An Organoruthenium Anticancer Agent Shows Unexpected Target Selectivity For Plectin

Organometallic metal(arene) anticancer agents require ligand exchange for their anticancer activity and this is generally believed to confer low selectivity for potential cellular targets. However, using an integrated proteomics-based target-response profiling approach as a potent hypothesis-generating procedure, we found an unexpected target selectivity of a ruthenium(arene) pyridinecarbothioamide (plecstatin) for plectin, a scaffold protein and cytolinker, which was validated in a plectin knock-out model in vitro. Plectin targeting shows potential as a strategy to inhibit tumor invasiveness as shown in cultured tumor spheroids while oral administration of plecstatin-1 to mice reduces tumor growth more efficiently in the invasive B16 melanoma than in the CT26 colon tumor model.     

Pattern‐avoiding permutations and Brownian excursion part I: Shapes and fluctuations

Permutations that avoid given patterns are among the most classical objects in combinatorics and have strong connections to many fields of mathematics, computer science and biology. In this paper we study the scaling limits of a random permutation avoiding a pattern of length 3 and their relations to Brownian excursion. Exploring this connection to Brownian excursion allows us to strengthen the recent results of Madras and Pehlivan [25] and Miner and Pak [29] as well as to understand many of the interesting phenomena that had previously gone unexplained. © 2016 Wiley Periodicals, Inc. Random Struct. Alg., 50, 394–419, 2017     

ThrEEBoost: Thresholded Boosting for Variable Selection and Prediction via Estimating Equations

Most variable selection techniques for high-dimensional models are designed to be used in settings, where observations are independent and completely observed. At the same time, there is a rich literature on approaches to estimation of low-dimensional parameters in the presence of correlation, missingness, measurement error, selection bias, and other characteristics of real data. In this article, we present ThrEEBoost (Thresholded EEBoost), a general-purpose variable selection technique which can accommodate such problem characteristics by replacing the gradient of the loss by an estimating function. ThrEEBoost generalizes the previously proposed EEBoost algorithm (Wolfson 2011 Wolfson, J. (2011), “EEBoost: A General Method for Prediction and Variable Selection Based on Estimating Equations,” Journal of the American Statistical Association, 106, 296–305.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) by allowing the number of regression coefficients updated at each step to be controlled by a thresholding parameter. Different thresholding parameter values yield different variable selection paths, greatly diversifying the set of models that can be explored; the optimal degree of thresholding can be chosen by cross-validation. ThrEEBoost was evaluated using simulation studies to assess the effects of different threshold values on prediction error, sensitivity, specificity, and the number of iterations to identify minimum prediction error under both sparse and nonsparse true models with correlated continuous outcomes. We show that when the true model is sparse, ThrEEBoost achieves similar prediction error to EEBoost while requiring fewer iterations to locate the set of coefficients yielding the minimum error. When the true model is less sparse, ThrEEBoost has lower prediction error than EEBoost and also finds the point yielding the minimum error more quickly. The technique is illustrated by applying it to the problem of identifying predictors of weight change in a longitudinal nutrition study. Supplementary materials are available online.     

Programming With Models: Writing Statistical Algorithms for General Model Structures With NIMBLE

We describe NIMBLE, a system for programming statistical algorithms for general model structures within R. NIMBLE is designed to meet three challenges: flexible model specification, a language for programming algorithms that can use different models, and a balance between high-level programmability and execution efficiency. For model specification, NIMBLE extends the BUGS language and creates model objects, which can manipulate variables, calculate log probability values, generate simulations, and query the relationships among variables. For algorithm programming, NIMBLE provides functions that operate with model objects using two stages of evaluation. The first stage allows specialization of a function to a particular model and/or nodes, such as creating a Metropolis-Hastings sampler for a particular block of nodes. The second stage allows repeated execution of computations using the results of the first stage. To achieve efficient second-stage computation, NIMBLE compiles models and functions via C++, using the Eigen library for linear algebra, and provides the user with an interface to compiled objects. The NIMBLE language represents a compilable domain-specific language (DSL) embedded within R. This article provides an overview of the design and rationale for NIMBLE along with illustrative examples including importance sampling, Markov chain Monte Carlo (MCMC) and Monte Carlo expectation maximization (MCEM). Supplementary materials for this article are available online.     

A new coercivity condition applied to semipositone integral equations with nonpositive,unbounded nonlinearities and applications to nonlocal BVPs

We consider the perturbed Hammerstein integral equation

$$\begin{aligned} y(t)=\gamma _1(t)H_1(\varphi _1(y))+\gamma _2(t)H_2(\varphi _2(y))+\lambda \int _0^1G(t,s)f(s,y(s)) \mathrm{d}s \end{aligned}$$

and demonstrate the existence of at least one positive solution in the case where this problem is semipostione—i.e., f is allowed to be negative on its domain. As applications of this abstract result, we demonstrate existence of at least one positive solution to a variety of boundary value problems in the ordinary differential equations setting as well as the setting of elliptic partial differential equations on annuli. Finally, two novel aspects of this study are that, first, our results allow for f to be strictly negative on its entire domain, and second, it can actually be the case that \(\lim _{y\rightarrow +\infty }f(t,y)=-\infty \), uniformly for \(t\in [0,1]\). In addition, these results can hold even if \(H_1\) and \(H_2\) are piecewise linear on their domains.

     

Synergistic Porosity and Charge Effects in a Supramolecular Porphyrin Cage Promote Efficient Photocatalytic CO2 Reduction**

We present a supramolecular approach to catalyzing photochemical CO₂ reduction through second-sphere porosity and charge effects. An iron porphyrin box ( PB ) bearing 24 cationic groups, FePB-2(P) , was made via post-synthetic modification of an alkyne-functionalized supramolecular synthon. FePB-2(P) promotes the photochemical CO₂ reduction reaction (CO₂RR) with 97 % selectivity for CO product, achieving turnover numbers (TON) exceeding 7000 and initial turnover frequencies (TOF_max) reaching 1400 min⁻¹. The cooperativity between porosity and charge results in a 41-fold increase in activity relative to the parent Fe tetraphenylporphyrin ( FeTPP ) catalyst, which is far greater than analogs that augment catalysis through porosity ( FePB-3(N ), 4-fold increase) or charge (Fe p-tetramethylanilinium porphyrin ( Fe-p-TMA ), 6-fold increase) alone. This work establishes that synergistic pendants in the secondary coordination sphere can be leveraged as a design element to augment catalysis at primary active sites within confined spaces.     

Ethene-1,1-disulfonyl Difluoride (EDSF) for SuFEx Click Chemistry: Synthesis of SuFExable 1,1-Bissulfonylfluoride Substituted Cyclobutene Hubs

We present the synthesis of 1,1-bis(fluorosulfonyl)-2-(pyridin-1-ium-1-yl)ethan-1-ide, a bench-stable precursor to ethene-1,1-disulfonyl difluoride (EDSF). The novel SuFEx reagent, EDSF, is demonstrated in the preparation of 26 unique 1,1-bissulfonylfluoride substituted cyclobutenes via a cycloaddition reaction. The regioselective click cycloaddition reaction is rapid, straightforward, and highly efficient, enabling the generation of highly functionalized 4-membered ring (4MR) carbocycles. These carbocycles are valuable structural motifs found in numerous bioactive natural products and pharmaceutically relevant small molecules. Additionally, we showcase diversification of the novel cyclobutene cores through selective Cs₂CO₃-activated SuFEx click chemistry between a single S−F group and an aryl alcohol, yielding the corresponding sulfonate ester products with high efficiency. Finally, density functional theory calculations offer mechanistic insights about the reaction pathway.     

Synthesis,Biochemical Characterization,and Genetic Encoding of a 1,2,4-Triazole Amino Acid as an Acetyllysine Mimic for Bromodomains of the BET Family

Lysine acetylation is a charge-neutralizing post-translational modification of proteins bound by bromodomains (Brds). A 1,2,4-triazole amino acid (ApmTri) was established as acetyllysine (Kac) mimic recruiting Brds of the BET family in contrast to glutamine commonly used for simulating this modification. Optimization of triazole substituents and side chain spacing allowed BET Brd recruitment to ApmTri-containing peptides with affinities similar to native substrates. Crystal structures of ApmTri-containing peptides in complex with two BET Brds revealed the binding mode which mirrored that of Kac ligands. ApmTri was genetically encoded and recombinant ApmTri-containing proteins co-enriched BRD3(2) from cellular lysates. This interaction was blocked by BET inhibitor JQ1. With genetically encoded ApmTri, biochemistry is now provided with a stable Kac mimic reflecting charge neutralization and Brd recruitment, allowing new investigations into BET proteins in vitro and in vivo.