RESUMO
Transportation networks play a critical role in human mobility and the exchange of goods, but they are also the primary vehicles for the worldwide spread of infections, and account for a significant fraction of CO2 emissions. We investigate the edge removal dynamics of two mature but fast-changing transportation networks: the Brazilian domestic bus transportation network and the U.S. domestic air transportation network. We use machine learning approaches to predict edge removal on a monthly time scale and find that models trained on data for a given month predict edge removals for the same month with high accuracy. For the air transportation network, we also find that models trained for a given month are still accurate for other months even in the presence of external shocks. We take advantage of this approach to forecast the impact of a hypothetical dramatic reduction in the scale of the U.S. air transportation network as a result of policies to reduce CO2 emissions. Our forecasting approach could be helpful in building scenarios for planning future infrastructure.
Assuntos
Dióxido de Carbono , Meios de Transporte , Brasil , Dióxido de Carbono/análise , Previsões , Humanos , Aprendizado de MáquinaAssuntos
Carcinoma de Células Escamosas/patologia , Timo/patologia , Neoplasias da Glândula Tireoide/patologia , Adulto , Antígenos CD5/metabolismo , Carcinoma Papilar/metabolismo , Carcinoma Papilar/patologia , Carcinoma de Células Escamosas/metabolismo , Carcinoma de Células Escamosas/cirurgia , Coristoma/metabolismo , Coristoma/patologia , Diagnóstico Diferencial , Feminino , Hamartoma/metabolismo , Hamartoma/patologia , Humanos , Proteínas Proto-Oncogênicas c-kit/metabolismo , Timoma/metabolismo , Timoma/patologia , Neoplasias do Timo/metabolismo , Neoplasias do Timo/patologia , Neoplasias da Glândula Tireoide/metabolismo , Neoplasias da Glândula Tireoide/cirurgia , Tireoidectomia/métodosRESUMO
The aim of the present study was to investigate the potential role of Toll-like receptor 4 (TLR4) in lipopolysaccharide (LPS)-induced preterm delivery. Intraperitoneal injection of LPS in the presence or absence of previous TLR4 blockade was performed to establish a murine model of preterm delivery. The incidences of preterm delivery and fetal death were calculated. Flow cytometry was performed to examine the percentages of blood CD45(+)CD86(+), CD3(+)CD69(+), CD19(+)CD69(+) and CD49b(+)CD69(+) cell subsets, and the percentages of placenta CD45(+)CD86(+), CD45(+)CD49b(+) and CD49b(+)CD69(+) cell subpopulations. In our study, an inflammation-induced preterm delivery model was established by intraperitoneal injection of LPS. Blocking TLR4 significantly decreased LPS-induced preterm delivery and fetal death. LPS treatment markedly up-regulated the percentages of blood CD45(+)CD86(+), CD3(+)CD69(+) and CD49b(+)CD69(+) cells, and of placenta CD45(+)CD86(+), CD45(+)CD49b(+) and CD49b(+)CD69(+) cells. TLR4 blockade almost completely abrogated LPS-induced elevated cell proportions. These data demonstrate that TLR4 plays a critical role in inflammation-induced preterm delivery.
