Much of the public first learned about epidemiological modeling during the early months of the coronavirus disease 2019 (COVID-19) pandemic. The first models resulted in more confusion than clarity. Even though coronavirus cases were rising exponentially in the United States and Europe, some models predicted a rapid peak followed by a rapid decline, whereas other models predicted cycles of infection continuing over several years. Much has been learned since those early months. In retrospect, it is clear that modeling requires both reliable data and an accurate understanding of how disease spreads, and that the field of epidemiological modeling requires a diversity of approaches. Support for this field must increase and be coordinated, with a designation of responsibilities among funding agencies.
Scientific research probes the deepest mysteries of the universe and of living things, and it creates applications and technologies that benefit humanity and create wealth. This “Beauty and Benefits of Science” is the theme of this 2013 AAAS Annual Meeting.
The subject of my address is a
The cosmological constant problem is examined in the context of both astronomy and physics. Effects of a nonzero cosmological constant are discussed with reference to expansion dynamics, the age of the universe, distance measures, comoving density of objects, growth of linear perturbations, and gravitational lens probabilities. The observational status of the cosmological constant is reviewed, with attention given to the existence of high-redshift objects, age derivation from globular clusters and cosmic nuclear data, dynamical tests of Omega sub Lambda, quasar absorption line statistics, gravitational lensing, and astrophysics of distant objects. Finally, possible solutions to the physicist's cosmological constant problem are examined.
While investigating microRNA targets, we have found that human genes divide into two roughly equal populations, based on the fraction of A plus T bases in their 3′ UTRs. Using the Gene Ontology database, we find significant functional differences between the two gene populations, with AT-rich genes implicated in transcription and translation processes, and GC-rich genes implicated in signal transduction and posttranslational protein modification. Better understanding of the background distribution of nucleotides in 3′ UTRs may allow improved prediction of microRNA-targeted genes in humans. We predict at least 1,200 KnownGene transcripts to be regulated by microRNAs. The large majority of these microRNA targets are in the AT-rich 3′ UTR population. However, notwithstanding this preference for AT-rich targets, microRNA targets are found preferentially to be regulatory genes themselves, including both transcription factors and posttranslational modifiers. These results suggest that some processes involving mRNA, of which microRNA regulation may be just one, require AT-richness of 3′ UTRs for functionality. A relationship, not simply one-to-one, between these 3′ UTR populations and large-scale genomic isochores is described.
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