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Dietary lysine content in poultry diets is critical to improve feed utilization efficiency, body protein deposition rate, and carcass traits of growing and finishing poultry. The objective of the current study was to estimate the optimum digestible lysine requirements for maximum growth performance, efficient utilization of nitrogen, and carcass traits of male Korean native ducklings for 3 wk after hatch. A total of 720 one-day-old male Korean native ducklings were used in a completely randomized design having 8 dietary treatments to provide a range of digestible lysine content from 0.44 to 1.07%. Ducklings were randomly allotted to 24 floor pens (6 replicates per treatment and 15 ducklings per pen) and were offered the respective diets on an ad libitum basis for the period of study. Body weight and feed intake were measured weekly to calculate feed conversion ratio. At the termination of the experiment, 2 ducklings per pen were euthanized via cervical dislocation to weigh empty body and drumsticks. The digestible lysine requirement was determined by taking a mean value after fitting the data to both linear-plateau and quadratic-plateau models. Digestible lysine requirements for Korean native ducklings for 3 wk after hatch were estimated to be 0.71, 0.74, 0.65 and 1.01% for maximum body weight, daily gain, and daily feed intake, and for minimum feed conversion ratio, respectively. [ABSTRACT FROM AUTHOR]

It is crucial to test the goodness of fit of a model before it is used to make statistical inferences. However, no satisfactory goodness of fit test is available for the case of categorical multilevel data which occur when categorical data are clustered or hierarchical in nature. Hence the aim of this paper is to develop a new goodness of fit test for multilevel binary data based on Hosmer and Lemeshow and Lipsitz et.al. In order to identify the properties of the developed test, simulation studies were carried out to assess the Type I error and the power. [ABSTRACT FROM PUBLISHER]

Since initial regulatory action in 2010 in Canada, bisphenol A (BPA) has been progressively replaced by structurally related alternative chemicals. Unfortunately, many of these chemicals are data-poor, limiting toxicological risk assessment. We used high-throughput transcriptomics to evaluate potential hazards and compare potencies of BPA and 15 BPA alternative chemicals in cultured breast cancer cells. MCF-7 cells were exposed to BPA and 15 alternative chemicals (0.0005-100 µM) for 48 h. TempO-Seq (BioSpyder Inc) was used to examine global transcriptomic changes and estrogen receptor alpha (ERα)-associated transcriptional changes. Benchmark concentration (BMC) analysis was conducted to identify 2 global transcriptomic points of departure: (1) the lowest pathway median gene BMC and (2) the 25th lowest rank-ordered gene BMC. ERα activation was evaluated using a published transcriptomic biomarker and an ERα-specific transcriptomic point of departure was derived. Genes fitting BMC models were subjected to upstream regulator and canonical pathway analysis in Ingenuity Pathway Analysis. Biomarker analysis identified BPA and 8 alternative chemicals as ERα active. Global and ERα transcriptomic points of departure produced highly similar potency rankings with bisphenol AF as the most potent chemical tested, followed by BPA and bisphenol C. Further, BPA and transcriptionally active alternative chemicals enriched similar gene sets associated with increased cell division and cancer-related processes. These data provide support for future read-across applications of transcriptomic profiling for risk assessment of data-poor chemicals and suggest that several BPA alternative chemicals may cause hazards at similar concentrations to BPA., (© His Majesty the King in Right of Canada, as represented by the Minister of Health, 2022.)

Genotoxicity assessment is a critical component in the development and evaluation of chemicals. Traditional genotoxicity assays (i.e., mutagenicity, clastogenicity, and aneugenicity) have been limited to dichotomous hazard classification, while other toxicity endpoints are assessed through quantitative determination of points-of-departures (PODs) for setting exposure limits. The more recent higher-throughput in vitro genotoxicity assays, many of which also provide mechanistic information, offer a powerful approach for determining defined PODs for potency ranking and risk assessment. In order to obtain relevant human dose context from the in vitro assays, in vitro to in vivo extrapolation (IVIVE) models are required to determine what dose would elicit a concentration in the body demonstrated to be genotoxic using in vitro assays. Previous work has demonstrated that application of IVIVE models to in vitro bioactivity data can provide PODs that are protective of human health, but there has been no evaluation of how these models perform with in vitro genotoxicity data. Thus, the Genetic Toxicology Technical Committee, under the Health and Environmental Sciences Institute, conducted a case study on 31 reference chemicals to evaluate the performance of IVIVE application to genotoxicity data. The results demonstrate that for most chemicals considered here (20/31), the PODs derived from in vitro data and IVIVE are health protective relative to in vivo PODs from animal studies. PODs were also protective by assay target: mutations (8/13 chemicals), micronuclei (9/12), and aneugenicity markers (4/4). It is envisioned that this novel testing strategy could enhance prioritization, rapid screening, and risk assessment of genotoxic chemicals., (© 2022 His Majesty the King in Right of Canada and The Authors. Environmental and Molecular Mutagenesis published by Wiley Periodicals LLC on behalf of Environmental Mutagen Society. Reproduced with the permission of the Minister of Health Canada. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)