Modélisation sociologique de la réalité virtuelle du musée

Introduction Depuis 1997, dans le cadre d’un projet intitulé « Les visiteurs des mondes virtuels et réels du musée », nous analysons la spécificité des perceptions et attentes des visiteurs du Musée d'anthropologie et d’ethnographie Pierre le Grand de l’Académie des Sciences de Saint‑Pétersbourg (MAE RAN, ou « Kunstkammer »). Le Musée a été créé par un édit de Pierre I le Grand en 1704 comme le premier musée d’Etat en Russie. Le « Kunstkammer » fut d'abord un « cabinet de curiosités », puis, ..

The Non-Coding Transcriptome of Prostate Cancer: Implications for Clinical Practice

Prostate cancer (PCa) is the most common type of cancer and the second leading cause of cancer-related death in men. Despite extensive research, the molecular mechanisms underlying PCa initiation and progression remain unclear, and there is increasing need of better biomarkers that can distinguish indolent from aggressive and life-threatening disease. With the advent of advanced genomic technologies in the last decade, it became apparent that the human genome encodes tens of thousands non-protein-coding RNAs (ncRNAs) with yet to be discovered function. It is clear now that the majority of ncRNAs exhibit highly specific expression patterns restricted to certain tissues and organs or developmental stages and that the expression of many ncRNAs is altered in disease and cancer, including cancer of the prostate. Such ncRNAs can serve as important biomarkers for PCa diagnosis, prognosis, or prediction of therapy response. In this review, we give an overview of the different types of ncRNAs and their function, describe ncRNAs relevant for the diagnosis and prognosis of PCa, and present emerging new aspects of ncRNA research that may contribute to the future utilization of ncRNAs as clinically useful therapeutic targets

Age dynamic in the central corneal thickness in children

Цел: Да се установи и анализира съществува ли динамика в биометричния показател централна роговична дебелина при българските деца от различни възрастови групи. Обект: Проучването обхваща 248 пациента/496 очи/, разпределени в четири възрастови групи. Метод: Ултразвукова пахиметрия с PacScanЗ00AP. Изводи: Установи се статистически значимо нарастване на средното ниво на ЦРД с възрастта на децата до 15 години. Средното ниво на ЦРД във втора и трета група е еднакво. С нарастване на възрастта нараства ЦРД и тя е най-голяма в четвърта група.Aim: To identify and analyze the dynamic of central corneal thickness in Bulgarian children in different age groups. Object: The study cover 248 patient / 496 eye / divided into four age groups. Method: Ultrasonic pachimetry with PacScan300AP. Conclusions: Establish a statistically signi? cant increase in the average level of CRD in children to 15 years old. Average CRD in the second and third group is the same. With increasing age increases CRD and it is greatest in the fourth group

Foliar epidermis morphology in Quercus (subgenus Quercus, section Quercus) in Iran

The foliar morphology of trichomes, epicuticular waxes and stomata in Quercus cedrorum, Q. infectoria subsp. boissieri, Q. komarovii, Q. longipes, Q. macranthera, Q. petraea subsp. iberica and Q. robur subsp. pedunculiflora were studied by scanning electron microscopy. The trichomes are mainly present on abaxial leaf surface in most species, but rarely they appear on adaxial surface. Five trichome types are identified as simple uniseriate, bulbous, solitary, fasciculate and stellate. The stomata of all studied species are of the anomocytic type, raised on the epidermis. The stomata rim may or may not be covered with epicuticular. The epicuticular waxes are mostly of the crystalloid type but smooth layer wax is observed in Q. robur subsp. pedunculiflora. Statistical analysis revealed foliar micromorphological features as been diagnostic characters in Quercus

An inventory of the Aspergillus niger secretome by combining in silico predictions with shotgun proteomics data

<p>Abstract</p> <p>Background</p> <p>The ecological niche occupied by a fungal species, its pathogenicity and its usefulness as a microbial cell factory to a large degree depends on its secretome. Protein secretion usually requires the presence of a N-terminal signal peptide (SP) and by scanning for this feature using available highly accurate SP-prediction tools, the fraction of potentially secreted proteins can be directly predicted. However, prediction of a SP does not guarantee that the protein is actually secreted and current <it>in silico </it>prediction methods suffer from gene-model errors introduced during genome annotation.</p> <p>Results</p> <p>A majority rule based classifier that also evaluates signal peptide predictions from the best homologs of three neighbouring <it>Aspergillus </it>species was developed to create an improved list of potential signal peptide containing proteins encoded by the <it>Aspergillus niger </it>genome. As a complement to these <it>in silico </it>predictions, the secretome associated with growth and upon carbon source depletion was determined using a shotgun proteomics approach. Overall, some 200 proteins with a predicted signal peptide were identified to be secreted proteins. Concordant changes in the secretome state were observed as a response to changes in growth/culture conditions. Additionally, two proteins secreted via a non-classical route operating in <it>A. niger </it>were identified.</p> <p>Conclusions</p> <p>We were able to improve the <it>in silico </it>inventory of <it>A. niger </it>secretory proteins by combining different gene-model predictions from neighbouring Aspergilli and thereby avoiding prediction conflicts associated with inaccurate gene-models. The expected accuracy of signal peptide prediction for proteins that lack homologous sequences in the proteomes of related species is 85%. An experimental validation of the predicted proteome confirmed <it>in silico </it>predictions.</p

Robust Multimodal Image Registration Using Deep Recurrent Reinforcement Learning

The crucial components of a conventional image registration method are the choice of the right feature representations and similarity measures. These two components, although elaborately designed, are somewhat handcrafted using human knowledge. To this end, these two components are tackled in an end-to-end manner via reinforcement learning in this work. Specifically, an artificial agent, which is composed of a combined policy and value network, is trained to adjust the moving image toward the right direction. We train this network using an asynchronous reinforcement learning algorithm, where a customized reward function is also leveraged to encourage robust image registration. This trained network is further incorporated with a lookahead inference to improve the registration capability. The advantage of this algorithm is fully demonstrated by our superior performance on clinical MR and CT image pairs to other state-of-the-art medical image registration methods

Mechanical properties of materials for 3D printed orthodontic retainers

Aim: The purpose of this study was to compare the mechanical properties of materials used for orthodontic retainers made by direct 3D printing and thermoforming. Materials and methods: Twenty-one specimens (n=7) from 3 different materials (Formlabs Dental LT Clear V2 - Formlabs Inc., Somerville, Massachusetts, USA; NextDent Ortho Flex - Vertex-Dental B.V., Soesterberg, The Netherlands, and Erkodent Erkodur - ERKODENT, Germany) were manufactured and their mechanical properties were evaluated. Two of the specimen groups were 3D printed and the other one was fabricated using a material for thermoforming. The statistical methods we applied were descriptive statistics, the Kruskal-Wallis and Dunn’s post-hoc tests. Results: With respect to Young’s modulus (E), the Kruskal-Wallis test (df=2, χ2=17.121, p=0.0002) showed a significant difference between the materials for direct 3D printing of orthodontic retainers (E=2762.4 MPa±115.16 MPa for group 1 and 2393.05 MPa±158.13 MPa for group 2) and thermoforming foils (group 3, E=1939.4 MPa±74.18 MPa). Statistically significant differences were also found between the flexural strength (FS) (Kruskal-Wallis test, df=2, χ2=17.818, p=0.0001) and F(max) (Kruskal-Wallis test, df=2, χ2=17.818, p=0.0001). Conclusions: The materials tested in the current study showed statistically significant differences in their Young’s modulus, flexural strength, and F(max)

Slx8 removes Pli1-dependent protein-SUMO conjugates including SUMOylated Topoisomerase I to promote genome stability

Peer reviewedPublisher PD