Encore is a member of a novel family of proteins and affects multiple processes in Drosophila oogenesis.

Mutations in the encore (enc) gene of Drosophila melanogaster cause one extra round of mitosis in the germline, resulting in the formation of egg chambers with extra nurse cells. In addition, enc mutations affect the accumulation of Gurken protein within the oocyte, leading to the production of ventralized eggs. Here we show that enc mutants also exhibit abnormalities in karyosome morphology, similar to other ventralizing mutants such as okra and spindle B. Unlike these mutants, however, the defects in Gurken accumulation and karyosome formation do not result from activation of a meiotic checkpoint. Furthermore, we demonstrate that the requirement for enc in these processes is temporally distinct from its role in germline mitosis. Cloning of the enc locus and generation of anti-Enc antibodies reveal that enc encodes a large novel protein that accumulates within the oocyte cytoplasm and colocalizes with grk mRNA. We argue that the enc mutant phenotypes reflect a role for Enc in the regulation of several RNA targets.

Post-transcriptional regulation of gurken by encore is required for axis determination in Drosophila.

Establishment of anterior-posterior and dorsal-ventral polarity within the Drosophila egg chamber requires signaling between the germline and the somatic cells of the ovary. The gene gurken (grk) encodes a TGFalpha-like protein that is localized within the developing oocyte and is thought to locally activate torpedo/Egfr (top/Egfr), the Drosophila homolog of the EGF receptor, which is expressed throughout the follicular epithelium surrounding the oocyte. grk-Egfr signaling is required early in oogenesis for specification of posterior follicle cell fate and later in oogenesis for dorsal follicle cell fate determination, thus establishing the axes of the egg shell and embryo. Previous studies have shown that these patterning processes are highly sensitive to changes in the levels and localization of grk mRNA. Here we show that post-transcriptional regulation of Grk protein levels is required for correct pattern formation. encore (enc), a gene that functions in the regulation of germline mitosis and maintenance of oocyte identity, is also required for the accumulation of Grk protein during oogenesis. We present evidence that enc regulates Grk post-transcriptionally to ensure adequate levels of signaling for establishment of the anterior-posterior and dorsal-ventral axes.

Encore, a gene required for the regulation of germ line mitosis and oocyte differentiation during Drosophila oogenesis.

During Drosophila oogenesis, a stem cell daughter undergoes precisely four rounds of mitosis to generate a cyst of 16 cells interconnected by cytoplasmic bridges. One of the cells becomes the oocyte while the remaining 15 cells differentiate as nurse cells. We hve identified a gene, encore, that is involved both in regulating the number of germline mitoses and in the process of oocyte differentation. Mutations in encore result in exactly one extra round of mitosis in the germline. Genetic and molecular studies indicate that this mitotic defect may be mediated through the gene bag-of-marbles. The isolation and characterization of multiple alleles of encore revealed that they were all temperature sensitive for this phenotype. Mutations in encore also affect the process of oocyte differentiation. Egg chambers are produced in which the oocyte nucleus has undergone endoreplication often resulting in the formation of 16 nurse cells. We argue that these two phenotypes produced by mutations in encore represent two independent requirements for encore during oogenesis.

A proposal for improving the role of exposure modeling in risk assessment.

This paper explores the adequacy of using currently available exposure assessment models for indoor air inhalation exposures in the context of the uncertainty that exists in both the dose-response assessment and the exposure assessment. A tiered system is proposed for implementing exposure assessments. Each tier involves additional research, but also would lead to reductions in uncertainty. The authors discuss a possible comprehensive research program that will permit the building of well-validated models for indoor air inhalation exposures among classes of chemicals, building types, and exposure scenarios. The authors believe that until such a research program is undertaken, modeling of exposures (and therefore risks) using the current, unvalidated modeling approaches provides little more than worst-case estimates that are useful primarily for making screening decisions about risks.

Effects of selected process parameters on emission rates of volatile organic chemicals from carpet.

There has been increased interest over the last several years in issues related to indoor air quality. Although the factors affecting indoor air quality are recognized to be very broad, ranging from building design, operation, and ventilation to biological contamination, recent emphasis has been placed on chemical contaminants, particularly volatile organic chemicals (VOCs). New floor covering systems, including new carpets, have been identified as a potential, short-term source of VOCs in the indoor air of new or renovated buildings. This report describes an exploratory study designed to examine several manufacturing variables and their effects on VOC emission rates from new carpets. It was based on a statistical experimental design and was conducted at a single carpet mill on a full-scale production line. The outcome variable, VOC emission rate, was examined relative to selected independent variables: latex type, latex amount, makeup air into the drying oven, residence time in the drying oven, and their interactions. Significant variables were identified for a number of emission rate models. The study results suggest that there are no simple answers for easily reducing VOC emission rates, but several conclusions could be inferred from the study as to future directions to pursue.

A rationale and framework for establishing the quality of human exposure assessments.

Exposure assessments, performed as input to an evaluation of potential human health risk, are an element of risk assessment. Risk assessment results feed governmental and corporate risk management decisions, which seek to balance the estimated potential human health risks with other factors. Risk managers presume that the risk information provided to them is scientifically valid and accurate. Government agencies have begun to apply a system known as good laboratory practices (GLP) to ensure adequate data quality on animal studies, which are often the first step in the health-effects evaluation of risk assessment. This paper explores a rationale and framework for establishing the quality of human exposure assessments and proposes a set of good exposure assessment practices (GEAP). The components of the proposed GEAP include the writing of a study protocol before conducting the study, consideration of available resources, specification of an exposure model, a study design (including sampling and analytical methods and data analysis), quality assurance, archiving, communications, and a statement of overall uncertainty in exposure estimates. The GEAP concept is offered as a starting point for developing a consensus among the community of exposure assessors regarding a minimum standard for good practices. If a consensus on GEAP can be reached and applied, exposure assessments would have improved scientific bases, interpretability, and utility.

Conservatism in maximally exposed individual (MEI) predictive exposure assessments: a first-cut analysis.

The United States Environmental Protection Agency (USEPA) sometimes applies exposure assessment models based upon the concept of a hypothetical "maximally exposed individual" (MEI) as a means of dealing with uncertainty. This concept has been described in the benzene NESHAPS rule, the proposed RCRA Corrective Action Rule, and the Clean Air Act reauthorization debate. This paper describes a first-cut analysis of the level of conservatism of the current MEI approach relative to a central estimate of exposure of the most exposed population around a source. The inherent level of conservatism of the current MEI model, which appears to be at least one order of magnitude, is usually left unstated. The significance of this conservatism is described along with some proposals for future research.

Homeobox containing genes in the nematode Caenorhabditis elegans.

We designed a unique 36-mer oligonucleotide probe, based on the most highly conserved amino acid sequences of Antennapedia-like homeodomains and the codon bias of Caenorhabditis elegans. This probe was then used to isolate four classes of genes from a C. elegans genomic library. Sequencing reveals that we have isolated three new homeobox genes, designated ceh-1, ceh-9 and ceh-10. The fourth homeobox gene, ceh-11, has recently been described by Schaller et al (Nucleic Acids Res. 18, 2033-2036). The amino acid sequence of ceh-1 is 87% similar to the honeybee H40 homeodomain, 85% similar to the Drosophila NK-1 homeodomain and 82% similar to the chicken CHox3 homeodomain. The sequence ceh-10 appears to be a member of the paired class of homeodomains. The other two sequences, ceh-9 and ceh-11, remain unclassified. Three of the four sequences have at least one intron within the homeobox region. Transcripts of ceh-10 and ceh-11 are present in embryonic RNA but are greatly diminished in later developmental stages. Three of the four new genes have been placed on the C. elegans genomic map.

Selecting experimental data for use in quantitative risk assessment: an expert-judgement approach.

In many cancer risk assessments the experimental data used in statistical modeling are selected by applying generic guidelines. The guidelines exclude use of some types of experimental data and often appear arbitrary since rules rather than scientific judgments guide selection of data. This paper implements an alternative approach in which data are selected based on the judgments of practicing scientists. Eight such scientists were identified through an explicit selection procedure to help select data for use in a dose-response assessment of formaldehyde. Judgements about appropriate data sets were then elicited in personal interviews using a formal interview protocol. Appropriate data sets were fit to the multistage model and used as the basis for low-dose extrapolation. Low-dose risk estimates are shown to be sensitive to the selection of data, especially the treatment of benign tumors. The recommendations of the experts also differ in some respects from the choices made in previously published risk assessments. This suggests that scientific judgement may be an appropriate method to augment guidelines when a broad range of data is available. The paper argues that the expert judgment approach has some advantages that are worth considering.

Expert scientific judgment and cancer risk assessment: a pilot study of pharmacokinetic data.

When high-dose tumor data are extrapolated to low doses, it is typically assumed that the dose of a carcinogen delivered to target cells is proportional to the dose administered to test animals, even at exposure levels below the experimental range. Since pharmacokinetic data are becoming available that in some cases question the validity of this assumption, risk assessors must decide whether to maintain the standard assumption. A pilot study of formaldehyde is reported that was undertaken to demonstrate how expert scientific judgment can help guide a controversial risk assessment where pharmacokinetic data are considered inconclusive. Eight experts on pharmacokinetic data were selected by a formal procedure, and each was interviewed personally using a structured interview protocol. The results suggest that expert scientific opinion is polarized in this case, a situation that risk assessors can respond to with a range of risk characterizations considered biologically plausible by the experts. Convergence of expert opinion is likely in this case of several specific research strategies ar executed in a competent fashion. Elicitation of expert scientific judgment is a promising vehicle for evaluating the quality of pharmacokinetic data, expressing uncertainty in risk assessment, and fashioning a research agenda that offers possible forging of scientific consensus.

The distribution of Student's t-statistic for small samples from lognormal exposure distributions.

To assess compliance with industrial hygiene exposure criteria (e.g., TLVs), it may be necessary to perform statistical tests of hypotheses based on relatively small samples. For pollutants with long biological half-lives, the parameter most relevant for determining the risk faced by workers is the long-term arithmetic average concentration of the pollutant. In industrial environments it is common for pollutant concentrations to be approximately lognormal. Unfortunately, when based on small samples from lognormal distributions, the ordinary Student's t-statistic has some undesirable characteristics which are not recognized widely by practicing industrial hygienists. The difficulties in using the ordinary Student's t-statistic to evaluate the average exposure have been demonstrated. The properties of alternative test statistics have been explored. Some general observations on the implications of these findings have been made.