High Fidelity Tape Transfer Printing Based On Chemically Induced Adhesive Strength Modulation

Transfer printing, a two-step process (i.e. picking up and printing) for heterogeneous integration, has been widely exploited for the fabrication of functional electronics system. To ensure a reliable process, strong adhesion for picking up and weak or no adhesion for printing are required. However, it is challenging to meet the requirements of switchable stamp adhesion. Here we introduce a simple, high fidelity process, namely tape transfer printing(TTP), enabled by chemically induced dramatic modulation in tape adhesive strength. We describe the working mechanism of the adhesion modulation that governs this process and demonstrate the method by high fidelity tape transfer printing several types of materials and devices, including Si pellets arrays, photodetector arrays, and electromyography (EMG) sensors, from their preparation substrates to various alien substrates. High fidelity tape transfer printing of components onto curvilinear surfaces is also illustrated

The use of a synthetic shoulder patch for large and massive rotator cuff tears – a feasibility study

Background The aim of this study was to explore the feasibility of using a non-absorbable biocompatible polyester patch to augment open repair of massive rotator cuff tears (Patch group) and compare outcomes with other treatment options (Non-patch group). Methods Participants referred to orthopaedic clinics for rotator cuff surgery were recruited. Choice of intervention (Patch or Non-patch) was based on patient preference and intra-operative findings. Oxford Shoulder Score (OSS), Shoulder Pain and Disability Index (SPADI), and Constant score were completed at baseline and 6 months. Shoulder MRI was performed at baseline and 6 months to assess fat fraction and Goutallier classification pre- and post- treatment. Feasibility outcomes (including retention, consent and missing data) were assessed. Results Sixty-eight participants (29 in the Patch group, 39 in Non-patch group) were included (mean age 65.3 years). Conversion to consent (92.6%), missing data (0% at baseline), and attrition rate (16%) were deemed successful feasibility endpoints. There was significant improvement in the Patch group compared to Non-patch at 6 months in OSS (difference in medians 9.76 (95% CI 2.25, 17.29) and SPADI: 22.97 (95% CI 3.02, 42.92), with no substantive differences in Constant score. The patch group had a higher proportion of participants improving greater than MCID for OSS (78% vs 62%) and SPADI (63% vs 50%) respectively. Analysis of the 48 paired MRIs demonstrated a slight increase in the fat fraction for supraspinatus (53 to 55%), and infraspinatus (26 to 29%) at 6 months. These differences were similar and in the same direction when the participants were analysed by treatment group. The Goutallier score remained the same or worsened one grade in both groups equally. Conclusions This study indicates that a definitive clinical trial investigating the use of a non-absorbable patch to augment repair of massive rotator cuff tears is feasible. In such patients, the patch has the potential to improve shoulder symptoms at 6 months

Linear approaches to intramolecular Förster Resonance Energy Transfer probe measurements for quantitative modeling

Numerous unimolecular, genetically-encoded Forster Resonance Energy Transfer (FRET) probes for monitoring biochemical activities in live cells have been developed over the past decade. As these probes allow for collection of high frequency, spatially resolved data on signaling events in live cells and tissues, they are an attractive technology for obtaining data to develop quantitative, mathematical models of spatiotemporal signaling dynamics. However, to be useful for such purposes the observed FRET from such probes should be related to a biological quantity of interest through a defined mathematical relationship, which is straightforward when this relationship is linear, and can be difficult otherwise. First, we show that only in rare circumstances is the observed FRET linearly proportional to a biochemical activity. Therefore in most cases FRET measurements should only be compared either to explicitly modeled probes or to concentrations of products of the biochemical activity, but not to activities themselves. Importantly, we find that FRET measured by standard intensity-based, ratiometric methods is inherently non-linear with respect to the fraction of probes undergoing FRET. Alternatively, we find that quantifying FRET either via (1) fluorescence lifetime imaging (FLIM) or (2) ratiometric methods where the donor emission intensity is divided by the directly-excited acceptor emission intensity (denoted R<sub>alt</sub>) is linear with respect to the fraction of probes undergoing FRET. This linearity property allows one to calculate the fraction of active probes based on the FRET measurement. Thus, our results suggest that either FLIM or ratiometric methods based on R<sub>alt</sub> are the preferred techniques for obtaining quantitative data from FRET probe experiments for mathematical modeling purpose

Preface

Preface - The second International Conference on Mathematical Modeling in Physical Sciences (IC-MSQUARE) took place at Prague, Czech Republic, from Sunday 1 September to Thursday 5 September 2013

Predicting cocaine consumption in Spain: A mathematical modelling approach

This is an author's accepted manuscript of an article published in “Drugs: Education, Prevention, and Policy "; Volume 18, Issue 2, 2011; copyright Taylor & Francis; available online at: http://dx.doi.org/10.3109/09687630903443299In this article, we analyse the evolution of cocaine consumption in Spain and we predict consumption trends over the next few years. Additionally, we simulate some scenarios which aim to reduce cocaine consumption in the future (sensitivity analysis). Assuming cocaine dependency is a socially transmitted epidemic disease, this leads us to propose an epidemiological-type mathematical model to study consumption evolution. Model sensitivity analysis allows us to design strategies and analyse their effects on cocaine consumption. The model predicts that 3.5% of the Spanish population will be habitual cocaine consumers by 2015. The simulations carried out suggest that cocaine consumption prevention strategies are the best policy to reduce the habitual consumer population. In this article, we show that epidemiological-type mathematical models can be a useful tool in the analysis of the repercussion of health policy proposals in the short-time future. © 2011 Informa UK Ltd.Sánchez, E.; Villanueva Micó, RJ.; Santonja, FJ.; Rubio, M. (2011). Predicting cocaine consumption in Spain: A mathematical modelling approach. Drugs: Education, Prevention, and Policy. 18(2):108-115. doi:10.3109/09687630903443299S108115182Blower, S. M., & Dowlatabadi, H. (1994). Sensitivity and Uncertainty Analysis of Complex Models of Disease Transmission: An HIV Model, as an Example. International Statistical Review / Revue Internationale de Statistique, 62(2), 229. doi:10.2307/1403510Dutra, L., Stathopoulou, G., Basden, S. L., Leyro, T. M., Powers, M. B., & Otto, M. W. (2008). A Meta-Analytic Review of Psychosocial Interventions for Substance Use Disorders. American Journal of Psychiatry, 165(2), 179-187. doi:10.1176/appi.ajp.2007.06111851Gorman, D. M., Mezic, J., Mezic, I., & Gruenewald, P. J. (2006). Agent-Based Modeling of Drinking Behavior: A Preliminary Model and Potential Applications to Theory and Practice. American Journal of Public Health, 96(11), 2055-2060. doi:10.2105/ajph.2005.063289Jódar, L., Santonja, F. J., & González-Parra, G. (2008). Modeling dynamics of infant obesity in the region of Valencia, Spain. Computers & Mathematics with Applications, 56(3), 679-689. doi:10.1016/j.camwa.2008.01.011JOHNSON, B., ROACHE, J., AITDAOUD, N., JAVORS, M., HARRISON, J., ELKASHEF, A., … BLOCH, D. (2006). A preliminary randomized, double-blind, placebo-controlled study of the safety and efficacy of ondansetron in the treatment of cocaine dependence. Drug and Alcohol Dependence, 84(3), 256-263. doi:10.1016/j.drugalcdep.2006.02.011Levin, F. R., Evans, S. M., Brooks, D. J., & Garawi, F. (2007). Treatment of cocaine dependent treatment seekers with adult ADHD: Double-blind comparison of methylphenidate and placebo. Drug and Alcohol Dependence, 87(1), 20-29. doi:10.1016/j.drugalcdep.2006.07.004Marino, S., Hogue, I. B., Ray, C. J., & Kirschner, D. E. (2008). A methodology for performing global uncertainty and sensitivity analysis in systems biology. Journal of Theoretical Biology, 254(1), 178-196. doi:10.1016/j.jtbi.2008.04.011Martcheva, M., & Castillo-Chavez, C. (2003). Diseases with chronic stage in a population with varying size. Mathematical Biosciences, 182(1), 1-25. doi:10.1016/s0025-5564(02)00184-0Nelder, J. A., & Mead, R. (1965). A Simplex Method for Function Minimization. The Computer Journal, 7(4), 308-313. doi:10.1093/comjnl/7.4.308Olsson, A., Sandberg, G., & Dahlblom, O. (2003). On Latin hypercube sampling for structural reliability analysis. Structural Safety, 25(1), 47-68. doi:10.1016/s0167-4730(02)00039-5Santonja, F. J., Tarazona, A. C., & Villanueva, R. J. (2008). A mathematical model of the pressure of an extreme ideology on a society. Computers & Mathematics with Applications, 56(3), 836-846. doi:10.1016/j.camwa.2008.01.001Schmitz, J. M., Stotts, A. L., Rhoades, H. M., & Grabowski, J. (2001). Naltrexone and relapse prevention treatment for cocaine-dependent patients. Addictive Behaviors, 26(2), 167-180. doi:10.1016/s0306-4603(00)00098-8Sharomi, O., & Gumel, A. B. (2008). Curtailing smoking dynamics: A mathematical modeling approach. Applied Mathematics and Computation, 195(2), 475-499. doi:10.1016/j.amc.2007.05.012Stotts, A. L., Mooney, M. E., Sayre, S. L., Novy, M., Schmitz, J. M., & Grabowski, J. (2007). Illusory predictors: Generalizability of findings in cocaine treatment retention research. Addictive Behaviors, 32(12), 2819-2836. doi:10.1016/j.addbeh.2007.04.020White, E., & Comiskey, C. (2007). Heroin epidemics, treatment and ODE modelling. Mathematical Biosciences, 208(1), 312-324. doi:10.1016/j.mbs.2006.10.00

Sorghum cobalt analysis on not determined wave length with atomic absorption spectrophotometer on background correction mode

This study was to know the better wave length on measuring cobalt content in forage sorghum hybrid (Sorghum bicolor) with an atomic absorption spectrophotometer. The analysis was on background correction mode with three wave lengths; 240.8, 240.7 (determined wave length or recommended wave length) and 240.6 nm, respectively. The larger absorbance value on the 240.7 nm, apparently, it might be considered as a good wave length but the smaller background value was a more important factor for the analysis as was shown on 240.6 nm. Correlation coefficients between the values on 240.7 nm: 240.6 nm and between them (240.8 nm: 240.6 nm) were higher and this common 240.6 nm was considered the better wave length.Key words: Atomic absorption spectrophotometer; background correction mode, cobalt analysis, forage sorghum, not determined wave lengths

Adenosine-mono-phosphate-activated protein kinase-independent effects of metformin in T cells

The anti-diabetic drug metformin regulates T-cell responses to immune activation and is proposed to function by regulating the energy-stress-sensing adenosine-monophosphate-activated protein kinase (AMPK). However, the molecular details of how metformin controls T cell immune responses have not been studied nor is there any direct evidence that metformin acts on T cells via AMPK. Here, we report that metformin regulates cell growth and proliferation of antigen-activated T cells by modulating the metabolic reprogramming that is required for effector T cell differentiation. Metformin thus inhibits the mammalian target of rapamycin complex I signalling pathway and prevents the expression of the transcription factors c-Myc and hypoxia-inducible factor 1 alpha. However, the inhibitory effects of metformin on T cells did not depend on the expression of AMPK in T cells. Accordingly, experiments with metformin inform about the importance of metabolic reprogramming for T cell immune responses but do not inform about the importance of AMPK

Terminal Pleistocene Alaskan genome reveals first founding population of Native Americans

Despite broad agreement that the Americas were initially populated via Beringia, the land bridge that connected far northeast Asia with northwestern North America during the Pleistocene epoch, when and how the peopling of the Americas occurred remains unresolved. Analyses of human remains from Late Pleistocene Alaska are important to resolving the timing and dispersal of these populations. The remains of two infants were recovered at Upward Sun River (USR), and have been dated to around 11.5 thousand years ago (ka). Here, by sequencing the USR1 genome to an average coverage of approximately 17 times, we show that USR1 is most closely related to Native Americans, but falls basal to all previously sequenced contemporary and ancient Native Americans. As such, USR1 represents a distinct Ancient Beringian population. Using demographic modelling, we infer that the Ancient Beringian population and ancestors of other Native Americans descended from a single founding population that initially split from East Asians around 36 ± 1.5 ka, with gene flow persisting until around 25 ± 1.1 ka. Gene flow from ancient north Eurasians into all Native Americans took place 25–20 ka, with Ancient Beringians branching off around 22–18.1 ka. Our findings support a long-term genetic structure in ancestral Native Americans, consistent with the Beringian ‘standstill model’. We show that the basal northern and southern Native American branches, to which all other Native Americans belong, diverged around 17.5–14.6 ka, and that this probably occurred south of the North American ice sheets. We also show that after 11.5 ka, some of the northern Native American populations received gene flow from a Siberian population most closely related to Koryaks, but not Palaeo-Eskimos, Inuits or Kets, and that Native American gene flow into Inuits was through northern and not southern Native American groups. Our findings further suggest that the far-northern North American presence of northern Native Americans is from a back migration that replaced or absorbed the initial founding population of Ancient Beringians

Causal Effect of Plasminogen Activator Inhibitor Type 1 on Coronary Heart Disease.

BACKGROUND: Plasminogen activator inhibitor type 1 (PAI-1) plays an essential role in the fibrinolysis system and thrombosis. Population studies have reported that blood PAI-1 levels are associated with increased risk of coronary heart disease (CHD). However, it is unclear whether the association reflects a causal influence of PAI-1 on CHD risk. METHODS AND RESULTS: To evaluate the association between PAI-1 and CHD, we applied a 3-step strategy. First, we investigated the observational association between PAI-1 and CHD incidence using a systematic review based on a literature search for PAI-1 and CHD studies. Second, we explored the causal association between PAI-1 and CHD using a Mendelian randomization approach using summary statistics from large genome-wide association studies. Finally, we explored the causal effect of PAI-1 on cardiovascular risk factors including metabolic and subclinical atherosclerosis measures. In the systematic meta-analysis, the highest quantile of blood PAI-1 level was associated with higher CHD risk comparing with the lowest quantile (odds ratio=2.17; 95% CI: 1.53, 3.07) in an age- and sex-adjusted model. The effect size was reduced in studies using a multivariable-adjusted model (odds ratio=1.46; 95% CI: 1.13, 1.88). The Mendelian randomization analyses suggested a causal effect of increased PAI-1 level on CHD risk (odds ratio=1.22 per unit increase of log-transformed PAI-1; 95% CI: 1.01, 1.47). In addition, we also detected a causal effect of PAI-1 on elevating blood glucose and high-density lipoprotein cholesterol. CONCLUSIONS: Our study indicates a causal effect of elevated PAI-1 level on CHD risk, which may be mediated by glucose dysfunction.This work was supported by NHLBI Intramural funds to O’Donnell and Johnson. Stephen Burgess is supported by a fellowship from the Wellcome Trust (100114)