Genetic dissection and prognostic modeling of overt stroke in sickle cell anemia

Sickle cell anemia (SCA) is a paradigmatic single gene disorder caused by homozygosity with respect to a unique mutation at the beta-globin locus. SCA is phenotypically complex, with different clinical courses ranging from early childhood mortality to a virtually unrecognized condition. Overt stroke is a severe complication affecting 6-8% of individuals with SCA. Modifier genes might interact to determine the susceptibility to stroke, but such genes have not yet been identified. Using Bayesian networks, we analyzed 108 SNPs in 39 candidate genes in 1,398 individuals with SCA. We found that 31 SNPs in 12 genes interact with fetal hemoglobin to modulate the risk of stroke. This network of interactions includes three genes in the TGF-beta pathway and SELP, which is associated with stroke in the general population. We validated this model in a different population by predicting the occurrence of stroke in 114 individuals with 98.2% accuracy.     

Synthesis and antitumour activity of new daunorubicin and adriamycin analogues

Summary A new synthetic procedure for the preparation of daunorubicin and adriamycin analogues bearing different substituents on ring D, has been developed. The new compounds display outstanding efficacy against experimental tumours of mice.     

A new synthetic sulfur-containing amino acid: S-aminoethylcysteine

Riassunto L'aminoetilcisteina, composto intermedio ipotetico di transulfurazione tra cisteina e etanolamina, è stata preparata cristallina sotto forma di monocloridrato, trattando la cisteina con bromoetilamina in ambiente alcalino.     

Glycolitic enzymes in the human amniotic fluid

Riassunto È stata messa in evidenza nel liquido amniotico di donne a termine di gravidanza la presenza di alcuni enzimi glicolitici. Sono riportati i dati quantitativi ottenuti per l'attività della fosforiboso-isomerasi, aldolasi, fosfoesoso-isomerasi e lattico-deidrogenasi. È stato determinato inoltre il contenuto proteico dei campioni di liquido amniotico presi in esame.     

Quasispecies diversity determines pathogenesis through cooperative interactions in a viral population

An RNA virus population does not consist of a single genotype; rather, it is an ensemble of related sequences, termed quasispecies. Quasispecies arise from rapid genomic evolution powered by the high mutation rate of RNA viral replication. Although a high mutation rate is dangerous for a virus because it results in nonviable individuals, it has been hypothesized that high mutation rates create a 'cloud' of potentially beneficial mutations at the population level, which afford the viral quasispecies a greater probability to evolve and adapt to new environments and challenges during infection. Mathematical models predict that viral quasispecies are not simply a collection of diverse mutants but a group of interactive variants, which together contribute to the characteristics of the population. According to this view, viral populations, rather than individual variants, are the target of evolutionary selection. Here we test this hypothesis by examining the consequences of limiting genomic diversity on viral populations. We find that poliovirus carrying a high-fidelity polymerase replicates at wild-type levels but generates less genomic diversity and is unable to adapt to adverse growth conditions. In infected animals, the reduced viral diversity leads to loss of neurotropism and an attenuated pathogenic phenotype. Notably, using chemical mutagenesis to expand quasispecies diversity of the high-fidelity virus before infection restores neurotropism and pathogenesis. Analysis of viruses isolated from brain provides direct evidence for complementation between members in the quasispecies, indicating that selection indeed occurs at the population level rather than on individual variants. Our study provides direct evidence for a fundamental prediction of the quasispecies theory and establishes a link between mutation rate, population dynamics and pathogenesis.     

Technoscientific approaches to deep time

In this paper, I argue that in order to understand the process behind the knowledge production in the historical sciences, we should change our theoretical focus slightly to consider the historical sciences as technoscientific disciplines. If we investigate the intertwinement of technology and theory, we can provide new insights into historical scientific knowledge production, preconditions, and aims. I will provide evidence for my claim by showing the central features of paleontological and paleobiological data practices of the nineteenth and twentieth centuries. In order to work with something that is imperfect and incomplete (the fossil record), paleontologists used different technological devices. These devices process, extract, correct, simulate, and eventually present paleontological explananda. Therefore, the appearance of anatomical features of non-manipulable fossilized organisms, phenomena such as mass-extinctions, or the life-like display of extinct specimens in a museum's hall, depend both on the correct use of technological devices and on the interplay between these devices and theories. Consequently, in order to capture its underlying epistemology, historical sciences should be analyzed and investigated against other technoscientific disciplines such as chemistry, synthetic biology, and nanotechnology, and not necessarily only against classical experimental sciences. This approach will help us understand how historical scientists can obtain their epistemic access to deep time.     

Weights and robustness of model-based seasonal adjustment

Model-based seasonal adjustment implicitly defines a set of weights at the ends of series as well as in the middle. Until now, with the exception of very simple models, the weights have been obtained numerically. In this paper we give the analytical expressions for the weights for both the structural and the ARIMA framework for a model which contains trend, seasonal and irregular component. In the final part of the paper we address the question of robustness of model-based seasonal adjustment. We analyse practically, using real time series, and theoretically, through the analysis of the shape of the weights, how the fitting of different specifications for the non-seasonal part affects the extraction of the seasonal component. © 1998 John Wiley & Sons, Ltd.     

A tiling resolution DNA microarray with complete coverage of the human genome

We constructed a tiling resolution array consisting of 32,433 overlapping BAC clones covering the entire human genome. This increases our ability to identify genetic alterations and their boundaries throughout the genome in a single comparative genomic hybridization (CGH) experiment. At this tiling resolution, we identified minute DNA alterations not previously reported. These alterations include microamplifications and deletions containing oncogenes, tumor-suppressor genes and new genes that may be associated with multiple tumor types. Our findings show the need to move beyond conventional marker-based genome comparison approaches, that rely on inference of continuity between interval markers. Our submegabase resolution tiling set for array CGH (SMRT array) allows comprehensive assessment of genomic integrity and thereby the identification of new genes associated with disease.     

Genetic organization of Drosophila bithorax complex

The Drosophila bithorax complex is subdivided into three major genes: Ultrabithorax+, abdominal-A+ and Abdominal-B+. Each of these genes plays its principal part in a particular anatomical domain of the body, where it is specifically required to determine the correct segmental pattern.