Energy Flows in Low-Entropy Complex Systems

Nature's many complex systems--physical, biological, and cultural--are islands of low-entropy order within increasingly disordered seas of surrounding, high-entropy chaos. Energy is a principal facilitator of the rising complexity of all such systems in the expanding Universe, including galaxies, stars, planets, life, society, and machines. A large amount of empirical evidence--relating neither entropy nor information, rather energy--suggests that an underlying simplicity guides the emergence and growth of complexity among many known, highly varied systems in the 14-billion-year-old Universe, from big bang to humankind. Energy flows are as centrally important to life and society as they are to stars and galaxies. In particular, the quantity energy rate density--the rate of energy flow per unit mass--can be used to explicate in a consistent, uniform, and unifying way a huge collection of diverse complex systems observed throughout Nature. Operationally, those systems able to utilize optimal amounts of energy tend to survive and those that cannot are non-randomly eliminated.Comment: 12 pages, 2 figures, review paper for special issue on Recent Advances in Non-Equilibrium Statistical Mechanics and its Application. arXiv admin note: text overlap with arXiv:1406.273

The Natural Science Underlying Big History

Nature's many varied complex systems—including galaxies, stars, planets, life, and society—are islands of order within the increasingly disordered Universe. All organized systems are subject to physical, biological, or cultural evolution, which together comprise the grander interdisciplinary subject of cosmic evolution. A wealth of observational data supports the hypothesis that increasingly complex systems evolve unceasingly, uncaringly, and unpredictably from big bang to humankind. These are global history greatly extended, big history with a scientific basis, and natural history broadly portrayed across ∼14 billion years of time. Human beings and our cultural inventions are not special, unique, or apart from Nature; rather, we are an integral part of a universal evolutionary process connecting all such complex systems throughout space and time. Such evolution writ large has significant potential to unify the natural sciences into a holistic understanding of who we are and whence we came. No new science (beyond frontier, nonequilibrium thermodynamics) is needed to describe cosmic evolution's major milestones at a deep and empirical level. Quantitative models and experimental tests imply that a remarkable simplicity underlies the emergence and growth of complexity for a wide spectrum of known and diverse systems. Energy is a principal facilitator of the rising complexity of ordered systems within the expanding Universe; energy flows are as central to life and society as they are to stars and galaxies. In particular, energy rate density—contrasting with information content or entropy production—is an objective metric suitable to gauge relative degrees of complexity among a hierarchy of widely assorted systems observed throughout the material Universe. Operationally, those systems capable of utilizing optimum amounts of energy tend to survive, and those that cannot are nonrandomly eliminated

Identification of Pathway-Specific Serum Biomarkers of Response to Glucocorticoid and Infliximab Treatment in Children with Inflammatory Bowel Disease

Objective: Serum biomarkers may serve to predict early response to therapy, identify relapse, and facilitate drug development in inflammatory bowel disease (IBD). Biomarkers are particularly important in children, in whom achieving early remission and minimizing procedures are especially beneficial. Methods: We profiled protein and micro RNA (miRNA) in serum from patients pre- and post-therapy, to identify molecular markers of pharmacodynamic effect. Serum was obtained from children with IBD before and after treatment with either corticosteroids (prednisone; n=12) or anti-tumor necrosis factor-α biologic (infliximab; n=7). Over 1,100 serum proteins were assayed using aptamer-based SOMAscan proteomics, and 22 miRNAs analyzed by quantitative real time PCR. Concordance of longitudinal changes between the groups was used to identify markers responsive to treatment. Bioinformatic analysis was used to build insight into mechanisms of changes in response to treatment. Results: We identified 18 proteins and three miRNAs responsive to both prednisone and infliximab. Eight markers that decreased are associated with inflammation and have gene promoters regulated by nuclear factor (NF)-κB. Several that increased are associated with resolving inflammation and tissue damage. We also identified six markers that appear to be steroid-specific, three of which have glucocorticoid receptor binding elements in their promoter region. Conclusions: Serum markers regulated by the inflammatory transcription factor NF-κB are potential candidates for pharmacodynamic biomarkers that, if correlated with later outcomes like endoscopic or histologic healing, could be used to monitor treatment, optimize dosing, and enhance drug development. The pharmacodynamic biomarkers identified here hold potential to improve both clinical care and drug development. Further studies are warranted to investigate these markers as early predictors of response, or possibly surrogate outcomes

Daily Dosing of Rifapentine Cures Tuberculosis in Three Months or Less in the Murine Model

Eric Nuermberger and colleagues found that after two months of treatment, mice with lung cultures positive for tuberculosis that received daily doses of rifapentine- and moxifloxacin-containing regimens converted to negative lung cultures. This finding could make possible the development of shorter treatment regimens for humans

The genomic landscape of balanced cytogenetic abnormalities associated with human congenital anomalies

Despite the clinical significance of balanced chromosomal abnormalities (BCAs), their characterization has largely been restricted to cytogenetic resolution. We explored the landscape of BCAs at nucleotide resolution in 273 subjects with a spectrum of congenital anomalies. Whole-genome sequencing revised 93% of karyotypes and demonstrated complexity that was cryptic to karyotyping in 21% of BCAs, highlighting the limitations of conventional cytogenetic approaches. At least 33.9% of BCAs resulted in gene disruption that likely contributed to the developmental phenotype, 5.2% were associated with pathogenic genomic imbalances, and 7.3% disrupted topologically associated domains (TADs) encompassing known syndromic loci. Remarkably, BCA breakpoints in eight subjects altered a single TAD encompassing MEF2C, a known driver of 5q14.3 microdeletion syndrome, resulting in decreased MEF2C expression. We propose that sequence-level resolution dramatically improves prediction of clinical outcomes for balanced rearrangements and provides insight into new pathogenic mechanisms, such as altered regulation due to changes in chromosome topology

Extensive sequencing of seven human genomes to characterize benchmark reference materials

The Genome in a Bottle Consortium, hosted by the National Institute of Standards and Technology (NIST) is creating reference materials and data for human genome sequencing, as well as methods for genome comparison and benchmarking. Here, we describe a large, diverse set of sequencing data for seven human genomes; five are current or candidate NIST Reference Materials. The pilot genome, NA12878, has been released as NIST RM 8398. We also describe data from two Personal Genome Project trios, one of Ashkenazim Jewish ancestry and one of Chinese ancestry. The data come from 12 technologies: BioNano Genomics, Complete Genomics paired-end and LFR, Ion Proton exome, Oxford Nanopore, Pacific Biosciences, SOLiD, 10X Genomics GemCode WGS, and Illumina exome and WGS paired-end, mate-pair, and synthetic long reads. Cell lines, DNA, and data from these individuals are publicly available. Therefore, we expect these data to be useful for revealing novel information about the human genome and improving sequencing technologies, SNP, indel, and structural variant calling, and de novo assembly