¿Por qué escribo? : Selección de textos producidos en los talleres de la UNLP (2013-2016)

Consideramos fundamental que el espíritu del bienestar de la comunidad universitaria se centre en la creación de espacios de expresión, de participación y de integración para los estudiantes de nuestra universidad; espacios que les permitan conocer, explorar o descubrir nuevas formas de ser en el mundo, de compartir la experiencia y enriquecerse a partir de la experiencia de los demás. El programa de talleres gratuitos para alumnos de todas las carreras de grado de la UNLP que llevamos adelante desde la Prosecretaría de Bienestar Universitario es una instancia de ello. Comenzamos en el año 2009 con una oferta modesta, pero variada, que permitía acercar a nuestros estudiantes a disciplinas por lo general poco contempladas en la oferta académica de nuestra universidad. Con el paso de los años el interés por los talleres creció tanto que fuimos sumando nuevas propuestas para incluir, por un lado, las inquietudes específicas que nos traían los estudiantes y, por el otro, para hacer posible que todos los interesados tuvieran un lugar de participación en el programa. El Taller de Lectura y Escritura, primero, y el Taller de Escritura Creativa en la Biblioteca Euforión, unos años más tarde, ambos pensados y llevados adelante por Analía Pinto, son ejemplos de ello; ejemplos ante todo de cuán significativo y transformador para las personas puede volverse un espacio a lo largo del tiempo si recibe la justa combinación de compromiso, dedicación y saber. Esta primera edición (y selección) de los trabajos escritos por los alumnos de los talleres de Lectura y de Escritura de la UNLP es una muestra, que nos enorgullece, de todo ese camino recorrido. Esperamos que lo disfruten.Prosecretaría de Bienestar Universitari

Does LLLT stimulate laryngeal carcinoma cells? An "in vitro" study

Low level laser therapy (LLLT) has been used successfully in biomedicine and some of the results are thought to be related to cell proliferation. The effects of LLLT on cell proliferation is debatable because studies have found both an increase and a decrease in proliferation of cell cultures. Cell culture is an excellent method to assess both effects and dose of treatment. The aim of this study was to assess the effect of 635nm and 670nm laser irradiation of H.Ep.2 cells in vitro using MTT (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide). The cells were obtained from squamous cell carcinoma (SCC) of the larynx and were routinely processed from defrost to the experimental condition. Twenty-four hours after transplantation the cells were irradiated with doses ranging from 0.04 to 0.48J/cm² for seven consecutive days (5 mW diode lasers: 635nm or 670nm, beam cross-section ~1mm) at local light doses between 0.04 and 0.48J/cm². The results showed that 635nm laser light did not significantly stimulate the proliferation of H.Ep.2 cells at doses of 0.04J/cm² to 0.48J/cm², However, 670nm laser irradiation led to an increased cell proliferation when compared to both control and 635nm irradiated cells. The best cell proliferation was found with 670nm laser irradiated cultures exposed to doses of doses of 0.04 to 0.48J/cm². We conclude that both dose and wavelength are factors that may affect cell proliferation of H.Ep.2 cells

Impact of Pectoralis Nerve Block (PECS) on postoperative pain in patients submitted to mastectomy with lymphadenectomy

ABSTRACT Objective: Breast cancer is the most common malignant neoplasm in women worldwide. Surgery has been traditional treatment and, generally, it´s mastectomy with lymphadenectomy, that can causes postoperative pain. Therefore, we seek to study regional anesthesic techniques that can minimize this effect, such as the interpectoral block (PECS). Methods: randomized controlled study with 82 patients with breast cancer who underwent mastectomy with lymphadenectomy from January 2020 to October 2021 in oncology hospital. Interventions: two randomized groups (control - exclusive general anesthesia and PECS group - received PECS block with levobupivacaine/ropivacaine and general anesthesia). We applied a questionnaire with Numeric Rating Scale for pain 24h after surgery. We used Shapiro-Wilk, Mann-Whitney and Chi-square tests, and analyzed the data in R version 4.0.0 (ReBEC). Results: in the PECS group, 50% were pain-free 24h after surgery and in the control group it was 42.86%. The majority who presented pain classified it as mild pain (VAS from 1 to 3) - (42.50%) PECS group and (40.48%) control group (p=0.28). Only 17.50% consumed opioids in the PECS group, similar to the control group with 21.43%. (p=0.65). There was a low rate of complications such as PONV in both groups. In the subgroup analysis, there was no statistical difference between the groups that used levobupivacaine or ropivacaine regarding postoperative pain and opioid consumption. Discussion: the studied group had a low rate of pain in the postoperative period and it influenced the statistical analysis. There wasn´t difference in postoperative pain in groups. Conclusion: was not possible to demonstrate better results with the association of the PECS block with total intravenous analgesia. Need further studies to assess the efficacy of the nerve block

Esofagectomia trans-hiatal versus transtorácica: experiência do Instituto Nacional do Câncer (INCA)

OBJETIVO: Analisar comparativamente a morbimortalidade e sobrevida após esofagectomia trans-hiatal (TH) ou transtorácica (TT). METODOS: Estudo retrospectivo não randomizado de 68 pacientes com neoplasia de esôfago operados no INCA entre 1997 e 2005, divididos em dois grupos: 1 - TH (33 pacientes); e 2 - TT (35 pacientes). RESULTADOS: A idade média foi 40,7 anos (25 - 74 anos), sendo 73,5% homens. Tumores do 1/3 médio predominaram no Grupo 2 (48,6% versus 21,2%, p = 0,02). A média de linfonodos dissecados foi maior no Grupo 2 (21,6 versus 17,8 linfonodos, p = 0,04), porém sem diferença no número de linfonodos metastáticos (4,1 versus 3,9 linfonodos, p = 0,85). O tempo cirúrgico médio foi maior no Grupo 2 (410 versus 270 minutos, p = 0,001). O tempo médio de internação também foi maior no Grupo 2 (19 versus 14 dias, p = 0,001). A morbidade operatória foi 50%, sem diferença significativa (42,4% versus 57,1%, p = 0,23). Fístula esofágica ocorreu em 13,2%, sem diferença significativa (9,1% versus 17,1%, p = 0,23). A mortalidade foi 5,8% (04 pacientes), sem diferença significativa (1,4% versus 4,4%, p = 0,83). CONCLUSÃO: Neste estudo, a morbimortalidade não apresentou diferença em relação à via de acesso para a esofagectomia, apesar do maior tempo cirúrgico e de permanência hospitalar na via TT. A sobrevida global em 3 e 5 anos também foi maior na TT, possivelmente devido a maior freqüência de estágios iniciais em pacientes submetidos à transtorácica

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

International audienceLiquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on $10^3$ pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype