Clinical and functional characterization of germline PIK3CA variants in patients with PIK3CA-related overgrowth spectrum disorders.

Mosaic variants in the PIK3CA gene, encoding the catalytic subunit of phosphoinositide 3-kinase (PI3K), produce constitutive PI3K activation, which causes PIK3CA-related overgrowth spectrum disorders. To date, fewer than 20 patients have been described with germline alterations in PIK3CA. In this study, we describe three unrelated individuals with overgrowth and germline PIK3CA variants. These variants were discovered through whole-exome sequencing and confirmed as germline by testing multiple tissue types, when available. Functional analysis using Patient 1's fibroblast cell line and two previously reported patients' cell lines showed increased phosphorylation of AKT during cellular starvation revealing constitutive activation of the phosphoinositide-3-kinase/protein kinase B/mechanistic target of rapamycin (PI3K/AKT/mTOR) pathway. Alternatively, stimulation of the cells by fetal bovine serum produced a reduced response, indicating an activated status of the PI3K complex reducing the pathway response to further external stimulation. Additional studies utilizing Biolog Phenotype Microarray technology indicated reduced energy production when cells were exposed to growth factors stimulating the PI3K/AKT/mTOR pathway, confirming the trend observed in the AKT phosphorylation test after stimulation. Furthermore, treatment with inhibitors of the PI3K/AKT/mTOR pathway rescued the normal energy response in the patients' cells. Collectively, these data demonstrate that disease-causing germline PIK3CA variants have a functional consequence, similar to mosaic variants in the PI3K/AKT/mTOR pathway.

Haploinsufficiency of the Sin3/HDAC corepressor complex member SIN3B causes a syndromic intellectual disability/autism spectrum disorder.

Proteins involved in transcriptional regulation harbor a demonstrated enrichment of mutations in neurodevelopmental disorders. The Sin3 (Swi-independent 3)/histone deacetylase (HDAC) complex plays a central role in histone deacetylation and transcriptional repression. Among the two vertebrate paralogs encoding the Sin3 complex, SIN3A variants cause syndromic intellectual disability, but the clinical consequences of SIN3B haploinsufficiency in humans are uncharacterized. Here, we describe a syndrome hallmarked by intellectual disability, developmental delay, and dysmorphic facial features with variably penetrant autism spectrum disorder, congenital malformations, corpus callosum defects, and impaired growth caused by disruptive SIN3B variants. Using chromosomal microarray or exome sequencing, and through international data sharing efforts, we identified nine individuals with heterozygous SIN3B deletion or single-nucleotide variants. Five individuals harbor heterozygous deletions encompassing SIN3B that reside within a ∼230 kb minimal region of overlap on 19p13.11, two individuals have a rare nonsynonymous substitution, and two individuals have a single-nucleotide deletion that results in a frameshift and predicted premature termination codon. To test the relevance of SIN3B impairment to measurable aspects of the human phenotype, we disrupted the orthologous zebrafish locus by genome editing and transient suppression. The mutant and morphant larvae display altered craniofacial patterning, commissural axon defects, and reduced body length supportive of an essential role for Sin3 function in growth and patterning of anterior structures. To investigate further the molecular consequences of SIN3B variants, we quantified genome-wide enhancer and promoter activity states by using H3K27ac ChIP-seq. We show that, similar to SIN3A mutations, SIN3B disruption causes hyperacetylation of a subset of enhancers and promoters in peripheral blood mononuclear cells. Together, these data demonstrate that SIN3B haploinsufficiency leads to a hitherto unknown intellectual disability/autism syndrome, uncover a crucial role of SIN3B in the central nervous system, and define the epigenetic landscape associated with Sin3 complex impairment.

Emerging roles for carbonic anhydrase in mesophyll conductance and photosynthesis.

Carbonic anhydrase (CA) is an abundant protein in most photosynthesizing organisms and higher plants. This review paper considers the physiological importance of the more abundant CA isoforms in photosynthesis, through their effects on CO2 diffusion and other processes in photosynthetic organisms. In plants, CA has multiple isoforms in three different families (α, ß and γ) and is mainly known to catalyze the CO2↔HCO3- equilibrium. This reversible conversion has a clear role in photosynthesis, primarily through sustaining the CO2 concentration at the site of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco). Despite showing the same major reaction mechanism, the three main CA families are evolutionarily distinct. For different CA isoforms, cellular localization and total gene expression as a function of developmental stage are predicted to determine the role of each family in relation to the net assimilation rate. Reaction-diffusion modeling and observational evidence support a role for CA activity in reducing resistance to CO2 diffusion inside mesophyll cells by facilitating CO2 transfer in both gas and liquid phases. In addition, physical and/or biochemical interactions between CAs and other membrane-bound compartments, for example aquaporins, are suggested to trigger a CO2 -sensing response by stomatal movement. In response to environmental stresses, changes in the expression level of CAs and/or stimulated deactivation of CAs may correspond with lower photosynthetic capacity. We suggest that further studies should focus on the dynamics of the relationship between the activity of CAs (with different subcellular localization, abundance and gene expression) and limitations due to CO2 diffusivity through the mesophyll and supply of CO2 to photosynthetic reactions.

Prediction of skin sensitization potency using machine learning approaches.

The replacement of animal use in testing for regulatory classification of skin sensitizers is a priority for US federal agencies that use data from such testing. Machine learning models that classify substances as sensitizers or non-sensitizers without using animal data have been developed and evaluated. Because some regulatory agencies require that sensitizers be further classified into potency categories, we developed statistical models to predict skin sensitization potency for murine local lymph node assay (LLNA) and human outcomes. Input variables for our models included six physicochemical properties and data from three non-animal test methods: direct peptide reactivity assay; human cell line activation test; and KeratinoSens™ assay. Models were built to predict three potency categories using four machine learning approaches and were validated using external test sets and leave-one-out cross-validation. A one-tiered strategy modeled all three categories of response together while a two-tiered strategy modeled sensitizer/non-sensitizer responses and then classified the sensitizers as strong or weak sensitizers. The two-tiered model using the support vector machine with all assay and physicochemical data inputs provided the best performance, yielding accuracy of 88% for prediction of LLNA outcomes (120 substances) and 81% for prediction of human test outcomes (87 substances). The best one-tiered model predicted LLNA outcomes with 78% accuracy and human outcomes with 75% accuracy. By comparison, the LLNA predicts human potency categories with 69% accuracy (60 of 87 substances correctly categorized). These results suggest that computational models using non-animal methods may provide valuable information for assessing skin sensitization potency. Copyright © 2017 John Wiley & Sons, Ltd.

Life satisfaction across nations: the effects of women's political status and public priorities.

Feminist scholars suggest that improving the quality of life of individuals living in nations around the world may be more readily achieved by increasing women's political power and by reorienting public-policy priorities, than by focusing primarily on economic growth. These considerations raise the question of which characteristics of societies are associated with the quality of life of the people in those societies. Here, we address this issue empirically by statistically analyzing cross-national data. We assess the effects of gender equality in the political sphere, as well as a variety of other factors, on the subjective well-being of nations, as indicated by average self-reported levels of life satisfaction. We find that people report the highest levels of life satisfaction in nations where women have greater political representation, where military spending is low, and where health care spending is high, controlling for a variety of other factors. GDP per capita, urbanization, and natural resource exploitation are not clearly associated with life satisfaction. These findings suggest that nations may be able to improve the subjective quality of life of people without increasing material wealth or natural resource consumption by increasing gender equality in politics and changing public spending priorities.

Serious Illness Communication Tool for Palliative Care Fellows: Development, Implementation, and Lessons Learned.

Introduction: Learning expert communication skills is a core educational goal within palliative care training, yet there are few communication-based educational tools specifically designed for specialty-trained palliative care providers. Objective: To develop and implement a tool to facilitate effective learning of serious illness communication for hospice and palliative medicine fellows. Methods: A novel formative assessment tool was developed within the UCLA Palliative Care Fellowship program, and utilized throughout the academic year on a weekly basis. Focus groups were held for fellows and faculty separately at the end of the academic year in order to gain insight into the experience and effectiveness of the tool. Focus group transcripts were analyzed through thematic analysis. Results: There was a 47% participation rate in the focus groups (n = 7). Qualitative analysis demonstrated positive impact of the tool in identifying learning goals, improving quality of feedback, and in standardizing language around advanced communication skills, with most value in the first half of the fellowship year. Some aspects of the tool were found to increase feedback anxiety, including the competency scoring component, frequency of use, and utilization with individual patient encounters. Conclusion: This novel communication tool provides an important addition to serious illness communication training of specialist palliative care providers, in creating a shared mental model for naming and organizing skills, as well as generating specific high quality learning goals and feedback. Preliminary feedback from our pilot implementation phase provided important information about how to refine the tool and remove components that unnecessarily added to feedback anxiety.

Workshop Report: Catalyzing Knowledge-Driven Discovery in Environmental Health Sciences through a Harmonized Language.

Harmonized language is essential to finding, sharing, and reusing large-scale, complex data. Gaps and barriers prevent the adoption of harmonized language approaches in environmental health sciences (EHS). To address this, the National Institute of Environmental Health Sciences and partners created the Environmental Health Language Collaborative (EHLC). The purpose of EHLC is to facilitate a community-driven effort to advance the development and adoption of harmonized language approaches in EHS. EHLC is a forum to pinpoint language harmonization gaps, to facilitate the development of, raise awareness of, and encourage the use of harmonization approaches and tools, and to develop new standards and recommendations. To ensure that EHLC's focus and structure would be sustainable long-term and meet the needs of the field, EHLC launched an inaugural workshop in September 2021 focused on "Developing Sustainable Language Solutions" and "Building a Sustainable Community". When the attendees were surveyed, 91% said harmonized language solutions would be of high value/benefit, and 60% agreed to continue contributing to EHLC efforts. Based on workshop discussions, future activities will focus on targeted collaborative use-case working groups in addition to offering education and training on ontologies, metadata, and standards, and developing an EHS language resource portal.

MIPHENO: data normalization for high throughput metabolite analysis.

BACKGROUND: High throughput methodologies such as microarrays, mass spectrometry and plate-based small molecule screens are increasingly used to facilitate discoveries from gene function to drug candidate identification. These large-scale experiments are typically carried out over the course of months and years, often without the controls needed to compare directly across the dataset. Few methods are available to facilitate comparisons of high throughput metabolic data generated in batches where explicit in-group controls for normalization are lacking. RESULTS: Here we describe MIPHENO (Mutant Identification by Probabilistic High throughput-Enabled Normalization), an approach for post-hoc normalization of quantitative first-pass screening data in the absence of explicit in-group controls. This approach includes a quality control step and facilitates cross-experiment comparisons that decrease the false non-discovery rates, while maintaining the high accuracy needed to limit false positives in first-pass screening. Results from simulation show an improvement in both accuracy and false non-discovery rate over a range of population parameters (p < 2.2 × 10(-16)) and a modest but significant (p < 2.2 × 10(-16)) improvement in area under the receiver operator characteristic curve of 0.955 for MIPHENO vs 0.923 for a group-based statistic (z-score). Analysis of the high throughput phenotypic data from the Arabidopsis Chloroplast 2010 Project (http://www.plastid.msu.edu/) showed ~ 4-fold increase in the ability to detect previously described or expected phenotypes over the group based statistic. CONCLUSIONS: Results demonstrate MIPHENO offers substantial benefit in improving the ability to detect putative mutant phenotypes from post-hoc analysis of large data sets. Additionally, it facilitates data interpretation and permits cross-dataset comparison where group-based controls are missing. MIPHENO is applicable to a wide range of high throughput screenings and the code is freely available as Additional file 1 as well as through an R package in CRAN.

Application of an Accessible Interface for Pharmacokinetic Modeling and In Vitro to In Vivo Extrapolation.

Regulatory toxicology testing has traditionally relied on in vivo methods to inform decision-making. However, scientific, practical, and ethical considerations have led to an increased interest in the use of in vitro and in silico methods to fill data gaps. While in vitro experiments have the advantage of rapid application across large chemical sets, interpretation of data coming from these non-animal methods can be challenging due to the mechanistic nature of many assays. In vitro to in vivo extrapolation (IVIVE) has emerged as a computational tool to help facilitate this task. Specifically, IVIVE uses physiologically based pharmacokinetic (PBPK) models to estimate tissue-level chemical concentrations based on various dosing parameters. This approach is used to estimate the administered dose needed to achieve in vitro bioactivity concentrations within the body. IVIVE results can be useful to inform on metrics such as margin of exposure or to prioritize potential chemicals of concern, but the PBPK models used in this approach have extensive data requirements. Thus, access to input parameters, as well as the technical requirements of applying and interpreting models, has limited the use of IVIVE as a routine part of in vitro testing. As interest in using non-animal methods for regulatory and research contexts continues to grow, our perspective is that access to computational support tools for PBPK modeling and IVIVE will be essential for facilitating broader application and acceptance of these techniques, as well as for encouraging the most scientifically sound interpretation of in vitro results. We highlight recent developments in two open-access computational support tools for PBPK modeling and IVIVE accessible via the Integrated Chemical Environment (https://ice.ntp.niehs.nih.gov/), demonstrate the types of insights these tools can provide, and discuss how these analyses may inform in vitro-based decision making.

Drug-facilitated sexual assault, impaired trauma memory, and implications for mental health treatment.

Background: Sexual assault (SA) is a highly prevalent global public health problem and a robust predictor of posttraumatic stress disorder (PTSD), substance use disorder (SUD), and suicidality. A large percentage are drug or alcohol facilitated (DFSA), impairing trauma memory and affecting the application of evidence-based treatments. Despite these problems, few have investigated DFSA-specific mental health (MH) needs. Objective: Goals of this study were (1) to identify psychological sequelae characterizing DFSA towards explaining why symptoms have been treatment-refractory, comparing survivors with involuntary substance ingestion (forced, covert: DFSA-I), voluntary ingestion (DFSA-V), and non-DFSA; and (2) to determine how impaired trauma memory relates to the development of PTSD and depression symptoms. Method: Data from a retrospective chart review of 74 adults receiving SA MH services at an outpatient trauma center are presented. The sample includes a 2-year cohort seen acutely at an urban rape treatment center. The study is one of the first to examine therapy records beyond case studies for DFSA. Logistic, Poisson, and negative binomial regression analyses of quantitative data and qualitative thematic analysis of trauma cognitions and treatment foci were conducted. Results: DFSA-V had five times greater odds of SUD, and notable substance-related self-blame compared to DFSA-I. DFSA-I had prominent relationship distress and self-blame for missing danger of perpetrator drugging. Survivors with impaired trauma memory had significantly fewer hyper-arousal and overall PTSD symptoms, and specifically less hypervigilance. No differences were found in re-experiencing symptoms. Conclusion: Impaired trauma memory is common in DFSA and is associated with fewer baseline hyper-arousal and overall PTS. Despite this, DFSA issues including re-experiencing symptoms that are particularly distressing without the ability to cognitively connect the intrusions contribute to increased treatment needs. Impaired memory limits the application of evidence-based treatments, and collectively these findings call for the development of trauma-specific treatment protocols to enhance recovery for DFSA survivors. HIGHLIGHTS: Survivors of drug-facilitated sexual assault have prominent PTSD including reexperiencing, though trauma memory may not be encoded. • Those absent trauma memory have less hyperarousal, but DFSA complications explain why it is treatment refractory and inform treatment development.

Antecedentes: La agresión sexual (AS) es un problema de salud pública mundial de alta prevalencia y es un sólido predictor del trastorno de estrés postraumático (TEPT), del trastorno por uso de sustancias (TUS) y de suicidalidad. Un gran porcentaje de AS son facilitadas por drogas o alcohol (ASFDA), deteriorando la memoria del trauma y afectando la aplicación de tratamientos basados en la evidencia. A pesar de estos problemas, pocos han investigado las necesidades de salud mental (SM) específicas de los ASFDA.Objetivo: Los objetivos de este estudio fueron; primero, identificar las secuelas psicológicas que caracterizan a las ASFDA para explicar por qué los síntomas han sido refractarios al tratamiento. Para ello, se comparó a sobrevivientes a una ingestión involuntaria de sustancias (forzada, encubierta: ASFDA-I), a una ingestión voluntaria (ASFDA-V), y a una AS no-ASFDA; y, segundo; determinar cómo el deterioro de la memoria del trauma se relaciona con el desarrollo de síntomas del TEPT y depresión.Método: Se presentan los datos de una revisión retrospectiva de las historias clínicas de 74 adultos que recibieron servicios de SM por AS en un centro de trauma para pacientes ambulatorios. La muestra incluye a una cohorte de 2 años en donde los casos de AS fueron vistos de forma aguda en un centro urbano de tratamiento para violación. El estudio es uno de los primeros, más allá de los estudios de casos, en examinar los registros de terapia por ASFDA. Se realizaron análisis de regresión logística, Poisson y binomial negativa de datos cuantitativos y un análisis temático cualitativo de las cogniciones del trauma y los puntos clave del tratamiento.Resultados: Los ASFDA-V tuvieron cinco veces más probabilidades de TUS y de un notable sentimiento de culpa relacionado con las sustancias comparado con los ASFDA-I. Las ASFDA tenían problemas de relación importantes y sentimientos de culpa por haber pasado por alto el peligro de que el agresor se drogara. Los sobrevivientes con deterioro de la memoria traumática tuvieron significativamente menos síntomas de hiperactivación y del TEPT en general y, específicamente, menos hipervigilancia. No se encontraron diferencias en los síntomas de reexperimentación.Conclusión: El deterioro de la memoria traumática es común en las ASFDA y se asocia con menos hiperactivación de base y síntomas postraumáticos en general. A pesar de esto, los problemas de los ASFDA incluyen a los síntomas de reexperimentación que son particularmente angustiantes y que restan la capacidad de conectar cognitivamente las intrusiones, por lo que contribuyen a aumentar las necesidades de tratamiento. El deterioro de la memoria limita la aplicación de tratamientos basados en la evidencia y, en conjunto, estos hallazgos exigen el desarrollo de protocolos de tratamiento específicos para trauma para mejorar la recuperación de los sobrevivientes a las ASFDA.

Advancing New Approach Methodologies (NAMs) for Tobacco Harm Reduction: Synopsis from the 2021 CORESTA SSPT-NAMs Symposium.

New approach methodologies (NAMs) are emerging chemical safety assessment tools consisting of in vitro and in silico (computational) methodologies intended to reduce, refine, or replace (3R) various in vivo animal testing methods traditionally used for risk assessment. Significant progress has been made toward the adoption of NAMs for human health and environmental toxicity assessment. However, additional efforts are needed to expand their development and their use in regulatory decision making. A virtual symposium was held during the 2021 Cooperation Centre for Scientific Research Relative to Tobacco (CORESTA) Smoke Science and Product Technology (SSPT) conference (titled "Advancing New Alternative Methods for Tobacco Harm Reduction"), with the goals of introducing the concepts and potential application of NAMs in the evaluation of potentially reduced-risk (PRR) tobacco products. At the symposium, experts from regulatory agencies, research organizations, and NGOs shared insights on the status of available tools, strengths, limitations, and opportunities in the application of NAMs using case examples from safety assessments of chemicals and tobacco products. Following seven presentations providing background and application of NAMs, a discussion was held where the presenters and audience discussed the outlook for extending the NAMs toxicological applications for tobacco products. The symposium, endorsed by the CORESTA In Vitro Tox Subgroup, Biomarker Subgroup, and NextG Tox Task Force, illustrated common ground and interest in science-based engagement across the scientific community and stakeholders in support of tobacco regulatory science. Highlights of the symposium are summarized in this paper.

Quantitative in vitro to in vivo extrapolation for developmental toxicity potency of valproic acid analogues.

BACKGROUND: The developmental toxicity potential (dTP) concentration from the devTOX quickPredict (devTOXqP ) assay, a metabolomics-based human induced pluripotent stem cell assay, predicts a chemical's developmental toxicity potency. Here, in vitro to in vivo extrapolation (IVIVE) approaches were applied to address whether the devTOXqP assay could quantitatively predict in vivo developmental toxicity lowest effect levels (LELs) for the prototypical teratogen valproic acid (VPA) and a group of structural analogues. METHODS: VPA and a series of structural analogues were tested with the devTOXqP assay to determine dTP concentration and we estimated the equivalent administered doses (EADs) that would lead to plasma concentrations equivalent to the in vitro dTP concentrations. The EADs were compared to the LELs in rat developmental toxicity studies, human clinical doses, and EADs reported using other in vitro assays. To evaluate the impact of different pharmacokinetic (PK) models on IVIVE outcomes, we compared EADs predicted using various open-source and commercially available PK and physiologically based PK (PBPK) models. To evaluate the effect of in vitro kinetics, an equilibrium distribution model was applied to translate dTP concentrations to free medium concentrations before subsequent IVIVE analyses. RESULTS: The EAD estimates for the VPA analogues based on different PK/PBPK models were quantitatively similar to in vivo data from both rats and humans, where available, and the derived rank order of the chemicals was consistent with observed in vivo developmental toxicity. Different models were identified that provided accurate predictions for rat prenatal LELs and conservative estimates of human safe exposure. The impact of in vitro kinetics on EAD estimates is chemical-dependent. EADs from this study were within range of predicted doses from other in vitro and model organism data. CONCLUSIONS: This study highlights the importance of pharmacokinetic considerations when using in vitro assays and demonstrates the utility of the devTOXqP human stem cell-based platform to quantitatively assess a chemical's developmental toxicity potency.

Data curation to support toxicity assessments using the Integrated Chemical Environment.

Humans are exposed to large numbers of chemicals during their daily activities. To assess and understand potential health impacts of chemical exposure, investigators and regulators need access to reliable toxicity data. In particular, reliable toxicity data for a wide range of chemistries are needed to support development of new approach methodologies (NAMs) such as computational models, which offer increased throughput relative to traditional approaches and reduce or replace animal use. NAMs development and evaluation require chemically diverse data sets that are typically constructed by incorporating results from multiple studies into a single, integrated view; however, integrating data is not always a straightforward task. Primary study sources often vary in the way data are organized and reported. Metadata and information needed to support interoperability and provide context are often lacking, which necessitates literature research on the assay prior to attempting data integration. The Integrated Chemical Environment (ICE) was developed to support the development, evaluation, and application of NAMs. ICE provides curated toxicity data and computational tools to integrate and explore available information, thus facilitating knowledge discovery and interoperability. This paper describes the data curation workflow for integrating data into ICE. Data destined for ICE undergo rigorous harmonization, standardization, and formatting processes using both automated and manual expert-driven approaches. These processes improve the utility of the data for diverse analyses and facilitate application within ICE or a user's external workflow while preserving data integrity and context. ICE data curation provides the structure, reliability, and accessibility needed for data to support chemical assessments.

FDA Emergency Use Authorization-Approved Novel Coronavirus Disease 2019, Pressure-Regulated, Mechanical Ventilator Splitter That Enables Differential Compliance Multiplexing.

Infection with the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), may cause viral pneumonia and acute respiratory distress syndrome (ARDS). Treatment of ARDS often requires mechanical ventilation and may take weeks for resolution. In areas with a large outbreaks, there may be shortages of ventilators available. While rudimentary methods for ventilator splitting have been described, given the range of independent ventilatory settings required for each patient, this solution is suboptimal. Here, we describe a device that can split a ventilator among up to four patients while allowing for individualized settings. The device has been validated in vitro and in vivo .

IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making.

During the past few decades, the science of toxicology has been undergoing a transformation from observational to predictive science. New approach methodologies (NAMs), including in vitro assays, in silico models, read-across, and in vitro to in vivo extrapolation (IVIVE), are being developed to reduce, refine, or replace whole animal testing, encouraging the judicious use of time and resources. Some of these methods have advanced past the exploratory research stage and are beginning to gain acceptance for the risk assessment of chemicals. A review of the recent literature reveals a burst of IVIVE publications over the past decade. In this review, we propose operational definitions for IVIVE, present literature examples for several common toxicity endpoints, and highlight their implications in decision-making processes across various federal agencies, as well as international organizations, including those in the European Union (EU). The current challenges and future needs are also summarized for IVIVE. In addition to refining and reducing the number of animals in traditional toxicity testing protocols and being used for prioritizing chemical testing, the goal to use IVIVE to facilitate the replacement of animal models can be achieved through their continued evolution and development, including a strategic plan to qualify IVIVE methods for regulatory acceptance.

A residue in loop 9 of the beta2-subunit stabilizes the closed state of the GABAA receptor.

In gamma-aminobutyric acid type A (GABA(A)) receptors, the structural elements that couple ligand binding to channel opening remain poorly defined. Here, site-directed mutagenesis was used to determine if Loop 9 on the non-GABA binding site interface of the beta2-subunit may be involved in GABA(A) receptor activation. Specifically, residues Gly(170)-Gln(185) of the beta2-subunit were mutated to alanine, co-expressed with wild-type alpha1- and gamma2S-subunits in human embryonic kidney (HEK) 293 cells and assayed for their activation by GABA, the intravenous anesthetic propofol and the endogenous neurosteroid pregnanolone using whole cell macroscopic recordings. Three mutants, G170A, V175A, and G177A, produced 2.5-, 6.7-, and 5.6-fold increases in GABA EC(50) whereas one mutant, Q185A, produced a 5.2-fold decrease in GABA EC(50). None of the mutations affected the ability of propofol or pregnanolone to potentiate a submaximal GABA response, but the Q185A mutant exhibited 8.3- and 3.5-fold increases in the percent direct activation by propofol and pregnanolone, respectively. Mutant Q185A receptors also had an increased leak current that was sensitive to picrotoxin, indicating an increased gating efficiency. Further Q185E, Q185L, and Q185W substitutions revealed a strong correlation between the hydropathy of the amino acid at this position and the GABA EC(50). Taken together, these results indicate that beta2 Loop 9 is involved in receptor activation by GABA, propofol, and pregnanolone and that beta2(Q185) participates in hydrophilic interactions that are important for stabilizing the closed state of the GABA(A) receptor.

Large-scale reverse genetics in Arabidopsis: case studies from the Chloroplast 2010 Project.

Traditionally, phenotype-driven forward genetic plant mutant studies have been among the most successful approaches to revealing the roles of genes and their products and elucidating biochemical, developmental, and signaling pathways. A limitation is that it is time consuming, and sometimes technically challenging, to discover the gene responsible for a phenotype by map-based cloning or discovery of the insertion element. Reverse genetics is also an excellent way to associate genes with phenotypes, although an absence of detectable phenotypes often results when screening a small number of mutants with a limited range of phenotypic assays. The Arabidopsis Chloroplast 2010 Project (www.plastid.msu.edu) seeks synergy between forward and reverse genetics by screening thousands of sequence-indexed Arabidopsis (Arabidopsis thaliana) T-DNA insertion mutants for a diverse set of phenotypes. Results from this project are discussed that highlight the strengths and limitations of the approach. We describe the discovery of altered fatty acid desaturation phenotypes associated with mutants of At1g10310, previously described as a pterin aldehyde reductase in folate metabolism. Data are presented to show that growth, fatty acid, and chlorophyll fluorescence defects previously associated with antisense inhibition of synthesis of the family of acyl carrier proteins can be attributed to a single gene insertion in Acyl Carrier Protein4 (At4g25050). A variety of cautionary examples associated with the use of sequence-indexed T-DNA mutants are described, including the need to genotype all lines chosen for analysis (even when they number in the thousands) and the presence of tagged and untagged secondary mutations that can lead to the observed phenotypes.

Exploring in vitro to in vivo extrapolation for exposure and health impacts of e-cigarette flavor mixtures.

In vitro to in vivo extrapolation (IVIVE) leverages in vitro biological activities to predict corresponding in vivo exposures, therefore potentially reducing the need for animal safety testing that are traditionally performed to support the hazard and risk assessment. Interpretation of IVIVE predictions are affected by various factors including the model type, exposure route and kinetic assumptions for the test article, and choice of in vitro assay(s) that are relevant to clinical outcomes. Exposure scenarios are further complicated for mixtures where the in vitro activity may stem from one or more components in the mixture. In this study, we used electronic cigarette (EC) aerosols, a complex mixture, to explore impacts of these factors on the use of IVIVE in hazard identification, using open-source pharmacokinetic models of varying complexity and publicly available data. Results suggest in vitro assay selection has a greater impact on exposure estimates than modeling approaches. Using cytotoxicity assays, high exposure estimates (>1000 EC cartridges (pods) or > 700 mL EC liquid per day) would be needed to obtain the in vivo plasma levels that are corresponding to in vitro assay data, suggesting acute toxicity would be unlikely in typical usage scenarios. When mechanistic (Tox21) assays were used, the exposure estimates were much lower for the low end, but the range of exposure estimate became wider across modeling approaches. These proof-of-concept results highlight challenges and complexities in IVIVE for mixtures.

Evaluation of Inhalation Exposures and Potential Health Impacts of Ingredient Mixtures Using in vitro to in vivo Extrapolation.

In vitro methods offer opportunities to provide mechanistic insight into bioactivity as well as human-relevant toxicological assessments compared to animal testing. One of the challenges for this task is putting in vitro bioactivity data in an in vivo exposure context, for which in vitro to in vivo extrapolation (IVIVE) translates in vitro bioactivity to clinically relevant exposure metrics using reverse dosimetry. This study applies an IVIVE approach to the toxicity assessment of ingredients and their mixtures in e-cigarette (EC) aerosols as a case study. Reported in vitro cytotoxicity data of EC aerosols, as well as in vitro high-throughput screening (HTS) data for individual ingredients in EC liquids (e-liquids) are used. Open-source physiologically based pharmacokinetic (PBPK) models are used to calculate the plasma concentrations of individual ingredients, followed by reverse dosimetry to estimate the human equivalent administered doses (EADs) needed to obtain these plasma concentrations for the total e-liquids. Three approaches (single actor approach, additive effect approach, and outcome-oriented ingredient integration approach) are used to predict EADs of e-liquids considering differential contributions to the bioactivity from the ingredients (humectant carriers [propylene glycol and glycerol], flavors, benzoic acid, and nicotine). The results identified critical factors for the EAD estimation, including the ingredients of the mixture considered to be bioactive, in vitro assay selection, and the data integration approach for mixtures. Further, we introduced the outcome-oriented ingredient integration approach to consider e-liquid ingredients that may lead to a common toxicity outcome (e.g., cytotoxicity), facilitating a quantitative evaluation of in vitro toxicity data in support of human risk assessment.

CATMoS: Collaborative Acute Toxicity Modeling Suite.

BACKGROUND: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. OBJECTIVES: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different end points: Lethal Dose 50 (LD50 value, U.S. Environmental Protection Agency hazard (four) categories, Globally Harmonized System for Classification and Labeling hazard (five) categories, very toxic chemicals [LD50 (LD50≤50mg/kg)], and nontoxic chemicals (LD50>2,000mg/kg). METHODS: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. RESULTS: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared with in vivo results. DISCUSSION: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for more than 800,000 chemicals have been made available via the National Toxicology Program's Integrated Chemical Environment tools and data sets (ice.ntp.niehs.nih.gov). The models are also implemented in a free, standalone, open-source tool, OPERA, which allows predictions of new and untested chemicals to be made. https://doi.org/10.1289/EHP8495.