Eficacia del diagnóstico prenatal no invasivo por células fetales libres en sangre materna 1990-2014. Revisión sistemática

ANTECEDENTES: El aislamiento de células fetales libres o ADN fetal en sangre materna abre una ventana de posibilidades diagnósticas no invasivas para patologías monogénicas y cromosómicas, además de permitir la identificación del sexo y del RH fetal. Actualmente existen múltiples estudios que evalúan la eficacia de estos métodos, mostrando resultados costo-efectivos y de menor riesgo que el estándar de oro. Este trabajo describe la evidencia encontrada acerca del diagnóstico prenatal no invasivo luego de realizar una revisión sistemática de la literatura. OBJETIVOS: El objetivo de este estudio fue reunir la evidencia que cumpla con los criterios de búsqueda, en el tema del diagnóstico fetal no invasivo por células fetales libres en sangre materna para determinar su utilidad diagnóstica.  MÉTODOS: Se realizó una revisión sistemática de la literatura con el fin de determinar si el diagnóstico prenatal no invasivo por células fetales libres en sangre materna es efectivo como método de diagnóstico.  RESULTADOS: Se encontraron 5,893 artículos que cumplían con los criterios de búsqueda; 67 cumplieron los criterios de inclusión: 49.3% (33/67) correspondieron a estudios de corte transversal, 38,8% (26/67) a estudios de cohortes y el 11.9% (8/67) a estudios casos y controles. Se obtuvieron resultados de sensibilidad, especificidad y tipo de prueba. CONCLUSIÓN: En la presente revisión sistemática, se evidencia como el diagnóstico prenatal no invasivo es una técnica feasible, reproducible y sensible para el diagnóstico fetal, evitando el riesgo de un diagnóstico invasivo.

Simulazione numerica di fenomeni aeroelastici con applicazione alle strutture civili

Il presente lavoro tratta lo studio dei fenomeni aeroelastici di interazione fra fluido e struttura, con il fine di provare a simularli mediante l’ausilio di un codice agli elementi finiti. Nel primo capitolo sono fornite alcune nozioni di fluidodinamica, in modo da rendere chiari i passaggi teorici fondamentali che portano alle equazioni di Navier-Stokes governanti il moto dei fluidi viscosi. Inoltre è illustrato il fenomeno della formazione di vortici a valle dei corpi tozzi dovuto alla separazione dello strato limite laminare, con descrizione anche di alcuni risultati ottenuti dalle simulazioni numeriche. Nel secondo capitolo vengono presi in rassegna i principali fenomeni di interazione fra fluido e struttura, cercando di metterne in luce le fondamenta della trattazione analitica e le ipotesi sotto le quali tale trattazione è valida. Chiaramente si tratta solo di una panoramica che non entra in merito degli sviluppi della ricerca più recente ma fornisce le basi per affrontare i vari problemi di instabilità strutturale dovuti a un particolare fenomeno di interazione con il vento. Il terzo capitolo contiene una trattazione più approfondita del fenomeno di instabilità per flutter. Tra tutti i fenomeni di instabilità aeroelastica delle strutture il flutter risulta il più temibile, soprattutto per i ponti di grande luce. Per questo si è ritenuto opportuno dedicargli un capitolo, in modo da illustrare i vari procedimenti con cui si riesce a determinare analiticamente la velocità critica di flutter di un impalcato da ponte, a partire dalle funzioni sperimentali denominate derivate di flutter. Al termine del capitolo è illustrato il procedimento con cui si ricavano sperimentalmente le derivate di flutter di un impalcato da ponte. Nel quarto capitolo è presentato l’esempio di studio dell’impalcato del ponte Tsing Ma ad Hong Kong. Sono riportati i risultati analitici dei calcoli della velocità di flutter e di divergenza torsionale dell’impalcato e i risultati delle simulazioni numeriche effettuate per stimare i coefficienti aerodinamici statici e il comportamento dinamico della struttura soggetta all’azione del vento. Considerazioni e commenti sui risultati ottenuti e sui metodi di modellazione numerica adottati completano l’elaborato.

Self-assembly of focal point oligo-catechol ethylene glycol dendrons on titanium oxide surfaces: adsorption kinetics, surface characterization, and nonfouling properties

This work covers the synthesis of second-generation, ethylene glycol dendrons covalently linked to a surface anchor that contains two, three, or four catechol groups, the molecular assembly in aqueous buffer on titanium oxide surfaces, and the evaluation of the resistance of the monomolecular adlayers against nonspecific protein adsorption in contact with full blood serum. The results were compared to those of a linear poly(ethylene glycol) (PEG) analogue with the same molecular weight. The adsorption kinetics as well as resulting surface coverages were monitored by ex situ spectroscopic ellipsometry (VASE), in situ optical waveguide lightmode spectroscopy (OWLS), and quartz crystal microbalance with dissipation (QCM-D) investigations. The expected compositions of the macromolecular films were verified by X-ray photoelectron spectroscopy (XPS). The results of the adsorption study, performed in a high ionic strength ("cloud-point") buffer at room temperature, demonstrate that the adsorption kinetics increase with increasing number of catechol binding moieties and exceed the values found for the linear PEG analogue. This is attributed to the comparatively smaller and more confined molecular volume of the dendritic macromolecules in solution, the improved presentation of the catechol anchor, and/or their much lower cloud-point in the chosen buffer (close to room temperature). Interestingly, in terms of mechanistic aspects of "nonfouling" surface properties, the dendron films were found to be much stiffer and considerably less hydrated in comparison to the linear PEG brush surface, closer in their physicochemical properties to oligo(ethylene glycol) alkanethiol self-assembled monolayers than to conventional brush surfaces. Despite these differences, both types of polymer architectures at saturation coverage proved to be highly resistant toward protein adsorption. Although associated with higher synthesis costs, dendritic macromolecules are considered to be an attractive alternative to linear polymers for surface (bio)functionalization in view of their spontaneous formation of ultrathin, confluent, and nonfouling monolayers at room temperature and their outstanding ability to present functional ligands (coupled to the termini of the dendritic structure) at high surface densities.

Altered expression of the PTR/NRT1 homologue OsPTR9 affects nitrogen utilization efficiency, growth and grain yield in rice

The plant PTR/NRT1 (peptide transporter/nitrate transporter 1) gene family comprises di/tripeptide and low-affinity nitrate transporters; some members also recognize other substrates such as carboxylates, phytohormones (auxin and abscisic acid), or defence compounds (glucosinolates). Little is known about the members of this gene family in rice (Oryza sativa L.). Here, we report the influence of altered OsPTR9 expression on nitrogen utilization efficiency, growth, and grain yield. OsPTR9 expression is regulated by exogenous nitrogen and by the day-night cycle. Elevated expression of OsPTR9 in transgenic rice plants resulted in enhanced ammonium uptake, promotion of lateral root formation and increased grain yield. On the other hand, down-regulation of OsPTR9 in a T-DNA insertion line (osptr9) and in OsPTR9-RNAi rice plants had the opposite effect. These results suggest that OsPTR9 might hold potential for improving nitrogen utilization efficiency and grain yield in rice breeding.

Anatomic pathways of peripancreatic fluid draining to mediastinum in recurrent acute pancreatitis: visible human project and CT study

BACKGROUND In past reports, researchers have seldom attached importance to achievements in transforming digital anatomy to radiological diagnosis. However, investigators have been able to illustrate communication relationships in the retroperitoneal space by drawing potential routes in computerized tomography (CT) images or a virtual anatomical atlas. We established a new imaging anatomy research method for comparisons of the communication relationships of the retroperitoneal space in combination with the Visible Human Project and CT images. Specifically, the anatomic pathways of peripancreatic fluid extension to the mediastinum that may potentially transform into fistulas were studied. METHODS We explored potential pathways to the mediastinum based on American and Chinese Visible Human Project datasets. These drainage pathways to the mediastinum were confirmed or corrected in CT images of 51 patients with recurrent acute pancreatitis in 2011. We also investigated whether additional routes to the mediastinum were displayed in CT images that were not in Visible Human Project images. PRINCIPAL FINDINGS All hypothesized routes to the mediastinum displayed in Visible Human Project images, except for routes from the retromesenteric plane to the bilateral retrorenal plane across the bilateral fascial trifurcation and further to the retrocrural space via the aortic hiatus, were confirmed in CT images. In addition, route 13 via the narrow space between the left costal and crural diaphragm into the retrocrural space was demonstrated for the first time in CT images. CONCLUSION This type of exploration model related to imaging anatomy may be used to support research on the communication relationships of abdominal spaces, mediastinal spaces, cervical fascial spaces and other areas of the body.

Cloning and characterization of human protease-activated receptor 4

Protease-activated receptors 1–3 (PAR1, PAR2, and PAR3) are members of a unique G protein-coupled receptor family. They are characterized by a tethered peptide ligand at the extracellular amino terminus that is generated by minor proteolysis. A partial cDNA sequence of a fourth member of this family (PAR4) was identified in an expressed sequence tag database, and the full-length cDNA clone has been isolated from a lymphoma Daudi cell cDNA library. The ORF codes for a seven transmembrane domain protein of 385 amino acids with 33% amino acid sequence identity with PAR1, PAR2, and PAR3. A putative protease cleavage site (Arg-47/Gly-48) was identified within the extracellular amino terminus. COS cells transiently transfected with PAR4 resulted in the formation of intracellular inositol triphosphate when treated with either thrombin or trypsin. A PAR4 mutant in which the Arg-47 was replaced with Ala did not respond to thrombin or trypsin. A hexapeptide (GYPGQV) representing the newly exposed tethered ligand from the amino terminus of PAR4 after proteolysis by thrombin activated COS cells transfected with either wild-type or the mutant PAR4. Northern blot showed that PAR4 mRNA was expressed in a number of human tissues, with high levels being present in lung, pancreas, thyroid, testis, and small intestine. By fluorescence in situ hybridization, the human PAR4 gene was mapped to chromosome 19p12.

GS32, a Novel Golgi SNARE of 32 kDa, Interacts Preferentially with Syntaxin 6

Syntaxin 1, synaptobrevins or vesicle-associated membrane proteins, and the synaptosome-associated protein of 25 kDa (SNAP-25) are key molecules involved in the docking and fusion of synaptic vesicles with the presynaptic membrane. We report here the molecular, cell biological, and biochemical characterization of a 32-kDa protein homologous to both SNAP-25 (20% amino acid sequence identity) and the recently identified SNAP-23 (19% amino acid sequence identity). Northern blot analysis shows that the mRNA for this protein is widely expressed. Polyclonal antibodies against this protein detect a 32-kDa protein present in both cytosol and membrane fractions. The membrane-bound form of this protein is revealed to be primarily localized to the Golgi apparatus by indirect immunofluorescence microscopy, a finding that is further established by electron microscopy immunogold labeling showing that this protein is present in tubular-vesicular structures of the Golgi apparatus. Biochemical characterizations establish that this protein behaves like a SNAP receptor and is thus named Golgi SNARE of 32 kDa (GS32). GS32 in the Golgi extract is preferentially retained by the immobilized GST–syntaxin 6 fusion protein. The coimmunoprecipitation of syntaxin 6 but not syntaxin 5 or GS28 from the Golgi extract by antibodies against GS32 further sustains the preferential interaction of GS32 with Golgi syntaxin 6.

Interaction of NPR1 with basic leucine zipper protein transcription factors that bind sequences required for salicylic acid induction of the PR-1 gene

The Arabidopsis thaliana NPR1 has been shown to be a key regulator of gene expression during the onset of a plant disease-resistance response known as systemic acquired resistance. The npr1 mutant plants fail to respond to systemic acquired resistance-inducing signals such as salicylic acid (SA), or express SA-induced pathogenesis-related (PR) genes. Using NPR1 as bait in a yeast two-hybrid screen, we identified a subclass of transcription factors in the basic leucine zipper protein family (AHBP-1b and TGA6) and showed that they interact specifically in yeast and in vitro with NPR1. Point mutations that abolish the NPR1 function in A. thaliana also impair the interactions between NPR1 and the transcription factors in the yeast two-hybrid assay. Furthermore, a gel mobility shift assay showed that the purified transcription factor protein, AHBP-1b, binds specifically to an SA-responsive promoter element of the A. thaliana PR-1 gene. These data suggest that NPR1 may regulate PR-1 gene expression by interacting with a subclass of basic leucine zipper protein transcription factors.

A Framework of Fuzzy Diagnosis

Fault diagnosis has become an important component in intelligent systems, such as intelligent control systems and intelligent eLearning systems. Reiter's diagnosis theory, described by first-order sentences, has been attracting much attention in this field. However, descriptions and observations of most real-world situations are related to fuzziness because of the incompleteness and the uncertainty of knowledge, e. g., the fault diagnosis of student behaviors in the eLearning processes. In this paper, an extension of Reiter's consistency-based diagnosis methodology, Fuzzy Diagnosis, has been proposed, which is able to deal with incomplete or fuzzy knowledge. A number of important properties of the Fuzzy diagnoses schemes have also been established. The computing of fuzzy diagnoses is mapped to solving a system of inequalities. Some special cases, abstracted from real-world situations, have been discussed. In particular, the fuzzy diagnosis problem, in which fuzzy observations are represented by clause-style fuzzy theories, has been presented and its solving method has also been given. A student fault diagnostic problem abstracted from a simplified real-world eLearning case is described to demonstrate the application of our diagnostic framework.

Approximate processing of massive continuous quantile queries over high-speed data streams

Quantile computation has many applications including data mining and financial data analysis. It has been shown that an is an element of-approximate summary can be maintained so that, given a quantile query d (phi, is an element of), the data item at rank [phi N] may be approximately obtained within the rank error precision is an element of N over all N data items in a data stream or in a sliding window. However, scalable online processing of massive continuous quantile queries with different phi and is an element of poses a new challenge because the summary is continuously updated with new arrivals of data items. In this paper, first we aim to dramatically reduce the number of distinct query results by grouping a set of different queries into a cluster so that they can be processed virtually as a single query while the precision requirements from users can be retained. Second, we aim to minimize the total query processing costs. Efficient algorithms are developed to minimize the total number of times for reprocessing clusters and to produce the minimum number of clusters, respectively. The techniques are extended to maintain near-optimal clustering when queries are registered and removed in an arbitrary fashion against whole data streams or sliding windows. In addition to theoretical analysis, our performance study indicates that the proposed techniques are indeed scalable with respect to the number of input queries as well as the number of items and the item arrival rate in a data stream.

Discovering user access pattern based on probabilistic latent factor model

There has been an increased demand for characterizing user access patterns using web mining techniques since the informative knowledge extracted from web server log files can not only offer benefits for web site structure improvement but also for better understanding of user navigational behavior. In this paper, we present a web usage mining method, which utilize web user usage and page linkage information to capture user access pattern based on Probabilistic Latent Semantic Analysis (PLSA) model. A specific probabilistic model analysis algorithm, EM algorithm, is applied to the integrated usage data to infer the latent semantic factors as well as generate user session clusters for revealing user access patterns. Experiments have been conducted on real world data set to validate the effectiveness of the proposed approach. The results have shown that the presented method is capable of characterizing the latent semantic factors and generating user profile in terms of weighted page vectors, which may reflect the common access interest exhibited by users among same session cluster.

A web recommendation technique based on probabilistic latent semantic analysis

Web transaction data between Web visitors and Web functionalities usually convey user task-oriented behavior pattern. Mining such type of click-stream data will lead to capture usage pattern information. Nowadays Web usage mining technique has become one of most widely used methods for Web recommendation, which customizes Web content to user-preferred style. Traditional techniques of Web usage mining, such as Web user session or Web page clustering, association rule and frequent navigational path mining can only discover usage pattern explicitly. They, however, cannot reveal the underlying navigational activities and identify the latent relationships that are associated with the patterns among Web users as well as Web pages. In this work, we propose a Web recommendation framework incorporating Web usage mining technique based on Probabilistic Latent Semantic Analysis (PLSA) model. The main advantages of this method are, not only to discover usage-based access pattern, but also to reveal the underlying latent factor as well. With the discovered user access pattern, we then present user more interested content via collaborative recommendation. To validate the effectiveness of proposed approach, we conduct experiments on real world datasets and make comparisons with some existing traditional techniques. The preliminary experimental results demonstrate the usability of the proposed approach.

Towards user profiling for web recommendation

Collaborative recommendation is one of widely used recommendation systems, which recommend items to visitor on a basis of referring other's preference that is similar to current user. User profiling technique upon Web transaction data is able to capture such informative knowledge of user task or interest. With the discovered usage pattern information, it is likely to recommend Web users more preferred content or customize the Web presentation to visitors via collaborative recommendation. In addition, it is helpful to identify the underlying relationships among Web users, items as well as latent tasks during Web mining period. In this paper, we propose a Web recommendation framework based on user profiling technique. In this approach, we employ Probabilistic Latent Semantic Analysis (PLSA) to model the co-occurrence activities and develop a modified k-means clustering algorithm to build user profiles as the representatives of usage patterns. Moreover, the hidden task model is derived by characterizing the meaningful latent factor space. With the discovered user profiles, we then choose the most matched profile, which possesses the closely similar preference to current user and make collaborative recommendation based on the corresponding page weights appeared in the selected user profile. The preliminary experimental results performed on real world data sets show that the proposed approach is capable of making recommendation accurately and efficiently.