The endangered whale shark (Rhincodon typus) is the largest fish on Earth and a long-lived member of the ancient Elasmobranchii clade. To characterize the relationship between genome features and biological traits, we sequenced and assembled the genome of the whale shark and compared its genomic and physiological features to those of 83 animals and yeast. We examined the scaling relationships between body size, temperature, metabolic rates, and genomic features and found both general correlations across the animal kingdom and features specific to the whale shark genome. Among animals, increased lifespan is positively correlated to body size and metabolic rate. Several genomic traits also significantly correlated with body size, including intron and gene length. Our large-scale comparative genomic analysis uncovered general features of metazoan genome architecture: Guanine and cytosine (GC) content and codon adaptation index are negatively correlated, and neural connectivity genes are longer than average genes in most genomes. Focusing on the whale shark genome, we identified multiple features that significantly correlate with lifespan. Among these were very long gene length, due to introns being highly enriched in repetitive elements such as CR1-like long interspersed nuclear elements, and considerably longer neural genes of several types, including connectivity, activity, and neurodegeneration genes. The whale shark genome also has the second slowest evolutionary rate observed in vertebrates to date. Our comparative genomics approach uncovered multiple genetic features associated with body size, metabolic rate, and lifespan and showed that the whale shark is a promising model for studies of neural architecture and lifespan.

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Many features of the sequence of action potentials produced by repeated stimulation of a patch of cardiac muscle can be modeled by a 1D mapping, but not the full behavior included in the restitution portrait. Specifically, recent experiments have found that (i) the dynamic and S1-S2 restitution curves are different (rate dependence) and (ii) the approach to steady state, which requires many action potentials (accommodation), occurs along a curve distinct from either restitution curve. Neither behavior can be produced by a 1D mapping. To address these shortcomings, ad hoc 2D mappings, where the second variable is a "memory" variable, have been proposed; these models exhibit qualitative features of the relevant behavior, but a quantitative fit is not possible. In this paper we introduce a new 2D mapping and determine a set of parameters for it that gives a quantitatively accurate description of the full restitution portrait measured from a bullfrog ventricle. The mapping can be derived as an asymptotic limit of an idealized ionic model in which a generalized concentration acts as a memory variable. This ionic basis clarifies how the present model differs from previous models. The ionic basis also provides the foundation for more extensive cardiac modeling: e.g., constructing a PDE model that may be used to study the effect of memory on propagation. The fitting procedure for the mapping is straightforward and can easily be applied to obtain a mathematical model for data from other experiments, including experiments on different species.

Many Drosophila species differ widely in their distributions and climate niches, making them excellent subjects for evolutionary genomic studies. Here, we have developed a database of high‐quality assemblies for 46 Drosophila species and one closely related Zaprionus. Fifteen of the genomes were newly sequenced, and 20 were improved with additional sequencing. New or improved annotations were generated for all 47 species, assisted by new transcriptomes for 19. Phylogenomic analyses of these data resolved several previously ambiguous relationships, especially in the melanogaster species group. However, it also revealed significant phylogenetic incongruence among genes, mainly in the form of incomplete lineage sorting in the subgenus Sophophora but also including asymmetric introgression in the subgenus Drosophila. Using the phylogeny as a framework and taking into account these incongruences, we then screened the data for genome‐wide signals of adaptation to different climatic niches. First, phylostratigraphy revealed relatively high rates of recent novel gene gain in three temperate pseudoobscura and five desert‐adapted cactophilic mulleri subgroup species. Second, we found differing ratios of nonsynonymous to synonymous substitutions in several hundred orthologues between climate generalists and specialists, with trends for significantly higher ratios for those in tropical and lower ratios for those in temperate‐continental specialists respectively than those in the climate generalists. Finally, resequencing natural populations of 13 species revealed tropics‐restricted species generally had smaller population sizes, lower genome diversity and more deleterious mutations than the more widespread species. We conclude that adaptation to different climates in the genus Drosophila has been associated with large‐scale and multifaceted genomic changes.

The effects of fluoxetine (FLU) and its active metabolite, norfluoxetine (NFLU), on the polysomnogram (PSG) of nine depressed outpatients (eight with major depression; one with bipolar II, depressed phase disorder) were investigated by contrasting PSG values prior to treatment and during administration of FLU. The PSG changes were correlated with daily dose, cumulative dosage, single serum concentrations, and the total area under the serum concentration curve (AUC) of both FLU and NFLU.KEY WORDS: Fluoxetine; Norfluoxetine; Polysomnography; Serotonin; Depression Fluoxetine (FLU)-a potent, specifIc, serotonin reup take inhibitor-is an effective treatment for major depression (for a review, see Depression Guideline Panel, 1993). Serotonin affects the regulation of the sleep-wake cycle. It plays a role in the induction and maintenance of sleep as well as the character of sleep stage macro architecture and rapid-eye-movement (REM) sleep expression Oouvet et al. 1989).Fluoxetine reportedly causes a shift toward lighter Fluoxetine clearly increased both stage 1 sleep time and rapid-eye-movement (REM) latency and decreased both percent REM and REM density. With a few exceptions, the cumulative dosage of FLU and the AUC of FLU and NFLU were better predictors of the changes in awake and movement time in the PSG than single-sample concentrations of FLU and NFLU taken at the time of PSG assessment. fNeuropsychopharmacology 10: 85-91, 1994J sleep that is reflected in increases in sleep latency and percentage of non-REM stage 1 sleep and decreases in total sleep time, sleep efficiency, and percentage of non REM stages 3 and 4 sleep (Nicholson and Pascoe 1986;Pastel and Fernstrom 1987;Kerkhofs et al. 1990;Keck et al. 1991;Keck and McElroy 1992). The duration of REM sleep and REM latency, as well as REM density, may also be affected by FLU (Nicholson and Pascoe 1988;von Bardeleben et al. 1989;Nicholson et al. 1989; Bakalian and Fernstrom 1990;Hanzel et al. 1991;Saletu et al. 1991). These effects likely depend upon both the dose and duration of FLU treatment.Changes in polysomnogram (PSG) measures as sociated with chronic FLU treatment in depressed sub jects have been incompletely studied (Schenck et al. 1992). Relationships among PSG measures and serum concentrations of FLU and its active metabolite norflu oxetine (NFLU) have not been previously reported in depressed patients. This pilot study evaluated the effect of FLU and NFLU on PSG measures in a group of medication-responsive depressed outpatients.