Zebrafish fin regeneration involves transient serotonin synthesis

The zebrafish is a vertebrate organism capable of regenerating many of its organs. Notably, it can undergo epimorphic regeneration of its fins after amputation. This process occurs through the formation of a wound epithelium and the dedifferentiation of mesenchymal and bone‐forming cells, which form a proliferative blastema. Here, we report that the entry into the regenerative process involves the local synthesis of serotonin (5‐hydroxytryptamine, 5‐HT) in the injury‐associated tissue. One day after wounding, intracellular accumulation of serotonin was induced in the stump below the amputation plane. During blastema formation, serotonin was detected in the mesenchyme at the vicinity of the amputation plane and in the apical wound epithelium. During the advanced outgrowth phase, this monoamine was no longer present in the blastema, suggesting a temporal involvement of serotonin in the postinjury area. We show the expression of two serotonin synthesizing enzymes, tryptophan hydroxylase 1a and 1b in the blastema, suggesting the local production of this monoamine. Neither depletion of serotonin by chemical inhibition of tryptophan hydroxylase, nor ectopic administration of this monoamine affected fin regeneration, indicating it does not play a role during this process. Finally, we found that the presence of serotonin during regeneration depends on fibroblast growth factor and retinoic acid signaling. Overall, our study demonstrates that the initiation of fin regeneration is associated with a transient synthesis of serotonin in the regrowing tissue

Decreased Risk of Squamous Cell Carcinoma of the Head and Neck in Users of Nonsteroidal Anti-Inflammatory Drugs

We evaluated the chemopreventive effect of nonsteroidal anti-inflammatory drug (NSAID) use in head and neck squamous cell carcinomas (HNSCC) by conducting a case-control study based on the administration of a standardized questionnaire to 71 incident HNSCC cases and same number of healthy controls. NSAID use was associated with a 75% reduction in risk of developing HNSCC. A significant risk reduction was noted in association with frequency of NSAID use. Restricting the analysis to aspirin users revealed a significant 90% reduction in risk of developing HNSCC. This study provides evidence for a significant reduction in the risk of developing HNSCC in users of NSAIDs, and specifically aspirin users

Equivalent forms of Dirac equations in curved spacetimes and generalized de Broglie relations

One may ask whether the relations between energy and frequency and between momentum and wave vector, introduced for matter waves by de Broglie, are rigorously valid in the presence of gravity. In this paper, we show this to be true for Dirac equations in a background of gravitational and electromagnetic fields. We first transform any Dirac equation into an equivalent canonical form, sometimes used in particular cases to solve Dirac equations in a curved spacetime. This canonical form is needed to apply the Whitham Lagrangian method. The latter method, unlike the WKB method, places no restriction on the magnitude of Planck's constant to obtain wave packets, and furthermore preserves the symmetries of the Dirac Lagrangian. We show using canonical Dirac fields in a curved spacetime, that the probability current has a Gordon decomposition into a convection current and a spin current, and that the spin current vanishes in the Whitham approximation, which explains the negligible effect of spin on wave packet solutions, independent of the size of Planck's constant. We further discuss the classical-quantum correspondence in a curved spacetime based on both Lagrangian and Hamiltonian formulations of the Whitham equations. We show that the generalized de Broglie relations in a curved spacetime are a direct consequence of Whitham's Lagrangian method, and not just a physical hypothesis as introduced by Einstein and de Broglie, and by many quantum mechanics textbooks.Comment: PDF, 32 pages in referee format. Added significant material on canonical forms of Dirac equations. Simplified Theorem 1 for normal Dirac equations. Added section on Gordon decomposition of the probability current. Encapsulated main results in the statement of Theorem

Detecting failure of climate predictions

The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty. Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies. Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055

Analyzing 2D gel images using a two-component empirical bayes model

<p>Abstract</p> <p>Background</p> <p>Two-dimensional polyacrylomide gel electrophoresis (2D gel, 2D PAGE, 2-DE) is a powerful tool for analyzing the proteome of a organism. Differential analysis of 2D gel images aims at finding proteins that change under different conditions, which leads to large-scale hypothesis testing as in microarray data analysis. Two-component empirical Bayes (EB) models have been widely discussed for large-scale hypothesis testing and applied in the context of genomic data. They have not been implemented for the differential analysis of 2D gel data. In the literature, the mixture and null densities of the test statistics are estimated separately. The estimation of the mixture density does not take into account assumptions about the null density. Thus, there is no guarantee that the estimated null component will be no greater than the mixture density as it should be.</p> <p>Results</p> <p>We present an implementation of a two-component EB model for the analysis of 2D gel images. In contrast to the published estimation method, we propose to estimate the mixture and null densities simultaneously using a constrained estimation approach, which relies on an iteratively re-weighted least-squares algorithm. The assumption about the null density is naturally taken into account in the estimation of the mixture density. This strategy is illustrated using a set of 2D gel images from a factorial experiment. The proposed approach is validated using a set of simulated gels.</p> <p>Conclusions</p> <p>The two-component EB model is a very useful for large-scale hypothesis testing. In proteomic analysis, the theoretical null density is often not appropriate. We demonstrate how to implement a two-component EB model for analyzing a set of 2D gel images. We show that it is necessary to estimate the mixture density and empirical null component simultaneously. The proposed constrained estimation method always yields valid estimates and more stable results. The proposed estimation approach proposed can be applied to other contexts where large-scale hypothesis testing occurs.</p

Associations between cigarette smoking and mitochondrial DNA abnormalities in buccal cells

DNA alterations in mitochondria are believed to play a role in carcinogenesis and are found in smoking-related cancers. We sought to replicate earlier findings for the association of smoking with increased mitochondrial DNA (mtDNA) content in buccal cells and further hypothesized that there would be an increased number of somatic mtDNA mutations in smokers. Buccal cells and blood lymphocytes were studied from 42 healthy smokers and 30 non-smokers. Temporal temperature gradient electrophoresis screening and sequencing was used to identify mtDNA mutations. The relative mtDNA content was determined by real-time polymerase chain reaction. Assuming that mtDNA in lymphocytes represents the inherited sequence, it was found that 31% of smokers harbored at least one somatic mtDNA mutation in buccal cells with a total of 39 point mutations and 8 short deletions/insertions. In contrast, only 23% of non-smokers possessed mutations with a total of 10 point mutations and no insertions/deletions detected. mtDNA somatic mutation density was higher in smokers (0.68/10 000 bp per person) than in non-smokers (0.2/10 000 bp per person). There was a statistically significant difference in the pattern of homoplasmy and heteroplasmy mutation changes between smokers and non-smokers. Whereas non-smokers had the most mutations in D-loop region (70%), smokers had mutations in both messenger RNA encoding gene (36%) and D-loop region (49%). The mean ratio of buccal cells to lymphocytes of mtDNA content in smokers was increased (2.81) when compared with non-smokers (0.46). These results indicate that cigarette smoke exposure affects mtDNA in buccal cells of smokers. Additional studies are needed to determine if mitochondrial mutation assays provide new or complementary information for estimating cigarette smoke exposure at the cellular level or as a cancer risk biomarker

Modulation of Serotonin Transporter Function during Fetal Development Causes Dilated Heart Cardiomyopathy and Lifelong Behavioral Abnormalities

BACKGROUND: Women are at great risk for mood and anxiety disorders during their childbearing years and may become pregnant while taking antidepressant drugs. In the treatment of depression and anxiety disorders, selective serotonin reuptake inhibitors (SSRIs) are the most frequently prescribed drugs, while it is largely unknown whether this medication affects the development of the central nervous system of the fetus. The possible effects are the product of placental transfer efficiency, time of administration and dose of the respective SSRI. METHODOLOGY/PRINCIPAL FINDINGS: In order to attain this information we have setup a study in which these parameters were measured and the consequences in terms of physiology and behavior are mapped. The placental transfer of fluoxetine and fluvoxamine, two commonly used SSRIs, was similar between mouse and human, indicating that the fetal exposure of these SSRIs in mice is comparable with the human situation. Fluvoxamine displayed a relatively low placental transfer, while fluoxetine showed a relatively high placental transfer. Using clinical doses of fluoxetine the mortality of the offspring increased dramatically, whereas the mortality was unaffected after fluvoxamine exposure. The majority of the fluoxetine-exposed offspring died postnatally of severe heart failure caused by dilated cardiomyopathy. Molecular analysis of fluoxetine-exposed offspring showed long-term alterations in serotonin transporter levels in the raphe nucleus. Furthermore, prenatal fluoxetine exposure resulted in depressive- and anxiety-related behavior in adult mice. In contrast, fluvoxamine-exposed mice did not show alterations in behavior and serotonin transporter levels. Decreasing the dose of fluoxetine resulted in higher survival rates and less dramatic effects on the long-term behavior in the offspring. CONCLUSIONS: These results indicate that prenatal fluoxetine exposure affects fetal development, resulting in cardiomyopathy and a higher vulnerability to affective disorders in a dose-dependent manner