Evaluation of Shear Bond Strength of Two Resin-Modified Glass-Ionomer Cements

Purpose: To compare the in-vitro shear bond strengths of a new paste-paste formulation of resin-modified glass-ionomer cement (Rm-GIC) to an exising powder-liquid formulation. The study will test the hypothesis that the new paste-paste formulation of Rm-GIC (Fuji-Cem ™, GC Corp, Tokyo, Japan) has the same bond strength as an existing popular powder-liquid formulation of Rm-GIC (Rely-X ™ Luting Cement, 3M, St. Paul, MN)Materials and Methods: A total of 33 human molars were sectioned parallel to the occlusal surface to expose mid-coronal dentin and mounted parallel to the bond shearing device on the universal testing machine (Instron). For Group I samples (Rely-X, n=15), the powder and liquid were measured and adjusted to achieve a ratio of 1.6 and mixed for 30 seconds as recommended by the manufacturer. For Group II (Fuji-Cem, n=18), the paste-paste was expressed from the paste-dispenser provided by the manufacturer and mixed for 10 seconds as recommended. After testing, the teeth from group II were bonded on a different site with the same material but mixed for 20 seconds (n=18). To ensure a uniform flow and bond surface area, the mixed cement was syringed into a cylindrical mould (diameter 2.38mm, height 2mm) and allowed to set under constant force. All samples were subjected to fracture by shear loading on a universal testing machine (Instron) at a uniform crosshead speed of .02 per minute and expressed as MPa. Values were analyzed at the pResults: Wilcoxon rank sums test showed significantly higher shear bond strength values for Rely-X compared to Fuji-Cem mixed both at 10 seconds and 20 seconds. Mixing for 20 seconds resulted in stronger bonds for Fuji-Cem compared to 10 seconds, but was still significantly lower than Rely-X.Conclusions: Within the limitations of the study, the Rely-X powder-liquid formula shows a significantly stronger dentin shear bond strength when compared to the new paste-paste formula of resin-modified glass ionomer cement, Fuji-Cem

On the exceptional damage-tolerance of gradient metallic materials

An experimental study is described on the fracture toughness and micro-mechanisms associated with the initiation and propagation of cracks in metallic nickel containing marked gradients in grain size, ranging from ∼30 nm to ∼4 μm. Specifically, cracks are grown in a gradient structured (GS) nickel with grain-size gradient ranging from the coarse macro-scale to nano-scale (CG → NG) and vice versa (NG → CG), with the measured crack-resistance R-curves compared to the corresponding behavior in uniform nano-grained (NG) and coarse-grained (CG) materials. It is found that the gradient structures display a much-improved combination of high strength and toughness compared to uniform grain-sized materials. However, based on J-integral measurements in the gradient materials, the crack-initiation toughness is far higher for cracks grown in the direction of the coarse-to-nano grained gradient than vice versa, a result which we ascribe primarily to excessive crack-tip blunting in the coarse-grained microstructure. Both gradient structures, however, display marked rising R-curve behavior with exceptional crack-growth toughnesses exceeding 200 MPa.m½

Micropapillary Variant of Urothelial Carcinoma

Micropapillary carcinoma (MPC) of urinary tract is an uncommon variant of urothelial carcinoma with significant diagnostic and prognostic implications. Though MPC shows characteristic microscopic features, there exists interobserver variability and also it needs to be differentiated from the metastasis from other organs. The prognosis is generally poor, depending on the proportion of the micropapillary component in some reports. Early cystectomy in cases with only lamina propria invasion may be indicated according to recent studies. This review outlines the general features of this entity and briefly comments on the controversies and the recent development

Collaborative Layer-wise Discriminative Learning in Deep Neural Networks

Intermediate features at different layers of a deep neural network are known to be discriminative for visual patterns of different complexities. However, most existing works ignore such cross-layer heterogeneities when classifying samples of different complexities. For example, if a training sample has already been correctly classified at a specific layer with high confidence, we argue that it is unnecessary to enforce rest layers to classify this sample correctly and a better strategy is to encourage those layers to focus on other samples. In this paper, we propose a layer-wise discriminative learning method to enhance the discriminative capability of a deep network by allowing its layers to work collaboratively for classification. Towards this target, we introduce multiple classifiers on top of multiple layers. Each classifier not only tries to correctly classify the features from its input layer, but also coordinates with other classifiers to jointly maximize the final classification performance. Guided by the other companion classifiers, each classifier learns to concentrate on certain training examples and boosts the overall performance. Allowing for end-to-end training, our method can be conveniently embedded into state-of-the-art deep networks. Experiments with multiple popular deep networks, including Network in Network, GoogLeNet and VGGNet, on scale-various object classification benchmarks, including CIFAR100, MNIST and ImageNet, and scene classification benchmarks, including MIT67, SUN397 and Places205, demonstrate the effectiveness of our method. In addition, we also analyze the relationship between the proposed method and classical conditional random fields models.Comment: To appear in ECCV 2016. Maybe subject to minor changes before camera-ready versio

Warmth suppresses and desensitizes damage-sensing ion channel TRPA1

<p>Abstract</p> <p>Background</p> <p>Acute or chronic tissue damage induces an inflammatory response accompanied by pain and alterations in local tissue temperature. Recent studies revealed that the transient receptor potential A1 (TRPA1) channel is activated by a wide variety of substances that are released following tissue damage to evoke nociception and neurogenic inflammation. Although the effects of a noxious range of cold temperatures on TRPA1 have been rigorously studied, it is not known how agonist-induced activation of TRPA1 is regulated by temperature over an innocuous range centred on the normal skin surface temperature. This study investigated the effect of temperature on agonist-induced currents in human embryonic kidney (HEK) 293 cells transfected with rat or human TRPA1 and in rat sensory neurons.</p> <p>Results</p> <p>Agonist-induced TRPA1 currents in HEK293 cells were strongly suppressed by warm temperatures, and almost abolished at 39°C. Such inhibition occurred when TRPA1 was activated by either electrophilic or non-electrophilic agonists. Warming not only decreased the apparent affinity of TRPA1 for mustard oil (MO), but also greatly enhanced the desensitization and tachyphylaxis of TRPA1. Warming also attenuated MO-induced ionic currents in sensory neurons. These results suggest that the extent of agonist-induced activity of TRPA1 may depend on surrounding tissue temperature, and local hyperthermia during acute inflammation could be an endogenous negative regulatory mechanism to attenuate persistent pain at the site of injury.</p> <p>Conclusion</p> <p>These results indicate that warmth suppresses and desensitizes damage-sensing ion channel TRPA1. Such warmth-induced suppression of TRPA1 may also explain, at least in part, the mechanistic basis of heat therapy that has been widely used as a supplemental anti-nociceptive approach.</p

Pathologic Findings of Amyloidosis: Recent Advances

Amyloids are aggregations of misfolded protein, which creates fibrillary structures. Unlike normally folded proteins, misfolded fibrils are insoluble and deposited extracellularly or intracellularly. The pathologic mechanism is still unclear, but resultant toxic oligomers within the tissue are known to damage the tissue via aberrant protein interactions. This condition has been known as amyloidosis. Different kinds of amyloid protein may cause similar or different clinical signs and symptoms, largely depending on the target organ it is deposited. However, because treatments and prognoses of each type are different drastically, it is critical to distinguish them and determine the specific type of amyloidosis. The confirmation and typing of amyloid heavily depend on pathologic examination of tissue. The gold standard method for the former is a Congo red staining and birefringence under polarized microscopy. The conventional way for the latter is immunohistochemistry (IHC), where most of the amyloid types can be classified. However, electron microscopy, mass spectrometry, or other molecular methods are required for typing some amyloids that are difficult to identify through IHC. In this chapter, we will describe basic concepts of amyloidosis and pathologic findings of amyloid deposition, including atypical structural deposition. Furthermore, we will review methodologies for amyloid typing briefly