Does laser treatment restore the bond strength of resin composites to recently bleached enamel? A systematic review and meta-analysis.

PURPOSE: To do a systematic review and meta-analysis to determine whether laser treatment affects the bond strength of resin composites to recently bleached enamel. METHODS: This report follows the Preferred Reporting Items for Systematic Reviews and Qualitative Analyses (PRISMA) statement. Medline via PubMed, Embase, Web of Science, and the Cochrane Library databases were searched with no limits on publication year. Two reviewers independently screened all titles and abstracts to perform the study selection, data extraction, and risk-of-bias assessments. A random-effects meta-analysis model was performed using Review Manager software (version 5.3, Cochrane Collaboration). RESULTS: From the 93 records identified, seven articles that met all the inclusion criteria were included in the systematic review, and six studies were included in the meta-analysis. The overall results showed a statistically significant difference in bond strength between the control group and laser-treated group (P= 0.04; mean difference: 5.27; 95% confidence interval: 0.28 to 10.27), favoring the laser-treated group. Subgroup analyses revealed that the tooth source (bovine or human teeth) contributed to the effect of laser treatment on the bleached enamel. CLINICAL SIGNIFICANCE: Laser treatment may increase the bond strength of resin composites to recently bleached enamel. Pretreatment with a laser, preferably with Nd:YAG (1 W, frequency of 10 Hz, irradiation time of 60 seconds) or CO2 lasers (0.5 W, frequency of 10 Hz, irradiation time of 60 seconds), may be recommended to restore the bond strength of recently bleached enamel.

Correction: Huang et al. High-Uniform and High-Efficient Color Conversion Nanoporous GaN-Based Micro-LED Display with Embedded Quantum Dots. Nanomaterials 2021, 11, 2696.

The authors wish to make following corrections in this paper [...].

High-Uniform and High-Efficient Color Conversion Nanoporous GaN-Based Micro-LED Display with Embedded Quantum Dots.

Quantum dot (QD)-based RGB micro-LED technology is seen as one of the most promising approaches towards full color micro-LED displays. In this work, we present a novel nanoporous GaN (NP-GaN) structure that can scatter light and host QDs, as well as a new type of micro-LED array based on an NP-GaN embedded with QDs. Compared to typical QD films, this structure can significantly enhance the light absorption and stability of QDs. As a result, the green and red QDs exhibited light conversion efficiencies of 90.3% and 96.1% respectively, leading to improvements to the luminous uniformity of the green and red subpixels by 90.7% and 91.2% respectively. This study provides a viable pathway to develop high-uniform and high-efficient color conversion micro-LED displays.

Inhibition of SARS-CoV-2 by Highly Potent Broad-Spectrum Anti-Coronaviral Tylophorine-Based Derivatives.

Tylophorine-based compounds and natural cardiotonic steroids (cardenolides and bufadienolides) are two classes of transmissible gastroenteritis coronavirus inhibitors, targeting viral RNA and host cell factors, respectively. We tested both types of compounds against two types of coronaviruses, to compare and contrast their antiviral properties, and with view to their further therapeutic development. Examples of both types of compounds potently inhibited the replication of both feline infectious peritonitis virus and human coronavirus OC43 with EC50 values of up to 8 and 16 nM, respectively. Strikingly, the tylophorine-based compounds tested inhibited viral yields of HCoV-OC43 to a much greater extent (7-8 log magnitudes of p.f.u./ml) than the cardiotonic steroids (about 2-3 log magnitudes of p.f.u./ml), as determined by end point assays. Based on these results, three tylophorine-based compounds were further examined for their anti-viral activities on two other human coronaviruses, HCoV-229E and SARS-CoV-2. These three tylophorine-based compounds inhibited HCoV-229E with EC50 values of up to 6.5 nM, inhibited viral yields of HCoV-229E by 6-7 log magnitudes of p.f.u./ml, and were also found to inhibit SARS-CoV-2 with EC50 values of up to 2.5-14 nM. In conclusion, tylophorine-based compounds are potent, broad-spectrum inhibitors of coronaviruses including SARS-CoV-2, and could be used for the treatment of COVID-19.

Investigation of the Optoelectronic Properties of Ti-doped Indium Tin Oxide Thin Film.

: In this study, direct-current magnetron sputtering was used to fabricate Ti-doped indium tin oxide (ITO) thin films. The sputtering power during the 350-nm-thick thin-film production process was fixed at 100 W with substrate temperatures increasing from room temperature to 500 °C. The Ti-doped ITO thin films exhibited superior thin-film resistivity (1.5 × 10-4 Ω/cm), carrier concentration (4.1 × 1021 cm-³), carrier mobility (10 cm²/Vs), and mean visible-light transmittance (90%) at wavelengths of 400-800 nm at a deposition temperature of 400 °C. The superior carrier concentration of the Ti-doped ITO alloys (>1021 cm-³) with a high figure of merit (81.1 × 10-³ Ω-¹) demonstrate the pronounced contribution of Ti doping, indicating their high suitability for application in optoelectronic devices.

Mutations in Ralstonia solanacearum loci involved in lipopolysaccharide biogenesis, phospholipid trafficking and peptidoglycan recycling render bacteriophage infection.

Ralstonia solanacearum causes deadly wilting on many crops worldwide. However, the information on its components important for cell integrity and interactions with phages is limited. By systematically characterizing mutants resistant to a T7-like phage, we showed that the biosynthesis of rough lipopolysaccharides (R-LPS) was crucial for maintaining the membrane integrity, while the production of smooth LPS (S-LPS) was required for the resistance to polymyxin B and phage adsorption. Furthermore, RSc0154/ampG disruption did not affect LPS production and phage adsorption but may have caused aberrant release of peptidoglycan fragments, thus hindering phage DNA injection into or virion release from the cell. Mutations in the RSc2958-RSc2962/mla cluster, although not affecting LPS production, may have caused elevated phospholipid level in the outer leaflet of the outer membrane, consequently sheltering the mutants from phage adsorption on the O-antigen. These results specify important roles of the biogenesis and homeogenesis of envelope components for R. solanacearum-phage interaction.

Roles of different forms of lipopolysaccharides in Ralstonia solanacearum pathogenesis.

Lipopolysaccharides (LPS) are critical components for the fitness of most gram-negative bacteria. Ralstonia solanacearum causes a deadly wilting disease in many crops; however, the pathogenic roles of different forms of LPS and their pathways of biogenesis remain unknown. By screening for phage-resistant mutants of R. solanacearum Pss4, whose genome sequence is unavailable, mutants with various types of structural defects in LPS were isolated. Pathogenesis assays of the mutants revealed that production of rough LPS (R-LPS), which does not contain O-polysaccharides, was sufficient to cause necrosis on Nicotiana benthamiana and induce the hypersensitive response on N. tabacum. However, biosynthesis of smooth LPS (S-LPS), which contains O-polysaccharides, was required for bacterial proliferation at infection sites on N. benthamiana leaves and for proliferation and causing wilt on tomato. Complementation tests confirmed the involvement of the previously unidentified cluster RSc2201 to RSc2204 in the formation of R. solanacearum S-LPS. With these data and the availability of the annotated genomic sequence of strain GMI1000, certain loci involved in key steps of R. solanacearum LPS biosynthesis were identified. The strategy of this work could be useful for similar studies in other bacteria without available genome sequences.

Dynamics of multicomponent vesicles in a viscous fluid.

We develop and investigate numerically a thermodynamically consistent model of two-dimensional multicomponent vesicles in an incompressible viscous fluid. The model is derived using an energy variation approach that accounts for different lipid surface phases, the excess energy (line energy) associated with surface phase domain boundaries, bending energy, spontaneous curvature, local inextensibility and fluid flow via the Stokes equations. The equations are high-order (fourth order) nonlinear and nonlocal due to incompressibil-ity of the fluid and the local inextensibility of the vesicle membrane. To solve the equations numerically, we develop a nonstiff, pseudo-spectral boundary integral method that relies on an analysis of the equations at small scales. The algorithm is closely related to that developed very recently by Veerapaneni et al. [81] for homogeneous vesicles although we use a different and more efficient time stepping algorithm and a reformulation of the inextensibility equation. We present simulations of multicomponent vesicles in an initially quiescent fluid and investigate the effect of varying the average surface concentration of an initially unstable mixture of lipid phases. The phases then redistribute and alter the morphology of the vesicle and its dynamics. When an applied shear is introduced, an initially elliptical vesicle tank-treads and attains a steady shape and surface phase distribution. A sufficiently elongated vesicle tumbles and the presence of different surface phases with different bending stiffnesses and spontaneous curvatures yields a complex evolution of the vesicle morphology as the vesicle bends in regions where the bending stiffness and spontaneous curvature are small.

Analysis of tumor vascularity using three-dimensional power Doppler ultrasound images.

Tumor vascularity is an important factor that has been shown to correlate with tumor malignancy and was demonstrated as a prognostic indicator for a wide range of cancers. Three-dimensional (3-D) power Doppler ultrasound (PDUS) offers a convenient tool for investigators to inspect the signals of blood flow and vascular structures in breast cancer. In this paper, a new computer-aided diagnosis (CAD) system for quantifying Doppler ultrasound images based on 3-D thinning algorithm and neural network is proposed. We extracted the skeleton of blood vessels from 3-D PDUS data to facilitate the capturing of morphological changes. Nine features including vessel-to-volume ratio, number of vascular trees, length of vessels, number of branching, mean of radius, number of cycles, and three tortuosity measures, were extracted from the thinning result. Benign and malignant tumors can therefore be differentiated by a score computed by a multilayered perceptron (MLP) neural network using these features as parameters. The proposed system was tested on 221 breast tumors, including 110 benign and 111 malignant lesions. The accuracy, sensitivity, specificity, and positive and negative predictive values were 88.69% (196/221), 91.89% (102/111), 85.45% (94/110), 86.44% (102/118), and 91.26% (94/103), respectively. The Az value of the ROC curve was 0.94. The results demonstrate a correlation between the morphology of blood vessels and tumor malignancy, indicating that the newly proposed method can retrieves a high accuracy in the classification of benign and malignant breast tumors.

Solid breast masses: neural network analysis of vascular features at three-dimensional power Doppler US for benign or malignant classification.

PURPOSE: To retrospectively evaluate the accuracy of neural network analysis of tumor vascular features at three-dimensional (3D) power Doppler ultrasonography (US) for classification of breast tumors as benign or malignant, with histologic findings as the reference standard. MATERIALS AND METHODS: This study was approved by the local ethics committee; informed consent was waived. Three-dimensional power Doppler US images of 221 solid breast masses (110 benign, 111 malignant) were obtained in 221 women (mean age, 46 years; range, 25-71 years). After narrowing down vessels to skeletons with a 3D thinning algorithm, six vascular feature values--vessel-to-volume ratio, number of vascular trees, total vessel length, longest path length, number of bifurcations, and vessel diameter-were computed. A neural network was used to classify tumors by using these features. Independent-samples t test and receiver operating characteristic (ROC) curve analysis were used. RESULTS: Mean values of vessel-to-volume ratio, number of vascular trees, total vessel length, longest path length, number of bifurcations, and vessel diameter were 0.0089 +/- 0.0073 (standard deviation), 26.41 +/- 14.73, 23.02 cm +/- 19.53, 8.44 cm +/- 10.38, 36.31 +/- 37.06, and 0.088 cm +/- 0.021 in malignant tumors, respectively, and 0.0028 +/- 0.0021, 9.69 +/- 6.75, 5.17 cm +/- 4.78, 1.68 cm +/- 1.79, 6.05 +/- 7.55, and 0.064 cm +/- 0.028 in benign tumors, respectively (P < .001 for all six features). Area under ROC curve (A(z)) values of the six features were 0.84, 0.87, 0.87, 0.82, 0.84, and 0.75, respectively. Accuracy, sensitivity, specificity, and positive and negative predictive values were 85% (187 of 221), 83% (96 of 115), 86% (91 of 106), 86% (96 of 111), and 83% (91 of 110), respectively, with A(z) of 0.92 based on all six feature values. CONCLUSION: Three-dimensional power Doppler US images and neural network analysis of features can aid in classification of breast tumors as benign or malignant.

Computer algorithm for analysing breast tumor angiogenesis using 3-D power Doppler ultrasound.

Angiogenesis provides blood supply for tumor expansion and also increases the opportunity for tumor cells to enter the blood or lymph circulation. Several proangiogenic factors as well as the contribution of the microenvironment to tumor-induced angiogenesis have been identified. Among these, vascular endothelial growth factor (VEGF) and the angiopoietin (Ang) family play a predominant role involved in the growth for endothelial cells. Tumor vessels are structurally and functionally abnormal because of an imbalance of these angiogenic regulators. In contrast to normal vessels, tumor vasculature is highly disorganized, tortuous and dilated, with uneven diameter and excessive branching. In other words, the morphologic features are likely to carry additional clues that, when used in conjunction with more established parameters, can improve the present diagnostic approaches. In our study, we present a new method that helps to capture the morphologic features from three-dimensional (3-D) power Doppler ultrasound (PDUS) images. After narrowing down the vessels into their skeletons using a 3-D thinning algorithm, we extracted seven features including vessel-to-volume ratio, number of vascular trees, number of bifurcation, mean of radius and three tortuosity measures, from the skeleton and applied a neural network to classify the tumors by using these features. In investigations into 221 solid breast tumors, including 110 benign and 111 malignant cases, the p values using the Student's t-test for all features were less than 0.05, indicating that the proposed features were deemed statistically significant. The A(Z) values for these seven features were 0.84, 0.87, 0.84, 0.75, 0.77, 0.79 and 0.69, respectively. The accuracy, sensitivity, specificity, and positive and negative predictive values were 80.09% (177 of 221), 80.18% (89 of 111), 80% (88 of 110), 80.18% (89 of 111) and 80% (88 of 110), respectively, with an A(Z) value of 0.89. The preliminary results show that the proposed method is feasible and has a good agreement with the diagnosis of the pathologists.