The Gift of Future Time: Islamic Welfare and Entrepreneurship in 21st century Indonesia

The attainment of religiously informed and socially responsible wealth is a desire widespread in the metropolises of Java, Indonesia, especially amongst the pious middle classes. This article aims at an understanding of the emergence and effects of an early 21st century desire for pious entrepreneurial success, by focusing on the practices people consistently and regularly undertake in order to actualise this. It claims that the religiously informed desire for entrepreneurial success is permeated by a mode of temporality that privileges the future at the expense of the past and the present. This temporal orientation has important consequences for subject-making, as it forces the subjectivities created to take a distinctively asymptotic form, resulting in the production of self-differing subjects; that is, subjects in which past, present and future actualisations lack coincidence and complete convergence

Empirical Power and Sample Size Calculations for Cluster-Randomized and Cluster-Randomized Crossover Studies

In recent years, the number of studies using a cluster-randomized design has grown dramatically. In addition, the cluster-randomized crossover design has been touted as a methodological advance that can increase efficiency of cluster-randomized studies in certain situations. While the cluster-randomized crossover trial has become a popular tool, standards of design, analysis, reporting and implementation have not been established for this emergent design. We address one particular aspect of cluster-randomized and cluster-randomized crossover trial design: estimating statistical power. We present a general framework for estimating power via simulation in cluster-randomized studies with or without one or more crossover periods. We have implemented this framework in the clusterPower software package for R, freely available online from the Comprehensive R Archive Network. Our simulation framework is easy to implement and users may customize the methods used for data analysis. We give four examples of using the software in practice. The clusterPower package could play an important role in the design of future cluster-randomized and cluster-randomized crossover studies. This work is the first to establish a universal method for calculating power for both cluster-randomized and cluster-randomized clinical trials. More research is needed to develop standardized and recommended methodology for cluster-randomized crossover studies

An appraisal of how the vitamin A-redox hypothesis can maintain honesty of carotenoid-dependent signals

The vitamin A-redox hypothesis provides an explanation for honest signaling of phenotypic quality by carotenoid-dependent traits. A key aspect of the vitamin A-redox hypothesis, applicable to both yellow and red coloration, is the hypothesized negative feedback of tightly regulated Vitamin A plasma levels on the enzyme responsible for sequestering both Vitamin A and carotenoids from the gut. We performed a meta-analysis and find that vitamin A levels are positively related to carotenoid plasma levels (r = 0.50, P = 0.0002). On the basis of this finding and further theoretical considerations, we propose that the vitamin A-redox hypothesis is unlikely to explain carotenoid-dependent honest signaling

Atypical CTSK Transcripts and ARNT Transcription Read-Through Into CTSK

The aryl hydrocarbon receptor nuclear translocator (ARNT) and cathepsin K (CTSK) genes lie in a tandem head-to-tail arrangement on human chromosome 1. The two genes are in extremely close proximity; the usual CTSK transcription start site is less than 1.4 kb downstream of the end of the longest reported ARNT transcript. By generating an RT-PCR product that overlaps both the 3′ end of ARNT and the 5′ end of CTSK, we show that ARNT transcripts may extend through the ARNT–CTSK intergenic region and progress into the CTSK gene. Furthermore, by using quantitative RT-PCR from several tissues to detect the ARNT expression signature in CTSK introns, we show that ARNT transcripts can read through into CTSK as far as CTSK intron 3, extending approximately 3.7 kb downstream of the end of the longest previously described ARNT mRNA. Given that ARNT and CTSK are expressed in an overlapping range of tissues, ARNT read-through may have a negative impact on CTSK transcript levels by interfering with CTSK expression. We also present evidence for novel CTSK transcripts following sequence analysis of CTSK-derived ESTs and RT-PCR products. These transcripts show alternate 5′ splicing and or 5′ extension and are sometimes initiated from a cryptic alternative promoter which is upstream of the known CTSK promoter and possibly in the 3′ UTR of ARNT

Evaluation of 16S rRNA gene PCR sensitivity and specificity for diagnosis of prosthetic joint infection: a prospective multicenter cross-sectional study

There is no standard method for the diagnosis of prosthetic joint infection (PJI). The contribution of 16S rRNA gene PCR sequencing on a routine basis remains to be defined. We performed a prospective multicenter study to assess the contributions of 16S rRNA gene assays in PJI diagnosis. Over a 2-year period, all patients suspected to have PJIs and a few uninfected patients undergoing primary arthroplasty (control group) were included. Five perioperative samples per patient were collected for culture and 16S rRNA gene PCR sequencing and one for histological examination. Three multicenter quality control assays were performed with both DNA extracts and crushed samples. The diagnosis of PJI was based on clinical, bacteriological, and histological criteria, according to Infectious Diseases Society of America guidelines. A molecular diagnosis was modeled on the bacteriological criterion (≥ 1 positive sample for strict pathogens and ≥ 2 for commensal skin flora). Molecular data were analyzed according to the diagnosis of PJI. Between December 2010 and March 2012, 264 suspected cases of PJI and 35 control cases were included. PJI was confirmed in 215/264 suspected cases, 192 (89%) with a bacteriological criterion. The PJIs were monomicrobial (163 cases [85%]; staphylococci, n = 108; streptococci, n = 22; Gram-negative bacilli, n = 16; anaerobes, n = 13; others, n = 4) or polymicrobial (29 cases [15%]). The molecular diagnosis was positive in 151/215 confirmed cases of PJI (143 cases with bacteriological PJI documentation and 8 treated cases without bacteriological documentation) and in 2/49 cases without confirmed PJI (sensitivity, 73.3%; specificity, 95.5%). The 16S rRNA gene PCR assay showed a lack of sensitivity in the diagnosis of PJI on a multicenter routine basis

Planning a cluster randomized trial with unequal cluster sizes: practical issues involving continuous outcomes

BACKGROUND: Cluster randomization design is increasingly used for the evaluation of health-care, screeening or educational interventions. At the planning stage, sample size calculations usually consider an average cluster size without taking into account any potential imbalance in cluster size. However, there may exist high discrepancies in cluster sizes. METHODS: We performed simulations to study the impact of an imbalance in cluster size on power. We determined by simulations to which extent four methods proposed to adapt the sample size calculations to a pre-specified imbalance in cluster size could lead to adequately powered trials. RESULTS: We showed that an imbalance in cluster size can be of high influence on the power in the case of severe imbalance, particularly if the number of clusters is low and/or the intraclass correlation coefficient is high. In the case of a severe imbalance, our simulations confirmed that the minimum variance weights correction of the variation inflaction factor (VIF) used in the sample size calculations has the best properties. CONCLUSION: Publication of cluster sizes is important to assess the real power of the trial which was conducted and to help designing future trials. We derived an adaptation of the VIF from the minimum variance weights correction to be used in case the imbalance can be a priori formulated such as "a proportion (γ) of clusters actually recruit a proportion (τ) of subjects to be included (γ ≤ τ)"

Preventing Bias in Cluster Randomised Trials

Bruno Giraudeau and Philippe Ravaud discuss the difficulties in preventing selection bias and applying intention-to-treat analysis in cluster randomized trials, and propose some solutions