Social welfare and profit maximization from revealed preferences

Consider the seller's problem of finding optimal prices for her $n$ (divisible) goods when faced with a set of $m$ consumers, given that she can only observe their purchased bundles at posted prices, i.e., revealed preferences. We study both social welfare and profit maximization with revealed preferences. Although social welfare maximization is a seemingly non-convex optimization problem in prices, we show that (i) it can be reduced to a dual convex optimization problem in prices, and (ii) the revealed preferences can be interpreted as supergradients of the concave conjugate of valuation, with which subgradients of the dual function can be computed. We thereby obtain a simple subgradient-based algorithm for strongly concave valuations and convex cost, with query complexity $O(m^2/\epsilon^2)$, where $\epsilon$ is the additive difference between the social welfare induced by our algorithm and the optimum social welfare. We also study social welfare maximization under the online setting, specifically the random permutation model, where consumers arrive one-by-one in a random order. For the case where consumer valuations can be arbitrary continuous functions, we propose a price posting mechanism that achieves an expected social welfare up to an additive factor of $O(\sqrt{mn})$ from the maximum social welfare. Finally, for profit maximization (which may be non-convex in simple cases), we give nearly matching upper and lower bounds on the query complexity for separable valuations and cost (i.e., each good can be treated independently)

Reproducibility of preclinical animal research improves with heterogeneity of study samples

Single-laboratory studies conducted under highly standardized conditions are the gold standard in preclinical animal research. Using simulations based on 440 preclinical studies across 13 different interventions in animal models of stroke, myocardial infarction, and breast cancer, we compared the accuracy of effect size estimates between single-laboratory and multi-laboratory study designs. Single-laboratory studies generally failed to predict effect size accurately, and larger sample sizes rendered effect size estimates even less accurate. By contrast, multi-laboratory designs including as few as 2 to 4 laboratories increased coverage probability by up to 42 percentage points without a need for larger sample sizes. These findings demonstrate that within-study standardization is a major cause of poor reproducibility. More representative study samples are required to improve the external validity and reproducibility of preclinical animal research and to prevent wasting animals and resources for inconclusive research

Size-Segregated Particle Number Concentrations and Respiratory Emergency Room Visits in Beijing, China

BACKGROUND: The link between concentrations of particulate matter (PM) and respiratory morbidity has been investigated in numerous studies. OBJECTIVES: The aim of this study was to analyze the role of different particle size fractions with respect to respiratory health in Beijing, China. METHODS: Data on particle size distributions from 3 nm to 1 mu m; PM10 (PM <= 10 mu m), nitrogen dioxide (NO2), and sulfur dioxide concentrations; and meteorologic variables were collected daily from March 2004 to December 2006. Concurrently, daily counts of emergency room visits (ERV) for respiratory diseases were obtained from the Peking University Third Hospital. We estimated pollutant effects in single-and two-pollutant generalized additive models, controlling for meteorologic and other time-varying covariates. Time-delayed associations were estimated using polynomial distributed lag, cumulative effects, and single lag models. RESULTS: Associations of respiratory ERV with NO2 concentrations and 100-1,000 nm-particle number or surface area concentrations were of similar magnitude-that is, approximately 5% increase in respiratory ERV with an interquartile range increase in air pollution concentration. In general, particles <50 nm were not positively associated with ERV, whereas particles 50-100 nm were adversely associated with respiratory ERV, both being fractions of ultrafine particles. Effect estimates from two-pollutant models were most consistent for NO2. CONCLUSIONS: Present levels of air pollution in Beijing were adversely associated with respiratory ERV. NO2 concentrations seemed to be a better surrogate for evaluating overall respiratory health effects of ambient air pollution than PM10 or particle number concentrations in Beijing.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000289065900032&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Environmental SciencesPublic, Environmental & Occupational HealthToxicologySCI(E)37ARTICLE4508-51311

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis

A Single-Step Sequencing Method for the Identification of Mycobacterium tuberculosis Complex Species

The Mycobacterium tuberculosis complex (MTC) comprises several closely related species responsible for strictly human and zoonotic tuberculosis. Some of the species are restricted to Africa and were responsible for the high prevalence of tuberculosis. However, their identification at species level is difficult and expansive. Accurate species identification of all members is warranted in order to distinguish between strict human and zoonotic tuberculosis, to trace source exposure during epidemiological studies, and for the appropriate treatment of patients. In this paper, the Exact Tandem Repeat D (ETR-D) intergenic region was investigated in order to distinguish MTC species. The ETR-D sequencing unambiguously identified MTC species type strain except M. pinnipedii and M. microti, and the results agreed with phenotypic and molecular identification. This finding offers a new tool for the rapid and accurate identification of MTC species in a single sequencing reaction, replacing the current time-consuming polyphasic approach. Its use could assist public health interventions and aid in the control of zoonotic transmission in African countries, and could be of particular interest with the current emergence of multidrug-resistant and extended-resistance isolates