SHEAR BOND STRENGTHS BETWEEN CERAMIC CORES AND VENEERING CERAMICS OF DENTAL BI-LAYERED CERAMIC SYSTEMS AND THE SENSITIVITY TO THERMOCYCLING

The purpose of this study was to investigate the bond strength between various commercial ceramic core materials and veneering ceramics of dental bi-layered ceramic combinations and the effect of thermocycling. The shear bond strength of four dental bi-layered ceramic combinations (white Cercon, yellow Cercon, white Lava, yellow Lava, IPS E.max) were tested. Metal ceramic combinations were conducted as a control group. Half of each group was subjected to thermocycling. All specimens were thereafter subjected to a shear force. The initial mean shear bond strength values in MPa ± S.D were 28.02 ± 3.04 for White Cercon Base/Cercon Ceram Kiss, 27.54 ± 2.20 for Yellow Cercon Base/Cercon Ceram Kiss, 28.43 ± 2.13for White Lava Frame/Lava Ceram, 27.36 ± 2.25 for Yellow Lava Frame/Lava Ceram, 47.10 ± 3.77 for IPS E.max Press/IPS E.max Ceram and 30.11 ± 2.15 for metal ceramic control. The highest shear strength was recorded for IPS E.max Press/IPS E.max Ceram before and after thermocycling. The mean shear bond strength values of five other combinations were not significantly different (P < 0.05). Lithium-disilicate based combinations produced the highest core-veneer bonds that overwhelmed the metal ceramic combinations. Thermocycling had no effect on the core-veneer bonds. The core-veneer bonds of zirconia based combinations were not weakened by the addition of coloring pigments

Drone-Based Cattle Detection Using Deep Neural Networks

© 2021, Springer Nature Switzerland AG. Cattle form an important source of farming in many countries. In literature, several attempts have been conducted to detect farm animals for different applications and purposes. However, these approaches have been based on detecting animals from images captured from ground level and most approaches use traditional machine learning approaches for their automated detection. In this modern era, Drones facilitate accessing images in challenging environments and scanning large-scale areas with minimum time, which enables many new applications to be established. Considering the fact that drones typically are flown at high altitude to facilitate coverage of large areas within a short time, the captured object size tend to be small and hence this significantly challenges the possible use of traditional machine learning algorithms for object detection. This research proposes a novel methodology to detect cattle in farms established in desert areas using Deep Neural Networks. We propose to detect animals based on a ‘group-of-animals’ concept and associated features in which different group sizes and animal density distribution are used. Two state-of-the-art Convolutional Neural Network (CNN) architectures, SSD-500 and YOLO V-3, are effectively configured, trained and used for the purpose and their performance efficiencies are compared. The results demonstrate the capability of the two generated CNN models to detect groups-of-animals in which the highest accuracy recorded was when using SSD-500 giving a F-score of 0.93, accuracy of 0.89 and mAP rate of 84.7

miRNA contributions to pediatric-onset multiple sclerosis inferred from GWAS.

ObjectiveOnset of multiple sclerosis (MS) occurs in childhood for approximately 5% of cases (pediatric MS, or ped-MS). Epigenetic influences are strongly implicated in MS pathogenesis in adults, including the contribution from microRNAs (miRNAs), small noncoding RNAs that affect gene expression by binding target gene mRNAs. Few studies have specifically examined miRNAs in ped-MS, but individuals developing MS at an early age may carry a relatively high burden of genetic risk factors, and miRNA dysregulation may therefore play a larger role in the development of ped-MS than in adult-onset MS. This study aimed to look for evidence of miRNA involvement in ped-MS pathogenesis.MethodsGWAS results from 486 ped-MS cases and 1362 controls from the U.S. Pediatric MS Network and Kaiser Permanente Northern California membership were investigated for miRNA-specific signals. First, enrichment of miRNA-target gene network signals was evaluated using MIGWAS software. Second, SNPs in miRNA genes and in target gene binding sites (miR-SNPs) were tested for association with ped-MS, and pathway analysis was performed on associated target genes.ResultsMIGWAS analysis showed that miRNA-target gene signals were enriched in GWAS (P = 0.038) and identified 39 candidate biomarker miRNA-target gene pairs, including immune and neuronal signaling genes. The miR-SNP analysis implicated dysregulation of miRNA binding to target genes in five pathways, mainly involved in immune signaling.InterpretationEvidence from GWAS suggests that miRNAs play a role in ped-MS pathogenesis by affecting immune signaling and other pathways. Candidate biomarker miRNA-target gene pairs should be further studied for diagnostic, prognostic, and/or therapeutic utility

Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-identification

© 2020, Springer Nature Switzerland AG. Visible-infrared person re-identification (VI-ReID) is a challenging cross-modality pedestrian retrieval problem. Due to the large intra-class variations and cross-modality discrepancy with large amount of sample noise, it is difficult to learn discriminative part features. Existing VI-ReID methods instead tend to learn global representations, which have limited discriminability and weak robustness to noisy images. In this paper, we propose a novel dynamic dual-attentive aggregation (DDAG) learning method by mining both intra-modality part-level and cross-modality graph-level contextual cues for VI-ReID. We propose an intra-modality weighted-part attention module to extract discriminative part-aggregated features, by imposing the domain knowledge on the part relationship mining. To enhance robustness against noisy samples, we introduce cross-modality graph structured attention to reinforce the representation with the contextual relations across the two modalities. We also develop a parameter-free dynamic dual aggregation learning strategy to adaptively integrate the two components in a progressive joint training manner. Extensive experiments demonstrate that DDAG outperforms the state-of-the-art methods under various settings

Erasing Sensorimotor Memories via PKMζ Inhibition

Sensorimotor cortex has a role in procedural learning. Previous studies suggested that this learning is subserved by long-term potentiation (LTP), which is in turn maintained by the persistently active kinase, protein kinase Mzeta (PKMζ). Whereas the role of PKMζ in animal models of declarative knowledge is established, its effect on procedural knowledge is not well understood. Here we show that PKMζ inhibition, via injection of zeta inhibitory peptide (ZIP) into the rat sensorimotor cortex, disrupts sensorimotor memories for a skilled reaching task even after several weeks of training. The rate of relearning the task after the memory disruption by ZIP was indistinguishable from the rate of initial learning, suggesting no significant savings after the memory loss. These results indicate a shared molecular mechanism of storage for declarative and procedural forms of memory

Bilateral heterochronic spontaneous hemothorax caused by pulmonary arteriovenous malformation in a gravid: A case report

Bilateral heterochronic spontaneous hemothorax as a result of pulmonary ateriovenous malformation is a very rarely happened disease. A 34-year-old woman presented major symptoms with right-sided chest pain and shortness of breath. The following contrast-enhanced computed tomographic scan of the chest showed a large amount of fluid in the right thorax with mediastinal shift, but without major vessel injury and 2 small dense opacities in the apical segment of the right lower lobe and in the posterior aspect of the left lower lobe. The patient underwent local resection of the right lower lobe. The pulmonary ateriovenous malformation was further identified by pathological examination. One month after she was discharged home, the symptoms described above recurred. A follow-up computed tomographic scan of the chest showed a large amount of fluid in the left thorax. During the emergency operation, we found a bullous lesion in the left lower lobe and a small blood vessel overlying the lesion that was actively bleeding. As stated above, local resection of the left lower lobe was performed once more. Pathological result was the same as observed previously. There were no postoperative complications and she was discharged from the hospital after two weeks. Two months later, she successfully delivered a healthy female infant. Up to now, regular follow-up observation has shown her to be perfectly asymptomatic

Radial Growth of Qilian Juniper on the Northeast Tibetan Plateau and Potential Climate Associations

There is controversy regarding the limiting climatic factor for tree radial growth at the alpine treeline on the northeastern Tibetan Plateau. In this study, we collected 594 increment cores from 331 trees, grouped within four altitude belts spanning the range 3550 to 4020 m.a.s.l. on a single hillside. We have developed four equivalent ring-width chronologies and shown that there are no significant differences in their growth-climate responses during 1956 to 2011 or in their longer-term growth patterns during the period AD 1110–2011. The main climate influence on radial growth is shown to be precipitation variability. Missing ring analysis shows that tree radial growth at the uppermost treeline location is more sensitive to climate variation than that at other elevations, and poor tree radial growth is particularly linked to the occurrence of serious drought events. Hence water limitation, rather than temperature stress, plays the pivotal role in controlling the radial growth of Sabina przewalskii Kom. at the treeline in this region. This finding contradicts any generalisation that tree-ring chronologies from high-elevation treeline environments are mostly indicators of temperature changes

Mutation screening of the RNF8, UBC13 and MMS2 genes in Northern Finnish breast cancer families

<p>Abstract</p> <p>Background</p> <p>Currently known susceptibility genes such as <it>BRCA1 </it>and <it>BRCA2 </it>explain less than 25% of familial aggregation of breast cancer, which suggests the involvement of additional susceptibility genes. RNF8, UBC13 and MMS2 are involved in the DNA damage response pathway and play important roles in BRCA1-mediated DNA damage recognition. Based on the evidence that several players in the ubiquitin-mediated BRCA1-dependent DDR seem to contribute to breast cancer predisposition, <it>RNF8, UBC13 </it>and <it>MMS2 </it>were considered plausible candidate genes for susceptibility to breast cancer.</p> <p>Methods</p> <p>The entire coding region and splice junctions of <it>RNF8, UBC13 </it>and <it>MMS2 </it>genes were screened for mutations in affected index cases from 123 Northern Finnish breast cancer families by using conformation sensitive gel electrophoresis, high resolution melting (HRM) analysis and direct sequencing.</p> <p>Results</p> <p>Mutation analysis revealed several changes in <it>RNF8 </it>and <it>UBC13</it>, whereas no aberrations were observed in <it>MMS2</it>. None of the found sequence changes appeared to associate with breast cancer susceptibility.</p> <p>Conclusions</p> <p>The present data suggest that mutations in <it>RNF8, UBC13 </it>and <it>MMS2 </it>genes unlikely make any sizeable contribution to breast cancer predisposition in Northern Finland.</p

Revealing the molecular signatures of host-pathogen interactions.

Advances in sequencing technology and genome-wide association studies are now revealing the complex interactions between hosts and pathogen through genomic variation signatures, which arise from evolutionary co-existence