Author(s): Guowei Deng, Qihui Wang, Min Yang, Bingke Li, Tao Han, Bo Chang, Xianghui Li, Xiaoling Zhang*, Zhonghui Li*.
Electron deficient compounds are extensively studied in the field of molecular materials. Compared to the simplest electron acceptors, multi-cyano heterocyclics performed excellent properties in electron-withdrawing ability, thermal stability, etc. This review provides a survey of the synthesis and modifications of two kinds of multi-cyano heterocyclics and their applications. To read out more, please visit: http://www.eurekaselect.com/161229/article
Author(s): María M. Pérez*, Oscar E. Pecho, Razvan Ghinea, Rosa Pulgar, Alvaro Della Bona.
Background: The final goal of color measurement or shade specification in dentistry is the reproduction by prosthetic materials of all important appearance characteristics of natural oral structures. The application of color science in dentistry is an objective way to measure and evaluate such structures and dental materials in clinical practice and dental research.
Methods: Literature on color science was reviewed to present new metrics to evaluate color differences of dental materials and dental structures. Visual acceptability and perceptibility values of color differences are reviewed and new whiteness indexes to describe whiteness in dentistry are presented.
Results: In the last decade, the CIELAB 50:50% perceptibility and acceptability thresholds were set to 1.2 and 2.7, respectively, and the CIEDE2000 50:50% perceptibility and acceptability thresholds were set to 0.8 and 1.8. The CIEDE2000 color-difference formula became increasingly popular in dentistry. Developments in color science have led to the description of tooth whiteness and changes in tooth whiteness based on whiteness indexes, with the most relevant being the WID whiteness index, which is a customized index based in CIELAB color space.
Conclusion: The application of color science in dentistry has allowed the precise description of tooth color and whiteness. The revised and new CIEDE2000 color-difference formula is expected to fully replace the outdated CIELAB formula in almost all dental applications. Recent psychophysical studies have reported values of visual thresholds and new whiteness indexes, which can serve as quality control tools to guide the selection of esthetic dental materials, evaluate clinical performance, and interpret visual and instrumental findings in clinical dentistry, dental research, and subsequent standardization. To read out more, please visit: http://www.eurekaselect.com/163911/article
Author(s): Gaetano Marenzi*, Med Erda Qorri, Pasquale Sammartino, Filomena Rusciano, Roberta Gasparro
Background: Platelet concentrates (PC) are blood-derived products for local application able to stimulate regeneration in soft and hard tissues, mimicking the physiological healing process. Their efficacy in oral surgical procedures is controversial and limited.
Objective: The study aims to critically analyze the available evidence for the effect of autogenous PC on wound healing of different oral surgical sites reported by more recent clinical studies.
Methods: Electronic and manual searches in three databases (Medline, Web of Science, Scopus) were performed to identify the clinical studies from January 2017 to December 2017 which reported the actual oral surgical indications and the benefit of local application of PC. All human studies evaluating PRP or PRF in a randomized controlled trial, case series, case report and systematic review were included. All animal, histologic and in vitro studies were excluded.
Results: Fifty-two studies were selected. The use of PRF was proposed in treating many oral surgical sites. Data availability with regard to the effect of PRF on new bone formation in GBR and horizontal/ vertical bone augmentation procedures varied from abundant to absent. Positive results concerning the effect of PRF on potential post-surgical complication (pain, swelling and trismus) were reported.
Conclusion: Few clinical indications could be determined: the literature on the topic was contradictory and the published data were difficult to interpret. Positive results were generally recorded for soft tissues and periodontal wound healing. No real benefit of PC application on bone regeneration was evidenced. To read out more, please visit: http://www.eurekaselect.com/163161/article
Background: Self Interacting Proteins (SIPs) play an essential role in various aspects of the structural and functional organization of the cell.
Objective: In the study, we presented a novelty sequence-based computational approach for predicting Self-interacting proteins using Weighed-Extreme Learning Machine (WELM) model combined with an Autocorrelation (AC) descriptor protein feature representation.
Method: The major advantage of the proposed method mainly lies in adopting an effective feature extraction method to represent candidate self-interacting proteins by using the evolutionary information embedded in PSI-BLAST-constructed Position Specific Scoring Matrix (PSSM); and then employing a reliable and effective WELM classifier to perform classify.
Result: In order to evaluate the performance, the proposed approach is applied to yeast and human SIP datasets. The experimental results show that our method obtained 93.43% and 98.15% prediction accuracies on yeast and human dataset, respectively. Extensive experiments are carried out to compare our approach with the SVM classifier and existing sequence-based method on yeast and human dataset. Experimental results show that the performance of our method is better than several other state-of-theart methods.
Conclusion: It is demonstrated that the proposed method is suitable for SIPs detection and can execute incredibly well for identifying Sips. In order to facilitate extensive studies for future proteomics research, we developed a freely available web server called WELM-AC-SIPs in Hypertext Preprocessor (PHP) for predicting SIPs. The web server including source code and the datasets are available at http://220.127.116.11:8888/WELMAC/. To read out more, please visit:http://www.eurekaselect.com/159690
Author(s): Wei Zhang, Wenchao Li, Jianming Zhang*, Ning Wang.
Background: Gene Regulatory Network (GRN) inference algorithms aim to explore casual interactions between genes and transcriptional factors. High-throughput transcriptomics data including DNA microarray and single cell expression data contain complementary information in network inference.
Objective: To enhance GRN inference, data integration across various types of expression data becomes an economic and efficient solution.
Method: In this paper, a novel E-alpha integration rule-based ensemble inference algorithm is proposed to merge complementary information from microarray and single cell expression data. This paper implements a Gradient Boosting Tree (GBT) inference algorithm to compute importance scores for candidate gene-gene pairs. The proposed E-alpha rule quantitatively evaluates the credibility levels of each information source and determines the final ranked list. Read out full article here: http://www.eurekaselect.com/168772
Starting from 2,3-dichloroquinoxaline, a synthetic strategy for the preparation of 1-(3- phenylpropyl)-4-(pyridinylmethoxy)[1,2,4]triazolo[4,3-a]quinoxalines is described. Read out full article here: http://www.eurekaselect.com/163737
In this study, we investigated the fusion of texture and morphometric features as a possible diagnostic biomarker for Alzheimer’s Disease (AD).
In particular, we classified subjects with Alzheimer’s disease, Mild Cognitive Impairment (MCI) and Normal Control (NC) based on texture and morphometric features. Currently, neuropsychiatric categorization provides the ground truth for AD and MCI diagnosis. This can then be supported by biological data such as the results of imaging studies. Cerebral atrophy has been shown to correlate strongly with cognitive symptoms. Hence, Magnetic Resonance (MR) images of the brain are important resources for AD diagnosis. In the proposed method, we used three different types of features identified from structural MR images: Gabor, hippocampus morphometric, and Two Dimensional (2D) and Three Dimensional (3D) Gray Level Co-occurrence Matrix (GLCM). The experimental results, obtained using a 5-fold cross-validated Support Vector Machine (SVM) with 2DGLCM and 3DGLCM multi-feature fusion approaches, indicate that we achieved 81.05% ±1.34, 86.61% ±1.25 correct classification rate with 95% Confidence Interval (CI) falls between (80.75-81.35) and (86.33-86.89) respectively, 83.33%±2.15, 84.21%±1.42 sensitivity and 80.95%±1.52, 85.00%±1.24 specificity in our classification of AD against NC subjects, thus outperforming recent works found in the literature. For the classification of MCI against AD, the SVM achieved a 76.31% ± 2.18, 78.95% ±2.26 correct classification rate, 75.00% ±1.34, 76.19%±1.84 sensitivity and 77.78% ±1.14, 82.35% ±1.34 specificity. Read out full article here: http://www.eurekaselect.com/166178
With the approval of gefitinib, erlotinib, afatinib, and osimertinib for clinical use, targeting Epidermal Growth Factor Receptor (EGFR) has been intensively pursued. Similar to most therapies, challenges related to the treatment resistance against these drugs have emerged over time, so new EGFR Tyrosine Kinase Inhibitors (TKIs) need to be developed. This study aimed to investigate the potential use of a series of thiophene-bearing quinazoline derivatives as EGFR inhibitors. We designed and synthesized nine quinazolin derivatives, among which five compounds (5e, 5f, 5g, 5h, and 5i) were reported for the first time. Read out full article here: http://www.eurekaselect.com/164334
This study was designed to develop a reliable method for simultaneous quantitation of Citalopram (CIT) and its main active metabolite, Desmethylcitalopram (DCIT), in saliva of patients undergoing treatment with CIT.
To compare two procedures of saliva purification, Solid-Phase (SPE) and Liquid-Liquid (LLE) extractions, saliva samples obtained from healthy volunteers were spiked with adequate quantities of CIT and DCIT. Different cartridges were used for SPE, while dichloromethane for LLE. Chromatographic separation and quantitation were carried out by UHPLC with DAD detector using a C-18 column and a mixture of acetonitrile and redistilled water (37:63, v:v) with the addition of formic acid (pH 3.5) as a mobile phase. Read out full article here: http://www.eurekaselect.com/157115
Journal Name: Combinatorial Chemistry & High Throughput Screening
A metabolic pathway is an important type of biological pathway, which is composed of a series of chemical reactions. It provides essential molecules and energies for living organisms. To date, several metabolic pathways have been uncovered. However, their completeness is still on the way. A number of prediction methods have been built to assign chemicals into certain metabolic pathway, which can further be used to predict novel latent chemicals for a given metabolic pathway. However, they did not make use of chemical properties in a system level to construct prediction models. Read out full article here: http://www.eurekaselect.com/168115