Optimizing metastatic-cascade-dependent Rac1 targeting in breast cancer: guidance using optical window intravital FRET imaging

Assessing drug response within live native tissue provides increased fidelity with regards to optimizing efficacy while minimizing off-target effects. Here, using longitudinal intravital imaging of a Rac1-Förster resonance energy transfer (FRET) biosensor mouse coupled with in vivo photoswitching to track intratumoral movement, we help guide treatment scheduling in a live breast cancer setting to impair metastatic progression. We uncover altered Rac1 activity at the center versus invasive border of tumors and demonstrate enhanced Rac1 activity of cells in close proximity to live tumor vasculature using optical window imaging. We further reveal that Rac1 inhibition can enhance tumor cell vulnerability to fluid-flow-induced shear stress and therefore improves overall anti-metastatic response to therapy during transit to secondary sites such as the lung. Collectively, this study demonstrates the utility of single-cell intravital imaging in vivo to demonstrate that Rac1 inhibition can reduce tumor progression and metastases in an autochthonous setting to improve overall survival.Alessia Floerchinger … Michael S. Sasmuel … et al

Monitoring AKT activity and targeting in live tissue and disease contexts using a real-time Akt-FRET biosensor mouse

Aberrant AKT activation occurs in a number of cancers, metabolic syndrome, and immune disorders, making it an important target for the treatment of many diseases. To monitor spatial and temporal AKT activity in a live setting, we generated an Akt-FRET biosensor mouse that allows longitudinal assessment of AKT activity using intravital imaging in conjunction with image stabilization and optical window technology. We demonstrate the sensitivity of the Akt-FRET biosensor mouse using various cancer models and verify its suitability to monitor response to drug targeting in spheroid and organotypic models. We also show that the dynamics of AKT activation can be monitored in real time in diverse tissues, including in individual islets of the pancreas, in the brown and white adipose tissue, and in the skeletal muscle. Thus, the Akt-FRET biosensor mouse provides an important tool to study AKT dynamics in live tissue contexts and has broad preclinical applications

Using the present to interpret the past: the role of ethnographic studies in Andean archaeology

Within Andean research it is common to use ethnographic analogies to aid the interpretation of archaeological remains, and ethnographers and archaeologists have developed shared research in technology, material culture and material practice. Although most of this research does not follow the detailed recording methods of spatial patterning envisioned in earlier formulations of ethnoarchaeology, it has had a profound effect on how archaeology in the region has been interpreted. This paper uses examples from the study of pottery production to address earlier debates about the use of ethnographic analogy, discusses the dangers of imposing an idealised or uniform vision of traditional Andean societies onto earlier periods (‘Lo Andino’) but stresses the benefits of combining ethnographic and archaeological research to explore continuities and changes in cultural practice and regional variations

Soft robotics systems for endoscopic interventions

The field of soft robotics has established itself as an important research topic within robotics, offering several advantages over traditional rigid robots. This paradigm shift introduced by advances in material science and manufacturing methods has enabled new capabilities. These emerging soft robotic systems can squeeze and move through narrow openings, elongate, navigate around obstacles, and are considered inherently safe. In particular, the healthcare domain has been identified as one of the areas that might benefit from applying soft robotic systems. This chapter focuses on the application of soft robotic systems for endoscopic interventions. At the outset, we provide an overview of endoscopic procedures and commercially available technologies and tools highlighting current challenges and how soft robotics might benefit. As soft robotic systems for healthcare application are a relatively young research area, we compiled a list of recommendations for creating soft robotic medical devices. Relevant topics include dimension requirements, biocompatibility as well as reliability of materials, durability specification, and ergonomics. Finally, a discussion of current soft robotic medical devices concerning the aforementioned endoscopic procedures will identify shortcomings and future research challenges

An empirical model for rainfall maximums conditioned to tropospheric water vapor over the Eastern Pacific Ocean

One of the most difficult weather variables to predict is rain, particularly intense rain. The main limitation is the complexity of the fluid dynamic equations used by predictive models with increasing uncertainties over time, especially in the description of brief, local, and high intensity precipitation events. Although computational, instrumental and theoretical improvements have been developed for models, it is still a challenge to estimate high intensity rainfall events, especially in terms of determining the maximum rainfall rates and the location of the event. Within this context, this research presents a statistical and relationship analysis of rainfall intensity rates, total precipitable water (TPW), and sea surface temperature (SST) over the ocean. An empirical model to estimate the maximum rainfall rates conditioned to TPW values is developed. The performance of the maximum rainfall rate model is spatially evaluated for a case study. High-resolution TRMM 2A12 satellite data with a resolution of 5.1 x 5.1 km and 1.67 s was used from January 2009 to December 2012, over the Eastern Pacific Nino area in the tropical Pacific Ocean (0-5 degrees S; 90-81 degrees W), comprising 326,092 rain pixels. After applying the model selection methodology, i.e., the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), an empirical exponential model between the maximum possible rain rates conditioned to TPW was found with R-2 = 0.96, indicating that the amount of TPW determines the maximum amount of rain that the atmosphere can precipitate exponentially. Spatially, this model unequivocally locates the rain event; however, the rainfall intensity is underestimated in the convective nucleus of the cloud. Thus, these results provide an additional constraint for maximum rain intensity values that should be adopted in dynamic models, improving the quantification of heavy rainfall event intensities and the correct location of these events

Machine Learning Techniques in Optical Networks: A Systematic Mapping Study

During the last decade, optical networks have become “smart networks”. Software-defined networks, software-defined optical networks, and elastic optical networks are some emerging technologies that provide a basis for promising innovations in the functioning and operation of optical networks. Machine learning algorithms are providing the possibility to develop this promising study area. Since machine learning can learn from a large amount of data available from the network elements. They can find a suitable solution for any environment and thus create more dynamic and flexible networks that improve the user experience. This paper performs a systematic mapping that provides an overview of machine learning in optical networks, identifies opportunities, and suggests future research lines. The study analyzed 96 papers from the 841 publications on this topic to find information about the use of machine learning techniques to solve problems related to the functioning and operation of optical networks. It is concluded that supervised machine learning techniques are mainly used for resource management, network monitoring, fault management, and traffic classification and prediction of an optical network. However, specific challenges need to be solved to successfully deploy this type of method in real communication systems since most of the research has been carried out in controlled experimental environments

Agentes Virtuales en Dispositivos Móviles

El incremento en las capacidades computacionales en los dispositivos móviles, ha despertado el interés de empresas e investigadores, en el desarrollo de Agentes Virtuales, que puedan ejecutarse sobre estos dispositivos. Este trabajo presenta el estado del arte, en lo referente al desarrollo de agentes virtuales sobre dispositivos móviles, nos permitirá ponernos en contexto sobre algunas plataformas que soportan su desarrollo y la arquitectura con la que se implementan, además de contextualizar las características y canales de comunicación utilizados para lograr que la interacción de un agente con el usuario sea la más real posible

Radiolysis of cytosine at cryogenic temperatures by swift heavy ion bombardments

We investigated the radiolysis effects on the cytosine in the solid phase irradiated by swift heavy ions as galactic cosmic ray analogues (GCRs). Infrared (IR) absorption spectroscopy was employed to monitor the physical and chemical radiolytic modifications. The targets were prepared on ZnSe in two different ways: (1) by dropping a nucleobase-water-ethanol solution on the substrate and evaporating the solvent and (2) by sublimation of nucleobase powders in an oven and condensation on the windows. Both types of samples present similar IR absorption spectra. From the exponential decrease of the areas of IR absorption bands as a function of projectile fluence, apparent destruction cross sections (σd) were determined and were found to be very similar for samples prepared using both techniques. The destruction cross section of solid cytosine at cryogenic temperatures follows an electronic stopping (Se) power law: σd = C Sen, where C is a constant and the exponential n is a dimensionless quantity. We determined σd = (3 ± 1) × 10-17 Se (1.25 ±0.06). New absorption features emerge from cytosine degradation, which can be attributed to OCN-, H2CO, and HNCO. By using the observed power law, the half-life of cytosine exposed to galactic cosmic rays was estimated in the order of Mega years. The findings reported here may help a better understanding of complex organic molecule radiostability