Relaxation kinetics in two-dimensional structures

We have studied the approach to equilibrium of islands and pores in two dimensions. The two-regime scenario observed when islands evolve according to a set of particular rules, namely relaxation by steps at low temperature and smooth at high temperature, is generalized to a wide class of kinetic models and the two kinds of structures. Scaling laws for equilibration times are analytically derived and confirmed by kinetic Monte Carlo simulations.Comment: 6 pages, 7 figures, 1 tabl

Gene expression time delays & Turing pattern formation systems

The incorporation of time delays can greatly affect the behaviour of partial differential equations and dynamical systems. In addition, there is evidence that time delays in gene expression due to transcription and translation play an important role in the dynamics of cellular systems. In this paper, we investigate the effects of incorporating gene expression time delays into a one-dimensional putative reaction diffusion pattern formation mechanism on both stationary domains and domains with spatially uniform exponential growth. While oscillatory behaviour is rare, we find that the time taken to initiate and stabilise patterns increases dramatically as the time delay is increased. In addition, we observe that on rapidly growing domains the time delay can induce a failure of the Turing instability which cannot be predicted by a naive linear analysis of the underlying equations about the homogeneous steady state. The dramatic lag in the induction of patterning, or even its complete absence on occasions, highlights the importance of considering explicit gene expression time delays in models for cellular reaction diffusion patterning

Machine Learning in Automated Text Categorization

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual definition of a classifier by domain experts) are a very good effectiveness, considerable savings in terms of expert manpower, and straightforward portability to different domains. This survey discusses the main approaches to text categorization that fall within the machine learning paradigm. We will discuss in detail issues pertaining to three different problems, namely document representation, classifier construction, and classifier evaluation.Comment: Accepted for publication on ACM Computing Survey

A single-dose comparison of the acute effects between the new somatostatin analog SOM230 and octreotide in acromegalic patients

Treatment with the somatostatin receptor (sst) subtype 2 predominant analogs octreotide and lanreotide induces clinical and biochemical cure in approximately 65% of acromegalic patients. GH-secreting pituitary adenomas, which are not controlled, also express sst(5). We compared the acute effects of octreotide and SOM230, a new somatostatin analog with high affinity for sst(1,2,3,5) on hormone release in acromegalic patients. In a single-dose, proof-of-concept study, 100 microg octreotide and 100 and 250 microg SOM230 were given s.c. to 12 patients with active acromegaly. Doses of 100 and 250 microg SOM230 dose-dependently suppressed GH levels from 2-8 h after administration (-38 +/- 7.7 vs. -61 +/- 6.7%, respectively; P < 0.01). A comparable suppression of GH levels by octreotide and 250 microg SOM230 was observed in eight patients (-65 +/- 7 vs. -72 +/- 7%, respectively). In three patients, the acute GH-lowering effect of 250 microg SOM230 was significantly superior to that of octreotide (-70 +/- 2 vs. -17 +/- 15%, respectively; P < 0.01). In one patient, the GH-lowering effect of octreotide was better than that of SOM230. Tolerability for SOM230 was good. Glucose levels were initially slightly elevated after octreotide and SOM230, compared with control day, whereas insulin levels were only significantly suppressed by octreotide. We conclude that SOM230 is an effective GH-lowering drug in acromegalic patients with the potential to increase the number of patients controlled during long-term medical treatment

SPACA3gene variants in a New Zealand cohort of infertile and fertile couples

SPRASA (also referred to as SLLP1) is a protein identified in the acrosome of human sperm and encoded by the gene SPACA3. SPRASA is associated with sperm-oocyte recognition and binding, and may play a role in fertility. In order to determine whether variants in the SPACA3 gene are associated with human infertility, we undertook a genetic analysis of 102 infertile and 104 fertile couples. Three gene variants were identified using PCR-based DNA sequencing; 1) an insertion of TGC within a quadruple tri-nucleotide (TGC) repeat region in the 5’ untranslated region (UTR) (g.–22TGC(4_5), 2) a guanine to adenosine transition at position 239 (c.239G> A) resulting in a non-synonymous amino acid substitution from cysteine to tyrosine (p.C80Y) at position 80 in the putative transmembrane region, and 3) a novel nucleotide variant (c.691G> C) located in the 3’UTR. A functional effect of the g.–22TGC (4_5) was confirmed by a luciferase expression assay, while the effects of the variants c.239G> A and c.691G> C were predicted using in silico analysis. Although the frequencies of these variants were not significantly different between the infertile and fertile populations, we present evidence that the variants could affect the expression levels or function of SPRASA, thereby affecting a couple's fertility. Larger populations, especially individuals/couples with unexplained infertility, need to be screened for these variants to validate a relationship with fertility

Special Libraries, April 1933

Volume 24, Issue 3https://scholarworks.sjsu.edu/sla_sl_1933/1002/thumbnail.jp

Identification of common genetic risk variants for autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.Peer reviewe