chokh/rx3 specifies the retinal pigment epithelium fate independently of eye morphogenesis

Despite the importance of the retinal pigment epithelium (RPE) for vision, the molecular processes involved in its specification are poorly understood. We identified two new mutant alleles for the zebrafish gene chokh (chk), which display a reduction or absence of the RPE. Unexpectedly, the neural retina (NR) in chk is specified and laminated, indicating that the regulatory network leading to NR development is largely independent of the RPE. Genetic mapping and molecular characterization revealed that chk encodes Rx3. Expression analyses show that otx2 and mitfb are not expressed in the prospective RPE of chk, indicating that the retinal homeobox gene rx3 acts upstream of the molecular network controlling RPE specification. Cellular transplantations demonstrate that rx3 function is autonomously required to specify the prospective RPE. Though rx2 is also absent in chk, neither rx2 nor rx1 is required for RPE development. Thus, our data provide the first indication that, in addition to controlling optic lobe evagination and proliferation, chk/rx3 also determines cellular fate.     

Evolution and inheritance of early embryonic patterning in Drosophila simulans and D. sechellia

Pattern formation in Drosophila is a widely studied example of a robust developmental system. Such robust systems pose a challenge to adaptive evolution, as they mask variation that selection may otherwise act upon. Yet we find variation in the localization of expression domains (henceforth "stripe allometry") in the pattern formation pathway. Specifically, we characterize differences in the gap genes giant and Kruppel, and the pair-rule gene even-skipped, which differ between the sibling species Drosophila simulans and D. sechellia. In a double-backcross experiment, stripe allometry is consistent with maternal inheritance of stripe positioning and multiple genetic factors, with a distinct genetic basis from embryo length. Embryos produced by F1 and F2 backcross mothers exhibit novel spatial patterns of gene expression relative to the parental species, with no measurable increase in positional variance among individuals. Buffering of novel spatial patterns in the backcross genotypes suggests that robustness need not be disrupted in order for the trait to evolve, and perhaps the system is incapable of evolving to prevent the expression of all genetic variation. This limitation, and the ability of natural selection to act on minute genetic differences that are within the "margin of error" for the buffering mechanism, indicates that developmentally buffered traits can evolve without disruption of robustness.     

Boolean network-based analysis of the apoptosis network: Irreversible apoptosis and stable surviving

To understand the design principles of the molecular interaction network associated with the irreversibility of cell apoptosis and the stability of cell surviving, we constructed a Boolean network integrating both the intrinsic and extrinsic pro-apoptotic pathways with pro-survival signal transduction pathways. We performed statistical analyses of the dependences of cell fate on initial states and on input signals. The analyses reproduced the well-known pro- and anti-apoptotic effects of key external signals and network components. We found that the external GF signal by itself did not change the apoptotic ratio from randomly chosen initial states when there is no external TNF signal, but can significantly offset apoptosis induced by the TNF signal. While a complete model produces the expected irreversibility of the apoptosis process, alternative models missing one or more of four selected inter-component connections indicate that the feedback loops directly involving the caspase 3 are essential for maintaining irreversibility of apoptosis. The feedback loops involving P53 showed compensating effects when those involving caspase 3 have been removed. The GF signal significantly increases the stability of the surviving states of the network. The apoptosis network seems to use different modules by design to control the irreversibility of the apoptosis process and the stability of the surviving states. Such a design may accommodate the needed plasticity for the network to adapt to different cellular environments: depending on the strength of external pro-surviving signals, apoptosis can be induced either easily or difficultly by pro-apoptotic signal of varying strengths, but proceed with invariable irreversibility.     

MicroRNAs: Oncogenes,tumor suppressors or master regulators of cancer heterogeneity?

The realization that microRNAs are intimately linked to cancer pathogenesis has spawned an explosion of research activity in recent years. Their presence is not merely predictive of tumor origin and behavior, they are causally linked to the emergence and development of cancer by acting as oncogenes or tumor suppressors. The understanding of the functional consequences of altered microRNA expression in cancer is progressing rapidly, even though the prediction of microRNA targets is still a hit and miss process. MicroRNAs may not act primarily by strongly reducing the expression of a few prominent cancer-regulatory genes, but by influencing the properties of the network of which these regulators are a central part. By coordinately regulating many genes, microRNAs are exquisitely suited to act as stabilizers of networks and to prevent extreme variations in phenotype due to intrinsic and extrinsic disturbances. Many advanced tumors show defects in microRNA expression and processing, which could increase phenotypic variability within tumors. This allows small subsets of cells with altered characteristics to emerge, which can have grave consequences as typically a small fraction of tumor cells is responsible for metastasis and treatment resistance, and ultimately treatment failure. Investigating microRNAs from the perspective of master regulators of network stability in cancer calls for new experimental approaches and may help to understand causes of cancer heterogeneity and disease progression.     

A powerful and robust test statistic for randomization inference in group-randomized trials with matched pairs of groups

For group-randomized trials, randomization inference based on rank statistics provides robust, exact inference against nonnormal distributions. However, in a matched-pair design, the currently available rank-based statistics lose significant power compared to normal linear mixed model (LMM) test statistics when the LMM is true. In this article, we investigate and develop an optimal test statistic over all statistics in the form of the weighted sum of signed Mann-Whitney-Wilcoxon statistics under certain assumptions. This test is almost as powerful as the LMM even when the LMM is true, but it is much more powerful for heavy tailed distributions. A simulation study is conducted to examine the power.     

Robust secret image sharing scheme resistance to maliciously tampered shadows by AMBTC and quantization

For (k, n)-threshold secret image sharing (SIS) scheme, only k or more than k complete parts can recover the secret information, and the correct image cannot be obtained if the count of shadow images is not enough or the shadow images are damaged. The existing schemes are weak in resisting large-area shadow image tampering. In this paper, we propose a robust secret image sharing scheme resisting to maliciously tampered shadow images by Absolute Moment Block Truncation Coding (AMBTC) and quantization (RSIS-AQ). The secret image is successively compressed in two ways: AMBTC and quantization. The sharing shadow images contain the sharing results of both compressed image from different parts, so that even the shadow images are faced with large-scale area of malicious tampering, the secret image can be recovered with acceptable visual quality. Compared with related works, our scheme can resist larger area of tampering and yield better recovered image visual quality. The experimental results prove the effectiveness of our scheme.     

Robustness of prevalence estimates derived from misclassified data from administrative databases

Because primary data collection can be expensive, researchers are increasingly using information collected in medical administrative databases for scientific purposes. This information, however, is typically collected for reasons other than research, and many such databases have been shown to contain substantial proportions of misclassification errors. For example, many administrative databases contain fields for patient diagnostic codes, but these are often missing or inaccurate, in part because physician reimbursement schemes depend on medical acts performed rather than any diagnosis. Errors in ascertaining which individuals have a given disease bias not only prevalence estimates, but also estimates of associations between the disease and other variables, such as medication use. We attempt to estimate the prevalence of osteoarthritis (OA) among elderly Quebeckers using a government administrative database. We compare a naive estimate relying solely on the physician diagnoses of OA listed in the database to estimates from several different Bayesian latent class models which adjust for misclassified physician diagnostic codes via use of other available diagnostic clues. We find that the prevalence estimates vary widely, depending on the model used and assumptions made. We conclude that any inferences from these databases need to be interpreted with great caution, until further work estimating the reliability of database items is carried out.     

Utilities of the P‐value Distribution Associated with Effect Size in Clinical Trials

The P‐value, which is widely used for assessing statistical evidence in randomized comparative clinical trials, is a function of the observed effect size of the experimental treatment relative to the control treatment. The relationship of the P‐value with the observed effect size at study completion and the effect size anticipated at the design stage has potential usefulness in providing guidance for planning and interpretation of a clinical trial. The post‐trial power associated with a statistically significant P‐value from a completed study is also a random variable and its use may assist in planning a follow‐up trial to confirm the statistically significant findings in an initial study. A measure of robustness is explored to quantify the degree of sensitivity of the observed P‐value to potential bias that may be contained in the observed effect size.