Neurologic complications in adult living donor liver transplant patients: an underestimated factor?

Liver transplantation is the only curative treatment in patients with end-stage liver disease. Neurological complications (NC) are increasingly reported to occur in patients after cadaveric liver transplantation. This retrospective cohort study aims to evaluate the incidence and causes of NC in living donor liver transplant (LDLT) patients in our transplant center. Between August 1998 and December 2005, 121 adult LDLT patients were recruited into our study. 17% of patients experienced NC, and it occurred significantly more frequently in patients with alcoholic cirrhosis (42%) and autoimmune hepatitis (43%) as compared with patients with hepatitis B or C (9/10%, P = 0.013). The most common NC was encephalopathy (47.6%) followed by seizures (9.5%). The choice of immunosuppression by calcineurin inhibitor (Tacrolimus or Cyclosporin A) showed no significant difference in the incidence of NC (19 vs. 17%). The occurrence of NC did not influence the clinical outcome, since mortality rate, median ICU stay and length of hospital stay were similar between the two groups. Most patients who survived showed a nearly complete recovery of their NC. NCs occur in approximately 1 in 6 patients after LDLT and seem to be predominantly transient in nature, without major impact on clinical outcome

Gaussian Tunneling Model of c-Axis Twist Josephson Junctions

We calculate the critical current density $J^J_c$ for c-axis Josephson tunneling between identical high temperature superconductors twisted an angle $\phi_0$ about the c-axis. We model the tunneling matrix element squared as a Gaussian in the change of wavevector q parallel to the junction, $<|t({\bf q})|^2>\propto\exp(-{\bf q}^2a^2/2\pi^2\sigma^2)$. The $J^J_c(\phi_0)/J^J_c(0)$ obtained for the s- and extended-s-wave order parameters (OP's) are consistent with the Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ data of Li {\it et al.}, but only for strongly incoherent tunneling, $\sigma^2\ge0.25$. A $d_{x^2-y^2}$-wave OP is always inconsistent with the data. In addition, we show that the apparent conventional sum rule violation observed by Basov et al. might be understandable in terms of incoherent c-axis tunneling, provided that the OP is not $d_{x^2-y^2}$-wave.Comment: 6 pages, 6 figure

Genetic Basis of Inherited Macular Dystrophies and Implications for Stem Cell Therapy

Untreatable hereditary macular dystrophy (HMD) presents a major burden to society in terms of the resulting patient disability and the cost to the healthcare provision system. HMD results in central vision loss in humans sufficiently severe for blind registration, and key issues in the development of therapeutic strategies to target these conditions are greater understanding of the causes of photoreceptor loss and the development of restorative procedures. More effective and precise analytical techniques coupled to the development of transgenic models of disease have led to a prolific growth in the identification and our understanding of the genetic mutations that underly HMD. Recent successes in driving differentiation of pluripotent cells towards specific somatic lineages have led to the development of more efficient protocols that can yield enriched populations of a desired phenotype. Retinal pigmented epithelial cells and photoreceptors derived from these are some of the most promising cells that may soon be used in the treatment of specific HMD, especially since rapid developments in the field of induced pluripotency have now set the stage for the production of patient-derived stem cells that overcome the ethical and methodological issues surrounding the use of embryonic derivatives. In this review we highlight a selection of HMD which appear suitable candidates for combinatorial restorative therapy, focusing specifically on where those photoreceptor loss occurs. This technology, along with increased genetic screening, opens up an entirely new pathway to restore vision in patients affected by HMD

Pediatric T- and NK-cell lymphomas: new biologic insights and treatment strategies

T- and natural killer (NK)-cell lymphomas are challenging childhood neoplasms. These cancers have varying presentations, vast molecular heterogeneity, and several are quite unusual in the West, creating diagnostic challenges. Over 20 distinct T- and NK-cell neoplasms are recognized by the 2008 World Health Organization classification, demonstrating the diversity and potential complexity of these cases. In pediatric populations, selection of optimal therapy poses an additional quandary, as most of these malignancies have not been studied in large randomized clinical trials. Despite their rarity, exciting molecular discoveries are yielding insights into these clinicopathologic entities, improving the accuracy of our diagnoses of these cancers, and expanding our ability to effectively treat them, including the use of new targeted therapies. Here, we summarize this fascinating group of lymphomas, with particular attention to the three most common subtypes: T-lymphoblastic lymphoma, anaplastic large cell lymphoma, and peripheral T-cell lymphoma-not otherwise specified. We highlight recent findings regarding their molecular etiologies, new biologic markers, and cutting-edge therapeutic strategies applied to this intriguing class of neoplasms

Natural selection for body shape in resource polymorphic Icelandic Arctic charr

Funding for this study was provided by Natural Sciences and Engineering Research Council of Canada and the Madame Vigdís Finnbogadóttir Scholarship.Resource polymorphisms exhibit remarkable intraspecific diversity and in many cases are expected to be maintained by diversifying selection. Phenotypic trade‐offs can constrain morphologically intermediate individuals from effectively exploiting both alternate resources, resulting in ecological barriers to gene flow. Determining if and how phenotypic trade‐offs cause fitness variation in the wild is challenging because of phenotypic and environmental correlations associated with alternative resource strategies. We investigated multiple pathways through which morphology could affect organismal performance, as measured by growth rate, and whether these effects generate diversifying selection in polymorphic Icelandic Arctic charr (Salvelinus alpinus) populations. We considered direct effects of morphology on growth and indirect effects via trophic resource use, estimated by stable isotopic signatures, and via parasitism associated with trophic resources. We sampled over 3 years in (lakes) Thingvallavatn and Vatnshlíðarvatn using the extended selection gradient path analytical approach and estimating size‐dependent mortality. We found evidence for diversifying selection only in Thingvallavatn: more streamlined and terminally mouthed planktivore charr experienced greater growth, with the opposite pattern in small benthic charr. However, this effect was mediated by parasitism and nontrophic pathways, rather than trophic performance as often expected. Detection of between‐morph differences in the presence (Vatnshlíðarvatn) and direction (Thingvallavatn) of size‐dependent mortality, together with nontrophic effects of shape, suggests that a morphological trophic performance explanation for polymorphism is insufficient. This rare insight into selection during early diversification suggests that a complex of interacting local factors must be considered to understand how phenotype influences fitness, despite morphological variation reflecting intuitive trade‐off explanations.PostprintPeer reviewe

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder