Platinum-Nucleos(t)ide Compounds as Possible Antimetabolites for Antitumor/Antiviral Therapy: Properties and Perspectives

Nucleoside analogues (NAs) are a family of compounds which include a variety of purine and pyrimidine derivatives, widely used as anticancer and antiviral agents. For their ability to compete with physiological nucleosides, NAs act as antimetabolites exerting their activity by interfering with the synthesis of nucleic acids. Much progress in the comprehension of their molecular mechanisms has been made, including providing new strategies for potentiating anticancer/antiviral activity. Among these strategies, new platinum-NAs showing a good potential to improve the therapeutic indices of NAs have been synthesized and studied. This short review aims to describe the properties and future perspectives of platinum-NAs, proposing these complexes as a new class of antimetabolites

A finite-volume scheme for fractional diffusion on bounded domains

We propose a new fractional Laplacian for bounded domains, expressed as a conservation law and thus particularly suited to finite-volume schemes. Our approach permits the direct prescription of no-flux boundary conditions. We first show the well-posedness theory for the fractional heat equation. We also develop a numerical scheme, which correctly captures the action of the fractional Laplacian and its anomalous diffusion effect. We benchmark numerical solutions for the Lévy–Fokker–Planck equation against known analytical solutions. We conclude by numerically exploring properties of these equations with respect to their stationary states and long-time asymptotics

Burpee interval training is associated with a more favorable affective valence and psychological response than traditional high intensity exercise

Acute psychological responses to physical activity may help explain long-term adherence to it. Thus, we compared acute psychological responses to different exercise protocols with identical durations. Eighteen moderately active young adults [Mage = 23, SD = 3 years; MVO2max (maximum oxygen consumption) = 42.8, SD = 4.3 mL kg1 min1 ; MBMI (body mass index) = 24, SD = 2 kg m2 ] completed three low-volume exercise sessions in a crossover research design: (a) sprint interval training (SIT), (b) burpee interval training (BIT) requiring 10 × 5 second efforts with 35 seconds of passive recovery, and (c) a single bout of vigorous intensity continuous training (VICT) requiring 6 minutes and 5 seconds of running at ∼85% of peak heart rate (HRpeak). We assessed participants’ ratings of perceived exertion (RPE), affective valence, enjoyment, intention, preference, and self-reported recovery and wellness before, during, and after each session. BIT was associated with significantly greater enjoyment, preference, and exercise intention (at 5 × week) than VICT (p ≤ .05). SIT elicited greater RPE (M = 5.38, SD = 2.00) than both BIT (M = 2.88, SD = 1.23) and VICT (M = 3.55, SD = 1.38) (p ≤ .05), and we observed a higher increase in RPE over time with SIT versus BIT (p = .019). For affective valence, SIT (M = 0.55, SD = 2.12) elicited a more aversive response than both BIT (M = 2.55, SD = 1.09) and VICT (M = 1.94, SD = 1.51) (p ≤ .05), and there was a higher increase in this aversive response to SIT over time (p < .05). Forty-eight-hour postexercise session muscle soreness was significantly lower with VICT than with BIT (p = .03). Overall, BIT was associated with more positive psychological responses than SIT and VICT

Recent GRBs observed with the 1.23m CAHA telescope and the status of its upgrade

We report on optical observations of Gamma-Ray Bursts (GRBs) followed up by our collaboration with the 1.23m telescope located at the Calar Alto observatory. The 1.23m telescope is an old facility, currently undergoing upgrades to enable fully autonomous response to GRB alerts. We discuss the current status of the control system upgrade of the 1.23m telescope. The upgrade is being done by the ARAE our group, based on members of IAA (Instituto de Astrofiisica de Andalucia). Currently the ARAE group is responsible to develop the BOOTES network of robotic telescopes based on the Remote Telescope System, 2nd Version (RTS2), which controls the available instruments and interacts with the EPICS database of Calar Alto. Currently the telescope can run fully autonomously or under observer supervision using RTS2. The fast reaction response mode for GRB reaction (typically with response times below 3 minutes from the GRB onset) still needs some development and testing. The telescope is usually operated in legacy interactive mode, with periods of supervised autonomous runs under RTS2. We show the preliminary results of several GRBs followed up with observer intervention during the testing phase of the 1.23m control software upgrade.Comment: 15 pages, 7 figures. Accepted for publication in the Special issue "Robotic Astronomy" of Advances in Astronomy. It includes two iterations with the referee

An attempt to analyse Iterative Data Snooping and L1-norm based on Monte Carlo simulation in the context of leveling networks

[EN] The goal of this paper is to evaluate the outlier identification performance of iterative Data Snooping (IDS) and L-1-norm in levelling networks by considering the redundancy of the network, number and size of the outliers. For this purpose, several Monte-Carlo experiments were conducted into three different levelling networks configurations. In addition, a new way to compare the results of IDS based on Least Squares (LS) residuals and robust estimators such as the L-1-norm has also been developed and presented. From the perspective of analysis only according to the success rate, it is shown that L-1-norm performs better than IDS for the case of networks with low redundancy ((r) over bar < 0.5), especially for cases where more than one outlier is present in the dataset. In the relationship between false positive rate and outlier identification success rate, however, IDS performs better than L-1-norm, independently of the levelling network configuration, number and size of outliers.Klein, I.; Suraci, SS.; De Oliveira, LC.; Rofatto, VF.; Matsuoka, MT.; Baselga Moreno, S. (2022). An attempt to analyse Iterative Data Snooping and L1-norm based on Monte Carlo simulation in the context of leveling networks. Survey Review. 54(382):70-78. https://doi.org/10.1080/00396265.2021.187833870785438

Performance comparison of least squares, iterative and global L1 Norm minimization and exhaustive search methods for outlier detection in leveling networks

[EN] Different approaches have been proposed to determine the possible outliers existing in a dataset. The most widely used consists in the application of the data snooping test over the least squares adjustment results. This strategy is very likely to succeed for the case of zero or one outliers but, contrary to what is often assumed, the same is not valid for the multiple outlier case, even in its iterative application scheme. Robust estimation, computed by iteratively reweighted least squares or a global optimization method, is other alternative approach which often produces good results in the presence of outliers, as is the case of exhaustive search methods that explore elimination of every possible set of observations. General statements, having universal validity, about the best way to compute a geodetic network with multiple outliers are impossible to be given due to the many different factors involved (type of network, number and size of possible errors, available computational force, etc.). However, we see in this paper that some conclusions can be drawn for the case of a leveling network, which has a certain geometrical simplicity compared with planimetric or three-dimensional networks though a usually high number of unknowns and relatively low redundancy. Among other results, we experience the occasional failure in the iterative application of the data snooping test, the relatively successful results obtained by both methods computing the robust estimator, which perform equivalently in this case, and the successful application of the exhaustive search method, for different cases that become increasingly intractable as the number of outliers approaches half the number of degrees of freedom of the network.Baselga Moreno, S.; Klein, I.; Suraci, SS.; Castro De Oliveira, L.; Matsuoka, MT.; Rofatto, VF. (2020). Performance comparison of least squares, iterative and global L1 Norm minimization and exhaustive search methods for outlier detection in leveling networks. Acta Geodynamica et Geomaterialia. 17(4):425-438. https://doi.org/10.13168/AGG.2020.003142543817

Global Optimization of Redescending Robust Estimators

[EN] Robust estimation has proved to be a valuable alternative to the least squares estimator for the cases where the dataset is contaminated with outliers. Many robust estimators have been designed to be minimally affected by the outlying observations and produce a good fit for the majority of the data. Among them, the redescending estimators have demonstrated the best estimation capabilities. It is little known, however, that the success of a robust estimation method depends not only on the robust estimator used but also on the way the estimator is computed. In the present paper, we show that for complicated cases, the predominant method of computing the robust estimator by means of an iteratively reweighted least squares scheme may result in a local optimum of significantly lower quality than the global optimum attainable by means of a global optimization method. Further, the sequential use of the proposed global robust estimation proves to successfully solve the problem of M-split estimation, that is, the determination of parameters of different functional models implicit in the data.Baselga Moreno, S.; Klein, I.; Sampaio Suraci, S.; Castro De Oliveira, L.; Tomio Matsuoka, M.; Francisco Rofatto, V. (2021). Global Optimization of Redescending Robust Estimators. Mathematical Problems in Engineering. 2021:1-13. https://doi.org/10.1155/2021/9929892S113202

p-Branes from Generalized Yang-Mills Theory

We consider the reduced, quenched version of a generalized Yang-Mills action in 4k-dimensional spacetime. This is a new kind of matrix theory which is mapped through the Weyl-Wigner-Moyal correspondence into a field theory over a non-commutative phase space. We show that the ``classical'' limit of this field theory is encoded into the effective action of an open, (4k-1)-dimensional, bulk brane enclosed by a dynamical, Chern-Simons type, (4k-2)-dimensional, boundary brane. The bulk action is a pure volume term, while the boundary action carries all the dynamical degrees of freedom.Comment: 8 pages, LaTeX 2e, no figure

Toll-like Receptor Signaling-deficient Cells Enhance Antitumor Activity of Cell-based Immunotherapy by Increasing Tumor Homing

Cancer immunotherapy aims to activate the immune system. Some immunotherapeutic agents can be loaded in carrier cells for delivering to the tumors. However, a challenge with cell-based therapies is the selection of the appropriate cells to produce effective clinical outcomes. We hypothesize that therapies based on cells presenting a natural low proinflammatory profile ("silent cells") in the peripheral blood would result in better antitumor responses by increasing their homing to the tumor site. We studied our hypothesis in an immunotherapy model consisting of mesenchymal stromal cells (MSCs) carrying oncolytic adenoviruses for the treatment of immunocompetent mice. Toll-like receptor signaling-deficient cells (TLR4, TLR9, or MyD88 knockout) were used as "silent cells," while regular MSCs were used as control. Although in vitro migration was similar in regular and knockout carrier cells, in vivo tumor homing of silent cells was significantly higher after systemic administration. This better homing to the tumor site was highly related to the mild immune response triggered by these silent cells in peripheral blood. As a result, the use of silent cells significantly improved the antitumor efficacy of the treatment in comparison with the use of regular MSCs. While cancer immunotherapies generally aim to boost local immune responses in the tumor microenvironment, low systemic inflammation after systemic administration of the treatment may indeed enhance their tumor homing and improve the overall antitumor effect. These findings highlight the importance of selecting appropriate donor cells as therapeutic carriers in cell-based therapies for cancer treatment. Cells carrying drugs, virus, or other antitumor agents are commonly used for the treatment of cancer. This research shows that silent cells are excellent carriers for immunotherapies, improving tumor homing and enhancing the antitumor effect.This study was funded by Instituto de Salud Carlos III (grants PI14CIII/00005, PI17CIII/00013, and ISCIII-PFIS FI18CIII/00017), Consejería de Educación, Juventud y Deporte of Comunidad de Madrid (grant P2017/BMD-3692), Fundación Oncohematología Infantil, Asociación Pablo Ugarte and AFANION, whose support we gratefully acknowledge.S