RESUMO
During the COVID-19 pandemic, contact tracing apps based on the Bluetooth Low Energy (BLE) technology found in smartphones have been deployed by multiple countries despite BLE's debatable performance for determining close contacts among users. Current solutions estimate proximity based on a single feature: the mean attenuation of the BLE signal. In this context, a new generation of these apps which better exploits data from the BLE signal and other sensors available on phones can be fostered. Collected data can be used to extract multiple features that feed machine learning models which can potentially improve the accuracy of today's solutions. In this work, we consider the use of machine learning models to evaluate different feature sets that can be extracted from the received BLE signal, and assess the performance gain as more features are introduced in these models. Since indoor conditions have a strong impact in assessing the risk of being exposed to the SARS-CoV-2, we analyze the environment (indoor or outdoor) role in these models, aiming at understanding the need for apps that could increase proximity accuracy if aware of its environment. Results show that a better accuracy can be obtained in outdoor locations with respect to indoor ones, and that indoor proximity estimation can benefit more from the introduction of more features with respect to the outdoor estimation case. Accuracy can be increased about 10% when multiple features are considered if the device is aware of its environment, reaching a performance of up to 83% in indoor spaces and up to 91% in outdoor ones. These results encourage future contact tracing apps to integrate this awareness not only to better assess the associated risk of a given environment but also to improve the proximity accuracy for detecting close contacts.
RESUMO
La Federación Nacional de Neurocirugía (FNNC) fue fundada en la ciudad de Rosario el 23 de agosto de 2019, con el objetivo de crear una organización que nu-clee a todas las sociedades y asociaciones de neurociru-gía de nuestro país, con un perfil netamente gremial. La FNNC reconoce a la Asociación Argentina de Neuroci-rugía (AANC) como la organización que rige la activi-dad académica-profesional de la neurocirugía en todo el territorio de la República Argentina.Uno de los propósitos principales es lograr condiciones laborales dignas y correctamente remuneradas para to-dos los neurocirujanos que residan en suelo argentino. Pensamos que una de las herramientas necesarias para conseguir dicho propósito es lograr un equilibrio entre el número de neurocirujanos en actividad, el número de plazas de residentes, y el número de habitantes en Ar-gentina.Actualmente no existen datos concretos para realizar un diagnóstico de situación. Es por ello que la FNNC, apoyada y avalada por la AANC, tomó la iniciativa de realizar un análisis descriptivo de la situación actual y su proyección en los próximos años en relación con el nú-mero de neurocirujanos en Argentina.El objetivo del presente trabajo es presentar de forma sintética y clara los aspectos más relevantes de dicho es-tudio.
Assuntos
Neurocirurgia , Trabalho , NeurocirurgiõesRESUMO
Studying tissue-independent components of cancer and defining pan-cancer subtypes could be addressed using tissue-specific molecular signatures if classification errors are controlled. Since PAM50 is a well-known, United States Food and Drug Administration (FDA)-approved and commercially available breast cancer signature, we applied it with uncertainty assessment to classify tumor samples from over 33 cancer types, discarded unassigned samples, and studied the emerging tumor-agnostic molecular patterns. The percentage of unassigned samples ranged between 55.5% and 86.9% in non-breast tissues, and gene set analysis suggested that the remaining samples could be grouped into two classes (named C1 and C2) regardless of the tissue. The C2 class was more dedifferentiated, more proliferative, with higher centrosome amplification, and potentially more TP53 and RB1 mutations. We identified 28 gene sets and 95 genes mainly associated with cell-cycle progression, cell-cycle checkpoints, and DNA damage that were consistently exacerbated in the C2 class. In some cancer types, the C1/C2 classification was associated with survival and drug sensitivity, and modulated the prognostic meaning of the immune infiltrate. Our results suggest that PAM50 could be repurposed for a pan-cancer context when paired with uncertainty assessment, resulting in two classes with molecular, biological, and clinical implications.