Metropolitan age-specific mortality trends at borough and neighborhood level: The case of Mexico City.

Understanding the spatial and temporal patterns of mortality rates in a highly heterogeneous metropolis, is a matter of public policy interest. In this context, there is no, to the best of our knowledge, previous studies that correlate both spatio-temporal and age-specific mortality rates in Mexico City. Spatio-temporal Kriging modeling was used over five age-specific mortality rates (from the years 2000 to 2016 in Mexico City), to gain both spatial (borough and neighborhood) and temporal (year and trimester) data level description. Mortality age-specific patterns have been modeled using multilevel modeling for longitudinal data. Posterior tests were carried out to compare mortality averages between geo-spatial locations. Mortality correlation extends in all study groups for as long as 12 years and as far as 13.27 km. The highest mortality rate takes place in the Cuauhtémoc borough, the commercial, touristic and cultural core downtown of Mexico City. On the contrary, Tlalpan borough is the one with the lowest mortality rates in all the study groups. Post-productive mortality is the first age-specific cause of death, followed by infant, productive, pre-school and scholar groups. The combinations of spatio-temporal Kriging estimation and time-evolution linear mixed-effect models, allowed us to unveil relevant time and location trends that may be useful for public policy planning in Mexico City.

Spatio-Temporal Representativeness of Air Quality Monitoring Stations in Mexico City: Implications for Public Health.

Assessment of the air quality in metropolitan areas is a major challenge in environmental sciences. Issues related include the distribution of monitoring stations, their spatial range, or missing information. In Mexico City, stations have been located spanning the entire Metropolitan zone for pollutants, such as CO, NO2, O3, SO2, PM2.5, PM10, NO, NO x , and PM CO . A fundamental question is whether the number and location of such stations are adequate to optimally cover the city. By analyzing spatio-temporal correlations for pollutant measurements, we evaluated the distribution and performance of monitoring stations in Mexico City from 2009 to 2018. Based on our analysis, air quality evaluation of those contaminants is adequate to cover the 16 boroughs of Mexico City, with the exception of SO2, since its spatial range is shorter than the one needed to cover the whole surface of the city. We observed that NO and NO x concentrations must be taken into account since their long-range dispersion may have relevant consequences for public health. With this approach, we may be able to propose policy based on systematic criteria to locate new monitoring stations.

Whole genome gene expression analysis reveals casiopeína-induced apoptosis pathways.

Copper-based chemotherapeutic compounds Casiopeínas, have been presented as able to promote selective programmed cell death in cancer cells, thus being proper candidates for targeted cancer therapy. DNA fragmentation and apoptosis-in a process mediated by reactive oxygen species-for a number of tumor cells, have been argued to be the main mechanisms. However, a detailed functional mechanism (a model) is still to be defined and interrogated for a wide variety of cellular conditions before establishing settings and parameters needed for their wide clinical application. In order to shorten the gap in this respect, we present a model proposal centered in the role played by intrinsic (or mitochondrial) apoptosis triggered by oxidative stress caused by the chemotherapeutic agent. This model has been inferred based on genome wide expression profiling in cervix cancer (HeLa) cells, as well as statistical and computational tests, validated via functional experiments (both in the same HeLa cells and also in a Neuroblastoma model, the CHP-212 cell line) and assessed by means of data mining studies.

The role of master regulators in the metabolic/transcriptional coupling in breast carcinomas.

Metabolic transformations have been reported as involved in neoplasms survival. This suggests a role of metabolic pathways as potential cancer pharmacological targets. Modulating tumor's energy production pathways may become a substantial research area for cancer treatment. The significant role of metabolic deregulation as inducing transcriptional instabilities and consequently whole-system failure, is thus of foremost importance. By using a data integration approach that combines experimental evidence for high-throughput genome wide gene expression, a non-equilibrium thermodynamics analysis, nonlinear correlation networks as well as database mining, we were able to outline the role that transcription factors MEF2C and MNDA may have as main master regulators in primary breast cancer phenomenology, as well as the possible interrelationship between malignancy and metabolic dysfunction. The present findings are supported by the analysis of 1191 whole genome gene expression experiments, as well as probabilistic inference of gene regulatory networks, and non-equilibrium thermodynamics of such data. Other evidence sources include pathway enrichment and gene set enrichment analyses, as well as motif comparison with a comprehensive gene regulatory network (of homologue genes) in Arabidopsis thaliana. Our key finding is that the non-equilibrium free energies provide a realistic description of transcription factor activation that when supplemented with gene regulatory networks made us able to find deregulated pathways. These analyses also suggest a novel potential role of transcription factor energetics at the onset of primary tumor development. Results are important in the molecular systems biology of cancer field, since deregulation and coupling mechanisms between metabolic activity and transcriptional regulation can be better understood by taking into account the way that master regulators respond to physicochemical constraints imposed by different phenotypic conditions.