851 research outputs found

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

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    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

    Interplay of Mre11 Nuclease with Dna2 plus Sgs1 in Rad51-Dependent Recombinational Repair

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    The Mre11/Rad50/Xrs2 complex initiates IR repair by binding to the end of a double-strand break, resulting in 5′ to 3′ exonuclease degradation creating a single-stranded 3′ overhang competent for strand invasion into the unbroken chromosome. The nuclease(s) involved are not well understood. Mre11 encodes a nuclease, but it has 3′ to 5′, rather than 5′ to 3′ activity. Furthermore, mutations that inactivate only the nuclease activity of Mre11 but not its other repair functions, mre11-D56N and mre11-H125N, are resistant to IR. This suggests that another nuclease can catalyze 5′ to 3′ degradation. One candidate nuclease that has not been tested to date because it is encoded by an essential gene is the Dna2 helicase/nuclease. We recently reported the ability to suppress the lethality of a dna2Δ with a pif1Δ. The dna2Δ pif1Δ mutant is IR-resistant. We have determined that dna2Δ pif1Δ mre11-D56N and dna2Δ pif1Δ mre11-H125N strains are equally as sensitive to IR as mre11Δ strains, suggesting that in the absence of Dna2, Mre11 nuclease carries out repair. The dna2Δ pif1Δ mre11-D56N triple mutant is complemented by plasmids expressing Mre11, Dna2 or dna2K1080E, a mutant with defective helicase and functional nuclease, demonstrating that the nuclease of Dna2 compensates for the absence of Mre11 nuclease in IR repair, presumably in 5′ to 3′ degradation at DSB ends. We further show that sgs1Δ mre11-H125N, but not sgs1Δ, is very sensitive to IR, implicating the Sgs1 helicase in the Dna2-mediated pathway

    Manipulating infrared photons using plasmons in transparent graphene superlattices

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    Superlattices are artificial periodic nanostructures which can control the flow of electrons. Their operation typically relies on the periodic modulation of the electric potential in the direction of electron wave propagation. Here we demonstrate transparent graphene superlattices which can manipulate infrared photons utilizing the collective oscillations of carriers, i.e., plasmons of the ensemble of multiple graphene layers. The superlattice is formed by depositing alternating wafer-scale graphene sheets and thin insulating layers, followed by patterning them all together into 3-dimensional photonic-crystal-like structures. We demonstrate experimentally that the collective oscillation of Dirac fermions in such graphene superlattices is unambiguously nonclassical: compared to doping single layer graphene, distributing carriers into multiple graphene layers strongly enhances the plasmonic resonance frequency and magnitude, which is fundamentally different from that in a conventional semiconductor superlattice. This property allows us to construct widely tunable far-infrared notch filters with 8.2 dB rejection ratio and terahertz linear polarizers with 9.5 dB extinction ratio, using a superlattice with merely five graphene atomic layers. Moreover, an unpatterned superlattice shields up to 97.5% of the electromagnetic radiations below 1.2 terahertz. This demonstration also opens an avenue for the realization of other transparent mid- and far-infrared photonic devices such as detectors, modulators, and 3-dimensional meta-material systems.Comment: under revie

    Classification of patients with knee osteoarthritis in clinical phenotypes: data from the osteoarthritis initiative

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    <div><p>Objectives</p><p>The existence of phenotypes has been hypothesized to explain the large heterogeneity characterizing the knee osteoarthritis. In a previous systematic review of the literature, six main phenotypes were identified: Minimal Joint Disease (MJD), Malaligned Biomechanical (MB), Chronic Pain (CP), Inflammatory (I), Metabolic Syndrome (MS) and Bone and Cartilage Metabolism (BCM). The purpose of this study was to classify a sample of individuals with knee osteoarthritis (KOA) into pre-defined groups characterized by specific variables that can be linked to different disease mechanisms, and compare these phenotypes for demographic and health outcomes.</p><p>Methods</p><p>599 patients were selected from the OAI database FNIH at 24 months’ time to conduct the study. For each phenotype, cut offs of key variables were identified matching the results from previous studies in the field and the data available for the sample. The selection process consisted of 3 steps. At the end of each step, the subjects classified were excluded from the further classification stages. Patients meeting the criteria for more than one phenotype were classified separately into a ‘complex KOA’ group.</p><p>Results</p><p>Phenotype allocation (including complex KOA) was successful for 84% of cases with an overlap of 20%. Disease duration was shorter in the MJD while the CP phenotype included a larger number of Women (81%). A significant effect of phenotypes on WOMAC pain (F = 16.736 p <0.001) and WOMAC physical function (F = 14.676, p < 0.001) was identified after controlling for disease duration.</p><p>Conclusion</p><p>This study signifies the feasibility of a classification of KOA subjects in distinct phenotypes based on subgroup-specific characteristics.</p></div

    Identification of differentially expressed genes using an annealing control primer system in stage III serous ovarian carcinoma

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    <p>Abstract</p> <p>Background</p> <p>Most patients with ovarian cancer are diagnosed with advanced stage disease (<it>i.e</it>., stage III-IV), which is associated with a poor prognosis. Differentially expressed genes (DEGs) in stage III serous ovarian carcinoma compared to normal tissue were screened by a new differential display method, the annealing control primer (ACP) system. The potential targets for markers that could be used for diagnosis and prognosis, for stage III serous ovarian cancer, were found by cluster and survival analysis.</p> <p>Methods</p> <p>The ACP-based reverse transcriptase polymerase chain reaction (RT PCR) technique was used to identify DEGs in patients with stage III serous ovarian carcinoma. The DEGs identified by the ACP system were confirmed by quantitative real-time PCR. Cluster analysis was performed on the basis of the expression profile produced by quantitative real-time PCR and survival analysis was carried out by the Kaplan-Meier method and Cox proportional hazards multivariate model; the results of gene expression were compared between chemo-resistant and chemo-sensitive groups.</p> <p>Results</p> <p>A total of 114 DEGs were identified by the ACP-based RT PCR technique among patients with stage III serous ovarian carcinoma. The DEGs associated with an apoptosis inhibitory process tended to be up-regulated clones while the DEGs associated with immune response tended to be down-regulated clones. Cluster analysis of the gene expression profile obtained by quantitative real-time PCR revealed two contrasting groups of DEGs. That is, a group of genes including: <it>SSBP1</it>, <it>IFI6 DDT</it>, <it>IFI27</it>, <it>C11orf92</it>, <it>NFKBIA</it>, <it>TNXB</it>, <it>NEAT1 </it>and <it>TFG </it>were up-regulated while another group of genes consisting of: <it>LAMB2</it>, <it>XRCC6</it>, <it>MEF2C</it>, <it>RBM5</it>, <it>FOXP1</it>, <it>NUDCP2</it>, <it>LGALS3</it>, <it>TMEM185A</it>, and <it>C1S </it>were down-regulated in most patients. Survival analysis revealed that the up-regulated genes such as <it>DDAH2, RNase K and TCEAL2 </it>might be associated with a poor prognosis. Furthermore, the prognosis of patients with chemo-resistance was predicted to be very poor when genes such as <it>RNase K, FOXP1</it>, <it>LAMB2 </it>and <it>MRVI1 </it>were up-regulated.</p> <p>Conclusion</p> <p>The DEGs in patients with stage III serous ovarian cancer were successfully and reliably identified by the ACP-based RT PCR technique. The DEGs identified in this study might help predict the prognosis of patients with stage III serous ovarian cancer as well as suggest targets for the development of new treatment regimens.</p

    Uptake of oxLDL and IL-10 production by macrophages requires PAFR and CD36 recruitment into the same lipid rafts

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    Macrophage interaction with oxidized low-density lipoprotein (oxLDL) leads to its differentiation into foam cells and cytokine production, contributing to atherosclerosis development. In a previous study, we showed that CD36 and the receptor for platelet-activating factor (PAFR) are required for oxLDL to activate gene transcription for cytokines and CD36. Here, we investigated the localization and physical interaction of CD36 and PAFR in macrophages stimulated with oxLDL. We found that blocking CD36 or PAFR decreases oxLDL uptake and IL-10 production. OxLDL induces IL-10 mRNA expression only in HEK293T expressing both receptors (PAFR and CD36). OxLDL does not induce IL-12 production. The lipid rafts disruption by treatment with βCD reduces the oxLDL uptake and IL-10 production. OxLDL induces co-immunoprecipitation of PAFR and CD36 with the constitutive raft protein flotillin-1, and colocalization with the lipid raft-marker GM1-ganglioside. Finally, we found colocalization of PAFR and CD36 in macrophages from human atherosclerotic plaques. Our results show that oxLDL induces the recruitment of PAFR and CD36 into the same lipid rafts, which is important for oxLDL uptake and IL-10 production. This study provided new insights into how oxLDL interact with macrophages and contributing to atherosclerosis development

    Heritability estimates of the Big Five personality traits based on common genetic variants

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    According to twin studies, the Big Five personality traits have substantial heritable components explaining 40–60% of the variance, but identification of associated genetic variants has remained elusive. Consequently, knowledge regarding the molecular genetic architecture of personality and to what extent it is shared across the different personality traits is limited. Using genomic-relatedness-matrix residual maximum likelihood analysis (GREML), we here estimated the heritability of the Big Five personality factors (extraversion, agreeableness, conscientiousness, neuroticism and openness for experience) in a sample of 5011 European adults from 527 469 single-nucleotide polymorphisms across the genome. We tested for the heritability of each personality trait, as well as for the genetic overlap between the personality factors. We found significant and substantial heritability estimates for neuroticism (15%, s.e.=0.08, P=0.04) and openness (21%, s.e.=0.08, P<0.01), but not for extraversion, agreeableness and conscientiousness. The bivariate analyses showed that the variance explained by common variants entirely overlapped between neuroticism and openness (rG=1.00, P <0.001), despite low phenotypic correlation (r=−0.09, P <0.001), suggesting that the remaining unique heritability may be determined by rare or structural variants. As far as we are aware of, this is the first study estimating the shared and unique heritability of all Big Five personality traits using the GREML approach. Findings should be considered exploratory and suggest that detectable heritability estimates based on common variants is shared between neuroticism and openness to experiences

    Synthesis and Characterization of ZnO Nanowire–CdO Composite Nanostructures

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    ZnO nanowire–CdO composite nanostructures were fabricated by a simple two-step process involving ammonia solution method and thermal evaporation. First, ZnO nanowires (NWs) were grown on Si substrate by aqueous ammonia solution method and then CdO was deposited on these ZnO NWs by thermal evaporation of cadmium chloride powder. The surface morphology and structure of the synthesized composite structures were analyzed by scanning electron microscopy, X-ray diffraction and transmission electron microscopy. The optical absorbance spectrum showed that ZnO NW–CdO composites can absorb light up to 550 nm. The photoluminescence spectrum of the composite structure does not show any CdO-related emission peak and also there was no band gap modification of ZnO due to CdO. The photocurrent measurements showed that ZnO NW–CdO composite structures have better photocurrent when compared with the bare ZnO NWs

    Crystalline TiO2 protective layer with graded oxygen defects for efficient and stable silicon-based photocathode

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    © 2018, The Author(s). The trade-offs between photoelectrode efficiency and stability significantly hinder the practical application of silicon-based photoelectrochemical devices. Here, we report a facile approach to decouple the trade-offs of silicon-based photocathodes by employing crystalline TiO2 with graded oxygen defects as protection layer. The crystalline protection layer provides high-density structure and enhances stability, and at the same time oxygen defects allow the carrier transport with low resistance as required for high efficiency. The silicon-based photocathode with black TiO2 shows a limiting current density of ~35.3 mA cm-2 and durability of over 100 h at 10 mA cm-2 in 1.0 M NaOH electrolyte, while none of photoelectrochemical behavior is observed in crystalline TiO2 protection layer. These findings have significant suggestions for further development of silicon-based, III–V compounds and other photoelectrodes and offer the possibility for achieving highly efficient and durable photoelectrochemical devices

    Bolus characteristics based on Magnetic Resonance Angiography

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    BACKGROUND: A detailed contrast bolus propagation model is essential for optimizing bolus-chasing Computed Tomography Angiography (CTA). Bolus characteristics were studied using bolus-timing datasets from Magnetic Resonance Angiography (MRA) for adaptive controller design and validation. METHODS: MRA bolus-timing datasets of the aorta in thirty patients were analyzed by a program developed with MATLAB. Bolus characteristics, such as peak position, dispersion and bolus velocity, were studied. The bolus profile was fit to a convolution function, which would serve as a mathematical model of bolus propagation in future controller design. RESULTS: The maximum speed of the bolus in the aorta ranged from 5–13 cm/s and the dwell time ranged from 7–13 seconds. Bolus characteristics were well described by the proposed propagation model, which included the exact functional relationships between the parameters and aortic location. CONCLUSION: The convolution function describes bolus dynamics reasonably well and could be used to implement the adaptive controller design
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