Structure and specificity of T cell receptor gamma/delta on major histocompatibility complex antigen-specific CD3+, CD4-, CD8- T lymphocytes.

Analyses of TCR-bearing murine and human T cells have defined a unique subpopulation of T cells that express the TCR-gamma/delta proteins. The specificity of TCR-gamma/delta T cells and their role in the immune response have not yet been elucidated. Here we examine alloreactive TCR-gamma/delta T cell lines and clones that recognize MHC-encoded antigens. A BALB/c nu/nu (H-2d)-derived H-2k specific T cell line and derived clones were both cytolytic and released lymphokines after recognition of a non-classical H-2 antigen encoded in the TL region of the MHC. These cells expressed the V gamma 2/C gamma 1 protein in association with a TCR-delta gene product encoded by a Va gene segment rearranged to two D delta and one J delta variable elements. A second MHC-specific B10 nu/nu (H-2b) TCR-gamma/delta T cell line appeared to recognize a classical H-2D-encoded MHC molecule and expressed a distinct V gamma/C gamma 4-encoded protein. These data suggest that many TCR-gamma/delta-expressing T cells may recognize MHC-linked antigens encoded within distinct subregions of the MHC. The role of MHC-specific TCR-gamma/delta cells in immune responses and their immunological significance are discussed

Projected free energies for polydisperse phase equilibria

A `polydisperse' system has an infinite number of conserved densities. We give a rational procedure for projecting its infinite-dimensional free energy surface onto a subspace comprising a finite number of linear combinations of densities (`moments'), in which the phase behavior is then found as usual. If the excess free energy of the system depends only on the moments used, exact cloud, shadow and spinodal curves result; two- and multi-phase regions are approximate, but refinable indefinitely by adding extra moments. The approach is computationally robust and gives new geometrical insights into the thermodynamics of polydispersity.Comment: 4 pages, REVTeX, uses multicol.sty and epsf.sty, 1 postscript figure include

Predicting phase equilibria in polydisperse systems

Many materials containing colloids or polymers are polydisperse: They comprise particles with properties (such as particle diameter, charge, or polymer chain length) that depend continuously on one or several parameters. This review focusses on the theoretical prediction of phase equilibria in polydisperse systems; the presence of an effectively infinite number of distinguishable particle species makes this a highly nontrivial task. I first describe qualitatively some of the novel features of polydisperse phase behaviour, and outline a theoretical framework within which they can be explored. Current techniques for predicting polydisperse phase equilibria are then reviewed. I also discuss applications to some simple model systems including homopolymers and random copolymers, spherical colloids and colloid-polymer mixtures, and liquid crystals formed from rod- and plate-like colloidal particles; the results surveyed give an idea of the rich phenomenology of polydisperse phase behaviour. Extensions to the study of polydispersity effects on interfacial behaviour and phase separation kinetics are outlined briefly.Comment: 48 pages, invited topical review for Journal of Physics: Condensed Matter; uses Institute of Physics style file iopart.cls (included

Linkage analysis of longitudinal data and design consideration

BACKGROUND: Statistical methods have been proposed recently to analyze longitudinal data in genetic studies. So far, little attention has been paid to examine the relationship among key factors in genetic longitudinal studies including power, the number of families or sibships, and the number of repeated measures per individual subjects. RESULTS: We proposed a variance component model that extends classic variance component models for a single quantitative trait to mapping longitudinal traits. Our model includes covariate effects and allows genetic effects to vary over time. Using our proposed model, we examined the power, pedigree structures, and sample size through simulation experiments. CONCLUSION: Our simulation results provide useful insights into the study design for genetic, longitudinal studies. For example, collecting a small number of large sibships is much more powerful than collecting a large number of small sibships or increasing the number of repeated measures, when the total number of measurements is comparable

Antidepressant use and risk of epilepsy and seizures in people aged 20 to 64 years: cohort study using a primary care database

Background: Epilepsy is a serious condition which can profoundly affect an individual’s life. While there is some evidence to suggest an association between antidepressant use and epilepsy and seizures it is conflicting and not conclusive. Antidepressant prescribing is rising in the UK so it is important to quantify absolute risks with individual antidepressants to enable shared decision making with patients. In this study we assess and quantify the association between antidepressant treatment and the risk of epilepsy and seizures in a large cohort of patients diagnosed with depression aged between 20 and 64 years. Methods: Data on 238,963 patients with a diagnosis of depression aged 20 to 64 from 687 UK practices were extracted from the QResearch primary care database. We used Cox’s proportional hazards to analyse the time to the first recorded diagnosis of epilepsy/seizures, excluding patients with a prior history and estimated hazard ratios for antidepressant exposure adjusting for potential confounding variables. Results: In the first 5 years of follow-up, 878 (0.37 %) patients had a first diagnosis of epilepsy/seizures with the hazard ratio (HR) significantly increased (P < 0.01) for all antidepressant drug classes and for 8 of the 11 most commonly prescribed drugs. The highest risks (in the first 5 years) compared with no treatment were for trazodone (HR 5.41, 95 % confidence interval (CI) 3.05 to 9.61, number needed to harm (NNH) 65), lofepramine (HR 3.09, 95 % CI 1.73 to 5.50, NNH 138), venlafaxine (HR 2.84, 95 % CI 1.97 to 4.08, NNH 156) and combined antidepressant treatment (HR 2.73, 95 % CI 1.52 to 4.91, NNH 166). Conclusions: Risk of epilepsy/seizures is significantly increased for all classes of antidepressant. There is a need for individual risk-benefit assessments in patients being considered for antidepressant treatment, especially those with ongoing mild depression or with additional risk factors. Residual confounding and indication bias may influence our results, so confirmation may be required from additional studies

N-Myc and GCN5 Regulate Significantly Overlapping Transcriptional Programs in Neural Stem Cells

Here we examine the functions of the Myc cofactor and histone acetyltransferase, GCN5/KAT2A, in neural stem and precursor cells (NSC) using a conditional knockout approach driven by nestin-cre. Mice with GCN5-deficient NSC exhibit a 25% reduction in brain mass with a microcephaly phenotype similar to that observed in nestin-cre driven knockouts of c- or N-myc. In addition, the loss of GCN5 inhibits precursor cell proliferation and reduces their populations in vivo, as does loss of N-myc. Gene expression analysis indicates that about one-sixth of genes whose expression is affected by loss of GCN5 are also affected in the same manner by loss of N-myc. These findings strongly support the notion that GCN5 protein is a key N-Myc transcriptional cofactor in NSC, but are also consistent with recruitment of GCN5 by other transcription factors and the use by N-Myc of other histone acetyltransferases. Putative N-Myc/GCN5 coregulated transcriptional pathways include cell metabolism, cell cycle, chromatin, and neuron projection morphogenesis genes. GCN5 is also required for maintenance of histone acetylation both at its putative specific target genes and at Myc targets. Thus, we have defined an important role for GCN5 in NSC and provided evidence that GCN5 is an important Myc transcriptional cofactor in vivo

c- and N-myc Regulate Neural Precursor Cell Fate, Cell Cycle, and Metabolism to Direct Cerebellar Development

Separate murine knockout (KO) of either c- or N-myc genes in neural stem and precursor cells (NSC) driven by nestin-cre causes microcephaly. The cerebellum is particularly affected in the N-myc KO, leading to a strong reduction in cerebellar granule neural progenitors (CGNP) and mature granule neurons. In humans, mutation of N-myc also causes microcephaly in Feingold Syndrome. We created a double KO (DKO) of c- and N-myc using nestin-cre, which strongly impairs brain growth, particularly that of the cerebellum. Granule neurons were almost absent from the Myc DKO cerebellum, and other cell types were relatively overrepresented, including astroglia, oligodendrocytes, and Purkinje neurons. These findings are indicative of a profound disruption of cell fate of cerebellar stem and precursors. DKO Purkinje neurons were strikingly lacking in normal arborization. Inhibitory neurons were ectopic and exhibited very abnormal GAD67 staining patterns. Also consistent with altered cell fate, the adult DKO cerebellum still retained a residual external germinal layer (EGL). CGNP in the DKO EGL were almost uniformly NeuN and p27KIP1 positive as well as negative for Math1 and BrdU at the peak of normal cerebellar proliferation at P6. The presence of some mitotic CGNP in the absence of S phase cells suggests a possible arrest in M phase. CGNP and NSC metabolism also was affected by loss of Myc as DKO cells exhibited weak nucleolin staining. Together these findings indicate that c- and N-Myc direct cerebellar development by maintaining CGNP and NSC populations through inhibiting differentiation as well as directing rapid cell cycling and active cellular metabolism

Co-Localization of the Oncogenic Transcription Factor MYCN and the DNA Methyl Binding Protein MeCP2 at Genomic Sites in Neuroblastoma

MYCN is a transcription factor that is expressed during the development of the neural crest and its dysregulation plays a major role in the pathogenesis of pediatric cancers such as neuroblastoma, medulloblastoma and rhabdomyosarcoma. MeCP2 is a CpG methyl binding protein which has been associated with a number of cancers and developmental disorders, particularly Rett syndrome.Using an integrative global genomics approach involving chromatin immunoprecipitation applied to microarrays, we have determined that MYCN and MeCP2 co-localize to gene promoter regions, as well as inter/intragenic sites, within the neuroblastoma genome (MYCN amplified Kelly cells) at high frequency (70.2% of MYCN sites were also positive for MeCP2). Intriguingly, the frequency of co-localization was significantly less at promoter regions exhibiting substantial hypermethylation (8.7%), as determined by methylated DNA immunoprecipitation (MeDIP) applied to the same microarrays. Co-immunoprecipitation of MYCN using an anti-MeCP2 antibody indicated that a MYCN/MeCP2 interaction occurs at protein level. mRNA expression profiling revealed that the median expression of genes with promoters bound by MYCN was significantly higher than for genes bound by MeCP2, and that genes bound by both proteins had intermediate expression. Pathway analysis was carried out for genes bound by MYCN, MeCP2 or MYCN/MeCP2, revealing higher order functions.Our results indicate that MYCN and MeCP2 protein interact and co-localize to similar genomic sites at very high frequency, and that the patterns of binding of these proteins can be associated with significant differences in transcriptional activity. Although it is not yet known if this interaction contributes to neuroblastoma disease pathogenesis, it is intriguing that the interaction occurs at the promoter regions of several genes important for the development of neuroblastoma, including ALK, AURKA and BDNF