Metabolomic evaluation of Mitomycin C and rapamycin in a personalized treatment of pancreatic cancer

In a personalized treatment designed for a patient with pancreatic cancer resistant to other treatments, the success of Mitomycin C (MMC) has been highlighted. This was revealed in a murine xenograft tumor model encompassing pancreatic adenocarcinoma cells extracted from the patient. The patient was found to exhibit a biallelic inactivation of the PALB2 gene, involved in DNA repair in addition to another mutation in the TSC2 gene that induces susceptibility of the tumor to therapeutic targets of the PI3K-mTOR pathway. The aim of the study was to apply metabolomics to elucidate the modes of action of each therapy, suggesting why MMC was so successful in this patient and why it could be a more popular choice in future pancreatic cancer treatment. The effectiveness of MMC compared to rapamycin (RM), another relevant therapeutic agent has been evaluated through liquid- and gas-chromatography mass spectrometry-based metabolomic analyses of the xenograft tumors. The relative concentrations of many metabolites in the xenograft tumors were found to be increased by MMC relative to other treatments (RM and a combination of both), including a number that are involved in central carbon metabolism (CCM). Metabolic fingerprinting revealed statistically significantly altered pathways including, but not restricted to, the pentose phosphate pathway, glycolysis, TCA cycle, purine metabolism, fatty acid biosynthesis, in addition to many significant lipid and amino acid alterations. Given the genetic background of the patient, it was expected that the combined therapy would be most effective; however, the most effective was MMC alone. It is proposed that the effectiveness of MMC is owed to its direct effect on CCM, a vital region of tumor metabolism

Theoretical priors in scalar-tensor cosmologies: Shift-symmetric Horndeski models

Attempts at constraining theories of late time accelerated expansion often assume broad priors for the parameters in their phenomenological description. Focusing on shift-symmetric scalar-tensor theories with standard gravitational wave speed, we show how a more careful analysis of their dynamical evolution leads to much narrower priors. In doing so, we propose a simple and accurate parametrisation of these theories, capturing the redshift dependence of the equation of state, $w(z)$, and the kinetic braiding parameter, $\alpha_{\rm B}(z)$, with only two parameters each, and derive their statistical distribution (a.k.a. theoretical priors) that fit the cosmology of the underlying model. We have considered two versions of the shift-symmetric model, one where the energy density of dark energy is given solely by the scalar field, and another where it also has a contribution from the cosmological constant. By including current data, we show how theoretical priors can be used to improve constraints by up to an order of magnitude. Moreover, we show that shift-symmetric theories without a cosmological constant are observationally viable. We work up to quartic order in first derivatives of the scalar in the action and our results suggest this truncation is a good approximation to more general shift-symmetric theories. This work establishes an actionable link between phenomenological parameterisations and Lagrangian-based theories, the two main approaches to test cosmological gravity and cosmic acceleration.Comment: 18 pages, 13 figures; Version as accepted in PRD - minor changes

A realist interpretation of quantum mechanics based on undecidability due to gravity

We summarize several recent developments suggesting that solving the problem of time in quantum gravity leads to a solution of the measurement problem in quantum mechanics. This approach has been informally called "the Montevideo interpretation". In particular we discuss why definitions in this approach are not "for all practical purposes" (fapp) and how the problem of outcomes is resolved.Comment: 7 pages, IOPAMS style, no figures, contributed to the proceedings of DICE 2010, Castiglioncello, slightly improved versio

Analytical marginalisation over photometric redshift uncertainties in cosmic shear analyses

As the statistical power of imaging surveys grows, it is crucial to account for all systematic uncertainties. This is normally done by constructing a model of these uncertainties and then marginalizing over the additional model parameters. The resulting high dimensionality of the total parameter spaces makes inferring the cosmological parameters significantly more costly using traditional Monte-Carlo sampling methods. A particularly relevant example is the redshift distribution, $p(z)$, of the source samples, which may require tens of parameters to describe fully. However, relatively tight priors can be usually placed on these parameters through calibration of the associated systematics. In this paper we show, quantitatively, that a linearisation of the theoretical prediction with respect to these calibratable systematic parameters allows us to analytically marginalise over these extra parameters, leading to a factor $\sim30$ reduction in the time needed for parameter inference, while accurately recovering the same posterior distributions for the cosmological parameters that would be obtained through a full numerical marginalisation over 160 $p(z)$ parameters. We demonstrate that this is feasible not only with current data and current achievable calibration priors but also for future Stage-IV datasets.Comment: 11 pages, 8 figures, prepared for submission to MNRAS, comments welcom

Analytical marginalization over photometric redshift uncertainties in cosmic shear analyses

As the statistical power of imaging surveys grows, it is crucial to account for all systematic uncertainties. This is normally done by constructing a model of these uncertainties and then marginalizing over the additional model parameters. The resulting high dimensionality of the total parameter spaces makes inferring the cosmological parameters significantly more costly using traditional Monte Carlo sampling methods. A particularly relevant example is the redshift distribution, p(⁠z ), of the source samples, which may require tens of parameters to describe fully. However, relatively tight priors can be usually placed on these parameters through calibration of the associated systematics. In this paper, we show, quantitatively, that a linearization of the theoretical prediction with respect to these calibrated systematic parameters allows us to analytically marginalize over these extra parameters, leading to a factor of ∼30 reduction in the time needed for parameter inference, while accurately recovering the same posterior distributions for the cosmological parameters that would be obtained through a full numerical marginalization over 160 p(⁠z ) parameters. We demonstrate that this is feasible not only with current data and current achievable calibration priors but also for future Stage-IV data sets

Combined drug triads for synergic neuroprotection in retinal degeneration

This review focuses on retina degeneration occurring during glaucoma, age-related macular degeneration (AMD), diabetic retinopathy (DR), and retinitis pigmentosa (RP), and on the potential therapeutic use of triads of repositioned medicines, addressed to distinct but complementary targets, to prevent, delay or stop retina cell death. Although myriad pathogenic mechanisms have been implicated in these disorders, common signaling pathways leading to apoptotic cell death to all of them, and to all neurodegenerative diseases are (i) calcium dyshomeostasis/excitotoxicity; (ii) oxidative stress/mitochondrial dysfunction, and (iii) neuroinflammation/P2X7 receptor activation. From a therapeutic point of view, it is relevant to consider the multitarget approach based on the use of combined medicines acting on complementary pathogenic mechanisms that has been highly successful in the treatment of chronic diseases such as cancer, AIDS, pain, hypertension, Parkinson’s disease, cardiac failure, depression, or the epilepsies as the basic mechanisms of cell death do not differ between the different CNS degenerative diseases. We suggest the multi-target therapy approach could be more effective compared with single-drug treatments. Used at doses lower than standard, these triads may also be safer and more efficient. After the establishment of a proof-of-concept in animal models of retinal degeneration, potential successful preclinical trials of such combinations may eventually drive to test this concept in clinical trials in patients, first to evaluate the safety and efficacy of the drug combinations in humans and then their therapeutic advantages, if any, seeking the prevention and/or the delay of retina degeneration and blindness.We thank the support received from the EU Horizon 2020 Research and Innovation Program under Maria Slodowska‐Curie, Grant/Award Number: Grant Agreement N. 766124; Fundación Teófilo Hernando; Spanish Ministry of Science and Innovation (FEDER-PID2019-106230RB-I00) and Generalitat Valenciana (IDIFEDER/2017/064, PROMETEO/2021/024)

Detection and Analysis of Anomalies in People Density and Mobility Through Wireless Smartphone Tracking

One of the challenges of this century is to use the data that a smart-city provides to make life easier for its inhabitants. Speci cally, within the area of urban mobility, the possibility of detecting anomalies in the movement of pedestrians and vehicles is an issue of vital importance for the planning and administration of a city. The aim of this paper is to propose a methodology to detect the movement of people from the information transmitted by their smart mobile devices, analyze these data, and be able to detect or recognize anomalies in their behavior. In order to validate this methodology, different experiments have been carried out based on real data aiming to extract knowledge, as well as obtaining a characterisation of the anomalies detected. The use of this methodology might help the city policy makers to better manage their mobility and transport resources.This work was supported by in part by the Dirección General de Tráfico under Project SPIP2017-02116, in part by the Ministerio de Ciencia, Innovación y Universidades under Grant RTI2018-102002-A-I00, in part by the Ministerio español de Economía y Competitividad under Grant TIN2017-85727-C4-2-P, in part by the FEDER under Grant TEC2015-68752, and in part by the FEDER y Junta de Andalucía under Project B-TIC-402-UGR18

Lie symmetries and solitons in nonlinear systems with spatially inhomogeneous nonlinearities

Using Lie group theory and canonical transformations we construct explicit solutions of nonlinear Schrodinger equations with spatially inhomogeneous nonlinearities. We present the general theory, use it to show that localized nonlinearities can support bound states with an arbitrary number solitons and discuss other applications of interest to the field of nonlinear matter waves