Hypoxia‐induced vascular endothelial growth factor expression causes vascular leakage in the brain

Formation of cerebral oedema caused by vascular leakage is a major problem in various injuries of the CNS, such as stroke, head injury and high‐altitude illness. A common feature of all these disorders is the fact that they are associated with tissue hypoxia. Hypoxia has therefore been suggested to be an important pathogenic factor for the induction of vascular leakage in the brain. Vascular endothelial growth factor (VEGF) is known as the major inducer of angiogenesis. Originally, however, it was described as a vascular permeability factor. As VEGF gene expression was shown to be upregulated by hypoxia, increased VEGF expression may link hypoxia and vascular leakage in the CNS in vivo. To delineate the role of VEGF in vascular leakage in the brain, we studied the effect of hypoxia on VEGF expression and vascular permeability in the brains of mice in vivo. Hypoxic exposure led to a significant increase in the levels of VEGF mRNA and protein in mouse brain that correlated with the severity of the hypoxic stimulus. Measurement of vascular permeability using the fluorescent marker sodium fluorescein revealed a two‐fold increase in fluorescence intensity in hypoxic brains, indicative of significant vascular leakage. Inhibition of VEGF activity by a neutralizing antibody completely blocked the hypoxia‐induced increase in vascular permeability. In conclusion, our data show that VEGF is responsible for hypoxia‐induced augmentation in vascular leakage following tissue hypoxia. Our findings might provide the basis for new therapeutic concepts for the treatment of cerebral oedem

PHOTOCHEMICAL RING-OPENING IN meso-CHLORINATED CHLOROPHYLLS

Irradiation of 20-chloro-chlorophylls of the a-type with visible light produces long-wavelength shifted photoproducts, which transform in the dark to linear tetrapyrroles (bile pigments). The possible significance for chlorophyll degradation is discussed

Experimental determination of the complete spin structure for anti-proton + proton -> anti-\Lambda + \Lambda at anti-proton beam momentum of 1.637 GeV/c

The reaction anti-proton + proton -> anti-\Lambda + \Lambda -> anti-proton + \pi^+ + proton + \pi^- has been measured with high statistics at anti-proton beam momentum of 1.637 GeV/c. The use of a transversely-polarized frozen-spin target combined with the self-analyzing property of \Lambda/anti-\Lambda decay allows access to unprecedented information on the spin structure of the interaction. The most general spin-scattering matrix can be written in terms of eleven real parameters for each bin of scattering angle, each of these parameters is determined with reasonable precision. From these results all conceivable spin-correlations are determined with inherent self-consistency. Good agreement is found with the few previously existing measurements of spin observables in anti-proton + proton -> anti-\Lambda + \Lambda near this energy. Existing theoretical models do not give good predictions for those spin-observables that had not been previously measured.Comment: To be published in Phys. Rev. C. Tables of results (i.e. Ref. 24) are available at http://www-meg.phys.cmu.edu/~bquinn/ps185_pub/results.tab 24 pages, 16 figure

Measurement of Spin Transfer Observables in Antiproton-Proton -> Antilambda-Lambda at 1.637 GeV/c

Spin transfer observables for the strangeness-production reaction Antiproton-Proton -> Antilambda-Lambda have been measured by the PS185 collaboration using a transversely-polarized frozen-spin target with an antiproton beam momentum of 1.637 GeV/c at the Low Energy Antiproton Ring at CERN. This measurement investigates observables for which current models of the reaction near threshold make significantly differing predictions. Those models are in good agreement with existing measurements performed with unpolarized particles in the initial state. Theoretical attention has focused on the fact that these models produce conflicting predictions for the spin-transfer observables D_{nn} and K_{nn}, which are measurable only with polarized target or beam. Results presented here for D_{nn} and K_{nn} are found to be in disagreement with predictions from existing models. These results also underscore the importance of singlet-state production at backward angles, while current models predict complete or near-complete triplet-state dominance.Comment: 5 pages, 3 figure

Differential Effects of HIF-1 Inhibition by YC-1 on the Overall Outcome and Blood-Brain Barrier Damage in a Rat Model of Ischemic Stroke

Hypoxia-inducible factor 1 (HIF-1) is a master regulator of cellular adaptation to hypoxia and has been suggested as a potent therapeutic target in cerebral ischemia. Here we show in an ischemic stroke model of rats that inhibiting HIF-1 and its downstream genes by 3-(5'-hydroxymethyl-2'-furyl)-1-benzylindazole (YC-1) significantly increases mortality and enlarges infarct volume evaluated by MRI and histological staining. Interestingly, the HIF-1 inhibition remarkably ameliorates ischemia-induced blood-brain barrier (BBB) disruption determined by Evans blue leakage although it does not affect brain edema. The result demonstrates that HIF-1 inhibition has differential effects on ischemic outcomes and BBB permeability. It indicates that HIF-1 may have different functions in different brain cells. Further analyses show that ischemia upregulates HIF-1 and its downstream genes erythropoietin (EPO), vascular endothelial growth factor (VEGF), and glucose transporter (Glut) in neurons and brain endothelial cells and that YC-1 inhibits their expression. We postulate that HIF-1-induced VEGF increases BBB permeability while certain other proteins coded by HIF-1's downstream genes such as epo and glut provide neuroprotection in an ischemic brain. The results indicate that YC-1 lacks the potential as a cerebral ischemic treatment although it confers certain protection to the cerebral vascular system

Experimental determination of the complete spin structure for p¯p→ Λ¯Λ at p{p¯}= 1.637 GeV/c

The reaction p.p → ^^ → .pπ+pπ− has been measured with high statistics at a beam momentum of pp. = 1.637 GeV/c. The use of a transversely polarized frozen-spin target combined with the self-analyzing property of ^/^ decay allows access to unprecedented information on the spin structure of the interaction. The most general spin-scattering matrix can be written in terms of 11 real parameters for each bin of scattering angle; each of these parameters is determined with reasonable precision. From these results, all conceivable spin correlations are determined with inherent self-consistency. Good agreement is found with the few previously existing measurements of spin observables in p.p → ^^ near this energy. Existing theoretical models do not give good predictions for those spin observables that had not been previously measured

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