Development and Validation of Apolipoprotein AI-Associated Lipoprotein Proteome Panel for the Prediction of Cholesterol Efflux Capacity and Coronary Artery Disease

BACKGROUND: Cholesterol efflux capacity (CEC) is a measure of HDL function that, in cell-based studies, has demonstrated an inverse association with cardiovascular disease. The cell-based measure of CEC is complex and low-throughput. We hypothesized that assessment of the lipoprotein proteome would allow for precise, high-throughput CEC prediction. METHODS: After isolating lipoprotein particles from serum, we used LC-MS/MS to quantify 21 lipoprotein-associated proteins. A bioinformatic pipeline was used to identify proteins with univariate correlation to cell-based CEC measurements and generate a multivariate algorithm for CEC prediction (pCE). Using logistic regression, protein coefficients in the pCE model were reweighted to yield a new algorithm predicting coronary artery disease (pCAD). RESULTS: Discovery using targeted LC-MS/MS analysis of 105 training and test samples yielded a pCE model comprising 5 proteins (Spearman r = 0.86). Evaluation of pCE in a case-control study of 231 specimens from healthy individuals and patients with coronary artery disease revealed lower pCE in cases (P = 0.03). Derived within this same study, the pCAD model significantly improved classification (P < 0.0001). Following analytical validation of the multiplexed proteomic method, we conducted a case-control study of myocardial infarction in 137 postmenopausal women that confirmed significant separation of specimen cohorts in both the pCE (P = 0.015) and pCAD (P = 0.001) models. CONCLUSIONS: Development of a proteomic pCE provides a reproducible high-throughput alternative to traditional cell-based CEC assays. The pCAD model improves stratification of case and control cohorts and, with further studies to establish clinical validity, presents a new opportunity for the assessment of cardiovascular health

Geometry and kinematics for a spherical-base integrated parallel mechanism

Parallel mechanisms, in general, have a rigid base and a moving platform connected by several limbs. For achieving higher mobility and dexterity, more degrees of freedom are introduced to the limbs. However, very few researchers focus on changing the design of the rigid base and making it foldable and reconfigurable to improve the performance of the mechanism. Inspired by manipulating an object with a metamorphic robotic hand, this paper presents for the first time a parallel mechanism with a reconfigurable base. This novel spherical-base integrated parallel mechanism has an enlarged workspace compared with traditional parallel manipulators. Evolution and structure of the proposed parallel mechanism is introduced and the geometric constraint of the mechanism is investigated based on mechanism decomposition. Further, kinematics of the proposed mechanism is reduced to the solution of a univariate polynomial of degree 8. Moreover, screw theory based Jacobian is presented followed by the velocity analysis of the mechanism

Residual stress measurement round robin on an electron beam welded joint between austenitic stainless steel 316L(N) and ferritic steel P91

This paper is a research output of DMW-Creep project which is part of a national UK programme through the RCUK Energy programme and India's Department of Atomic Energy. The research is focussed on understanding the characteristics of welded joints between austenitic stainless steel and ferritic steel that are widely used in many nuclear power generating plants and petrochemical industries as well as conventional coal and gas-fired power systems. The members of the DMW-Creep project have under- taken parallel round robin activities measuring the residual stresses generated by a dissimilar metal weld (DMW) between AISI 316L(N) austenitic stainless steel and P91 ferritic-martensitic steel. Electron beam (EB) welding was employed to produce a single bead weld on a plate specimen and an additional smoothing pass (known cosmetic pass) was then introduced using a defocused beam. The welding re- sidual stresses have been measured by five experimental methods including (I) neutron diffraction (ND), (II) X-Ray diffraction (XRD), (III) contour method (CM), (IV) incremental deep hole drilling (iDHD) and (V) incremental centre hole drilling (iCHD). The round robin measurements of weld residual stresses are compared in order to characterise surface and sub-surface residual stresses comprehensively

Co3O4 Nanocrystals on Graphene as a Synergistic Catalyst for Oxygen Reduction Reaction

Catalysts for oxygen reduction and evolution reactions are at the heart of key renewable energy technologies including fuel cells and water splitting. Despite tremendous efforts, developing oxygen electrode catalysts with high activity at low costs remains a grand challenge. Here, we report a hybrid material of Co3O4 nanocrystals grown on reduced graphene oxide (GO) as a high-performance bi-functional catalyst for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). While Co3O4 or graphene oxide alone has little catalytic activity, their hybrid exhibits an unexpected, surprisingly high ORR activity that is further enhanced by nitrogen-doping of graphene. The Co3O4/N-doped graphene hybrid exhibits similar catalytic activity but superior stability to Pt in alkaline solutions. The same hybrid is also highly active for OER, making it a high performance non-precious metal based bi-catalyst for both ORR and OER. The unusual catalytic activity arises from synergetic chemical coupling effects between Co3O4 and graphene.Comment: published in Nature Material

Properties of Light Flavour Baryons in Hypercentral quark model

The light flavour baryons are studied within the quark model using the hyper central description of the three-body system. The confinement potential is assumed as hypercentral coulomb plus power potential ($hCPP_\nu$) with power index $\nu$. The masses and magnetic moments of light flavour baryons are computed for different power index, $\nu$ starting from 0.5 to 1.5. The predicted masses and magnetic moments are found to attain a saturated value with respect to variation in $\nu$ beyond the power index $\nu>$ 1.0. Further we computed transition magnetic moments and radiative decay width of light flavour baryons. The results are in good agreement with known experimental as well as other theoretical models.Comment: Accepted in Pramana J. of Physic

Morphology and Nanomechanics of Sensory Neurons Growth Cones following Peripheral Nerve Injury

A prior peripheral nerve injury in vivo, promotes a rapid elongated mode of sensory neurons neurite regrowth in vitro. This in vitro model of conditioned axotomy allows analysis of the cellular and molecular mechanisms leading to an improved neurite re-growth. Our differential interference contrast microscopy and immunocytochemistry results show that conditioned axotomy, induced by sciatic nerve injury, did not increase somatic size of adult lumbar sensory neurons from mice dorsal root ganglia sensory neurons but promoted the appearance of larger neurites and growth cones. Using atomic force microscopy on live neurons, we investigated whether membrane mechanical properties of growth cones of axotomized neurons were modified following sciatic nerve injury. Our data revealed that neurons having a regenerative growth were characterized by softer growth cones, compared to control neurons. The increase of the growth cone membrane elasticity suggests a modification in the ratio and the inner framework of the main structural proteins

Flavopiridol Pharmacogenetics: Clinical and Functional Evidence for the Role of SLCO1B1/OATP1B1 in Flavopiridol Disposition

Flavopiridol is a cyclin-dependent kinase inhibitor in phase II clinical development for treatment of various forms of cancer. When administered with a pharmacokinetically (PK)-directed dosing schedule, flavopiridol exhibited striking activity in patients with refractory chronic lymphocytic leukemia. This study aimed to evaluate pharmacogenetic factors associated with inter-individual variability in pharmacokinetics and outcomes associated with flavopiridol therapy.Thirty-five patients who received single-agent flavopiridol via the PK-directed schedule were genotyped for 189 polymorphisms in genes encoding 56 drug metabolizing enzymes and transporters. Genotypes were evaluated in univariate and multivariate analyses as covariates in a population PK model. Transport of flavopiridol and its glucuronide metabolite was evaluated in uptake assays in HEK-293 and MDCK-II cells transiently transfected with SLCO1B1. Polymorphisms in ABCC2, ABCG2, UGT1A1, UGT1A9, and SLCO1B1 were found to significantly correlate with flavopiridol PK in univariate analysis. Transport assay results indicated both flavopiridol and flavopiridol-glucuronide are substrates of the SLCO1B1/OATP1B1 transporter. Covariates incorporated into the final population PK model included bilirubin, SLCO1B1 rs11045819 and ABCC2 rs8187710. Associations were also observed between genotype and response. To validate these findings, a second set of data with 51 patients was evaluated, and overall trends for associations between PK and PGx were found to be consistent.Polymorphisms in transport genes were found to be associated with flavopiridol disposition and outcomes. Observed clinical associations with SLCO1B1 were functionally validated indicating for the first time its relevance as a transporter of flavopiridol and its glucuronide metabolite. A second 51-patient dataset indicated similar trends between genotype in the SLCO1B1 and other candidate genes, thus providing support for these findings. Further study in larger patient populations will be necessary to fully characterize and validate the clinical impact of polymorphisms in SLCO1B1 and other transporter and metabolizing enzyme genes on outcomes from flavopiridol therapy

Efficacy, Tolerability, and Biomarker Analyses of Once-Every-2-Weeks Cetuximab Plus First-Line FOLFOX or FOLFIRI in Patients With KRAS or All RAS Wild-Type Metastatic Colorectal Cancer: The Phase 2 APEC Study

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Small Tympanic Membrane Perforations in the Inferior Quadrants Do Not Impact the Manubrium Vibration in Guinea Pigs

BACKGROUND: It has been believed that location of the perforation has a significant impact on hearing loss. However, recent studies have demonstrated that the perforation sites had no impact on hearing loss. We measured the velocity and pattern of the manubrium vibration in guinea pigs with intact and perforated eardrum using a laser Doppler vibrometer in order to determine the effects of different location perforations on the middle ear transfer functions. METHODS: Two bullas from 2 guinea pigs were used to determine stability of the umbo velocities, and 12 bullas from six guinea pigs to determine the effects of different location perforations on sound transmission. The manubrium velocity was measured at three points on the manubrium in the frequencies of 0.5-8 kHz before and after a perforation was made. The sites of perforations were in anterior-inferior (AI) quadrants of left ears and posterior-inferior (PI) quadrants of right ears. RESULTS: The manubrium vibration velocity losses were noticed in the perforated ears only below 1.5 kHz. The maximum velocity loss was about 7 dB at 500 Hz with the PI perforation. No significant difference in the velocity loss was found between AI and PI perforations. The average ratio of short process velocity to the umbo velocity was approximately 0.5 at all frequencies. No significant differences were found before and after perforation at all frequencies (p>0.05) except 7 kHz (p = 0.004) for both AI and PI perforations. CONCLUSIONS: The manubrium vibration velocity losses from eardrum perforation were frequency-dependent and the largest losses occur at low frequencies. Manubrium velocity losses caused by small acute inferior perforations in guinea pigs have no significant impact on middle ear sound transmission at any frequency tested. The manubrium vibration axis may be perpendicular to the manubrium below 8 kHz in guinea pigs

Insights gained from the reverse engineering of gene networks in keloid fibroblasts

<p>Abstract</p> <p>Background</p> <p>Keloids are protrusive claw-like scars that have a propensity to recur even after surgery, and its molecular etiology remains elusive. The goal of reverse engineering is to infer gene networks from observational data, thus providing insight into the inner workings of a cell. However, most attempts at modeling biological networks have been done using simulated data. This study aims to highlight some of the issues involved in working with experimental data, and at the same time gain some insights into the transcriptional regulatory mechanism present in keloid fibroblasts.</p> <p>Methods</p> <p>Microarray data from our previous study was combined with microarray data obtained from the literature as well as new microarray data generated by our group. For the physical approach, we used the fREDUCE algorithm for correlating expression values to binding motifs. For the influence approach, we compared the Bayesian algorithm BANJO with the information theoretic method ARACNE in terms of performance in recovering known influence networks obtained from the KEGG database. In addition, we also compared the performance of different normalization methods as well as different types of gene networks.</p> <p>Results</p> <p>Using the physical approach, we found consensus sequences that were active in the keloid condition, as well as some sequences that were responsive to steroids, a commonly used treatment for keloids. From the influence approach, we found that BANJO was better at recovering the gene networks compared to ARACNE and that transcriptional networks were better suited for network recovery compared to cytokine-receptor interaction networks and intracellular signaling networks. We also found that the NFKB transcriptional network that was inferred from normal fibroblast data was more accurate compared to that inferred from keloid data, suggesting a more robust network in the keloid condition.</p> <p>Conclusions</p> <p>Consensus sequences that were found from this study are possible transcription factor binding sites and could be explored for developing future keloid treatments or for improving the efficacy of current steroid treatments. We also found that the combination of the Bayesian algorithm, RMA normalization and transcriptional networks gave the best reconstruction results and this could serve as a guide for future influence approaches dealing with experimental data.</p