernandez Ramos, Rosa. University of California at Irvine; Estados Unidos. University of California at Berkeley; Estados UnidosFil: Altszyler Lemcovich, Edgar Jaim. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Figueroa, Caroline A.. University of California at Berkeley; Estados UnidosFil: Avila Garcia, Patricia. University of California at Berkeley; Estados UnidosFil: Aguilera, Adriana Lucia. University of California at Berkeley; Estados Unidos. University of San Francisco; Estados Unido

Modelado de Procesos de Neurorrehabilitación

La Neurorrehabilitación es un proceso clínico que se centra en el abordaje de la alteración del sistema nervioso. Existe una enorme variabilidad tanto en la tipología como en el grado de las lesiones neurológicas, lo que la convierte en un proceso extremadamente complejo de analizar y comprender. El presente trabajo se centra en el modelado de las principales actividades que se llevan a cabo en el contexto de la Neurorrehabilitación actual con el objetivo de detectar aquellos puntos en que puedan ser mejoradas, tanto a nivel organizativo como a nivel de ejecución. Por otra parte, se trata de comprenderlas en profundidad para tratar de transformarlas posteriormente en nuevas actividades automatizadas y monitorizadas que se ajusten al nuevo paradigma de rehabilitación ubicua, personalizada y basada en la evidencia

Knowledge representation tool for cognitiveprocesses modeling

In the last decades, neuropsychological theories tend to consider cognitive functions as a result of the whole brainwork and not as individual local areas of its cortex. Studies based on neuroimaging techniques have increased in the last years, promoting an exponential growth of the body of knowledge about relations between cognitive functions and brain structures [1]. However, so fast evolution make complicated to integrate them in verifiable theories and, even more, translated in to cognitive rehabilitation. The aim of this research work is to develop a cognitive process-modeling tool. The purpose of this system is, in the first term, to represent multidimensional data, from structural and functional connectivity, neuroimaging, data from lesion studies and derived data from clinical intervention [2][3]. This will allow to identify consolidated knowledge, hypothesis, experimental designs, new data from ongoing studies and emerging results from clinical interventions. In the second term, we pursuit to use Artificial Intelligence to assist in decision making allowing to advance towards evidence based and personalized treatments in cognitive rehabilitation. This work presents the knowledge base design of the knowledge representation tool. It is compound of two different taxonomies (structure and function) and a set of tags linking both taxonomies at different levels of structural and functional organization. The remainder of the abstract is organized as follows: Section 2 presents the web application used for gathering necessary information for generating the knowledge base, Section 3 describes knowledge base structure and finally Section 4 expounds reached conclusions

DEVELOPMENT OF AN ALL-PURPOSE FREE PHOTOGRAMMETRIC TOOL

Photogrammetry is currently facing some challenges and changes mainly related to automation, ubiquitous processing and variety of applications. Within an ISPRS Scientific Initiative a team of researchers from USAL, UCLM, FBK and UNIBO have developed an open photogrammetric tool, called GRAPHOS (inteGRAted PHOtogrammetric Suite). GRAPHOS allows to obtain dense and metric 3D point clouds from terrestrial and UAV images. It encloses robust photogrammetric and computer vision algorithms with the following aims: (i) increase automation, allowing to get dense 3D point clouds through a friendly and easy-to-use interface; (ii) increase flexibility, working with any type of images, scenarios and cameras; (iii) improve quality, guaranteeing high accuracy and resolution; (iv) preserve photogrammetric reliability and repeatability. Last but not least, GRAPHOS has also an educational component reinforced with some didactical explanations about algorithms and their performance. The developments were carried out at different levels: GUI realization, image pre-processing, photogrammetric processing with weight parameters, dataset creation and system evaluation. The paper will present in detail the developments of GRAPHOS with all its photogrammetric components and the evaluation analyses based on various image datasets. GRAPHOS is distributed for free for research and educational needs

Dysfunctional 3D model based on structural and neuropsychological information

Acquired brain injury (ABI) 1-2 refers to any brain damage occurring after birth. It usually causes certain damage to portions of the brain. ABI may result in a significant impairment of an individuals physical, cognitive and/or psychosocial functioning. The main causes are traumatic brain injury (TBI), cerebrovascular accident (CVA) and brain tumors. The main consequence of ABI is a dramatic change in the individuals daily life. This change involves a disruption of the family, a loss of future income capacity and an increase of lifetime cost. One of the main challenges in neurorehabilitation is to obtain a dysfunctional profile of each patient in order to personalize the treatment. This paper proposes a system to generate a patient s dysfunctional profile by integrating theoretical, structural and neuropsychological information on a 3D brain imaging-based model. The main goal of this dysfunctional profile is to help therapists design the most suitable treatment for each patient. At the same time, the results obtained are a source of clinical evidence to improve the accuracy and quality of our rehabilitation system. Figure 1 shows the diagram of the system. This system is composed of four main modules: image-based extraction of parameters, theoretical modeling, classification and co-registration and visualization module

PHOTOMATCH: AN OPEN-SOURCE MULTI-VIEW and MULTI-MODAL FEATURE MATCHING TOOL for PHOTOGRAMMETRIC APPLICATIONS

Automatic feature matching is a crucial step in Structure-from-Motion (SfM) applications for 3D reconstruction purposes. From an historical perspective we can say now that SIFT was the enabling technology that made SfM a successful and fully automated pipeline. SIFT was the ancestor of a wealth of detector/descriptor methods that are now available. Various research activities have tried to benchmark detector/descriptors operators, but a clear outcome is difficult to be drawn. This paper presents an ISPRS Scientific Initiative aimed at providing the community with an educational open-source tool (called PhotoMatch) for tie point extractions and image matching. Several enhancement and decolorization methods can be initially applied to an image dataset in order to improve the successive feature extraction steps. Then different detector/descriptor combinations are possible, coupled with different matching strategies and quality control metrics. Examples and results show the implemented functionality of PhotoMatch which has also a tutorial for shortly explaining the implemented methods

Towards a combined use of geophysics and remote sensing techniques for the characterization of a singular building: “El Torreón” (the tower) at Ulaca oppidum (Solosancho, Ávila, Spain)

This research focuses on the study of the ruins of a large building known as “El Torreón” (the Tower), belonging to the Ulaca oppidum (Solosancho, Province of Ávila, Spain). Different remote sensing and geophysical approaches have been used to fulfil this objective, providing a better understanding of the building’s functionality in this town, which belongs to the Late Iron Age (ca. 300–50 BCE). In this sense, the outer limits of the ruins have been identified using photogrammetry and convergent drone flights. An additional drone flight was conducted in the surrounding area to find additional data that could be used for more global interpretations. Magnetometry was used to analyze the underground bedrock structure and ground penetrating radar (GPR) was employed to evaluate the internal layout of the ruins. The combination of these digital methodologies (surface and underground) has provided a new perspective for the improved interpretation of “El Torreón” and its characteristics. Research of this type presents additional guidelines for better understanding of the role of this structure with regards to other buildings in the Ulaca oppidum. The results of these studies will additionally allow archaeologists to better plan future interventions while presenting new data that can be used for the interpretation of this archaeological complex on a larger scale

A stroll through the loop-tree duality

The Loop-Tree Duality (LTD) theorem is an innovative technique to deal with multi-loop scattering amplitudes, leading to integrand-level representations over a Euclidean space. In this article, we review the last developments concerning this framework, focusing on the manifestly causal representation of multi-loop Feynman integrals and scattering amplitudes, and the definition of dual local counter-terms to cancel infrared singularities