Dietary carbohydrate restriction as the first approach in diabetes management: critical review and evidence base.

The inability of current recommendations to control the epidemic of diabetes, the specific failure of the prevailing low-fat diets to improve obesity, cardiovascular risk, or general health and the persistent reports of some serious side effects of commonly prescribed diabetic medications, in combination with the continued success of low-carbohydrate diets in the treatment of diabetes and metabolic syndrome without significant side effects, point to the need for a reappraisal of dietary guidelines. The benefits of carbohydrate restriction in diabetes are immediate and well documented. Concerns about the efficacy and safety are long term and conjectural rather than data driven. Dietary carbohydrate restriction reliably reduces high blood glucose, does not require weight loss (although is still best for weight loss), and leads to the reduction or elimination of medication. It has never shown side effects comparable with those seen in many drugs. Here we present 12 points of evidence supporting the use of low-carbohydrate diets as the first approach to treating type 2 diabetes and as the most effective adjunct to pharmacology in type 1. They represent the best-documented, least controversial results. The insistence on long-term randomized controlled trials as the only kind of data that will be accepted is without precedent in science. The seriousness of diabetes requires that we evaluate all of the evidence that is available. The 12 points are sufficiently compelling that we feel that the burden of proof rests with those who are opposed.

The mitochondrial genome sequence of Mus terricolor: comparison with Mus musculus domesticus and implications for xenomitochondrial mouse modeling.

Knowledge of the mitochondrial DNA (mtDNA) sequence of divergent murine species is critical from both a phylogenetic perspective and in understanding nuclear-mitochondrial interactions, particularly as the latter influences our xenocybrid models of mitochondrial disease. To this end, the sequence of the mitochondrial genome of the murine species Mus terricolor (formerly Mus dunni) is reported and compared with the published sequence for the common laboratory mouse Mus musculus domesticus strain C57BL/6J. These species are of interest because xenomitochondrial cybrid mice were created that harbor M. terricolor mtDNA in a M. m. domesticus nuclear background. Although the total of 1763 nucleotide substitutions represents striking heterogeneity, the majority of these are silent, leading to highly conserved protein sequences with only 159 amino acid differences. Moreover, 58% of these amino acid differences represented conservative substitutions. All of the tRNA genes and rRNA genes have homology of 91% or greater. The control region shows the greatest heterogeneity, as expected, with 85% homology overall. Regions of 100% homology were found for Conserved Sequence Block I, Conserved Sequence Block III and the L-strand origin of replication. Complex I genes showed the greatest degree of difference among protein-coding genes with amino acid homology of 91-97% among the seven mitochondrial genes. Complexes III and IV genes show high homology ranging from 98-100%. From these data, complex I differences appear most critical for the viability of M. m. domesticus: M. terricolor cybrids. Moreover, the sequence information reported here should be useful in identifying critical regions for mitochondrial transfer between species, for furthering the understanding of mitochondrial dynamics and pathology in transmitochondrial organisms, and for the study of Mus genus origins.

Group testing to annihilate pairs applied to DNA cross-hybridization elimination using SYBR Green I.

A group testing (or pooling) method for DNA strands that identifies at least one strand in a pair of cross-hybridized oligonucleotides is given. This pooling method can be extended to any population of objects where certain pairs together produce an observable function or signal. Pairs of objects may work together to produce an undesirable result or a detrimental function. If just a single element of such a pair is identified and eliminated, then the undesirable function of that pair is destroyed. In particular, the ability to ensure that a set DNA probes do not yield undesired cross-hybridizations is important when these probes and/or their complements are used in the production of a hybridization signal that is intended to convey information. Here we report a "proof of principle" method, similar to those used to screen DNA libraries, that screens pools of probes for unwanted cross-hybridization events and identifies the offending probes. In the reported experiment, a cross-hybridized duplex in a pool of probes is detected by using the fluorescent dye SYBR Green I. This dye is known to produce greater fluorescence when bound to duplex DNA as opposed to single-stranded DNA. The method described here is sensitive, fast, and simple.

New t-gap insertion-deletion-like metrics for DNA hybridization thermodynamic modeling.

We discuss the concept of t-gap block isomorphic subsequences and use it to describe new abstract string metrics that are similar to the Levenshtein insertion-deletion metric. Some of the metrics that we define can be used to model a thermodynamic distance function on single-stranded DNA sequences. Our model captures a key aspect of the nearest neighbor thermodynamic model for hybridized DNA duplexes. One version of our metric gives the maximum number of stacked pairs of hydrogen bonded nucleotide base pairs that can be present in any secondary structure in a hybridized DNA duplex without pseudoknots. Thermodynamic distance functions are important components in the construction of DNA codes, and DNA codes are important components in biomolecular computing, nanotechnology, and other biotechnical applications that employ DNA hybridization assays. We show how our new distances can be calculated by using a dynamic programming method, and we derive a Varshamov-Gilbert-like lower bound on the size of some of codes using these distance functions as constraints. We also discuss software implementation of our DNA code design methods.