Confidence-ranked reconstruction of census microdata from published statistics.

A reconstruction attack on a private dataset D takes as input some publicly accessible information about the dataset and produces a list of candidate elements of D. We introduce a class of data reconstruction attacks based on randomized methods for nonconvex optimization. We empirically demonstrate that our attacks can not only reconstruct full rows of D from aggregate query statistics Q(D)∈ℝm but can do so in a way that reliably ranks reconstructed rows by their odds of appearing in the private data, providing a signature that could be used for prioritizing reconstructed rows for further actions such as identity theft or hate crime. We also design a sequence of baselines for evaluating reconstruction attacks. Our attacks significantly outperform those that are based only on access to a public distribution or population from which the private dataset D was sampled, demonstrating that they are exploiting information in the aggregate statistics Q(D) and not simply the overall structure of the distribution. In other words, the queries Q(D) are permitting reconstruction of elements of this dataset, not the distribution from which D was drawn. These findings are established both on 2010 US decennial Census data and queries and Census-derived American Community Survey datasets. Taken together, our methods and experiments illustrate the risks in releasing numerically precise aggregate statistics of a large dataset and provide further motivation for the careful application of provably private techniques such as differential privacy.

A Unified Strategy for the Asymmetric Synthesis of Highly Substituted 1,2-Amino Alcohols Leading to Highly Substituted Bisoxazoline Ligands.

A general procedure for the asymmetric synthesis of highly substituted 1,2-amino alcohols in high yield and diastereoselectivity is described that uses organometallic additions of a wide range of nucleophiles to tert-butylsulfinimines as the key step. The addition of organolithium reagents to these imines follows a modified Davis model. The diastereoselectivity for this reaction depends significantly on both the nucleophile and electrophile. These highly substituted 1,2-amino alcohols are used to synthesize stereochemically diverse and structurally novel, polysubstituted 2,2'-methylene(bisoxazoline) ligands in high yields.

Enantioselective, Lewis Base-Catalyzed, Intermolecular Sulfenoamination of Alkenes.

A method for the catalytic, enantioselective, intermolecular, 1,2-sulfenoamination of alkenes is described. Functionalization is achieved through the intermediacy of an enantioenriched, configurationally stable thiiranium ion generated by Lewis base activation of a readily available sulfur electrophile. A diverse set of anilines and benzylamines react with different styrenes to afford products in good yield and stereoselectivity. Downstream manipulation of the products is facilitated by deprotonation of the amines to enable carbon-sulfur bond cleavage.

Private algorithms for the protected in social network search.

Motivated by tensions between data privacy for individual citizens and societal priorities such as counterterrorism and the containment of infectious disease, we introduce a computational model that distinguishes between parties for whom privacy is explicitly protected, and those for whom it is not (the targeted subpopulation). The goal is the development of algorithms that can effectively identify and take action upon members of the targeted subpopulation in a way that minimally compromises the privacy of the protected, while simultaneously limiting the expense of distinguishing members of the two groups via costly mechanisms such as surveillance, background checks, or medical testing. Within this framework, we provide provably privacy-preserving algorithms for targeted search in social networks. These algorithms are natural variants of common graph search methods, and ensure privacy for the protected by the careful injection of noise in the prioritization of potential targets. We validate the utility of our algorithms with extensive computational experiments on two large-scale social network datasets.

PREVALENCE OF HEALED LONG-BONE FRACTURES IN WILD CARNIVORES FROM THE NORTHEASTERN UNITED STATES.

Museum specimens representing 12 species of terrestrial carnivores from the northeastern United States were inspected for evidence of healed long-bone fractures. Of 413 individuals, 18 (4.4%) exhibited healed fractures. Thirteen (72.2%) occurred in hind limbs; five (27.8%) occurred in forelimbs. Mustelids had the highest prevalence of healed long-bone fractures (38.8%) of all observed fractures. Within family, 5.6% of Canidae and 2.8% of Mustelidae exhibited healed fractures. Bobcats had the highest taxon prevalence of fractures, 18%. Observational data to assess use of and behavior near roads could provide insight to causes of fracture. Capture in combination with noninvasive examination techniques could be employed to determine incidence of healed fractures in wild populations. Individuals with healed fractures could then be tracked via radio telemetry to determine if these animals behave differently than uninjured conspecifics, and assess long-term survivability and fitness.

A Reaction-Based Fluorescent Probe for Imaging of Formaldehyde in Living Cells.

Formaldehyde (FA), in the 0.2-0.4 mM range, is produced and maintained endogenously via enzymatic pathways. At these levels, FA can promote cell proliferation as well as mediate memory formation. Once elevated, FA stress is known to induce cognitive impairments, memory loss, and neurodegeneration owing to its potent DNA and protein cross-linking mechanisms. Optical imaging is a powerful noninvasive approach used to study FA in living systems; however, biocompatible chemical probes for FA are currently lacking. Herein, we report the design, synthesis, and biological evaluation of Formaldehyde Probe 1 (FP1), a new fluorescent indicator based on the 2-aza-Cope sigmatropic rearrangement. The remarkable sensitivity, selectivity, and photostability of FP1 has enabled us to visualize FA in live HEK293TN and Neuroscreen-1 cells. We envision that FP1 will find widespread applications in the study of FA associated with normal and pathological processes.

Inhibition of myeloperoxidase: evaluation of 2H-indazoles and 1H-indazolones.

Myeloperoxidase (MPO) produces hypohalous acids as a key component of the innate immune response; however, release of these acids extracellularly results in inflammatory cell and tissue damage. The two-step, one-pot Davis-Beirut reaction was used to synthesize a library of 2H-indazoles and 1H-indazolones as putative inhibitors of MPO. A structure-activity relationship study was undertaken wherein compounds were evaluated utilizing taurine-chloramine and MPO-mediated H2O2 consumption assays. Docking studies as well as toxicophore and Lipinski analyses were performed. Fourteen compounds were found to be potent inhibitors with IC50 values <1µM, suggesting these compounds could be considered as potential modulators of pro-oxidative tissue injury pertubated by the inflammatory MPO/H2O2/HOCl/HOBr system.

Triazolbenzo[d]thiazoles: efficient synthesis and biological evaluation as neuroprotective agents.

A number of (1H-1,2,3-triazol-1-yl)benzo[d]thiazoles were synthesized utilizing a versatile Cu-catalyzed azide-alkyne click reaction (CuAAC) on tautomeric benzo[4,5]thiazolo[3,2-d]tetrazole (1) and 2-azidobenzo[d]thiazole (2) starting materials. Moreover, one of the resulting products of this investigation, triazolbenzo[d]thiazole 22, was found to possess significant neuroprotective activity in human neuroblastoma (SH-SY5Y) cells.

STATISTICS. The reusable holdout: Preserving validity in adaptive data analysis.

Misapplication of statistical data analysis is a common cause of spurious discoveries in scientific research. Existing approaches to ensuring the validity of inferences drawn from data assume a fixed procedure to be performed, selected before the data are examined. In common practice, however, data analysis is an intrinsically adaptive process, with new analyses generated on the basis of data exploration, as well as the results of previous analyses on the same data. We demonstrate a new approach for addressing the challenges of adaptivity based on insights from privacy-preserving data analysis. As an application, we show how to safely reuse a holdout data set many times to validate the results of adaptively chosen analyses.