Chemoselective Immobilization of Proteins by Microcontact Printing and Bio‐orthogonal Click Reactions

Herein, a combination of microcontact printing of functionalized alkanethiols and site‐specific modification of proteins is utilized to chemoselectively immobilize proteins onto gold surfaces, either by oxime‐ or copper‐catalyzed alkyne–azide click chemistry. Two molecules capable of click reactions were synthesized, an aminooxy‐functionalized alkanethiol and an azide‐functionalized alkanethiol, and self‐assembled monolayer (SAM) formation on gold was confirmed by IR spectroscopy. The alkanethiols were then individually patterned onto gold surfaces by microcontact printing. Site‐specifically modified proteins—horse heart myoglobin (HHMb) containing an N‐terminal α‐oxoamide and a red fluorescent protein (mCherry‐CVIA) with a C‐terminal alkyne—were immobilized by incubation onto respective stamped functionalized alkanethiol patterns. Pattern formation was confirmed by fluorescence microscopy.     

An analysis of programming language statement frequency in C,C++, and Java source code

Statement frequency data can inform programming language research and provide a solid basis for frequency‐based code analysis. This paper presents an analysis of programming language statement frequency in a large corpus of C, C++, and Java source code, comprised of more than 54 million lines of code. Across these languages, the top four work‐performing statement types are Method/Function Call, Assignment, If, and Return. As compared to studies of Formula Translating System, Common Business Oriented Language and Programming Language One in the 1970s, the main change is the prevalence of method/function calls. Statement use frequency across languages is remarkably similar, and within each individual language, most statement types have a frequency distribution that occupies a small range. A more detailed examination of assignment and looping statement types shows that many assignments simply involve copying of data and that C++/Java use for statements more than C. Copyright © 2014 John Wiley & Sons, Ltd.     

DP-Fair: a unifying theory for optimal hard real-time multiprocessor scheduling

We consider the problem of optimal real-time scheduling of periodic and sporadic tasks on identical multiprocessors. A number of recent papers have used the notions of fluid scheduling and deadline partitioning to guarantee optimality and improve performance. This article develops a unifying theory with the DP-Fair scheduling policy and examines how it overcomes problems faced by greedy scheduling algorithms. In addition, we present DP-Wrap, a simple DP-Fair scheduling algorithm which serves as a least common ancestor to other recent algorithms. The DP-Fair scheduling policy is extended to address the problem of scheduling sporadic task sets with arbitrary deadlines.     

Tuning of vertically-aligned carbon nanotube diameter and areal density through catalyst pre-treatment

By controlling the timing and duration of hydrogen exposure in a fixed thermal process, we tuned the diameters of carbon nanotubes (CNTs) within a vertically aligned film by a factor of 2, and tuned the areal densities by an order of magnitude. The CNT structure is correlated with the catalyst morphology, suggesting that while chemical reduction of the catalyst layer is required for growth, prolonged H2 exposure not only reduces the iron oxide and enables agglomeration of the Fe film, but also leads to catalyst coarsening. Control of this coarsening process allows tuning of CNT characteristics.     

A methodology for auto-calibrating urban building energy models using surrogate modeling techniques

Owners of large building portfolios such as university campuses have long relied on building energy models to predict potential energy savings from various efficiency upgrades. Traditional calibration procedures for individual building model are time intensive and require specially trained personnel, making their applications to campuses with hundreds of buildings prohibitive. Recently proposed automatic calibration techniques reduce the manual effort during calibration but require hundreds of thousands of energy simulations which increase their cost. To reduce the computational effort of these methods, this paper proposes a methodology that uses a data-driven approximation technique. Instead of brute-force simulations using detailed engineering models, this study employs statistical surrogate models with an optimization algorithm to estimate properties of unknown building parameters. Results demonstrate that when envelope information is available, this workflow yields sufficiently accurate estimates of hard to observe building characteristics, about 500 times faster than traditional approaches.     

Genetic Risk Scores for Maternal Lipid Levels and Their Association with Preterm Birth

Maternal lipid profiles are associated with risk for preterm birth (PTB), although the lipid component and effect size are inconsistent between studies. It is also unclear whether these associations are the result of excessive changes in lipid metabolism during pregnancy or genetic variability in genes controlling basal lipid metabolism. This study investigates the association between genetic risk scores (GRS) for four lipid components (high-density lipoprotein [HDL-C], low-density lipoprotein [LDL-C], triacylglycerols [TAG], and total cholesterol [TC]) with risk for PTB. Subjects included 954 pregnant women from California for whom second trimester serum samples were available, of which 479 gave birth preterm and 475 gave birth at term. We genotyped 96 single-nucleotide polymorphisms, which were selected from genome-wide association studies of lipid levels in adult populations. Lipid-specific GRS were constructed for HDL-C, LDL-C, TAG, and TC. The associations between GRS and PTB were analyzed using logistic regression. A higher HDL-C GRS was associated with increased risk for PTB overall and spontaneous PTB. Higher TAG and TC GRS were associated with decreased risk for PTB overall and spontaneous PTB. This study identifies counter-intuitive associations between lipid GRS and spontaneous PTB. Further replication studies are needed to confirm these findings, but they suggest that our current scientific understanding of the relationship between lipid metabolism, PTB, and genetics is incomplete.     

Microbiota Dysbiosis and Gut Barrier Dysfunction Associated with Non-Alcoholic Fatty Liver Disease Are Modulated by a Specific Metabolic Cofactors’ Combination

The gut is a selective barrier that not only allows the translocation of nutrients from food, but also microbe-derived metabolites to the systemic circulation that flows through the liver. Microbiota dysbiosis occurs when energy imbalances appear due to an unhealthy diet and a sedentary lifestyle. Dysbiosis has a critical impact on increasing intestinal permeability and epithelial barrier deterioration, contributing to bacterial and antigen translocation to the liver, triggering non-alcoholic fatty liver disease (NAFLD) progression. In this study, the potential therapeutic/beneficial effects of a combination of metabolic cofactors (a multi-ingredient; MI) (betaine, N-acetylcysteine, L-carnitine, and nicotinamide riboside) against NAFLD were evaluated. In addition, we investigated the effects of this metabolic cofactors’ combination as a modulator of other players of the gut-liver axis during the disease, including gut barrier dysfunction and microbiota dysbiosis. Diet-induced NAFLD mice were distributed into two groups, treated with the vehicle (NAFLD group) or with a combination of metabolic cofactors (NAFLD-MI group), and small intestines were harvested from all animals for histological, molecular, and omics analysis. The MI treatment ameliorated gut morphological changes, decreased gut barrier permeability, and reduced gene expression of some proinflammatory cytokines. Moreover, epithelial cell proliferation and the number of goblet cells were increased after MI supplementation. In addition, supplementation with the MI combination promoted changes in the intestinal microbiota composition and diversity, as well as modulating short-chain fatty acids (SCFAs) concentrations in feces. Taken together, this specific combination of metabolic cofactors can reverse gut barrier disruption and microbiota dysbiosis contributing to the amelioration of NAFLD progression by modulating key players of the gut-liver axis.     

Fingerprinting Biogenic Aldehydes through Pattern Recognition Analyses of Excitation–Emission Matrices

Biogenic carbonyls, especially aldehydes, have previously demonstrated their potential to serve as early diagnostic biomarkers for disease and injury that have not been fully realized owing, in part, to the lack of a rapid and simple point-of-care method for aldehyde identification. The ability to determine which carbonyl compound is elevated and not just the total aldehydic load may provide more disease- or injury-specific diagnostic information. Toward this end, a novel fluorophore is presented that is able to form a complex with biogenic carbonyls under catalyst-free conditions so as to give a fluorescent fingerprint of the resulting hydrazone. The successful identification of bound carbonyls was accomplished with a newly described algorithm that applied principal curvature analysis of excitation–emission matrices to reduce surface features to ellipse representations, followed by a pattern-matching routine. With this algorithm, carbonyls were identified over a range of concentrations, and mixture components were successfully parsed. Overall, the results presented lay the groundwork for novel implementations of chemometrics to low-cost, rapid, and simple-to-implement point-of-care diagnostics.