RNA pentaloop structures as effective targets of regulators belonging to the RsmA/CsrA protein family.

In the Gac/Rsm signal transduction pathway of Pseudomonas fluorescens CHA0, the dimeric RNA-binding proteins RsmA and RsmE, which belong to the vast bacterial RsmA/CsrA family, effectively repress translation of target mRNAs containing a typical recognition sequence near the translation start site. Three small RNAs (RsmX, RsmY, RsmZ) with clustered recognition sequences can sequester RsmA and RsmE and thereby relieve translational repression. According to a previously established structural model, the RsmE protein makes optimal contacts with an RNA sequence 5'- (A)/(U)CANGGANG(U)/(A)-3', in which the central ribonucleotides form a hexaloop. Here, we questioned the relevance of the hexaloop structure in target RNAs. We found that two predicted pentaloop structures, AGGGA (in pltA mRNA encoding a pyoluteorin biosynthetic enzyme) and AAGGA (in mutated pltA mRNA), allowed effective interaction with the RsmE protein in vivo. By contrast, ACGGA and AUGGA were poor targets. Isothermal titration calorimetry measurements confirmed the strong binding of RsmE to the AGGGA pentaloop structure in an RNA oligomer. Modeling studies highlighted the crucial role of the second ribonucleotide in the loop structure. In conclusion, a refined structural model of RsmE-RNA interaction accommodates certain pentaloop RNAs among the preferred hexaloop RNAs.

Natural classification of knots

The principal objective of the knot theory is to provide a simple way of classifying and ordering all the knot types. Here, we propose a natural classification of knots based on their intrinsic position in the knot space that is defined by the set of knots to which a given knot can be converted by individual intersegmental passages. In addition, we characterize various knots using a set of simple quantum numbers that can be determined upon inspection of minimal crossing diagram of a knot. These numbers include: crossing number; average three-dimensional writhe; number of topological domains; and the average relaxation value

HIERFSTAT, a package for R to compute and test hierarchical F-statistics

The package HIERFSTAT for the statistical software R, created by the R Development Core Team, allows the estimate of hierarchical F-statistics from a hierarchy with any numbers of levels. In addition, it allows testing the statistical significance of population differentiation for these different levels, using a generalized likelihood-ratio test. The package HIERFSTAT is available at http://www.unil.ch/popgen/softwares/hierfstat.htm.

AWSum-Combining Classification with Knowledge Aquisition

Many classifiers achieve high levels of accuracy but have limited applicability in real world situations because they do not lead to a greater understanding or insight into the^way features influence the classification. In areas such as health informatics a classifier that clearly identifies the influences on classification can be used to direct research and formulate interventions. This research investigates the practical applications of Automated Weighted Sum, (AWSum), a classifier that provides accuracy comparable to other techniques whilst providing insight into the data. This is achieved by calculating a weight for each feature value that represents its influence on the class value. The merits of this approach in classification and insight are evaluated on a Cystic Fibrosis and Diabetes datasets with positive results.

Active learning methods for remote sensing image classification

In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.

Minimal data requirements for a continuous monitoring of the quality of care using the DRG classification.

The DRG classification provides a useful tool for the evaluation of hospital care. Indicators such as readmissions and mortality rates adjusted for the hospital Casemix could be adopted in Switzerland at the price of minor additions to the hospital discharge record. The additional information required to build patients histories and to identify the deaths occurring after hospital discharge is detailed.

Sample size and statistical power in the hierarchical analysis of variance: applications in morphometry of the nervous system.

Analysis of variance is commonly used in morphometry in order to ascertain differences in parameters between several populations. Failure to detect significant differences between populations (type II error) may be due to suboptimal sampling and lead to erroneous conclusions; the concept of statistical power allows one to avoid such failures by means of an adequate sampling. Several examples are given in the morphometry of the nervous system, showing the use of the power of a hierarchical analysis of variance test for the choice of appropriate sample and subsample sizes. In the first case chosen, neuronal densities in the human visual cortex, we find the number of observations to be of little effect. For dendritic spine densities in the visual cortex of mice and humans, the effect is somewhat larger. A substantial effect is shown in our last example, dendritic segmental lengths in monkey lateral geniculate nucleus. It is in the nature of the hierarchical model that sample size is always more important than subsample size. The relative weight to be attributed to subsample size thus depends on the relative magnitude of the between observations variance compared to the between individuals variance.

Intrinsically photosensitive retinal ganglion cells: classification, function and clinical implications.

PURPOSE OF REVIEW: The discovery of a new class of intrinsically photosensitive retinal ganglion cells (ipRGCs) revealed their superior role for various nonvisual biological functions, including the pupil light reflex, and circadian photoentrainment. RECENT FINDINGS: Recent works have identified and characterized several anatomically and functionally distinct ipRGC subtypes and have added strong new evidence for the accessory role of ipRGCs in the visual system in humans. SUMMARY: This review summarizes current concepts related to ipRGC morphology, central connections and behavioural functions and highlights recent studies having clinical relevance to ipRGCs. Clinical implications of the melanopsin system are widespread, particularly as related to chronobiology.

The meiosis-specific recombinase hDmc1 forms ring structures and interacts with hRad51.

Eukaryotic cells encode two homologs of Escherichia coli RecA protein, Rad51 and Dmc1, which are required for meiotic recombination. Rad51, like E.coli RecA, forms helical nucleoprotein filaments that promote joint molecule and heteroduplex DNA formation. Electron microscopy reveals that the human meiosis-specific recombinase Dmc1 forms ring structures that bind single-stranded (ss) and double-stranded (ds) DNA. The protein binds preferentially to ssDNA tails and gaps in duplex DNA. hDmc1-ssDNA complexes exhibit an irregular, often compacted structure, and promote strand-transfer reactions with homologous duplex DNA. hDmc1 binds duplex DNA with reduced affinity to form nucleoprotein complexes. In contrast to helical RecA/Rad51 filaments, however, Dmc1 filaments are composed of a linear array of stacked protein rings. Consistent with the requirement for two recombinases in meiotic recombination, hDmc1 interacts directly with hRad51.

Profiling of counterfeit medicines by vibrational spectroscopy

Counterfeit pharmaceutical products have become a widespread problem in the last decade. Various analytical techniques have been applied to discriminate between genuine and counterfeit products. Among these, Near-infrared (NIR) and Raman spectroscopy provided promising results.The present study offers a methodology allowing to provide more valuable information fororganisations engaged in the fight against counterfeiting of medicines.A database was established by analyzing counterfeits of a particular pharmaceutical product using Near-infrared (NIR) and Raman spectroscopy. Unsupervised chemometric techniques (i.e. principal component analysis - PCA and hierarchical cluster analysis - HCA) were implemented to identify the classes within the datasets. Gas Chromatography coupled to Mass Spectrometry (GC-MS) and Fourier Transform Infrared Spectroscopy (FT-IR) were used to determine the number of different chemical profiles within the counterfeits. A comparison with the classes established by NIR and Raman spectroscopy allowed to evaluate the discriminating power provided by these techniques. Supervised classifiers (i.e. k-Nearest Neighbors, Partial Least Squares Discriminant Analysis, Probabilistic Neural Networks and Counterpropagation Artificial Neural Networks) were applied on the acquired NIR and Raman spectra and the results were compared to the ones provided by the unsupervised classifiers.The retained strategy for routine applications, founded on the classes identified by NIR and Raman spectroscopy, uses a classification algorithm based on distance measures and Receiver Operating Characteristics (ROC) curves. The model is able to compare the spectrum of a new counterfeit with that of previously analyzed products and to determine if a new specimen belongs to one of the existing classes, consequently allowing to establish a link with other counterfeits of the database.

Une nouvelle Classification des néoptasies intraépithélates vulvaires [A new classification of vulvar intraepithelial neoplasia (VIN)]

Vulvar cancer is a rare disease and its screening is depending on the quality and the relevance of our clinical examination. Incidence of vulvar cancer and especially precancerous lesions, vulvar intraepithelial neoplasias (VIN), increased during these last years. The new terminology of vulvar intraepithelial neoplasia will help us to identify high risk groups which could develop a cancer: usual and differentiated VIN. An early diagnosis is essential to propose an adequate treatment. Management is a major point according to the rising incidence of these lesions in younger women. Until we can observe a benefit from the vaccination against human papillomavirus, we must increase the quality of screening by a careful examination of the vulva.

Structures et pratiques économiques dans l'oeuvre d'Émile Zola, l'exemple de Germinal

Fer de lance du naturalisme, Émile Zola a construit chacun de ses romans avec un souci remarquable du détail. Germinal (1885), treizième opus des Rougon-Macquart, n'échappe pas à cette règle. La description que Zola réalise des mines de Montsou et de ses habitants se fonde sur un vaste travail préparatoire mené sur le terrain, et à travers de nombreuses lectures, dont certaines de nature économique. Bien que Zola n'ait pas cherché à inscrire son travail dans le champ de l'économie politique, son interprétation des structures et pratiques économiques dans Germinal constitue à la fois le témoignage d'un écrivain singulier sur l'univers minier de la deuxième partie du XIXe siècle, et une source presque historique des réalités d'un monde aujourd'hui disparu. Cette contribution met en évidence la manière dont Zola a transcrit, dans son ouvrage, le fruit de ses modestes recherches économiques sur l'industrie minière. Elle confronte récit zolien et théorie économique dans le champ des ressources naturelles et dans celui des rapports entre crise et activité minière.