Properties of Graphene: A Theoretical Perspective

In this review, we provide an in-depth description of the physics of monolayer and bilayer graphene from a theorist's perspective. We discuss the physical properties of graphene in an external magnetic field, reflecting the chiral nature of the quasiparticles near the Dirac point with a Landau level at zero energy. We address the unique integer quantum Hall effects, the role of electron correlations, and the recent observation of the fractional quantum Hall effect in the monolayer graphene. The quantum Hall effect in bilayer graphene is fundamentally different from that of a monolayer, reflecting the unique band structure of this system. The theory of transport in the absence of an external magnetic field is discussed in detail, along with the role of disorder studied in various theoretical models. We highlight the differences and similarities between monolayer and bilayer graphene, and focus on thermodynamic properties such as the compressibility, the plasmon spectra, the weak localization correction, quantum Hall effect, and optical properties. Confinement of electrons in graphene is nontrivial due to Klein tunneling. We review various theoretical and experimental studies of quantum confined structures made from graphene. The band structure of graphene nanoribbons and the role of the sublattice symmetry, edge geometry and the size of the nanoribbon on the electronic and magnetic properties are very active areas of research, and a detailed review of these topics is presented. Also, the effects of substrate interactions, adsorbed atoms, lattice defects and doping on the band structure of finite-sized graphene systems are discussed. We also include a brief description of graphane -- gapped material obtained from graphene by attaching hydrogen atoms to each carbon atom in the lattice.Comment: 189 pages. submitted in Advances in Physic

Transcriptome profiling of sheep granulosa cells and oocytes during early follicular development obtained by Laser Capture Microdissection

<p>Abstract</p> <p>Background</p> <p>Successful achievement of early folliculogenesis is crucial for female reproductive function. The process is finely regulated by cell-cell interactions and by the coordinated expression of genes in both the oocyte and in granulosa cells. Despite many studies, little is known about the cell-specific gene expression driving early folliculogenesis. The very small size of these follicles and the mixture of types of follicles within the developing ovary make the experimental study of isolated follicular components very difficult.</p> <p>The recently developed laser capture microdissection (LCM) technique coupled with microarray experiments is a promising way to address the molecular profile of pure cell populations. However, one main challenge was to preserve the RNA quality during the isolation of single cells or groups of cells and also to obtain sufficient amounts of RNA.</p> <p>Using a new LCM method, we describe here the separate expression profiles of oocytes and follicular cells during the first stages of sheep folliculogenesis.</p> <p>Results</p> <p>We developed a new tissue fixation protocol ensuring efficient single cell capture and RNA integrity during the microdissection procedure. Enrichment in specific cell types was controlled by qRT-PCR analysis of known genes: six oocyte-specific genes (<it>SOHLH2</it>, <it>MAEL</it>, <it>MATER</it>, <it>VASA</it>, <it>GDF9</it>, <it>BMP15</it>) and three granulosa cell-specific genes (<it>KL</it>, <it>GATA4</it>, <it>AMH</it>).</p> <p>A global gene expression profile for each follicular compartment during early developmental stages was identified here for the first time, using a bovine Affymetrix chip. Most notably, the granulosa cell dataset is unique to date. The comparison of oocyte vs. follicular cell transcriptomes revealed 1050 transcripts specific to the granulosa cell and 759 specific to the oocyte.</p> <p>Functional analyses allowed the characterization of the three main cellular events involved in early folliculogenesis and confirmed the relevance and potential of LCM-derived RNA.</p> <p>Conclusions</p> <p>The ovary is a complex mixture of different cell types. Distinct cell populations need therefore to be analyzed for a better understanding of their potential interactions. LCM and microarray analysis allowed us to identify novel gene expression patterns in follicular cells at different stages and in oocyte populations.</p

Quality of life data as prognostic indicators of survival in cancer patients: an overview of the literature from 1982 to 2008

<p>Abstract</p> <p>Background</p> <p>Health-related quality of life and survival are two important outcome measures in cancer research and practice. The aim of this paper is to examine the relationship between quality of life data and survival time in cancer patients.</p> <p>Methods</p> <p>A review was undertaken of all the full publications in the English language biomedical journals between 1982 and 2008. The search was limited to cancer, and included the combination of keywords 'quality of life', 'patient reported-outcomes' 'prognostic', 'predictor', 'predictive' and 'survival' that appeared in the titles of the publications. In addition, each study was examined to ensure that it used multivariate analysis. Purely psychological studies were excluded. A manual search was also performed to include additional papers of potential interest.</p> <p>Results</p> <p>A total of 451 citations were identified in this rapid and systematic review of the literature. Of these, 104 citations on the relationship between quality of life and survival were found to be relevant and were further examined. The findings are summarized under different headings: heterogeneous samples of cancer patients, lung cancer, breast cancer, gastro-oesophageal cancers, colorectal cancer, head and neck cancer, melanoma and other cancers. With few exceptions, the findings showed that quality of life data or some aspects of quality of life measures were significant independent predictors of survival duration. Global quality of life, functioning domains and symptom scores - such as appetite loss, fatigue and pain - were the most important indicators, individually or in combination, for predicting survival times in cancer patients after adjusting for one or more demographic and known clinical prognostic factors.</p> <p>Conclusion</p> <p>This review provides evidence for a positive relationship between quality of life data or some quality of life measures and the survival duration of cancer patients. Pre-treatment (baseline) quality of life data appeared to provide the most reliable information for helping clinicians to establish prognostic criteria for treating their cancer patients. It is recommended that future studies should use valid instruments, apply sound methodological approaches and adequate multivariate statistical analyses adjusted for socio-demographic characteristics and known clinical prognostic factors with a satisfactory validation strategy. This strategy is likely to yield more accurate and specific quality of life-related prognostic variables for specific cancers.</p

Comparison Of Generic And Lung Cancer-Specific Quality Of Life Instruments For Predictive Ability Of Survival In Patients With Advanced Lung Cancer

Background Our purpose is to examine the relationship of Health related quality of life measured by EORTC QLQc30, QLQ-LC13; FACT-L, LCSS, Eq5D) with survival in advanced lung cancer patients. A total of 299 Lung Cancer (LC) patients were, included in this national multicenter Project entitled of “the LC Quality of Life Project (AKAYAK). Baseline scores were analyzed by using Cox’s proportional hazard regression to identify factors that influenced survival. Univariate and multivariate models were run for each of the scales included in the study. Results Mean and median survival were 12.5 and 8.0 months respectively. Clinical stage (as TNM), comorbidity; symptom scales of fatigue, insomnia, appetit loss and constipation were associated with survival after adjustment for age and sex. Global, physical and role functioning scales of QLQc30; physical and functional scales of LCS and TOI of the FACT-L was also associated with survival. Mobility and Usual activities dimensions of the Eq5D; Physical functioning and the constipation symptom scale of the QLQ-c30; and LCS and TOI scores of the FACT-L remained statistically significant after adjustment. LC13 and LCSS scales were not predictors of survival. Conclusions HRQOL serves as an additional predictive factor for survival that supplements traditional clinical factors. Besides the strong predictive ability of ECOG on survival, FACT-L and the Eq5D are the most promising HRQOL instruments for this purpose.PubMedWoSScopu