The 'law of requisite variety' may assist climate change negotiations:a review of the Kyoto and Durban meetings

Ashby wrote about cybernetics, during which discourse he described a Law that attempts to resolve difficulties arising in complex situations – he suggested using variety to combat complexity. In this paper, we note that the delegates to the UN Framework Convention on Climate Change (UNFCCC) meeting in Kyoto, 1997, were offered a ‘simplifying solution’ to cope with the complexity of discussing multiple pollutants allegedly contributing to ‘climate change’. We assert that the adoption of CO2eq has resulted in imprecise thinking regarding the ‘carbon footprint’ – that is, ‘CO2’ – to the exclusion of other pollutants. We propose, as Ashby might have done, that the CO2eq and other factors within the ‘climate change’ negotiations be disaggregated to allow careful and specific individual solutions to be agreed on each factor. We propose a new permanent and transparent ‘action group’ be in charge of agenda setting and to manage the messy annual meetings. This body would be responsible for achieving accords at these annual meetings, rather than forcing this task on national hosts. We acknowledge the task is daunting and we recommend moving on from Ashby's Law to Beer's Viable Systems approach

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Improved Resolution Haplogroup G Phylogeny in the Y Chromosome, Revealed by a Set of Newly Characterized SNPs

Background: Y-SNP haplogroup G (hgG), defined by Y-SNP marker M201, is relatively uncommon in the United States general population, with only 8 additional sub-markers characterized. Many of the previously described eight sub-markers are either very rare (2–4%) or do not distinguish between major populations within this hg. In fact, prior to the current study, only 2 % of our reference Caucasian population belonged to hgG and all of these individuals were in sub-haplogroup G2a, defined by P15. Additional Y-SNPs are needed in order to differentiate between individuals within this haplogroup. Principal Findings: In this work we have investigated whether we could differentiate between a population of 63 hgG individuals using previously uncharacterized Y-SNPs. We have designed assays to test these individuals using all known hgG SNPs (n = 9) and an additional 16 unreported/undefined Y-SNPS. Using a combination of DNA sequence and genetic genealogy databases, we have uncovered a total of 15 new hgG SNPs that had been previously reported but not phylogenetically characterized. Ten of the new Y-SNPs are phylogenetically equivalent to M201, one is equivalent to P15 and, interestingly, four create new, separate haplogroups. Three of the latter are more common than many of the previously defined Y-SNPs. Y-STR data from these individuals show that DYS385*12 is present in (70%) of G2a3b1-U13 individuals while only 4 % of non-G2a3b1-U13 individuals posses the DYS385*12 allele. Conclusions: This study uncovered several previously undefined Y-SNPs by using data from several database sources. Th

Genetic approaches to understanding the causes of stuttering

Stuttering is a common but poorly understood speech disorder. Evidence accumulated over the past several decades has indicated that genetic factors are involved, and genetic linkage studies have begun to identify specific chromosomal loci at which causative genes are likely to reside. A detailed investigation of one such region on chromosome 12 has identified mutations in the GNPTAB gene that are associated with stuttering in large families and in the general population. Subsequent studies identified mutations in the functionally related GNPTG and NAGPA genes. Mutations in these genes disrupt the lysosomal targeting pathway that generates the Mannose 6-phosphate signal, which directs a diverse group of enzymes to their target location in the lysosome of the cell. While mutations in these three genes can be identified in less than 10% of cases of familial stuttering, this knowledge allows a variety of new studies that can help identify the neuropathology that underlies this disorder

Asymmetric Switching in a Homodimeric ABC Transporter: A Simulation Study

ABC transporters are a large family of membrane proteins involved in a variety of cellular processes, including multidrug and tumor resistance and ion channel regulation. Advances in the structural and functional understanding of ABC transporters have revealed that hydrolysis at the two canonical nucleotide-binding sites (NBSs) is co-operative and non-simultaneous. A conserved core architecture of bacterial and eukaryotic ABC exporters has been established, as exemplified by the crystal structure of the homodimeric multidrug exporter Sav1866. Currently, it is unclear how sequential ATP hydrolysis arises in a symmetric homodimeric transporter, since it implies at least transient asymmetry at the NBSs. We show by molecular dynamics simulation that the initially symmetric structure of Sav1866 readily undergoes asymmetric transitions at its NBSs in a pre-hydrolytic nucleotide configuration. MgATP-binding residues and a network of charged residues at the dimer interface are shown to form a sequence of putative molecular switches that allow ATP hydrolysis only at one NBS. We extend our findings to eukaryotic ABC exporters which often consist of two non-identical half-transporters, frequently with degeneracy substitutions at one of their two NBSs. Interestingly, many residues involved in asymmetric conformational switching in Sav1866 are substituted in degenerate eukaryotic NBS. This finding strengthens recent suggestions that the interplay of a consensus and a degenerate NBS in eukaroytic ABC proteins pre-determines the sequence of hydrolysis at the two NBSs

The diagnostic accuracy of a laser fluorescence device and digital radiography in detecting approximal caries lesions in posterior permanent teeth: an in vivo study

The aim of this in vivo study was to test the diagnostic accuracy of a pen-type laser fluorescence (LFpen) device in detecting approximal caries lesions, in posterior permanent teeth, at the cavitation and non-cavitation thresholds, and compare it with that of digital bitewing radiography. Thirty patients (aged 18–37), who attended the Faculty of Dentistry at Damascus University for a dental examination, were consecutively screened. Ninety approximal surfaces of posterior permanent teeth without frank cavitations, enamel hypoplasia or restorations were selected and examined using the LFpen (DIAGNOdent pen) and digital bitewing radiography. The reference standard was the visual-tactile inspection, after performing temporary tooth separation, using orthodontic rubber rings, placed for 7 days. The status of included approximal surfaces was recorded as intact/sound, with white/brown spots or cavitated. One trained examiner performed all examinations. There were statistically significant differences in LFpen readings between the three types of approximal surface status (P < 0.001). The optimal cut-off values for detecting approximal caries lesions in posterior permanent teeth were >16 and 8 at the cavitation and non-cavitation thresholds respectively. The sensitivity, specificity and accuracy (measured by the area under the receiver-operating characteristic curve) were 100, 85 and 95 and 92, 90 and 95% at the cavitation and non-cavitation thresholds respectively. The intra-class correlation coefficient for intra-examiner reliability was 0.95. The diagnostic accuracy of the LFpen was significantly higher than that of digital bitewing radiography (P < 0.001). The LFpen’s diagnostic performance was accurate and significantly better than digital bitewing radiography in detecting approximal caries lesions, in posterior permanent teeth. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10103-017-2157-2) contains supplementary material, which is available to authorized users

Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays

We use high-density single nucleotide polymorphism (SNP) genotyping microarrays to demonstrate the ability to accurately and robustly determine whether individuals are in a complex genomic DNA mixture. We first develop a theoretical framework for detecting an individual's presence within a mixture, then show, through simulations, the limits associated with our method, and finally demonstrate experimentally the identification of the presence of genomic DNA of specific individuals within a series of highly complex genomic mixtures, including mixtures where an individual contributes less than 0.1% of the total genomic DNA. These findings shift the perceived utility of SNPs for identifying individual trace contributors within a forensics mixture, and suggest future research efforts into assessing the viability of previously sub-optimal DNA sources due to sample contamination. These findings also suggest that composite statistics across cohorts, such as allele frequency or genotype counts, do not mask identity within genome-wide association studies. The implications of these findings are discussed

The plausibility of a role for mercury in the etiology of autism: a cellular perspective

Autism is defined by a behavioral set of stereotypic and repetitious behavioral patterns in combination with social and communication deficits. There is emerging evidence supporting the hypothesis that autism may result from a combination of genetic susceptibility and exposure to environmental toxins at critical moments in development. Mercury (Hg) is recognized as a ubiquitous environmental neurotoxin and there is mounting evidence linking it to neurodevelopmental disorders, including autism. Of course, the evidence is not derived from experimental trials with humans but rather from methods focusing on biomarkers of Hg damage, measurements of Hg exposure, epidemiological data, and animal studies. For ethical reasons, controlled Hg exposure in humans will never be conducted. Therefore, to properly evaluate the Hg-autism etiological hypothesis, it is essential to first establish the biological plausibility of the hypothesis. This review examines the plausibility of Hg as the primary etiological agent driving the cellular mechanisms by which Hg-induced neurotoxicity may result in the physiological attributes of autism. Key areas of focus include: (1) route and cellular mechanisms of Hg exposure in autism; (2) current research and examples of possible genetic variables that are linked to both Hg sensitivity and autism; (3) the role Hg may play as an environmental toxin fueling the oxidative stress found in autism; (4) role of mitochondrial dysfunction; and (5) possible role of Hg in abnormal neuroexcitory and excitotoxity that may play a role in the immune dysregulation found in autism. Future research directions that would assist in addressing the gaps in our knowledge are proposed