Evaluation of 3D printed PCL/PLGA/beta-TCP versus collagen membranes for guided bone regeneration in a beagle implant model

Here, we compared 3D-printed polycaprolactone/poly(lactic-co-glycolic acid)/beta-tricalcium phosphate (PCL/PLGA/beta-TCP) membranes with the widely used collagen membranes for guided bone regeneration (GBR) in beagle implant models. For mechanical property comparison in dry and wet conditions and cytocompatibility determination, we analyzed the rate and pattern of cell proliferation of seeded fibroblasts and preosteoblasts using the cell counting kit-8 assay and scanning electron microscopy. Osteogenic differentiation was verified using alizarin red S staining. At 8 weeks following implantation in vivo using beagle dogs, computed tomography and histological analyses were performed after sacrifice. Cell proliferation rates in vitro indicated that early cell attachment was higher in collagen than in PCL/PLGA/beta-TCP membranes; however, the difference subsided by day 7. Similar outcomes were found for osteogenic differentiation, with approximately 2.5 times greater staining in collagen than PCL/PLGA/beta-TCP, but without significant difference by day 14. In vivo, bone regeneration in the defect area, represented by new bone formation and bone-to-implant contact, paralleled those associated with collagen membranes. However, tensile testing revealed that whereas the PCL/PLGA/beta-TCP membrane mechanical properties were conserved in both wet and dry states, the tensile property of collagen was reduced by 99% under wet conditions. Our results demonstrate in vitro and in vivo that PCL/PLGA/beta-TCP membranes have similar levels of biocompatibility and bone regeneration as collagen membranes. In particular, considering that GBR is always applied to a wet environment (e.g. blood, saliva), we demonstrated that PCL/PLGA/beta-TCP membranes maintained their form more reliably than collagen membranes in a wet setting, confirming their appropriateness as a GBR membrane.11109Ysciescopu

Sum-Rate Maximization for UAV Relay-Aided Fluid Antenna System with NOMA

Fluid Antenna System (FAS), Non-Orthogonal Multiple Access (NOMA), and Unmanned Aerial Vehicle (UAV) have been explored as promising technologies for sixth-generation (6G) wireless networks. However, a single technology alone will not be sufficient to meet the stringent performance requirements of 6G. Thus, in this paper, we propose a NOMA-based UAV Relay-Aided FAS to address this challenge. Specifically, we jointly optimize the active port, power allocation, and UAV altitude to maximize the achievable sum-rate of Ground Users (GUs) while satisfying minimum rate requirements. To tackle this non-convex optimization problem, we decouple it into two sub-problems: a large-scale fading optimization problem and a small-scale fading optimization problem. We demonstrate that the large-scale fading problem can be solved using a one-dimensional search method, while the small-scale fading problem can be addressed with closed-form expressions. Our simulation results show that FAS consistently outperforms Traditional Antenna System (TAS). Moreover, the combination of FAS and NOMA greatly benefits from the joint optimization of both small-scale and large-scale fadings in UAV relay-aided communications, resulting in substantial performance improvements over the existing TAS and Orthogonal Multiple Access (OMA) combination

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis

Bambara groundnut (Vigna subterranea (L.) Verdc.) is an African legume and is a promising underutilized crop with good seed nutritional values. Low temperature stress in a number of African countries at night, such as Botswana, can effect the growth and development of bambara groundnut, leading to losses in potential crop yield. Therefore, in this study we developed a computational pipeline to identify and analyze the genes and gene modules associated with low temperature stress responses in bambara groundnut using the cross-species microarray technique (as bambara groundnut has no microarray chip) coupled with network-based analysis. Analyses of the bambara groundnut transcriptome using cross-species gene expression data resulted in the identification of 375 and 659 differentially expressed genes (p<0.01) under the sub-optimal (23°C) and very sub-optimal (18°C) temperatures, respectively, of which 110 genes are commonly shared between the two stress conditions. The construction of a Highest Reciprocal Rank-based gene co-expression network, followed by its partition using a Heuristic Cluster Chiseling Algorithm resulted in 6 and 7 gene modules in sub-optimal and very sub-optimal temperature stresses being identified, respectively. Modules of sub-optimal temperature stress are principally enriched with carbohydrate and lipid metabolic processes, while most of the modules of very sub-optimal temperature stress are significantly enriched with responses to stimuli and various metabolic processes. Several transcription factors (from MYB, NAC, WRKY, WHIRLY & GATA classes) that may regulate the downstream genes involved in response to stimulus in order for the plant to withstand very sub-optimal temperature stress were highlighted. The identified gene modules could be useful in breeding for low-temperature stress tolerant bambara groundnut varieties

Integrating Diverse Datasets Improves Developmental Enhancer Prediction

Gene-regulatory enhancers have been identified using various approaches, including evolutionary conservation, regulatory protein binding, chromatin modifications, and DNA sequence motifs. To integrate these different approaches, we developed EnhancerFinder, a two-step method for distinguishing developmental enhancers from the genomic background and then predicting their tissue specificity. EnhancerFinder uses a multiple kernel learning approach to integrate DNA sequence motifs, evolutionary patterns, and diverse functional genomics datasets from a variety of cell types. In contrast with prediction approaches that define enhancers based on histone marks or p300 sites from a single cell line, we trained EnhancerFinder on hundreds of experimentally verified human developmental enhancers from the VISTA Enhancer Browser. We comprehensively evaluated EnhancerFinder using cross validation and found that our integrative method improves the identification of enhancers over approaches that consider a single type of data, such as sequence motifs, evolutionary conservation, or the binding of enhancer-associated proteins. We find that VISTA enhancers active in embryonic heart are easier to identify than enhancers active in several other embryonic tissues, likely due to their uniquely high GC content. We applied EnhancerFinder to the entire human genome and predicted 84,301 developmental enhancers and their tissue specificity. These predictions provide specific functional annotations for large amounts of human non-coding DNA, and are significantly enriched near genes with annotated roles in their predicted tissues and lead SNPs from genome-wide association studies. We demonstrate the utility of EnhancerFinder predictions through in vivo validation of novel embryonic gene regulatory enhancers from three developmental transcription factor loci. Our genome-wide developmental enhancer predictions are freely available as a UCSC Genome Browser track, which we hope will enable researchers to further investigate questions in developmental biology. © 2014 Erwin et al

Study of hadronic event-shape variables in multijet final states in pp collisions at √s=7 TeV

Peer reviewe

MoveBox: Democratizing MoCap for the Microsoft Rocketbox Avatar Library

This paper presents MoveBox an open sourced toolbox for animating motion captured (MoCap) movements onto the Microsoft Rocketbox library of avatars. Motion capture is performed using a single depth sensor, such as Azure Kinect or Windows Kinect V2. Motion capture is performed in real-time using a single depth sensor, such as Azure Kinect or Windows Kinect V2, or extracted from existing RGB videos offline leveraging deep-learning computer vision techniques. Our toolbox enables real-time animation of the user’s avatar by converting the transformations between systems that have different joints and hierarchies. Additional features of the toolbox include recording, playback and looping animations, as well as basic audio lip sync, blinking and resizing of avatars as well as finger and hand animations. Our main contribution is both in the creation of this open source tool as well as the validation on different devices and discussion of MoveBox’s capabilities by end users

Constraints on parton distribution functions and extraction of the strong coupling constant from the inclusive jet cross section in pp collisions at √s=7 TeV

Peer reviewe

Efficacy and Safety of Evogliptin Add-on Therapy to Dapagliflozin/Metformin Combinations in Patients with Poorly Controlled Type 2 Diabetes Mellitus: A 24-Week Multicenter Randomized Placebo-Controlled Parallel-Design Phase-3 Trial with a 28-Week Extension

Background: This study investigates the long-term efficacy and safety of evogliptin add-on therapy in patients with inadequately controlled type 2 diabetes mellitus (T2DM) previously received dapagliflozin and metformin (DAPA/MET) combination. Methods: In this multicenter randomized placebo-controlled phase 3 trial, patients with glycosylated hemoglobin (HbA1c) levels 7.0% to 10.5% (n=283) previously used DAPA 10 mg plus MET (≥1,000 mg) were randomly assigned to the evogliptin 5 mg once daily or placebo group (1:1). The primary endpoint was the difference in the HbA1c level from baseline at week 24, and exploratory endpoints included the efficacy and safety of evogliptin over 52 weeks (trial registration: ClinicalTrials.gov NCT04170998). Results: Evogliptin add-on to DAPA/MET therapy was superior in HbA1c reduction compared to placebo at weeks 24 and 52 (least square [LS] mean difference, –0.65% and –0.55%; 95% confidence interval [CI], –0.79 to –0.51 and –0.71 to –0.39; P&lt;0.0001). The proportion of patients achieving HbA1c &lt;7% was higher in the triple combination group at week 52 (32.14% vs. 8.51% in placebo; odds ratio, 5.62; P&lt;0.0001). Evogliptin significantly reduced the fasting glucose levels and mean daily glucose levels with improvement in homeostatic model assessment of β-cell function (LS mean difference, 9.04; 95% CI, 1.86 to 16.21; P=0.0138). Adverse events were similar between the groups, and no serious adverse drug reactions were reported in the evogliptin group. Conclusion: Long-term triple combination with evogliptin added to DAPA/MET showed superior HbA1c reduction and glycemic control compared to placebo at 52 weeks and was well tolerated

Neogenin expression may be inversely correlated to the tumorigenicity of human breast cancer

BACKGROUND: Neogenin is expressed in cap cells that have been suggested to be mammary stem or precursor cells. Neogenin is known to play an important role in mammary morphogenesis; however its relationship to tumorigenesis remains to be elucidated. METHODS: To compare the expression levels of neogenin in cells with different tumorigenicity, the expression levels in M13SV1, M13SV1R2 and M13SV1R2N1 cells, which are immortalized derivatives of type I human breast epithelial cells, were evaluated. Then we measured the expression level of neogenin in paired normal and cancer tissues from eight breast cancer patients. Tissue array analysis was performed for 54 human breast tissue samples with different histology, and the results were divided into four categories (none, weak, moderate, strong) by a single well-trained blinded pathologist and statistically analyzed. RESULTS: The nontumorigenic M13SV1 cells and normal tissues showed stronger expression of neogenin than the M13SV1R2N1 cells and the paired cancer tissues. In the tissue array, all (8/8) of the normal breast tissues showed strong neogenin expression, while 93.5% (43/46) of breast cancer tissues had either no expression or only moderate levels of neogenin expression. There was a significant difference, in the expression level of neogenin, in comparisons between normal and infiltrating ductal carcinoma (p < 0.001). CONCLUSION: Neogenin may play a role in mammary carcinogenesis as well as morphogenesis, and the expression may be inversely correlated with mammary carcinogenicity. The value of neogenin as a potential prognostic factor needs further evaluation