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Brzezinski, K. et al. (2023). Detection of range shifts in proton beam therapy using the J-PET scanner: a patient simulation study. Phys. Med. Biol., 68(14), 145016–17pp.
Abstract: Objective. The Jagiellonian positron emission tomography (J-PET) technology, based on plastic scintillators, has been proposed as a cost effective tool for detecting range deviations during proton therapy. This study investigates the feasibility of using J-PET for range monitoring by means of a detailed Monte Carlo simulation study of 95 patients who underwent proton therapy at the Cyclotron Centre Bronowice (CCB) in Krakow, Poland. Approach. Discrepancies between prescribed and delivered treatments were artificially introduced in the simulations by means of shifts in patient positioning and in the Hounsfield unit to the relative proton stopping power calibration curve. A dual-layer, cylindrical J-PET geometry was simulated in an in-room monitoring scenario and a triple-layer, dual-head geometry in an in-beam protocol. The distribution of range shifts in reconstructed PET activity was visualized in the beam's eye view. Linear prediction models were constructed from all patients in the cohort, using the mean shift in reconstructed PET activity as a predictor of the mean proton range deviation. Main results. Maps of deviations in the range of reconstructed PET distributions showed agreement with those of deviations in dose range in most patients. The linear prediction model showed a good fit, with coefficient of determination r (2) = 0.84 (in-room) and 0.75 (in-beam). Residual standard error was below 1 mm: 0.33 mm (in-room) and 0.23 mm (in-beam). Significance. The precision of the proposed prediction models shows the sensitivity of the proposed J-PET scanners to shifts in proton range for a wide range of clinical treatment plans. Furthermore, it motivates the use of such models as a tool for predicting proton range deviations and opens up new prospects for investigations into the use of intra-treatment PET images for predicting clinical metrics that aid in the assessment of the quality of delivered treatment.
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Borys, D. et al, & Brzezinski, K. (2022). ProTheRaMon-a GATE simulation framework for proton therapy range monitoring using PET imaging. Phys. Med. Biol., 67(22), 224002–15pp.
Abstract: Objective. This paper reports on the implementation and shows examples of the use of the ProTheRaMon framework for simulating the delivery of proton therapy treatment plans and range monitoring using positron emission tomography (PET). ProTheRaMon offers complete processing of proton therapy treatment plans, patient CT geometries, and intra-treatment PET imaging, taking into account therapy and imaging coordinate systems and activity decay during the PET imaging protocol specific to a given proton therapy facility. We present the ProTheRaMon framework and illustrate its potential use case and data processing steps for a patient treated at the Cyclotron Centre Bronowice (CCB) proton therapy center in Krakow, Poland. Approach. The ProTheRaMon framework is based on GATE Monte Carlo software, the CASToR reconstruction package and in-house developed Python and bash scripts. The framework consists of five separated simulation and data processing steps, that can be further optimized according to the user's needs and specific settings of a given proton therapy facility and PET scanner design. Main results. ProTheRaMon is presented using example data from a patient treated at CCB and the J-PET scanner to demonstrate the application of the framework for proton therapy range monitoring. The output of each simulation and data processing stage is described and visualized. Significance. We demonstrate that the ProTheRaMon simulation platform is a high-performance tool, capable of running on a computational cluster and suitable for multi-parameter studies, with databases consisting of large number of patients, as well as different PET scanner geometries and settings for range monitoring in a clinical environment. Due to its modular structure, the ProTheRaMon framework can be adjusted for different proton therapy centers and/or different PET detector geometries. It is available to the community via github (Borys et al 2022).
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Di Gregorio, E., Staelens, M., Hosseinkhah, N., Karimpoor, M., Liburd, J., Lim, L., et al. (2024). Raman Spectroscopy Reveals Photobiomodulation-Induced α-Helix to β-Sheet Transition in Tubulins: Potential Implications for Alzheimer's and Other Neurodegenerative Diseases. Nanomaterials, 14(13), 1093–21pp.
Abstract: In small clinical studies, the application of transcranial photobiomodulation (PBM), which typically delivers low-intensity near-infrared (NIR) to treat the brain, has led to some remarkable results in the treatment of dementia and several neurodegenerative diseases. However, despite the extensive literature detailing the mechanisms of action underlying PBM outcomes, the specific mechanisms affecting neurodegenerative diseases are not entirely clear. While large clinical trials are warranted to validate these findings, evidence of the mechanisms can explain and thus provide credible support for PBM as a potential treatment for these diseases. Tubulin and its polymerized state of microtubules have been known to play important roles in the pathology of Alzheimer's and other neurodegenerative diseases. Thus, we investigated the effects of PBM on these cellular structures in the quest for insights into the underlying therapeutic mechanisms. In this study, we employed a Raman spectroscopic analysis of the amide I band of polymerized samples of tubulin exposed to pulsed low-intensity NIR radiation (810 nm, 10 Hz, 22.5 J/cm2 dose). Peaks in the Raman fingerprint region (300-1900 cm-1)-in particular, in the amide I band (1600-1700 cm-1)-were used to quantify the percentage of protein secondary structures. Under this band, hidden signals of C=O stretching, belonging to different structures, are superimposed, producing a complex signal as a result. An accurate decomposition of the amide I band is therefore required for the reliable analysis of the conformation of proteins, which we achieved through a straightforward method employing a Voigt profile. This approach was validated through secondary structure analyses of unexposed control samples, for which comparisons with other values available in the literature could be conducted. Subsequently, using this validated method, we present novel findings of statistically significant alterations in the secondary structures of polymerized NIR-exposed tubulin, characterized by a notable decrease in alpha-helix content and a concurrent increase in beta-sheets compared to the control samples. This PBM-induced alpha-helix to beta-sheet transition connects to reduced microtubule stability and the introduction of dynamism to allow for the remodeling and, consequently, refreshing of microtubule structures. This newly discovered mechanism could have implications for reducing the risks associated with brain aging, including neurodegenerative diseases like Alzheimer's disease, through the introduction of an intervention following this transition.
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Bruschini, R., & Gonzalez, P. (2023). chi(c1)(2p): an overshadowed charmoniumlike resonance. J. High Energy Phys., 02(2), 216–23pp.
Abstract: A thorough study of the J(PC )= 1(++) elastic D0 & macr;D*(0) and D+D*(-) scattering, where the form of the meson-meson interaction is inferred from lattice QCD calculations of string breaking, is carried out for center-of-mass energies up to 4 GeV. We show that the presence of chi c1(3872), which can be naturally assigned to either a bound or virtual charmoniumlike state close below the D0 & macr;D*0 threshold, can overshadow a quasiconventional charmoniumlike resonance lying above threshold. This makes difficult the experimental detection of this resonance through the D0 & macr;D*(0) and D+D*(-) channels, despite being its expected main decay modes. We analyze alternative strong and electromagnetic decay modes. Comparison with existing data shows that this resonance may have already been observed through its decay to omega J/psi.
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Gariazzo, S., de Salas, P. F., Pisanti, O., & Consiglio, R. (2022). PArthENoPE revolutions. Comput. Phys. Commun., 271, 108205–13pp.
Abstract: This paper presents the main features of a new and updated version of the program PArthENoPE, which the community has been using for many years for computing the abundances of light elements produced during Big Bang Nucleosynthesis. This is the third release of the PArthENoPE code, after the 2008 and the 2018 ones, and will be distributed from the code's website, http://parthenope.na.infn.it. Apart from minor changes, the main improvements in this new version include a revisited implementation of the nuclear rates for the most important reactions of deuterium destruction, H-2(p,gamma) He-3, H-2(d, n)He-3 and H-2(d, p)H-3, and a re-designed GUI, which extends the functionality of the previous one. The new GUI, in particular, supersedes the previous tools for running over grids of parameters with a better management of parallel runs, and it offers a brand-new set of functions for plotting the results. Program summary Program title: PArthENoPE 3.0 CPC Library link to program files: https://doi.org/10.17632/wygr7d8yt9.2 Developer's repository link: http://parthenope.na.infn.it Licensing provisions: GPLv3 Programming language: Fortran 77 and Python Nature of problem: Computation of yields of light elements synthesized in the primordial universe Solution method: Livermore Solver for Ordinary Differential Equations (LSODE) for stiff and nonstiff systems, Python GUI for running and plotting Journal reference of previous version: Comput. Phys. Commun. 233 (2018) 237-242 Does the new version supersede the previous version?: Yes Reasons for the new version: Update of the physics and improvements in the GUI Summary of revisions: Update of the physics implemented in the Fortran code and improvements in the GUI functionalities, in particular new plotting functions.
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Villanueva-Domingo, P., Mena, O., & Palomares-Ruiz, S. (2021). A Brief Review on Primordial Black Holes as Dark Matter. Front. Astron. Space Sci., 8, 681084–10pp.
Abstract: Primordial black holes (PBHs) represent a natural candidate for one of the components of the dark matter (DM) in the Universe. In this review, we shall discuss the basics of their formation, abundance and signatures. Some of their characteristic signals are examined, such as the emission of particles due to Hawking evaporation and the accretion of the surrounding matter, effects which could leave an impact in the evolution of the Universe and the formation of structures. The most relevant probes capable of constraining their masses and population are discussed.
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Han, C., Lopez-Ibañez, M. L., Melis, A., Vives, O., Wu, L., & Yang, J. M. (2020). LFV and (g-2) in non-universal SUSY models with light higgsinos. J. High Energy Phys., 05(5), 102–32pp.
Abstract: We consider a supersymmetric type-I seesaw framework with non-universal scalar masses at the GUT scale to explain the long-standing discrepancy of the anomalous magnetic moment of the muon. We find that it is difficult to accommodate the muon g-2 while keeping charged-lepton flavor violating processes under control for the conventional SO(10)-based relation between the up sector and neutrino sector. However, such tension can be relaxed by adding a Georgi-Jarlskog factor for the Yukawa matrices, which requires a non-trivial GUT-based model. In this model, we find that both observables are compatible for small mixings, CKM-like, in the neutrino Dirac Yukawa matrix.
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Calibbi, L., Lopez-Ibañez, M. L., Melis, A., & Vives, O. (2020). Muon and electron g – 2 and lepton masses in flavor models. J. High Energy Phys., 06(6), 087–23pp.
Abstract: The stringent experimental bound on μ-> e gamma is compatible with a simultaneous and sizable new physics contribution to the electron and muon anomalous magnetic moments (g – 2)(l) (l = e, mu), only if we assume a non-trivial flavor structure of the dipole operator coefficients. We propose a mechanism in which the realization of the (g – 2)(l) correction is manifestly related to the mass generation through a flavor symmetry. A radiative flavon correction to the fermion mass gives a contribution to the anomalous magnetic moment. In this framework, we introduce a chiral enhancement from a non-trivial O(1) quartic coupling of the scalar potential. We show that the muon and electron anomalies can be simultaneously explained in a vast region of the parameter space with predicted vector-like mediators of masses as large as M chi is an element of [0.6, 2.5] TeV.
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Real, D., & Calvo, D. (2022). Production requirements and functional tests of the KM3NeT Digital Optical Module Power Board. Nucl. Instrum. Methods Phys. Res. A, 1042, 167426–3pp.
Abstract: The KM3NeT research facility is being built in the Mediterranean Sea. It consists of matrices of optical detectors, the so-called Digital Optical Module. Each of this elementary detector holds a set of 31 small-area photomultipliers, which detect the Cherenkov light generated by secondary particles produced in neutrino interactions. It includes also the acquisition electronics and the power board which supplies both, the acquisition electronics and the photomultipliers. The production of electronics boards needs to have a high quality and reliability level as it is going to be deployed for more than ten years without any maintenance possible. This work presents the requirements and the qualification tests being implemented in order to increase the reliability of the Power Board of the acquisition electronics of KM3NeT during the mass production. At the moment, more than one thousand board have been produced. Results on the production of the boards, including the production yield is presented. From the already produced boards, more than 350 have been already deployed and are operative in the detectors.
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Folgado, M. G., & Sanz, V. (2022). Exploring the political pulse of a country using data science tools. J. Comput. Soc. Sci., 5, 987–1000.
Abstract: In this paper we illustrate the use of Data Science techniques to analyse complex human communication. In particular, we consider tweets from leaders of political parties as a dynamical proxy to political programmes and ideas. We also study the temporal evolution of their contents as a reaction to specific events. We analyse levels of positive and negative sentiment in the tweets using new tools adapted to social media. We also train a Fully-Connected Neural Network (FCNN) to recognise the political affiliation of a tweet. The FCNN is able to predict the origin of the tweet with a precision in the range of 71-75%, and the political leaning (left or right) with a precision of around 90%. This study is meant to be viewed as an example of how to use Twitter data and different types of Data Science tools for a political analysis.
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