Anger as a moderator of safer sex motivation among low-income urban women.

PubMed

Schroder, Kerstin E E; Carey, Michael P

2005-10-01

Theoretical models suggest that both HIV knowledge and HIV risk perception inform rational decision making and, thus, predict safer sex motivation and behavior. However, the amount of variance explained by knowledge and risk perception is typically small. In this cross-sectional study, we investigated whether the predictive power of HIV knowledge and HIV risk perception on safer sex motivation is affected by trait anger. We hypothesized that anger may disrupt rational decision making, distorting the effects of both HIV knowledge and risk perception on safer sex intentions. Data from 232 low-income, urban women at risk for HIV infection were used to test a path model with past sexual risk behavior, HIV knowledge, and HIV risk perception as predictors of safer sex intentions. Moderator effects of anger on safer sex intentions were tested by simultaneous group comparisons between high-anger and low-anger women (median split). The theoretically expected "rational pattern" was found among low-anger women only, including (a) a positive effect of knowledge on safer sex intentions, and (b) buffer (inhibitor) effects of HIV knowledge and HIV risk perception on the negative path leading from past risk behavior to safer sex intentions. Among high-anger women, an "irrational pattern" emerged, with no effects of HIV knowledge and negative effects of both past risk behavior and HIV risk perception on safer sex intentions. In sum, the results suggest that rational knowledge- and risk-based decisions regarding safer sex may be limited to low-anger women.

Anger as a Moderator of Safer Sex Motivation among Low Income Urban Women

PubMed Central

Carey, Michael P.

2005-01-01

Theoretical models suggest that both HIV knowledge and HIV risk perception inform rational decision-making and, thus, predict safer sex motivation and behavior. However, the amount of variance explained by knowledge and risk perception is typically small. In this cross-sectional study, we investigated whether the predictive power of HIV knowledge and HIV risk perception on safer sex motivation is affected by trait anger. We hypothesized that anger may disrupt rational-decision making, distorting the effects of both HIV knowledge and risk perception on safer sex intentions. Data from 232 low-income, urban women at risk for HIV infection were used to test a path model with past sexual risk behavior, HIV knowledge, and HIV risk perception as predictors of safer sex intentions. Moderator effects of anger on safer sex intentions were tested by simultaneous group comparisons between high-anger and low-anger women (median-split). The theoretically expected “rational pattern” was found among low-anger women only, including (a) a positive effect of knowledge on safer sex intentions, and (b) buffer (inhibitor) effects of HIV knowledge and HIV risk perception on the negative path leading from past risk behavior to safer sex intentions. Among high-anger women, an “irrational pattern” emerged, with no effects of HIV knowledge and negative effects of both past risk behavior and HIV risk perception on safer sex intentions. In sum, the results suggest that rational knowledge and risk-based decisions regarding safer sex may be limited to low-anger women. PMID:16247592

Too many chemicals, too little time: Rapid in silico methods to characterize and predict ADME properties for chemical toxicity and exposure potential

EPA Science Inventory

Evaluating proposed alternative chemical structures to support the design of safer chemicals and products is an important component of EPA's Green Chemistry and Design for the Environment (DfE) Programs. As such, science-based alternatives assessment is essential to support EPA's...

Predicting the Future: Opportunities and Challenges for the Chemical Industry to Apply 21st-Century Toxicity Testing

PubMed Central

Settivari, Raja S; Ball, Nicholas; Murphy, Lynea; Rasoulpour, Reza; Boverhof, Darrell R; Carney, Edward W

2015-01-01

Interest in applying 21st-century toxicity testing tools for safety assessment of industrial chemicals is growing. Whereas conventional toxicology uses mainly animal-based, descriptive methods, a paradigm shift is emerging in which computational approaches, systems biology, high-throughput in vitro toxicity assays, and high-throughput exposure assessments are beginning to be applied to mechanism-based risk assessments in a time- and resource-efficient fashion. Here we describe recent advances in predictive safety assessment, with a focus on their strategic application to meet the changing demands of the chemical industry and its stakeholders. The opportunities to apply these new approaches is extensive and include screening of new chemicals, informing the design of safer and more sustainable chemical alternatives, filling information gaps on data-poor chemicals already in commerce, strengthening read-across methodology for categories of chemicals sharing similar modes of action, and optimizing the design of reduced-risk product formulations. Finally, we discuss how these predictive approaches dovetail with in vivo integrated testing strategies within repeated-dose regulatory toxicity studies, which are in line with 3Rs principles to refine, reduce, and replace animal testing. Strategic application of these tools is the foundation for informed and efficient safety assessment testing strategies that can be applied at all stages of the product-development process. PMID:25836969

Predicting the future: opportunities and challenges for the chemical industry to apply 21st-century toxicity testing.

PubMed

Settivari, Raja S; Ball, Nicholas; Murphy, Lynea; Rasoulpour, Reza; Boverhof, Darrell R; Carney, Edward W

2015-03-01

Interest in applying 21st-century toxicity testing tools for safety assessment of industrial chemicals is growing. Whereas conventional toxicology uses mainly animal-based, descriptive methods, a paradigm shift is emerging in which computational approaches, systems biology, high-throughput in vitro toxicity assays, and high-throughput exposure assessments are beginning to be applied to mechanism-based risk assessments in a time- and resource-efficient fashion. Here we describe recent advances in predictive safety assessment, with a focus on their strategic application to meet the changing demands of the chemical industry and its stakeholders. The opportunities to apply these new approaches is extensive and include screening of new chemicals, informing the design of safer and more sustainable chemical alternatives, filling information gaps on data-poor chemicals already in commerce, strengthening read-across methodology for categories of chemicals sharing similar modes of action, and optimizing the design of reduced-risk product formulations. Finally, we discuss how these predictive approaches dovetail with in vivo integrated testing strategies within repeated-dose regulatory toxicity studies, which are in line with 3Rs principles to refine, reduce, and replace animal testing. Strategic application of these tools is the foundation for informed and efficient safety assessment testing strategies that can be applied at all stages of the product-development process.

STS-64 SAFER Assembly

NASA Image and Video Library

1993-12-10

S93-50137 (December 1993) --- This small mobility-aiding back harness, complemented in extravehicular activity (EVA) with a hand controller unit and called the Simplified Aid for EVA Rescue (SAFER) system, will get extensive in-space evaluation and testing during the STS-64 mission. In this view the SAFER is open to reveal the gas supply and thrusters. SAFER is to fly on STS-76 as well.

Molecular simulation studies on chemical reactivity of methylcyclopentadiene.

PubMed

Wang, Qingsheng; Zhang, Yingchun; Rogers, William J; Mannan, M Sam

2009-06-15

Molecular simulations are important to predict thermodynamic values for reactive chemicals especially when sufficient experimental data are not available. Methylcyclopentadiene (MCP) is an example of a highly reactive and hazardous compound in the chemical process industry. In this work, chemical reactivity of 2-methylcyclopentadiene, including isomerization, dimerization, and oxidation reactions, is investigated in detail by theoretical computational chemistry methods and empirical thermodynamic-energy correlation. On the basis of molecular simulations, an average value of -15.2 kcal/mol for overall heat of dimerization and -45.6 kcal/mol for overall heat of oxidation were obtained in gaseous phase at 298 K and 1 atm. These molecular simulation studies can provide guidance for the design of safer chemical processes, safer handling of MCP, and also provide useful information for an investigation of the T2 Laboratories explosion on December 19, 2007, in Florida.

Predictors of safer sex on the college campus: a social cognitive theory analysis.

PubMed

O'Leary, A; Goodhart, F; Jemmott, L S; Boccher-Lattimore, D

1992-05-01

In April and May 1989, the authors surveyed a sample of students enrolled on four college campuses in New Jersey (N = 923) concerning their HIV transmission-related behavior, knowledge, and a variety of conceptual variables taken primarily from social cognitive theory that were thought to be potentially predictive of safer sexual behavior. Analyses of sexually active, unmarried students' responses indicated that men expected more negative outcomes of condom use and were more likely to have sexual intercourse while under the influence of alcohol or other drugs, whereas women reported higher perceived self-efficacy to practice safer sex. Regression analyses indicated that, among the factors assessed, stronger perceptions of self-efficacy to engage in safer behavior, expecting fewer negative outcomes of condom use, and less frequency of sex in conjunction with alcohol or other drug use significantly predicted safer sexual behavior. Enhanced self-efficacy to discuss personal history with a new partner was associated with a greater number of risky encounters. Implications of these findings for intervention efforts with students are discussed.

SaferProducts.gov

MedlinePlus

... Register & Respond Search Recalls & Reports About Questions Welcome Consumers Report your unsafe product on SaferProducts.gov. Tell CPSC. ... Unsafe Product Business Sign In Search Recalls/Repairs & Reports Advanced Search Most ... does not guarantee the accuracy, completeness, or adequacy of the contents of the Publicly Available Consumer Product Safety Information Database on SaferProducts.gov, particularly ...

Pedestrian Safer Journey

Science.gov Websites

Pedestrian Safer Journey Skills for Safe Walking for Ages 5 to 18 Use in the classroom or one-on -one. To start, click on an age group below: Ages 5-9 Ages 10-14 Ages 15-18 What is Pedestrian Safer get the conversation started with children and youth. Three videos - one for each of three age groups

Systematic chemical-genetic and chemical-chemical interaction datasets for prediction of compound synergism

PubMed Central

Wildenhain, Jan; Spitzer, Michaela; Dolma, Sonam; Jarvik, Nick; White, Rachel; Roy, Marcia; Griffiths, Emma; Bellows, David S.; Wright, Gerard D.; Tyers, Mike

2016-01-01

The network structure of biological systems suggests that effective therapeutic intervention may require combinations of agents that act synergistically. However, a dearth of systematic chemical combination datasets have limited the development of predictive algorithms for chemical synergism. Here, we report two large datasets of linked chemical-genetic and chemical-chemical interactions in the budding yeast Saccharomyces cerevisiae. We screened 5,518 unique compounds against 242 diverse yeast gene deletion strains to generate an extended chemical-genetic matrix (CGM) of 492,126 chemical-gene interaction measurements. This CGM dataset contained 1,434 genotype-specific inhibitors, termed cryptagens. We selected 128 structurally diverse cryptagens and tested all pairwise combinations to generate a benchmark dataset of 8,128 pairwise chemical-chemical interaction tests for synergy prediction, termed the cryptagen matrix (CM). An accompanying database resource called ChemGRID was developed to enable analysis, visualisation and downloads of all data. The CGM and CM datasets will facilitate the benchmarking of computational approaches for synergy prediction, as well as chemical structure-activity relationship models for anti-fungal drug discovery. PMID:27874849

[Negotiating safer sex].

PubMed

Gordon, G; Charnock, D

1991-01-01

Women have generally assumed responsibility for contraception since the appearance of oral contraceptives and IUDs. But AIDS prevention programs are now asking women to assume responsibility for safer sex through use of condoms, a male method. Women are being asked to carry condoms, to negotiate their use each time they have sex, and to insist if the partner resists. The problem with this strategy is that frequently it is the male partner who makes sexual decisions, and women have less negotiating power. Women are considered feminine if they assume a passive role in sexual activity. This work suggests strategies to improve the negotiating power of women. Options and problems of speaking about safer sex vary in accordance with the nature of the relationship. A woman with a new partner can try to ascertain his sexual history, but may gain no information on his probable health even if he tells her the truth. It may be easier to convince him to use a condom at least in the beginning of the romance. Women working in the sex industry often have greater trouble convincing their friends and lovers to use a condom than their clients. Some family planning workers have begun to speak of safer sex with all their clients. Role playing and workshops or discussions with small groups of women having similar problems may help women overcome their reticence about discussing sexual topics. Some general suggestions to help women negotiate safer sex include choosing an opportune moment and planning in advance what to say; daring to speak directly without beating around the bush (the partner may also be gathering courage to speak); practicing placing condoms on objects and if necessary placing one on the partner without speaking; being honest with the partner about sex, love, and fidelity; and remembering that protection from condoms is mutual given that it is not possible to know who is infected. Until now, programs to help women practice safer sex have concentrated on sex industry

Safer Environment

EPA Pesticide Factsheets

The U.S. Environmental Protection Agency (EPA) has proposed Mercury and Air Toxics Standards (MATS) for power plants to limit mercury, acid gases and other toxic pollution from power plants. This page describes how new rules mean a safer environment.

Safer Systems: A NextGen Aviation Safety Strategic Goal

NASA Technical Reports Server (NTRS)

Darr, Stephen T.; Ricks, Wendell R.; Lemos, Katherine A.

2008-01-01

The Joint Planning and Development Office (JPDO), is charged by Congress with developing the concepts and plans for the Next Generation Air Transportation System (NextGen). The National Aviation Safety Strategic Plan (NASSP), developed by the Safety Working Group of the JPDO, focuses on establishing the goals, objectives, and strategies needed to realize the safety objectives of the NextGen Integrated Plan. The three goal areas of the NASSP are Safer Practices, Safer Systems, and Safer Worldwide. Safer Practices emphasizes an integrated, systematic approach to safety risk management through implementation of formalized Safety Management Systems (SMS) that incorporate safety data analysis processes, and the enhancement of methods for ensuring safety is an inherent characteristic of NextGen. Safer Systems emphasizes implementation of safety-enhancing technologies, which will improve safety for human-centered interfaces and enhance the safety of airborne and ground-based systems. Safer Worldwide encourages coordinating the adoption of the safer practices and safer systems technologies, policies and procedures worldwide, such that the maximum level of safety is achieved across air transportation system boundaries. This paper introduces the NASSP and its development, and focuses on the Safer Systems elements of the NASSP, which incorporates three objectives for NextGen systems: 1) provide risk reducing system interfaces, 2) provide safety enhancements for airborne systems, and 3) provide safety enhancements for ground-based systems. The goal of this paper is to expose avionics and air traffic management system developers to NASSP objectives and Safer Systems strategies.

Using Social Cognitive Theory to Predict Safer Sex Behaviors in African American College Students

ERIC Educational Resources Information Center

Kanekar, Amar; Sharma, Manoj

2009-01-01

Safer sex is important for protection against STDs and HIV/AIDS. Most of the HIV-related research is targeted towards high-risk groups such as prostitutes, gays and substance abusers there is evidence that HIV/AIDS is increasing in college students particularly among African-American college students. The purpose of this study was to study…

The Architecture of Chemical Alternatives Assessment.

PubMed

Geiser, Kenneth; Tickner, Joel; Edwards, Sally; Rossi, Mark

2015-12-01

Chemical alternatives assessment is a method rapidly developing for use by businesses, governments, and nongovernment organizations seeking to substitute chemicals of concern in production processes and products. Chemical alternatives assessment is defined as a process for identifying, comparing, and selecting safer alternatives to chemicals of concern (including those in materials, processes, or technologies) on the basis of their hazards, performance, and economic viability. The process is intended to provide guidance for assuring that chemicals of concern are replaced with safer alternatives that are not likely to be later regretted. Conceptually, the assessment methods are developed from a set of three foundational pillars and five common principles. Based on a number of emerging alternatives assessment initiatives, in this commentary, we outline a chemical alternatives assessment blueprint structured around three broad steps: Scope, Assessment, and Selection and Implementation. Specific tasks and tools are identified for each of these three steps. While it is recognized that on-going practice will further refine and develop the method and tools, it is important that the structure of the assessment process remain flexible, adaptive, and focused on the substitution of chemicals of concern with safer alternatives. © 2015 Society for Risk Analysis.

PREDICTING CHEMICAL RESIDUES IN AQUATIC FOOD CHAINS

EPA Science Inventory

The need to accurately predict chemical accumulation in aquatic organisms is critical for a variety of environmental applications including the assessment of contaminated sediments. Approaches for predicting chemical residues can be divided into two general classes, empirical an...

How to sell safer sex.

PubMed

Overs, C

1991-09-01

Social and economic factors determine the extent of the sex industry in societies. Despite AIDS, the sex industry will continue to thrive. Accordingly, health promotion strategies aimed at sex workers and their clients should not stem from the belief that the industry should cease to exist. This paper offers advice in developing and implementing programs to promote safer sex among sex workers. The social context is 1 element to consider in planning successful campaigns. Interventions must be combined with well-planned prevention campaigns aimed at entire populations. The opinions and participation of those involved in the industry should also be sought, while worker discussion and action upon other community issues should not be discouraged. Care should be given to target the numerous and diverse sex worker audiences in addition to other persons related to and involved in the industry. Programs should address the main obstacles to practicing safer sex, and attention should be given to ensure the provision of an adequate and regular supply of cheap or free condoms through varied distribution channels. In the area of service provision, sex workers need easy access to social support and health care services from which they are often excluded. Activities conducted around the world include the marketing of safer sex, distributing printed information on HIV and AIDS to clients, training sex workers to pass designated constructive ideas to others involved in the sex industry, referring sex workers to sex businesses supportive of safer sex practices, and developing street theater and cabaret shows in bars.

Correlates of safer sex communication among college students.

PubMed

Diiorio, C; Dudley, W N; Lehr, S; Soet, J E

2000-09-01

Correlates of safer sex communication among college students The purpose of this study was to examine factors that are thought to promote communication about safer sex and HIV among college students in the United States of America and to determine the extent to which communication about safer sex is important in the use of condoms. A better understanding of factors associated with safer sex communication can be helpful in developing HIV and STD prevention programmes for college students. Following approval from the institutional review boards of the six participating colleges and universities, researchers collected data from a random sample of students. The study included participant responses if participants were 18-25 years of age, single and sexually active. For the sample of 1349 participants, the mean age was 20.6 years. Sixty-three per cent of the sample was female, 50.5% white, 42.3% African-American, and the remainder of other ethnic groups. Over 50% of respondents reported frequent condom use, with 28% noting that they used a condom every time and 30.6% reporting condom use almost every time they had sex. Only 9.6% indicated that they never used a condom. The results of hierarchical multiple regression analysis revealed that the perception of quality of general communication with parents, the perception of a partner's attitude towards communication, communication self-efficacy, and communication outcome expectancies, were associated with safer sex communication. However, the association between safer sex communication and condom use was weak, suggesting that other factors excluded from this study are important in determining condom use for this sample of respondents. The findings provide some implications for HIV interventions. Interventions that enhance self-efficacy and positive outcome expectancies related to communication about safer sex are likely to foster discussion with a sexual partner. However, they might not lead to actual condom use.

Predictions of Chemical Species via Diode Laser Spectroscopy

NASA Technical Reports Server (NTRS)

Chen, Shin-Juh; Silver, Joel A.; Dahm, Werner J. A.; Piltch, Nancy D.; Salzman, Jack (Technical Monitor)

2001-01-01

A technique to predict temperature and chemical species in flames from absorbance measurement of one chemical species is presented. Predicted temperature and mole fractions of methane and water agreed well with measured and published results.

Using a narrative to spark safer sex communication.

PubMed

Donné, Lennie; Hoeks, John; Jansen, Carel

2017-10-01

College students are a group at risk for contracting sexually transmitted infections (STIs). While they are generally well informed about STIs, they do not consistently use condoms. An important element in preventing STIs is safer sex communication, especially with a sexual partner. This may be difficult, however, because of a lack of experience in talking about safer sex or because of the absence of suitable role models. In this study, a narrative intervention was tested that was developed to provide receivers with a social script for safer sex communication. An experiment was conducted among college students ( N  = 225) who were exposed to either a narrative intervention or a non-narrative (brochure) intervention, followed by a post-test questionnaire. In the narrative condition, part of the participants completed a pre-test questionnaire before being exposed to the intervention. Compared to pre-test scores, the narrative positively influenced safer sex communication intentions. The results show no significant differences between post-test scores of the narrative and the non-narrative condition. Mediation analyses showed that narrative processes (identification and transportation) were positively related to safer sex communication. In this study, we investigated both the effects of a narrative intervention on safer sex communication intentions, and the mechanisms of narrative processing underlying these effects. The narrative turned out to be as effective as a brochure version with the same information. Our mediation analyses suggest that narratives can be made more persuasive by increasing the reader's involvement with the story as a whole, and with one of the characters in particular.

Seismographs, sensors, and satellites: Better technology for safer communities

USGS Publications Warehouse

Groat, C.G.

2004-01-01

In the past 25 years, our ability to measure, monitor, and model the processes that lead to natural disasters has increased dramatically. Equally important has been the improvement in our technological capability to communicate information about hazards to those whose lives may be affected. These innovations in tracking and communicating the changes-floods, earthquakes, wildfires, volcanic eruptions-in our dynamic planet, supported by a deeper understanding of earth processes, enable us to expand our predictive capabilities and point the way to a safer future. ?? 2004 Elsevier Ltd. All rights reserved.

Using a narrative to spark safer sex communication

PubMed Central

Donné, Lennie; Hoeks, John; Jansen, Carel

2017-01-01

Objective: College students are a group at risk for contracting sexually transmitted infections (STIs). While they are generally well informed about STIs, they do not consistently use condoms. An important element in preventing STIs is safer sex communication, especially with a sexual partner. This may be difficult, however, because of a lack of experience in talking about safer sex or because of the absence of suitable role models. In this study, a narrative intervention was tested that was developed to provide receivers with a social script for safer sex communication. Design: An experiment was conducted among college students (N = 225) who were exposed to either a narrative intervention or a non-narrative (brochure) intervention, followed by a post-test questionnaire. In the narrative condition, part of the participants completed a pre-test questionnaire before being exposed to the intervention. Results: Compared to pre-test scores, the narrative positively influenced safer sex communication intentions. The results show no significant differences between post-test scores of the narrative and the non-narrative condition. Mediation analyses showed that narrative processes (identification and transportation) were positively related to safer sex communication. Conclusion: In this study, we investigated both the effects of a narrative intervention on safer sex communication intentions, and the mechanisms of narrative processing underlying these effects. The narrative turned out to be as effective as a brochure version with the same information. Our mediation analyses suggest that narratives can be made more persuasive by increasing the reader’s involvement with the story as a whole, and with one of the characters in particular. PMID:28919639

Safer Choice Partner of the Year Awards Application Form

EPA Pesticide Factsheets

EPA's Design for the Environment program developed the Safer Product Labeling Program Partner of the Year Award program to recognize DfE stakeholders that have furthered the safer chemistry goals of the program

Determinants of Safer Sex Behaviors among College Students

ERIC Educational Resources Information Center

Kanekar, Amar; Sharma, Manoj

2010-01-01

Safer sex behaviors (monogamy, sexual abstinence, correct and consistent condom usage) are important for prevention of sexually transmitted diseases and HIV/AIDS among college students. The purpose of this article was to review studies addressing determinants of safer sex behaviors among college students. In order to collect materials for this…

Prediction of Chemical Function: Model Development and ...

EPA Pesticide Factsheets

The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

The applicability of chemical alternatives assessment for engineered nanomaterials.

PubMed

Hjorth, Rune; Hansen, Steffen Foss; Jacobs, Molly; Tickner, Joel; Ellenbecker, Michael; Baun, Anders

2017-01-01

The use of alternatives assessment to substitute hazardous chemicals with inherently safer options is gaining momentum worldwide as a legislative and corporate strategy to minimize consumer, occupational, and environmental risks. Engineered nanomaterials represent an interesting case for alternatives assessment approaches, because they can be considered both emerging "chemicals" of concern, as well as potentially safer alternatives to hazardous chemicals. However, comparing the hazards of nanomaterials to traditional chemicals or to other nanomaterials is challenging, and critical elements in chemical hazard and exposure assessment may have to be fundamentally altered to sufficiently address nanomaterials. The aim of this paper is to assess the overall applicability of alternatives assessment methods for nanomaterials and to outline recommendations to enhance their use in this context. The present paper focuses on the adaptability of existing hazard and exposure assessment approaches to engineered nanomaterials as well as strategies to design inherently safer nanomaterials. We argue that alternatives assessment for nanomaterials is complicated by the sheer number of nanomaterials possible. As a result, the inclusion of new data tools that can efficiently and effectively evaluate nanomaterials as substitutes is needed to strengthen the alternatives assessment process. However, we conclude that with additional tools to enhance traditional hazard and exposure assessment modules of alternatives assessment, such as the use of mechanistic toxicity screens and control banding tools, alternatives assessment can be adapted to evaluate engineered nanomaterials as potential substitutes for chemicals of concern and to ensure safer nanomaterials are incorporated in the design of new products. Integr Environ Assess Manag 2017;13:177-187. © 2016 SETAC. © 2016 SETAC.

EPA'S TOXCAST PROGRAM FOR PREDICTING TOXICITY AND PRIORITIZING ENVIRONMENTAL CHEMICALS

EPA Science Inventory

ToxCast is a research program to predict or forecast toxicity by evaluating a broad spectrum of chemicals and effects; physical-chemical properties, predicted bioactivities, HTS and cell-based assays, and genomics. Data will be interpretively linked to known or predicted toxicol...

Wear your hat: representational resistance in safer sex discourse.

PubMed

Nelson, S D

1994-01-01

Through an analysis of four posters used by the AIDS Action Committee of Massachusetts, this article asks how representation can effectively promote safer sex practices. The images under investigation have different targeted groups--one is aimed at African-American men, one at Latinas, and two at gay men. Using a frame-work that connects definitions of sex in the respective communities with differences surrounding gender, race, and class, the imagery is unpacked in order to expose the effects of safer sex representation. This essay then argues that the degree to which ingrained definitions of sex are challenged constitutes a determining factor in the success or failure of safer sex representations.

Safer stops for vulnerable customers

DOT National Transportation Integrated Search

2003-03-01

This synthesis report presents a brief synopsis of the current literature and technologies being used in the development of safer and more secure bus stops. While the focus is more specifically with regard to vulnerable populations - women, children,...

Responsible men, blameworthy women: Black heterosexual men's discursive constructions of safer sex and masculinity.

PubMed

Bowleg, Lisa; Heckert, Andrea L; Brown, Tia L; Massie, Jenné S

2015-04-01

Although Black heterosexual men (BHM) in the United States rank among those most affected by HIV, research about how safer sex messages shape their safer sex behaviors is rare, highlighting the need for innovative qualitative methodologies such as critical discursive psychology (CDP). This CDP study examined how: (a) BHM construct safer sex and masculinity; (b) BHM positioned themselves in relation to conventional masculinity; and (c) discursive context (individual interview vs. focus group) shaped talk about safer sex and masculinity. Data included individual interviews (n = 30) and 4 focus groups (n = 26) conducted with 56 self-identified Black/African American heterosexual men, ages 18 to 44. Analyses highlighted 5 main constructions: (a) condoms as signifiers of "safe" women; (b) blaming women for STI/responsibility for safer sex; (c) relationship/trust/knowledge; (d) condom mandates; and (e) public health safer sex. Discourses positioned BHM in terms of conventional masculinity when talk denied men's agency for safer sex and/or contraception, or positioned women as deceitful, or apathetic about sexual risk and/or pregnancy. Notably, discourses also spotlighted alternative masculinities relevant to taking responsibility for safer sex or sexual exclusivity. Discursive context, namely the homosocial nature of focus group discussions, shaped how participants conversed about safer sex, and masculinity but not the content of that talk. In denying BHM's responsibility for safer sex, BHM's discourses about safer sex and masculinity often mirror public health messages, underscoring a critical need to sync these discourses to reduce sexual risk, and develop gender-transformative safer sex interventions for BHM. (c) 2015 APA, all rights reserved).

Safer choices: reducing teen pregnancy, HIV, and STDs.

PubMed Central

Coyle, K.; Basen-Engquist, K.; Kirby, D.; Parcel, G.; Banspach, S.; Collins, J.; Baumler, E.; Carvajal, S.; Harrist, R.

2001-01-01

OBJECTIVES: This study evaluated the long-term effectiveness of Safer Choices, a theory-based, multi-component educational program designed to reduce sexual risk behaviors and increase protective behaviors in preventing HIV, other STDs, and pregnancy among high school students. METHODS: The study used a randomized controlled trial involving 20 high schools in California and Texas. A cohort of 3869 ninth-grade students was tracked for 31 months from fall semester 1993 (baseline) to spring semester 1996 (31-month follow-up). Data were collected using self-report surveys administered by trained data collectors. Response rate at 31-month follow-up was 79%. RESULTS: Safer Choices had its greatest effect on measures involving condom use. The program reduced the frequency of intercourse without a condom during the three months prior to the survey, reduced the number of sexual partners with whom students had intercourse without a condom, and increased use of condoms and other protection against pregnancy at last intercourse. Safer Choices also improved 7 of 13 psychosocial variables, many related to condom use, but did not have a significant effect upon rates of sexual initiation. CONCLUSIONS: The Safer Choices program was effective in reducing important risk behaviors for HIV, other STDs, and pregnancy and in enhancing most psychosocial determinants of such behavior. PMID:11889277

Application of the industrial hygiene hierarchy of controls to prioritize and promote safer methods of pest control: a case study.

PubMed

Weinberg, Justine Lew; Bunin, Lisa J; Das, Rupali

2009-01-01

In 2005, the California Department of Public Health, Occupational Health Branch (OHB) investigated an incident of pesticide exposure and identified 27 vineyard workers who became ill due to drift of cyfluthrin, a pesticide being applied to a neighboring orange field to control katydids. Another pest, citrus thrips, was also present in the field. We investigated safer alternatives for katydid and thrips control to prevent illness due to pesticide exposure and used the industrial hygiene hierarchy of controls to prioritize the control methods. OHB evaluated factors that contributed to pesticide exposure and identified safer alternatives by conducting literature reviews on katydid and thrips control, drift prevention technology, and other relevant topics, and by interviewing integrated pest management advisors, conventional and organic growers, equipment manufacturers, county agricultural commissioners, pest control advisors, regulatory agencies, and others. We prioritized methods using the industrial hygiene hierarchy of controls. We identified safer pest control practices that incorporated hazard elimination, chemical substitution, engineering controls, and administrative controls, including employer policies and government regulations.

Shopping for a safer car

DOT National Transportation Integrated Search

2010-01-01

This brochure provides some helpful tips on what to look for when shopping for a safer car. Automakers are increasingly advertising the safety features of their cars. The problem is sorting out their claims and zeroing in on the safety features that ...

Safer-drinking Strategies Used by Chronically Homeless Individuals with Alcohol Dependence

PubMed Central

Grazioli, Véronique S.; Hicks, Jennifer; Kaese, Greta; Lenert, James; Collins, Susan E.

2015-01-01

Chronically homeless individuals with alcohol dependence experience severe alcohol-related consequences. It is therefore important to identify factors that might be associated with reduced alcohol-related harm, such as the use of safer-drinking strategies. Whereas effectiveness of safer-drinking strategies has been well-documented among young adults, no studies have explored this topic among more severely affected populations, such as chronically homeless individuals with alcohol dependence. The aims of this study were thus to qualitatively and quantitatively document safer-drinking strategies used in this population. Participants (N=31) were currently or formerly chronically homeless individuals with alcohol dependence participating in a pilot study of extended-release naltrexone and harm-reduction counseling. At weeks 0 and 8, research staff provided a list of safer-drinking strategies for participants to endorse. Implementation of endorsed safer-drinking strategies was recorded at the next appointment. At both time points, strategies to buffer the effects of alcohol on the body (e.g., eating prior to and during drinking) were most highly endorsed, followed by changing the manner in which one drinks (e.g., spacing drinks), and reducing alcohol consumption. Quantitative analyses indicated that all participants endorsed safer-drinking strategies, and nearly all strategies were implemented (80–90% at weeks 0 and 8, respectively). These preliminary findings indicate that chronically homeless people with alcohol dependence use strategies to reduce harm associated with their drinking. Larger randomized controlled trials are needed to test whether interventions that teach safer-drinking strategies may reduce overall alcohol-related harm in this population. PMID:25690515

Integrating MBSE into Ongoing Projects: Requirements Validation and Test Planning for the ISS SAFER

NASA Technical Reports Server (NTRS)

Anderson, Herbert A.; Williams, Antony; Pierce, Gregory

2016-01-01

The International Space Station (ISS) Simplified Aid for Extra Vehicular Activity (EVA) Rescue (SAFER) is the spacewalking astronaut's final safety measure against separating from the ISS and being unable to return safely. Since the late 1990s, the SAFER has been a standard element of the spacewalking astronaut's equipment. The ISS SAFER project was chartered to develop a new block of SAFER units using a highly similar design to the legacy SAFER (known as the USA SAFER). An on-orbit test module was also included in the project to enable periodic maintenance/propulsion system checkout on the ISS SAFER. On the ISS SAFER project, model-based systems engineering (MBSE) was not the initial systems engineering (SE) approach, given the volume of heritage systems engineering and integration (SE&I) products. The initial emphasis was ensuring traceability to ISS program standards as well as to legacy USA SAFER requirements. The requirements management capabilities of the Cradle systems engineering tool were to be utilized to that end. During development, however, MBSE approaches were applied selectively to address specific challenges in requirements validation and test and verification (T&V) planning, which provided measurable efficiencies to the project. From an MBSE perspective, ISS SAFER development presented a challenge and an opportunity. Addressing the challenge first, the project was tasked to use the original USA SAFER operational and design requirements baseline, with a number of additional ISS program requirements to address evolving certification expectations for systems operating on the ISS. Additionally, a need to redesign the ISS SAFER avionics architecture resulted in a set of changes to the design requirements baseline. Finally, the project added an entirely new functionality for on-orbit maintenance. After initial requirements integration, the system requirements count was approaching 1000, which represented a growth of 4x over the original USA SAFER system

Correlation of chemical shifts predicted by molecular dynamics simulations for partially disordered proteins.

PubMed

Karp, Jerome M; Eryilmaz, Ertan; Erylimaz, Ertan; Cowburn, David

2015-01-01

There has been a longstanding interest in being able to accurately predict NMR chemical shifts from structural data. Recent studies have focused on using molecular dynamics (MD) simulation data as input for improved prediction. Here we examine the accuracy of chemical shift prediction for intein systems, which have regions of intrinsic disorder. We find that using MD simulation data as input for chemical shift prediction does not consistently improve prediction accuracy over use of a static X-ray crystal structure. This appears to result from the complex conformational ensemble of the disordered protein segments. We show that using accelerated molecular dynamics (aMD) simulations improves chemical shift prediction, suggesting that methods which better sample the conformational ensemble like aMD are more appropriate tools for use in chemical shift prediction for proteins with disordered regions. Moreover, our study suggests that data accurately reflecting protein dynamics must be used as input for chemical shift prediction in order to correctly predict chemical shifts in systems with disorder.

Type I and II β-turns prediction using NMR chemical shifts.

PubMed

Wang, Ching-Cheng; Lai, Wen-Chung; Chuang, Woei-Jer

2014-07-01

A method for predicting type I and II β-turns using nuclear magnetic resonance (NMR) chemical shifts is proposed. Isolated β-turn chemical-shift data were collected from 1,798 protein chains. One-dimensional statistical analyses on chemical-shift data of three classes β-turn (type I, II, and VIII) showed different distributions at four positions, (i) to (i + 3). Considering the central two residues of type I β-turns, the mean values of Cο, Cα, H(N), and N(H) chemical shifts were generally (i + 1) > (i + 2). The mean values of Cβ and Hα chemical shifts were (i + 1) < (i + 2). The distributions of the central two residues in type II and VIII β-turns were also distinguishable by trends of chemical shift values. Two-dimensional cluster analyses on chemical-shift data show positional distributions more clearly. Based on these propensities of chemical shift classified as a function of position, rules were derived using scoring matrices for four consecutive residues to predict type I and II β-turns. The proposed method achieves an overall prediction accuracy of 83.2 and 84.2% with the Matthews correlation coefficient values of 0.317 and 0.632 for type I and II β-turns, indicating that its higher accuracy for type II turn prediction. The results show that it is feasible to use NMR chemical shifts to predict the β-turn types in proteins. The proposed method can be incorporated into other chemical-shift based protein secondary structure prediction methods.

Predicting carcinogenicity of diverse chemicals using probabilistic neural network modeling approaches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singh, Kunwar P., E-mail: kpsingh_52@yahoo.com; Environmental Chemistry Division, CSIR-Indian Institute of Toxicology Research, Post Box 80, Mahatma Gandhi Marg, Lucknow 226 001; Gupta, Shikha

Robust global models capable of discriminating positive and non-positive carcinogens; and predicting carcinogenic potency of chemicals in rodents were developed. The dataset of 834 structurally diverse chemicals extracted from Carcinogenic Potency Database (CPDB) was used which contained 466 positive and 368 non-positive carcinogens. Twelve non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals and nonlinearity in the data were evaluated using Tanimoto similarity index and Brock–Dechert–Scheinkman statistics. Probabilistic neural network (PNN) and generalized regression neural network (GRNN) models were constructed for classification and function optimization problems using the carcinogenicity end point in rat. Validation of the models wasmore » performed using the internal and external procedures employing a wide series of statistical checks. PNN constructed using five descriptors rendered classification accuracy of 92.09% in complete rat data. The PNN model rendered classification accuracies of 91.77%, 80.70% and 92.08% in mouse, hamster and pesticide data, respectively. The GRNN constructed with nine descriptors yielded correlation coefficient of 0.896 between the measured and predicted carcinogenic potency with mean squared error (MSE) of 0.44 in complete rat data. The rat carcinogenicity model (GRNN) applied to the mouse and hamster data yielded correlation coefficient and MSE of 0.758, 0.71 and 0.760, 0.46, respectively. The results suggest for wide applicability of the inter-species models in predicting carcinogenic potency of chemicals. Both the PNN and GRNN (inter-species) models constructed here can be useful tools in predicting the carcinogenicity of new chemicals for regulatory purposes. - Graphical abstract: Figure (a) shows classification accuracies (positive and non-positive carcinogens) in rat, mouse, hamster, and pesticide data yielded by optimal PNN model. Figure (b) shows generalization and

Predicting the chemical stability of monatomic chains

NASA Astrophysics Data System (ADS)

Lin, Zheng-Zhe; Chen, Xi

2013-02-01

A simple model for evaluating the thermal atomic transfer rates in nanosystems (Lin Z.-Z. et al., EPL, 94 (2011) 40002) was developed to predict the chemical reaction rates of nanosystems with small gas molecules. The accuracy of the model was verified by MD simulations for molecular adsorption and desorption on a monatomic chain. By the prediction, a monatomic carbon chain should survive for 1.2 × 102 years in the ambient of 1 atm O2 at room temperature, and it is very invulnerable to N2, H2O, NO2, CO and CO2, while a monatomic gold chain quickly ruptures in vacuum. It is worth noting that since the model can be easily applied via common ab initio calculations, it could be widely used in the prediction of chemical stability of nanosystems.

A Market-Basket Approach to Predict the Acute Aquatic Toxicity of Munitions and Energetic Materials.

PubMed

Burgoon, Lyle D

2016-06-01

An ongoing challenge in chemical production, including the production of insensitive munitions and energetics, is the ability to make predictions about potential environmental hazards early in the process. To address this challenge, a quantitative structure activity relationship model was developed to predict acute fathead minnow toxicity of insensitive munitions and energetic materials. Computational predictive toxicology models like this one may be used to identify and prioritize environmentally safer materials early in their development. The developed model is based on the Apriori market-basket/frequent itemset mining approach to identify probabilistic prediction rules using chemical atom-pairs and the lethality data for 57 compounds from a fathead minnow acute toxicity assay. Lethality data were discretized into four categories based on the Globally Harmonized System of Classification and Labelling of Chemicals. Apriori identified toxicophores for categories two and three. The model classified 32 of the 57 compounds correctly, with a fivefold cross-validation classification rate of 74 %. A structure-based surrogate approach classified the remaining 25 chemicals correctly at 48 %. This result is unsurprising as these 25 chemicals were fairly unique within the larger set.

Safer sex in tourist resorts.

PubMed

Ford, N; Inman, M

1992-01-01

A survey in Torbay, England, indicated substantial sexual interaction of an unsafe kind between young residents and tourists. A pilot programme is described which sought to promote safer sexual behaviour: the attention of both tourists and local people who frequented nightclubs was engaged by peer groups who conveyed educational messages.

The safer clinical systems project in renal care.

PubMed

Weale, Andy R

2013-09-01

Current systems in place in healthcare are designed to detect harm after it has happened (e.g critical incident reports) and make recommendations based on an assessment of that event. Safer Clinical Systems, a Health Foundation funded project, is designed to proactively search for risk within systems, rather than being reactive to harm. The aim of the Safer Clinical Systems project in Renal Care was to reduce the risks associated with shared care for patients who are undergoing surgery but are looked after peri-operatively by nephrology teams on nephrology wards. This report details our findings of the diagnostic phase of Safer Clinical Systems: the proactive search for risk. We have evaluated the current system of care using a set of risk evaluation and process mapping tools (Failure Modes and Effects Analysis (FMEA) and Hierarchical Task Analysis HTA). We have engaged staff with the process mapping and risk assessment tools. We now understand our system and understand where the highest risk tasks are undertaken during a renal in-patient stay during which a patient has an operation. These key tasks occur across the perioperaive period and are not confined to one aspect of care. A measurement strategy and intervention plan have been designed around these tasks. Safer Clinical Systems has identified high risk, low reliability tasks in our system. We look forward to fully reporting these data in 2014. © 2013 European Dialysis and Transplant Nurses Association/European Renal Care Association.

High-throughput dietary exposure predictions for chemical migrants from food contact substances for use in chemical prioritization.

PubMed

Biryol, Derya; Nicolas, Chantel I; Wambaugh, John; Phillips, Katherine; Isaacs, Kristin

2017-11-01

Under the ExpoCast program, United States Environmental Protection Agency (EPA) researchers have developed a high-throughput (HT) framework for estimating aggregate exposures to chemicals from multiple pathways to support rapid prioritization of chemicals. Here, we present methods to estimate HT exposures to chemicals migrating into food from food contact substances (FCS). These methods consisted of combining an empirical model of chemical migration with estimates of daily population food intakes derived from food diaries from the National Health and Nutrition Examination Survey (NHANES). A linear regression model for migration at equilibrium was developed by fitting available migration measurements as a function of temperature, food type (i.e., fatty, aqueous, acidic, alcoholic), initial chemical concentration in the FCS (C 0 ) and chemical properties. The most predictive variables in the resulting model were C 0 , molecular weight, log K ow , and food type (R 2 =0.71, p<0.0001). Migration-based concentrations for 1009 chemicals identified via publicly-available data sources as being present in polymer FCSs were predicted for 12 food groups (combinations of 3 storage temperatures and food type). The model was parameterized with screening-level estimates of C 0 based on the functional role of chemicals in FCS. By combining these concentrations with daily intakes for food groups derived from NHANES, population ingestion exposures of chemical in mg/kg-bodyweight/day (mg/kg-BW/day) were estimated. Calibrated aggregate exposures were estimated for 1931 chemicals by fitting HT FCS and consumer product exposures to exposures inferred from NHANES biomonitoring (R 2 =0.61, p<0.001); both FCS and consumer product pathway exposures were significantly predictive of inferred exposures. Including the FCS pathway significantly impacted the ratio of predicted exposures to those estimated to produce steady-state blood concentrations equal to in-vitro bioactive concentrations

Safer childbirth: a rights-based approach.

PubMed

Boama, Vincent; Arulkumaran, Sabaratnam

2009-08-01

The Millennium Development Goals (MDGs) set very high targets for women's reproductive health through reductions in maternal and infant mortality, among other things. Reductions in maternal mortality and morbidity can be achieved through various different approaches, such as the confidential review of maternal deaths, use of evidence-based treatments and interventions, using a health systems approach, use of information technology, global and regional partnerships, and making pregnancy safer through initiatives that increase the focus on human rights. A combination of these and other approaches can have a synergistic impact on reductions in maternal mortality. This paper highlights some of the current global efforts on safer pregnancy with a focus on reproductive rights. We encourage readers to do more in every corner of the world to advocate for women's reproductive rights and, in this way, we may achieve the MDGs by 2015.

Seriously mentally ill women's safer sex behaviors and the theory of reasoned action.

PubMed

Randolph, Mary E; Pinkerton, Steven D; Somlai, Anton M; Kelly, Jeffrey A; McAuliffe, Timothy L; Gibson, Richard H; Hackl, Kristin

2009-10-01

Seriously mentally ill women at risk for HIV infection (n = 96) participated in structured interviews assessing sexual and substance-use behavior over a 3-month period. The majority of the women (63.5%) did not use condoms. Consistent with the theory of reasoned action, attitudes toward condom use and perceived social norms about safer sex were associated with safer sex intentions. Supplementing variables from the theory of reasoned action with safer sex self-efficacy explained additional variance in safer sex intentions. Greater safer sex intentions were related to both greater condom use and less frequent unprotected intercourse. In addition, less frequent sex after drug use and a less fatalistic outlook were associated with less frequent unprotected intercourse. Life circumstances specific to this population are particularly important to examine to improve the effectiveness of risk reduction interventions for seriously mentally ill women.

SAFER CVIEW interface re-certification : description of re-certification process for CVISN stakeholders : version 1.0

DOT National Transportation Integrated Search

2008-04-23

In order to improve data quality in the SAFER system, two major software changes have been made in the recent SAFER releases. SAFER version 4.9, released in October 2005, has implemented data rules (SAFER CR 131) to support the requirements for manda...

Gaming for Safer Sex: Young German and Turkish People Report No Specific Culture-Related Preferences Toward Educational Games Promoting Safer Sex.

PubMed

Brüll, Phil; Ruiter, Robert A C; Wiers, Reinout W; Kok, Gerjo

2016-12-01

Comprehensive sex education programs specifically designed for adolescents and young adults that take into account gender norms and cultural background have shown promise as a means of countering the high sexually transmitted infection rate in young people. Recently, digital gaming interventions delivered on computers or mobile devices have emerged as another way to promote safer sex behavior in a young population. Tailoring these computer-based interventions to their target population has been recognized to increase positive behavior outcomes. In this qualitative study, we investigated whether young female and male adults from two different cultural backgrounds (all living in Germany) would have different preferences and needs in relation to an educational game promoting safer sex. We conducted four semistructured focus group interviews comprising open-ended questions with male and female participants who had either a German or a Turkish background. In total, 20 individuals, aged between 18 and 22 years, from two socially diverse and ethnically mixed vocational schools in Germany participated. Independent of cultural background and gender, participants preferred a real-world design with a first-person visual perspective over a fantasy-like third-person perspective. Furthermore, they preferred highly customizable avatars. All participants mentioned the importance of including an alcohol-intoxicated avatar and most participants wanted there to be additional information available about various safer sex approaches and about the use of different barrier protection methods. Males and females reported similar preferences for the design of an educational game promoting safer sex, with the only difference being exactly how the topic of having sexual intercourse should be addressed in the game. Males preferred a direct approach, whereas females had a preference for treating this subject more sympathetically. Educational games offer anonymity and can provide young people

Safety and fitness electronic records system (SAFER) : draft master test plan

DOT National Transportation Integrated Search

1995-12-31

The purpose of this plan is to establish a formal set of guidelines and activities to be : adhered to and performed by JHU/APL and the developer to ensure that the SAFER System has been tested successfully and is fully compliant with the SAFER System...

An integrated multi-label classifier with chemical-chemical interactions for prediction of chemical toxicity effects.

PubMed

Liu, Tao; Chen, Lei; Pan, Xiaoyong

2018-05-31

Chemical toxicity effect is one of the major reasons for declining candidate drugs. Detecting the toxicity effects of all chemicals can accelerate the procedures of drug discovery. However, it is time-consuming and expensive to identify the toxicity effects of a given chemical through traditional experiments. Designing quick, reliable and non-animal-involved computational methods is an alternative way. In this study, a novel integrated multi-label classifier was proposed. First, based on five types of chemical-chemical interactions retrieved from STITCH, each of which is derived from one aspect of chemicals, five individual classifiers were built. Then, several integrated classifiers were built by integrating some or all individual classifiers. By testing the integrated classifiers on a dataset with chemicals and their toxicity effects in Accelrys Toxicity database and non-toxic chemicals with their performance evaluated by jackknife test, an optimal integrated classifier was selected as the proposed classifier, which provided quite high prediction accuracies and wide applications. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Predictive Modeling of Chemical Hazard by Integrating Numerical Descriptors of Chemical Structures and Short-term Toxicity Assay Data

PubMed Central

Rusyn, Ivan; Sedykh, Alexander; Guyton, Kathryn Z.; Tropsha, Alexander

2012-01-01

Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction of in vivo toxicity of drug candidates or environmental chemicals, adding value to candidate selection in drug development or in a search for less hazardous and more sustainable alternatives for chemicals in commerce. The development of traditional QSAR models is enabled by numerical descriptors representing the inherent chemical properties that can be easily defined for any number of molecules; however, traditional QSAR models often have limited predictive power due to the lack of data and complexity of in vivo endpoints. Although it has been indeed difficult to obtain experimentally derived toxicity data on a large number of chemicals in the past, the results of quantitative in vitro screening of thousands of environmental chemicals in hundreds of experimental systems are now available and continue to accumulate. In addition, publicly accessible toxicogenomics data collected on hundreds of chemicals provide another dimension of molecular information that is potentially useful for predictive toxicity modeling. These new characteristics of molecular bioactivity arising from short-term biological assays, i.e., in vitro screening and/or in vivo toxicogenomics data can now be exploited in combination with chemical structural information to generate hybrid QSAR–like quantitative models to predict human toxicity and carcinogenicity. Using several case studies, we illustrate the benefits of a hybrid modeling approach, namely improvements in the accuracy of models, enhanced interpretation of the most predictive features, and expanded applicability domain for wider chemical space coverage. PMID:22387746

Computational prediction of chemical reactions: current status and outlook.

PubMed

Engkvist, Ola; Norrby, Per-Ola; Selmi, Nidhal; Lam, Yu-Hong; Peng, Zhengwei; Sherer, Edward C; Amberg, Willi; Erhard, Thomas; Smyth, Lynette A

2018-06-01

Over the past few decades, various computational methods have become increasingly important for discovering and developing novel drugs. Computational prediction of chemical reactions is a key part of an efficient drug discovery process. In this review, we discuss important parts of this field, with a focus on utilizing reaction data to build predictive models, the existing programs for synthesis prediction, and usage of quantum mechanics and molecular mechanics (QM/MM) to explore chemical reactions. We also outline potential future developments with an emphasis on pre-competitive collaboration opportunities. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Application of quantum-chemical methods to prediction of the carcinogenicity of chemical substances].

PubMed

Zholdikova, Z I; Kharchevnikova, N V

2006-01-01

A version of logical-combinatorial JSM type intelligent system was used to predict the presence and the degree of a carcinogenic effect. This version was based on combined description of chemical substances including both structural and numeric parameters. The new version allows for the fact that the toxicity and danger caused by chemical substances often depend on their biological activation in the organism. The authors substantiate classifying chemicals according to their carcinogenic activity, and illustrate the use of the system to predict the carcinogenicity of polycyclic aromatic hydrocarbons using a model of bioactivation via the formation of diolepoxides, and the carcinogenicity of halogenated alkanes using a model of bioactivation via oxidative dehalogenation. The paper defined the boundary level of an energetic parameter, the exceeding of which correlated with the inhibition of halogenated alkanes's metabolism and the absence of carcinogenic activity.

Predicting drug side-effect profiles: a chemical fragment-based approach

PubMed Central

2011-01-01

Background Drug side-effects, or adverse drug reactions, have become a major public health concern. It is one of the main causes of failure in the process of drug development, and of drug withdrawal once they have reached the market. Therefore, in silico prediction of potential side-effects early in the drug discovery process, before reaching the clinical stages, is of great interest to improve this long and expensive process and to provide new efficient and safe therapies for patients. Results In the present work, we propose a new method to predict potential side-effects of drug candidate molecules based on their chemical structures, applicable on large molecular databanks. A unique feature of the proposed method is its ability to extract correlated sets of chemical substructures (or chemical fragments) and side-effects. This is made possible using sparse canonical correlation analysis (SCCA). In the results, we show the usefulness of the proposed method by predicting 1385 side-effects in the SIDER database from the chemical structures of 888 approved drugs. These predictions are performed with simultaneous extraction of correlated ensembles formed by a set of chemical substructures shared by drugs that are likely to have a set of side-effects. We also conduct a comprehensive side-effect prediction for many uncharacterized drug molecules stored in DrugBank, and were able to confirm interesting predictions using independent source of information. Conclusions The proposed method is expected to be useful in various stages of the drug development process. PMID:21586169

Predicting Chemical Toxicity from Proteomics and Computational Chemistry

DTIC Science & Technology

2008-07-30

similarity spaces, BD Gute and SC Basak, SAR QSAR Environ. Res., 17, 37-51 (2006). Predicting pharmacological and toxicological activity of heterocyclic...affinity of dibenzofurans: a hierarchical QSAR approach, authored jointly by Basak and Mills; Division of Chemical Toxicology iii. Prediction of blood...biodescriptors vis-ä-vis chemodescriptors in predictive toxicology e) Development of integrated QSTR models using the combined set of chemodescriptors and

Characterization and Prediction of Chemical Functions and ...

EPA Pesticide Factsheets

Assessing exposures from the thousands of chemicals in commerce requires quantitative information on the chemical constituents of consumer products. Unfortunately, gaps in available composition data prevent assessment of exposure to chemicals in many products. Here we propose filling these gaps via consideration of chemical functional role. We obtained function information for thousands of chemicals from public sources and used a clustering algorithm to assign chemicals into 35 harmonized function categories (e.g., plasticizers, antimicrobials, solvents). We combined these functions with weight fraction data for 4115 personal care products (PCPs) to characterize the composition of 66 different product categories (e.g., shampoos). We analyzed the combined weight fraction/function dataset using machine learning techniques to develop quantitative structure property relationship (QSPR) classifier models for 22 functions and for weight fraction, based on chemical-specific descriptors (including chemical properties). We applied these classifier models to a library of 10196 data-poor chemicals. Our predictions of chemical function and composition will inform exposure-based screening of chemicals in PCPs for combination with hazard data in risk-based evaluation frameworks. As new information becomes available, this approach can be applied to other classes of products and the chemicals they contain in order to provide essential consumer product data for use in exposure-b

Artificial Neural Network Prediction of Chemical-Disease Relationships using Readily Available Chemical Properties

DTIC Science & Technology

2014-03-27

C15H13N3O4S Potassium Bromide 0119000100 BrK Potassium Permanganate 0158030400 MnO4K Prazosin 0383410801 C19H21N5O4 Propranolol-HCl 0259350302...chemicals and correctly match it to a single disease category. Potassium permanganate and ethylene glycol can both be correctly linked to disease group...chemical is linked to the same disease, the network is unable to predict the same disease for the multiple chemicals. Potassium permanganate and

EPAs ToxCast Research Program: Developing Predictive Bioactivity Signatures for Chemicals

EPA Science Inventory

The international community needs better predictive tools for assessing the hazards and risks of chemicals. It is technically feasible to collect bioactivity data on virtually all chemicals of potential concern ToxCast is providing a proof of concept for obtaining predictive, b...

70 Years of Making the World Safer

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

This video shows our roles in making the world safer — working to end World War II, providing stable isotopes for research, providing unique precision manufacturing capabilities, and meeting nonproliferation and global security missions.

Chemical structure-based predictive model for methanogenic anaerobic biodegradation potential.

PubMed

Meylan, William; Boethling, Robert; Aronson, Dallas; Howard, Philip; Tunkel, Jay

2007-09-01

Many screening-level models exist for predicting aerobic biodegradation potential from chemical structure, but anaerobic biodegradation generally has been ignored by modelers. We used a fragment contribution approach to develop a model for predicting biodegradation potential under methanogenic anaerobic conditions. The new model has 37 fragments (substructures) and classifies a substance as either fast or slow, relative to the potential to be biodegraded in the "serum bottle" anaerobic biodegradation screening test (Organization for Economic Cooperation and Development Guideline 311). The model correctly classified 90, 77, and 91% of the chemicals in the training set (n = 169) and two independent validation sets (n = 35 and 23), respectively. Accuracy of predictions of fast and slow degradation was equal for training-set chemicals, but fast-degradation predictions were less accurate than slow-degradation predictions for the validation sets. Analysis of the signs of the fragment coefficients for this and the other (aerobic) Biowin models suggests that in the context of simple group contribution models, the majority of positive and negative structural influences on ultimate degradation are the same for aerobic and methanogenic anaerobic biodegradation.

Seriously Mentally Ill Women’s Safer Sex Behaviors and the Theory of Reasoned Action

PubMed Central

Randolph, Mary E.; Pinkerton, Steven D.; Somlai, Anton M.; Kelly, Jeffrey A.; Gibson, Richard H.; Hackl, Kristin

2014-01-01

Seriously mentally ill women at risk for HIV infection (n = 96) participated in structured interviews assessing sexual and substance use behavior over a 3-month period. The majority of the women (63.5%) did not use condoms. Consistent with the Theory of Reasoned Action, condom use attitudes and perceived social norms about safer sex were associated with safer sex intentions. Supplementing TRA variables with safer sex self-efficacy explained additional variance in safer sex intentions. Greater safer sex intentions were related to both greater condom use and to less frequent unprotected intercourse. In addition, less frequent sex after drug use and a less fatalistic outlook were associated with less frequent unprotected intercourse. Life circumstances specific to this population are particularly important to examine to improve the effectiveness of risk reduction interventions for seriously mentally ill women. PMID:19458268

Using Technology to Create Safer Schools.

ERIC Educational Resources Information Center

Townley, Arthur J.; Martinez, Kenneth

1995-01-01

Although classes to create student self-esteem and antigang programs are gaining in popularity, most school districts have not used available technology to help create safer campuses. Increased availability of telephones and two-way radios would enhance school security, along with incorporation of newer technologies such as computers, digitized…

Chemical Strips Anodic Film From Aluminum

NASA Technical Reports Server (NTRS)

Eichinger, Eric C.

1993-01-01

Phosphoric acid solution offers advantages over other stripping solutions. More effective than other strippers and safer to use. Relatively environmentally benign, phosphoric acid stripper ceases its chemical attack so less process control is needed in its use.

Evaluation of the California Safer Consumer Products Regulation and the impact on consumers and product manufacturers.

PubMed

Cowan, Dallas M; Kingsbury, Tony; Perez, Angela L; Woods, Tyler A; Kovochich, Michael; Hill, Denise S; Madl, Amy K; Paustenbach, Dennis J

2014-02-01

Chemistry enables more than 95% of products in the marketplace. Over the past 20 years, various entities began to generate inventories of chemicals ("chemical watch lists") potentially associated with human or environmental health risks. Some lists included thousands of chemicals, while others listed only a few chemistries with limited properties or toxicological endpoints (e.g., neurotoxicants). Enacted on October 1, 2013, the California Safer Consumer Products Regulation (SCP) utilized data from chemical inventory lists to create one master list. This paper aims to discuss the background and requirements of this regulation. Additionally, we wanted to understand the universe of Candidate Chemicals identified by the Regulation. Data from all 23 chemical lists identified in the SCP Regulation were entered into a database. The most prevalent chemicals among the ∼2900 chemicals are identified, including the most prevalent chemical, lead, appearing on 65% of lists, followed by DEHP (52%), perchloroethylene (48%), and benzene (48%). Our results indicated that the most prevalent Candidate Chemicals were either persistent, bioaccumulative, carcinogenic, or reprotoxic. This regulation will have wide-ranging impact in California and throughout the global supply chain, which is highlighted through selected examples and case studies. Copyright © 2013 Elsevier Inc. All rights reserved.

Integrating Biological and Chemical Data for Hepatotoxicity Prediction (SOT)

EPA Science Inventory

The U.S. EPA ToxCastTM program is screening thousands of environmental chemicals for bioactivity using hundreds of high-throughput in vitro assays to build predictive models of toxicity. A set of 677 chemicals were represented by 711 bioactivity descriptors (from ToxCast assays),...

The SAFER Latinos Project: Addressing a Community Ecology Underlying Latino Youth Violence

ERIC Educational Resources Information Center

Edberg, Mark; Cleary, Sean D.; Collins, Elizabeth; Klevens, Joanne; Leiva, Rodrigo; Bazurto, Martha; Rivera, Ivonne; del Cid, Alex Taylor; Montero, Luisa; Calderon, Melba

2010-01-01

This paper describes the intervention model, early implementation experience, and challenges for the "Seguridad, Apoyo, Familia, Educacion, y Recursos" (SAFER) Latinos project. The SAFER Latinos project is an attempt to build the evidence for a multilevel participatory youth violence prevention model tailored to the specific circumstances of…

Development of estrogen receptor beta binding prediction model using large sets of chemicals.

PubMed

Sakkiah, Sugunadevi; Selvaraj, Chandrabose; Gong, Ping; Zhang, Chaoyang; Tong, Weida; Hong, Huixiao

2017-11-03

We developed an ER β binding prediction model to facilitate identification of chemicals specifically bind ER β or ER α together with our previously developed ER α binding model. Decision Forest was used to train ER β binding prediction model based on a large set of compounds obtained from EADB. Model performance was estimated through 1000 iterations of 5-fold cross validations. Prediction confidence was analyzed using predictions from the cross validations. Informative chemical features for ER β binding were identified through analysis of the frequency data of chemical descriptors used in the models in the 5-fold cross validations. 1000 permutations were conducted to assess the chance correlation. The average accuracy of 5-fold cross validations was 93.14% with a standard deviation of 0.64%. Prediction confidence analysis indicated that the higher the prediction confidence the more accurate the predictions. Permutation testing results revealed that the prediction model is unlikely generated by chance. Eighteen informative descriptors were identified to be important to ER β binding prediction. Application of the prediction model to the data from ToxCast project yielded very high sensitivity of 90-92%. Our results demonstrated ER β binding of chemicals could be accurately predicted using the developed model. Coupling with our previously developed ER α prediction model, this model could be expected to facilitate drug development through identification of chemicals that specifically bind ER β or ER α .

Parents' constructions of communication with their children about safer sex.

PubMed

Hyde, Abbey; Drennan, Jonathan; Butler, Michelle; Howlett, Etaoine; Carney, Marie; Lohan, Maria

2013-12-01

To analyse how a sample of parents reportedly communicated with their adolescent and preadolescent children about safer sex (contraceptive and condom use). Among the plethora of existing research available on parent-child communication about sexuality (more broadly), very few studies detail the substance and tenor of what parents actually convey specifically about safer sex. The study adopted a qualitative methodology and involved interviewing 43 parents (32 mothers and 11 fathers). Data were analysed using modified analytical induction. Findings indicated that although the majority of parents professed to being open about sexuality with their children, only a minority reportedly conveyed direct messages about contraception and condom use. Moreover, these direct messages appeared to be imparted at a superficial level. Parents were more likely to communicate such messages in a tacit manner through innuendo and intimation. The complacency that parents displayed about the need to undertake safer sex education with their adolescents arose from an understanding that this was covered adequately at school and the belief that their teenager was not in a romantic relationship. In addition, some parents expressed concern that discussing safer sex with teenagers might actually encourage sexual activity. We conclude that some parents may consider themselves to have engaged in sexuality education around safer sex when it appears to be predominantly surface-level education; that what constitutes 'doing' sexuality education is far from clear-cut may cast some light on why there is little consistency in the literature on the impact of parental communication on sexual health outcomes for young people. For nurses engaged in sexuality health promotion with parents, we caution about presenting unequivocal messages to parents about the impact of parental communication about sexuality on adolescent sexual behaviour without due acknowledgement of the grey areas indicated in the

SeqAPASS: Predicting chemical susceptibility to threatened/endangered species

EPA Science Inventory

Conservation of a molecular target across species can be used as a line-of-evidence to predict the likelihood of chemical susceptibility. The web-based Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS; https://seqapass.epa.gov/seqapass/) application was devel...

THE FUTURE OF TOXICOLOGY-PREDICTIVE TOXICOLOGY: AN EXPANDED VIEW OF CHEMICAL TOXICITY

EPA Science Inventory

A chemistry approach to predictive toxicology relies on structure−activity relationship (SAR) modeling to predict biological activity from chemical structure. Such approaches have proven capabilities when applied to well-defined toxicity end points or regions of chemical space. T...

Cytotoxicity of ZnO Nanoparticles Can Be Tailored by Modifying Their Surface Structure: A Green Chemistry Approach for Safer Nanomaterials.

PubMed

Punnoose, Alex; Dodge, Kelsey; Rasmussen, John W; Chess, Jordan; Wingett, Denise; Anders, Catherine

2014-07-07

ZnO nanoparticles (NP) are extensively used in numerous nanotechnology applications; however, they also happen to be one of the most toxic nanomaterials. This raises significant environmental and health concerns and calls for the need to develop new synthetic approaches to produce safer ZnO NP, while preserving their attractive optical, electronic, and structural properties. In this work, we demonstrate that the cytotoxicity of ZnO NP can be tailored by modifying their surface-bound chemical groups, while maintaining the core ZnO structure and related properties. Two equally sized (9.26 ± 0.11 nm) ZnO NP samples were synthesized from the same zinc acetate precursor using a forced hydrolysis process, and their surface chemical structures were modified by using different reaction solvents. X-ray diffraction and optical studies showed that the lattice parameters, optical properties, and band gap (3.44 eV) of the two ZnO NP samples were similar. However, FTIR spectroscopy showed significant differences in the surface structures and surface-bound chemical groups. This led to major differences in the zeta potential, hydrodynamic size, photocatalytic rate constant, and more importantly, their cytotoxic effects on Hut-78 cancer cells. The ZnO NP sample with the higher zeta potential and catalytic activity displayed a 1.5-fold stronger cytotoxic effect on cancer cells. These results suggest that by modifying the synthesis parameters/conditions and the surface chemical structures of the nanocrystals, their surface charge density, catalytic activity, and cytotoxicity can be tailored. This provides a green chemistry approach to produce safer ZnO NP.

Cytotoxicity of ZnO Nanoparticles Can Be Tailored by Modifying Their Surface Structure: A Green Chemistry Approach for Safer Nanomaterials

PubMed Central

2015-01-01

ZnO nanoparticles (NP) are extensively used in numerous nanotechnology applications; however, they also happen to be one of the most toxic nanomaterials. This raises significant environmental and health concerns and calls for the need to develop new synthetic approaches to produce safer ZnO NP, while preserving their attractive optical, electronic, and structural properties. In this work, we demonstrate that the cytotoxicity of ZnO NP can be tailored by modifying their surface-bound chemical groups, while maintaining the core ZnO structure and related properties. Two equally sized (9.26 ± 0.11 nm) ZnO NP samples were synthesized from the same zinc acetate precursor using a forced hydrolysis process, and their surface chemical structures were modified by using different reaction solvents. X-ray diffraction and optical studies showed that the lattice parameters, optical properties, and band gap (3.44 eV) of the two ZnO NP samples were similar. However, FTIR spectroscopy showed significant differences in the surface structures and surface-bound chemical groups. This led to major differences in the zeta potential, hydrodynamic size, photocatalytic rate constant, and more importantly, their cytotoxic effects on Hut-78 cancer cells. The ZnO NP sample with the higher zeta potential and catalytic activity displayed a 1.5-fold stronger cytotoxic effect on cancer cells. These results suggest that by modifying the synthesis parameters/conditions and the surface chemical structures of the nanocrystals, their surface charge density, catalytic activity, and cytotoxicity can be tailored. This provides a green chemistry approach to produce safer ZnO NP. PMID:25068096

PREDICTING THE EFFECTIVENESS OF CHEMICAL-PROTECTIVE CLOTHING MODEL AND TEST METHOD DEVELOPMENT

EPA Science Inventory

A predictive model and test method were developed for determining the chemical resistance of protective polymeric gloves exposed to liquid organic chemicals. The prediction of permeation through protective gloves by solvents was based on theories of the solution thermodynamics of...

Prediction of chemical speciation in stabilized/solidified wastes using a general chemical equilibrium model. Part 1: Chemical representation of cementitious binders

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, J.Y.; Batchelor, B.

1999-03-01

Chemical equilibrium models are useful to evaluate stabilized/solidified waste. A general equilibrium model, SOLTEQ, a modified version of MINTEQA2 for S/S, was applied to predict the chemical speciations in the stabilized/solidified waste form. A method was developed to prepare SOLTEQ input data that can chemically represent various stabilized/solidified binders. Taylor`s empirical model was used to describe partitioning of alkali ions. As a result, SOLTEQ could represent chemical speciation in pure binder systems such as ordinary Portland cement and ordinary Portland cement + fly ash. Moreover, SOLTEQ could reasonably describe the effects on the chemical speciation due to variations in water-to-cement,more » fly ash contents, and hydration times of various binder systems. However, this application of SOLTEQ was not accurate in predicting concentrations of Ca, Si, and SO{sub 4} ions, due to uncertainties in the CSH solubility model and K{sub sp} values of cement hydrates at high pH values.« less

The problem of current toxic chemicals management.

PubMed

Tickner, Joel; Geiser, Ken

2004-01-01

In this article, we explore the limitations of current chemicals management policies worldwide and the evolution of new European, International and U.S. policies to address the problem of toxic chemicals control. It is becoming increasingly apparent that current chemicals management policies in Europe and the United States are inadequate. There is a general lack of toxicity and exposure information on chemicals in commerce and the vast majority of chemicals were considered safe until proven guilty in legislation. Governments must then prove each chemical is dangerous through a slow and resource-intensive risk assessment process. For more than a decade, Nordic countries, such as Denmark and Sweden, have actively promoted integrated chemicals policies to address contamination of critical waterways. They have successfully used a variety of voluntary and mandatory policy tools, such as education, procurement, lists of chemicals of concern, eco-labeling, research and development on safer substitutes, and chemical phase-out requirements, to encourage companies using chemicals to reduce their reliance on harmful substances and to develop safer substitutes. While previously isolated to particular countries, innovative and exciting European-wide policies to promote sustainable chemicals management are now moving forward, including the recently published draft Registration, Evaluation and Authorization of CHemicals (REACH) policy of the European Union. A sweeping change in chemicals management policies in Europe is inevitable and it will ultimately affect manufacturers in the U.S. and globally. The European movement provides an opportunity to initiate a discussion on integrated chemicals policy in the U.S. where some innovative initiatives already are underway.

Predicting hepatotoxicity using ToxCast in vitro bioactivity and chemical structure

EPA Science Inventory

Background: The U.S. EPA ToxCastTM program is screening thousands of environmental chemicals for bioactivity using hundreds of high-throughput in vitro assays to build predictive models of toxicity. We represented chemicals based on bioactivity and chemical structure descriptors ...

MODELING A MIXTURE: PBPK/PD APPROACHES FOR PREDICTING CHEMICAL INTERACTIONS.

EPA Science Inventory

Since environmental chemical exposures generally involve multiple chemicals, there are both regulatory and scientific drivers to develop methods to predict outcomes of these exposures. Even using efficient statistical and experimental designs, it is not possible to test in vivo a...

Predicting the bioconcentration factor of highly hydrophobic organic chemicals.

PubMed

Garg, Rajni; Smith, Carr J

2014-07-01

Bioconcentration refers to the process of uptake and buildup of chemicals in living organisms. Experimental measurement of bioconcentration factor (BCF) is time-consuming and expensive, and is not feasible for a large number of chemicals of regulatory concern. Quantitative structure-activity relationship (QSAR) models are used for estimating BCF values to help in risk assessment of a chemical. This paper presents the results of a QSAR study conducted to address an important problem encountered in the prediction of the BCF of highly hydrophobic chemicals. A new QSAR model is derived using a dataset of diverse organic chemicals previously tested in a United States Environmental Protection Agency laboratory. It is noted that the linear relationship between the BCF and hydrophobic parameter, i.e., calculated octanol-water partition coefficient (ClogP), breaks down for highly hydrophobic chemicals. The parabolic QSAR equation, log BCF=3.036 ClogP-0.197 ClogP(2)-0.808 MgVol (n=28, r(2)=0.817, q(2)=0.761, s=0.558) (experimental log BCF range=0.44-5.29, ClogP range=3.16-11.27), suggests that a non-linear relationship between BCF and the hydrophobic parameter, along with inclusion of additional molecular size, weight and/or volume parameters, should be considered while developing a QSAR model for more reliable prediction of the BCF of highly hydrophobic chemicals. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Bitter or not? BitterPredict, a tool for predicting taste from chemical structure.

PubMed

Dagan-Wiener, Ayana; Nissim, Ido; Ben Abu, Natalie; Borgonovo, Gigliola; Bassoli, Angela; Niv, Masha Y

2017-09-21

Bitter taste is an innately aversive taste modality that is considered to protect animals from consuming toxic compounds. Yet, bitterness is not always noxious and some bitter compounds have beneficial effects on health. Hundreds of bitter compounds were reported (and are accessible via the BitterDB http://bitterdb.agri.huji.ac.il/dbbitter.php ), but numerous additional bitter molecules are still unknown. The dramatic chemical diversity of bitterants makes bitterness prediction a difficult task. Here we present a machine learning classifier, BitterPredict, which predicts whether a compound is bitter or not, based on its chemical structure. BitterDB was used as the positive set, and non-bitter molecules were gathered from literature to create the negative set. Adaptive Boosting (AdaBoost), based on decision trees machine-learning algorithm was applied to molecules that were represented using physicochemical and ADME/Tox descriptors. BitterPredict correctly classifies over 80% of the compounds in the hold-out test set, and 70-90% of the compounds in three independent external sets and in sensory test validation, providing a quick and reliable tool for classifying large sets of compounds into bitter and non-bitter groups. BitterPredict suggests that about 40% of random molecules, and a large portion (66%) of clinical and experimental drugs, and of natural products (77%) are bitter.

Flash-point prediction for binary partially miscible mixtures of flammable solvents.

PubMed

Liaw, Horng-Jang; Lu, Wen-Hung; Gerbaud, Vincent; Chen, Chan-Cheng

2008-05-30

Flash point is the most important variable used to characterize fire and explosion hazard of liquids. Herein, partially miscible mixtures are presented within the context of liquid-liquid extraction processes. This paper describes development of a model for predicting the flash point of binary partially miscible mixtures of flammable solvents. To confirm the predictive efficacy of the derived flash points, the model was verified by comparing the predicted values with the experimental data for the studied mixtures: methanol+octane; methanol+decane; acetone+decane; methanol+2,2,4-trimethylpentane; and, ethanol+tetradecane. Our results reveal that immiscibility in the two liquid phases should not be ignored in the prediction of flash point. Overall, the predictive results of this proposed model describe the experimental data well. Based on this evidence, therefore, it appears reasonable to suggest potential application for our model in assessment of fire and explosion hazards, and development of inherently safer designs for chemical processes containing binary partially miscible mixtures of flammable solvents.

Predicting soil formation on the basis of transport-limited chemical weathering

NASA Astrophysics Data System (ADS)

Yu, Fang; Hunt, Allen Gerhard

2018-01-01

Soil production is closely related to chemical weathering. It has been shown that, under the assumption that chemical weathering is limited by solute transport, the process of soil production is predictable. However, solute transport in soil cannot be described by Gaussian transport. In this paper, we propose an approach based on percolation theory describing non-Gaussian transport of solute to predict soil formation (the net production of soil) by considering both soil production from chemical weathering and removal of soil from erosion. Our prediction shows agreement with observed soil depths in the field. Theoretical soil formation rates are also compared with published rates predicted using soil age-profile thickness (SAST) method. Our formulation can be incorporated directly into landscape evolution models on a point-to-point basis as long as such models account for surface water routing associated with overland flow. Further, our treatment can be scaled-up to address complications associated with continental-scale applications, including those from climate change, such as changes in vegetation, or surface flow organization. The ability to predict soil formation rates has implications for understanding Earth's climate system on account of the relationship to chemical weathering of silicate minerals with the associated drawdown of atmospheric carbon, but it is also important in geomorphology for understanding landscape evolution, including for example, the shapes of hillslopes, and the net transport of sediments to sedimentary basins.

QSAR modeling for predicting mutagenic toxicity of diverse chemicals for regulatory purposes.

PubMed

Basant, Nikita; Gupta, Shikha

2017-06-01

The safety assessment process of chemicals requires information on their mutagenic potential. The experimental determination of mutagenicity of a large number of chemicals is tedious and time and cost intensive, thus compelling for alternative methods. We have established local and global QSAR models for discriminating low and high mutagenic compounds and predicting their mutagenic activity in a quantitative manner in Salmonella typhimurium (TA) bacterial strains (TA98 and TA100). The decision treeboost (DTB)-based classification QSAR models discriminated among two categories with accuracies of >96% and the regression QSAR models precisely predicted the mutagenic activity of diverse chemicals yielding high correlations (R 2 ) between the experimental and model-predicted values in the respective training (>0.96) and test (>0.94) sets. The test set root mean squared error (RMSE) and mean absolute error (MAE) values emphasized the usefulness of the developed models for predicting new compounds. Relevant structural features of diverse chemicals that were responsible and influence the mutagenic activity were identified. The applicability domains of the developed models were defined. The developed models can be used as tools for screening new chemicals for their mutagenicity assessment for regulatory purpose.

Modelling Chemical Reasoning to Predict and Invent Reactions.

PubMed

Segler, Marwin H S; Waller, Mark P

2017-05-02

The ability to reason beyond established knowledge allows organic chemists to solve synthetic problems and invent novel transformations. Herein, we propose a model that mimics chemical reasoning, and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180 000 randomly selected binary reactions. The data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-)discovering novel transformations (even including transition metal-catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph and because each single reaction prediction is typically achieved in a sub-second time frame, the model can be used as a high-throughput generator of reaction hypotheses for reaction discovery. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

NREL Blows Up Batteries to Make the World Safer (Text Version) | NREL

Science.gov Websites

World Safer (Text Version) Making lithium-ion batteries safer for earthlings and astronauts is something very large explosions] Not like that. Matt blows up lithium-ion batteries to test them for safety. Matt technology used by NASA in outer space. Matt and his team study battery failure using innovative technologies

Application of an ecological framework to examine barriers to the adoption of safer conception strategies by HIV-affected couples.

PubMed

Saleem, Haneefa T; Surkan, Pamela J; Kerrigan, Deanna; Kennedy, Caitlin E

2016-01-01

Safer conception interventions can significantly reduce the risk of horizontal HIV transmission between HIV-serodiscordant partners. However, prior to implementing safer conception interventions, it is essential to understand potential barriers to their adoption so that strategies can be developed to overcome these barriers. This paper examines potential barriers to the adoption of safer conception strategies by HIV-affected couples in Iringa, Tanzania using an ecological framework. We interviewed 30 HIV-positive women, 30 HIV-positive men and 30 health providers engaged in delivering HIV-related services. We also conducted direct observations at five health facilities. Findings suggest that there are multiple barriers to safer conception that operate at the individual, relational, environmental, structural, and super-structural levels. The barriers to safer conception identified are complex and interact across these levels. Barriers at the individual level included antiretroviral adherence, knowledge of HIV status, knowledge and acceptability of safer conception strategies, and poor nutrition. At the relational level, unplanned pregnancies, non-disclosure of status, gendered power dynamics within relationships, and patient-provider interactions posed a threat to safer conception. HIV stigma and distance to health facilities were environmental barriers to safer conception. At the structural level there were multiple barriers to safer conception, including limited safer conception policy guidelines for people living with HIV (PLHIV), lack of health provider training in safer conception strategies and preconception counseling for PLHIV, limited resources, and lack of integration of HIV and sexual and reproductive health services. Poverty and gender norms were super-structural factors that influenced and reinforced barriers to safer conception, which influenced and operated across different levels of the framework. Multi-level interventions are needed to ensure

Prediction of Chemical Function: Model Development and Application

EPA Science Inventory

The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (...

Consensus statement: Supporting Safer Conception and Pregnancy For Men And Women Living with and Affected by HIV.

PubMed

Matthews, Lynn T; Beyeza-Kashesya, Jolly; Cooke, Ian; Davies, Natasha; Heffron, Renee; Kaida, Angela; Kinuthia, John; Mmeje, Okeoma; Semprini, Augusto E; Weber, Shannon

2018-06-01

Safer conception interventions reduce HIV incidence while supporting the reproductive goals of people living with or affected by HIV. We developed a consensus statement to address demand, summarize science, identify information gaps, outline research and policy priorities, and advocate for safer conception services. This statement emerged from a process incorporating consultation from meetings, literature, and key stakeholders. Three co-authors developed an outline which was discussed and modified with co-authors, working group members, and additional clinical, policy, and community experts in safer conception, HIV, and fertility. Co-authors and working group members developed and approved the final manuscript. Consensus across themes of demand, safer conception strategies, and implementation were identified. There is demand for safer conception services. Access is limited by stigma towards PLWH having children and limits to provider knowledge. Efficacy, effectiveness, safety, and acceptability data support a range of safer conception strategies including ART, PrEP, limiting condomless sex to peak fertility, home insemination, male circumcision, STI treatment, couples-based HIV testing, semen processing, and fertility care. Lack of guidelines and training limit implementation. Key outstanding questions within each theme are identified. Consumer demand, scientific data, and global goals to reduce HIV incidence support safer conception service implementation. We recommend that providers offer services to HIV-affected men and women, and program administrators integrate safer conception care into HIV and reproductive health programs. Answers to outstanding questions will refine services but should not hinder steps to empower people to adopt safer conception strategies to meet reproductive goals.

PREDICTING EVAPORATION RATES AND TIMES FOR SPILLS OF CHEMICAL MIXTURES

EPA Science Inventory

Spreadsheet and short-cut methods have been developed for predicting evaporation rates and evaporation times for spills (and constrained baths) of chemical mixtures. Steady-state and time-varying predictions of evaporation rates can be made for six-component mixtures, includ...

In silico prediction of potential chemical reactions mediated by human enzymes.

PubMed

Yu, Myeong-Sang; Lee, Hyang-Mi; Park, Aaron; Park, Chungoo; Ceong, Hyithaek; Rhee, Ki-Hyeong; Na, Dokyun

2018-06-13

Administered drugs are often converted into an ineffective or activated form by enzymes in our body. Conventional in silico prediction approaches focused on therapeutically important enzymes such as CYP450. However, there are more than thousands of different cellular enzymes that potentially convert administered drug into other forms. We developed an in silico model to predict which of human enzymes including metabolic enzymes as well as CYP450 family can catalyze a given chemical compound. The prediction is based on the chemical and physical similarity between known enzyme substrates and a query chemical compound. Our in silico model was developed using multiple linear regression and the model showed high performance (AUC = 0.896) despite of the large number of enzymes. When evaluated on a test dataset, it also showed significantly high performance (AUC = 0.746). Interestingly, evaluation with literature data showed that our model can be used to predict not only enzymatic reactions but also drug conversion and enzyme inhibition. Our model was able to predict enzymatic reactions of a query molecule with a high accuracy. This may foster to discover new metabolic routes and to accelerate the computational development of drug candidates by enabling the prediction of the potential conversion of administered drugs into active or inactive forms.

Development of bovine serum albumin-water partition coefficients predictive models for ionogenic organic chemicals based on chemical form adjusted descriptors.

PubMed

Ding, Feng; Yang, Xianhai; Chen, Guosong; Liu, Jining; Shi, Lili; Chen, Jingwen

2017-10-01

The partition coefficients between bovine serum albumin (BSA) and water (K BSA/w ) for ionogenic organic chemicals (IOCs) were different greatly from those of neutral organic chemicals (NOCs). For NOCs, several excellent models were developed to predict their logK BSA/w . However, it was found that the conventional descriptors are inappropriate for modeling logK BSA/w of IOCs. Thus, alternative approaches are urgently needed to develop predictive models for K BSA/w of IOCs. In this study, molecular descriptors that can be used to characterize the ionization effects (e.g. chemical form adjusted descriptors) were calculated and used to develop predictive models for logK BSA/w of IOCs. The models developed had high goodness-of-fit, robustness, and predictive ability. The predictor variables selected to construct the models included the chemical form adjusted averages of the negative potentials on the molecular surface (V s-adj - ), the chemical form adjusted molecular dipole moment (dipolemoment adj ), the logarithm of the n-octanol/water distribution coefficient (logD). As these molecular descriptors can be calculated from their molecular structures directly, the developed model can be easily used to fill the logK BSA/w data gap for other IOCs within the applicability domain. Furthermore, the chemical form adjusted descriptors calculated in this study also could be used to construct predictive models on other endpoints of IOCs. Copyright © 2017 Elsevier Inc. All rights reserved.

70 Years of Making the World Safer: Extended

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

Extended version with narration. This video shows our roles in making the world safer — working to end World War II, providing stable isotopes for research, providing unique precision manufacturing capabilities, and meeting nonproliferation and global security missions.

[Application of near infrared reflectance spectroscopy to predict meat chemical compositions: a review].

PubMed

Tao, Lin-Li; Yang, Xiu-Juan; Deng, Jun-Ming; Zhang, Xi

2013-11-01

In contrast to conventional methods for the determination of meat chemical composition, near infrared reflectance spectroscopy enables rapid, simple, secure and simultaneous assessment of numerous meat properties. The present review focuses on the use of near infrared reflectance spectroscopy to predict meat chemical compositions. The potential of near infrared reflectance spectroscopy to predict crude protein, intramuscular fat, fatty acid, moisture, ash, myoglobin and collagen of beef, pork, chicken and lamb is reviewed. This paper discusses existing questions and reasons in the current research. According to the published results, although published results vary considerably, they suggest that near-infrared reflectance spectroscopy shows a great potential to replace the expensive and time-consuming chemical analysis of meat composition. In particular, under commercial conditions where simultaneous measurements of different chemical components are required, near infrared reflectance spectroscopy is expected to be the method of choice. The majority of studies selected feature-related wavelengths using principal components regression, developed the calibration model using partial least squares and modified partial least squares, and estimated the prediction accuracy by means of cross-validation using the same sample set previously used for the calibration. Meat fatty acid composition predicted by near-infrared spectroscopy and non-destructive prediction and visualization of chemical composition in meat using near-infrared hyperspectral imaging and multivariate regression are the hot studying field now. On the other hand, near infrared reflectance spectroscopy shows great difference for predicting different attributes of meat quality which are closely related to the selection of calibration sample set, preprocessing of near-infrared spectroscopy and modeling approach. Sample preparation also has an important effect on the reliability of NIR prediction; in particular

Safer sexual practices among African American women: intersectional socialisation and sexual assertiveness.

PubMed

Brown, Danice L; Blackmon, Sha'Kema; Shiflett, Alexandra

2018-06-01

Scholars have posited that childhood socialisation experiences may play a key role in influencing behaviours and attitudes that contribute to the acquisition of HIV. This study examined the links between past ethnic-racial and gender socialisation, sexual assertiveness and the safe sexual practices of African American college women utilising a cluster analytic approach. After identifying separate racial-gender and ethnic-gender socialisation profiles, results indicated that ethnic-gender socialisation cluster profiles were directly associated with sexual assertiveness and safer sex behaviour. Greater levels of ethnic socialisation and low traditional gender role socialisation were found to be associated with greater sexual assertiveness and safer sex behaviour. Further analysis showed that sexual assertiveness mediated the links between the identified ethnic-gender socialisation profiles and safer sex behaviour. Implications for policy and programme development are discussed.

[Sexual Behavior and Self-Efficacy for the Negotiation of Safer Sex in Heterosexual Persons.

PubMed

Pérez-Jiménez, David; Santiago-Rivas, Marimer; Serrano-García, Irma

2009-05-01

Self-efficacy has been defined as one of the factors that may facilitate or impede safer sex. Studies reveal that peoples in steady relationships practice safer sex less often that those in casual relationships. We conducted a study with 447 sexually active heterosexual adults. A self-administered questionnaire was designed to study the sexual behavior, the male condom use and the practice of mutual masturbation, and the self-efficacy toward these practices. Results show that most men are sexually active and that there is a low frequency of male condom use and the practice of mutual masturbation as safer sex. The majority of those who use the male condom are engage in casual relationships. However, participants have high levels of self-efficacy toward these practices. Although self-efficacy is one of the factors that influence in deciding to practice safer sex, it is not sufficient to reach this goal.

SAFER Inspection of Space Shuttle Thermal Protection System

NASA Technical Reports Server (NTRS)

Scoville, Zebulon C.; Rajula, Sudhakar

2005-01-01

In the aftermath of the space shuttle Columbia accident, it quickly became clear that new methods would need to be developed that would provide the capability to inspect and repair the shuttle's thermal protection system (TPS). A boom extension to the Remote Manipulator System (RMS) with a laser topography sensor package was identified as the primary means for measuring the damage depth in acreage tile as well as scanning Reinforced Carbon- Carbon (RCC) surfaces. However, concern over the system's fault tolerance made it prudent to investigate alternate means of acquiring close range photographs and contour depth measurements in the event of a failure. One method that was identified early was to use the Simplified Aid For EVA Rescue (SAFER) propulsion system to allow EVA access to damaged areas of concern. Several issues were identified as potential hazards to SAFER use for this operation. First, the ability of an astronaut to maintain controlled flight depends upon efficient technique and hardware reliability. If either of these is insufficient during flight operations, a safety tether must be used to rescue the crewmember. This operation can jeopardize the integrity of the Extra-vehicular Mobility Unit (EMU) or delicate TPS materials. Controls were developed to prevent the likelihood of requiring a tether rescue, and procedures were written to maximize the chances for success if it cannot be avoided. Crewmember ability to manage tether cable tension during nominal flight also had to be evaluated to ensure it would not negatively affect propellant consumption. Second, although propellant consumption, flight control, orbital dynamics, and flight complexity can all be accurately evaluated in Virtual Reality (VR) Laboratory at Johnson Space Center, there are some shortcomings. As a crewmember's hand is extended to simulate measurement of tile damage, it will pass through the vehicle without resistance. In reality, this force will push the crewmember away from the

About Using Predictive Models and Tools To Assess Chemicals under TSCA

EPA Pesticide Factsheets

As part of EPA's effort to promote chemical safety, OPPT provides public access to predictive models and tools which can help inform the public on the hazards and risks of substances and improve chemical management decisions.

PREDICTING TOXICOLOGICAL ENDPOINTS OF CHEMICALS USING QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS (QSARS)

EPA Science Inventory

Quantitative structure-activity relationships (QSARs) are being developed to predict the toxicological endpoints for untested chemicals similar in structure to chemicals that have known experimental toxicological data. Based on a very large number of predetermined descriptors, a...

Prediction of biodegradability from chemical structure: Modeling or ready biodegradation test data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loonen, H.; Lindgren, F.; Hansen, B.

1999-08-01

Biodegradation data were collected and evaluated for 894 substances with widely varying chemical structures. All data were determined according to the Japanese Ministry of International Trade and Industry (MITI) I test protocol. The MITI I test is a screening test for ready biodegradability and has been described by Organization for Economic Cooperation and Development (OECD) test guideline 301 C and European Union (EU) test guideline C4F. The chemicals were characterized by a set of 127 predefined structural fragments. This data set was used to develop a model for the prediction of the biodegradability of chemicals under standardized OECD and EUmore » ready biodegradation test conditions. Partial least squares (PLS) discriminant analysis was used for the model development. The model was evaluated by means of internal cross-validation and repeated external validation. The importance of various structural fragments and fragment interactions was investigated. The most important fragments include the presence of a long alkyl chain; hydroxy, ester, and acid groups (enhancing biodegradation); and the presence of one or more aromatic rings and halogen substituents (regarding biodegradation). More than 85% of the model predictions were correct for using the complete data set. The not readily biodegradable predictions were slightly better than the readily biodegradable predictions (86 vs 84%). The average percentage of correct predictions from four external validation studies was 83%. Model optimization by including fragment interactions improve the model predicting capabilities to 89%. It can be concluded that the PLS model provides predictions of high reliability for a diverse range of chemical structures. The predictions conform to the concept of readily biodegradable (or not readily biodegradable) as defined by OECD and EU test guidelines.« less

Prediction of chemical biodegradability using support vector classifier optimized with differential evolution.

PubMed

Cao, Qi; Leung, K M

2014-09-22

Reliable computer models for the prediction of chemical biodegradability from molecular descriptors and fingerprints are very important for making health and environmental decisions. Coupling of the differential evolution (DE) algorithm with the support vector classifier (SVC) in order to optimize the main parameters of the classifier resulted in an improved classifier called the DE-SVC, which is introduced in this paper for use in chemical biodegradability studies. The DE-SVC was applied to predict the biodegradation of chemicals on the basis of extensive sample data sets and known structural features of molecules. Our optimization experiments showed that DE can efficiently find the proper parameters of the SVC. The resulting classifier possesses strong robustness and reliability compared with grid search, genetic algorithm, and particle swarm optimization methods. The classification experiments conducted here showed that the DE-SVC exhibits better classification performance than models previously used for such studies. It is a more effective and efficient prediction model for chemical biodegradability.

Toxicity challenges in environmental chemicals: Prediction of ...

EPA Pesticide Factsheets

Physiologically based pharmacokinetic (PBPK) models bridge the gap between in vitro assays and in vivo effects by accounting for the adsorption, distribution, metabolism, and excretion of xenobiotics, which is especially useful in the assessment of human toxicity. Quantitative structure-activity relationships (QSAR) serve as a vital tool for the high-throughput prediction of chemical-specific PBPK parameters, such as the fraction of a chemical unbound by plasma protein (Fub). The presented work explores the merit of utilizing experimental pharmaceutical Fub data for the construction of a universal QSAR model, in order to compensate for the limited range of high-quality experimental Fub data for environmentally relevant chemicals, such as pollutants, pesticides, and consumer products. Independent QSAR models were constructed with three machine-learning algorithms, k nearest neighbors (kNN), random forest (RF), and support vector machine (SVM) regression, from a large pharmaceutical training set (~1000) and assessed with independent test sets of pharmaceuticals (~200) and environmentally relevant chemicals in the ToxCast program (~400). Small descriptor sets yielded the optimal balance of model complexity and performance, providing insight into the biochemical factors of plasma protein binding, while preventing over fitting to the training set. Overlaps in chemical space between pharmaceutical and environmental compounds were considered through applicability of do

Predicting organ toxicity using in vitro bioactivity data and chemical structure

EPA Science Inventory

Animal testing alone cannot practically evaluate the health hazard posed by tens of thousands of environmental chemicals. Computational approaches together with high-throughput experimental data may provide more efficient means to predict chemical toxicity. Here, we use a superv...

First flight test results of the Simplified Aid For EVA Rescue (SAFER) propulsion unit

NASA Technical Reports Server (NTRS)

Meade, Carl J.

1995-01-01

The Simplified Aid for EVA Rescue (SAFER) is a small, self-contained, propulsive-backpack system that provides free-flying mobility for an astronaut engaged in a space walk, also known as extravehicular activity (EVA.) SAFER contains no redundant systems and is intended for contingency use only. In essence, it is a small, simplified version of the Manned Maneuvering Unit (MMU) last flown aboard the Space Shuttle in 1985. The operational SAFER unit will only be used to return an adrift EVA astronaut to the spacecraft. Currently, if an EVA crew member inadvertently becomes separated from the Space Shuttle, the Orbiter will maneuver to within the crew member's reach envelope, allowing the astronaut to regain contact with the Orbiter. However, with the advent of operations aboard the Russian MIR Space Station and the International Space Station, the Space Shuttle will not be available to effect a timely rescue. Under these conditions, a SAFER unit would be worn by each EVA crew member. Flight test of the pre-production model of SAFER occurred in September 1994. The crew of Space Shuttle Mission STS-64 flew a 6.9 hour test flight which included performance, flying qualities, systems, and operational utility evaluations. We found that the unit offers adequate propellant and control authority to stabilize and enable the return of a tumbling/separating crew member. With certain modifications, production model of SAFER can provide self-rescue capability to a separated crew member. This paper will present the program background, explain the flight test results and provide some insight into the complex operations of flight test in space.

Alcohol risk management in college settings: the safer California universities randomized trial.

PubMed

Saltz, Robert F; Paschall, Mallie J; McGaffigan, Richard P; Nygaard, Peter M O

2010-12-01

Potentially effective environmental strategies have been recommended to reduce heavy alcohol use among college students. However, studies to date on environmental prevention strategies are few in number and have been limited by their nonexperimental designs, inadequate sample sizes, and lack of attention to settings where the majority of heavy drinking events occur. To determine whether environmental prevention strategies targeting off-campus settings would reduce the likelihood and incidence of student intoxication at those settings. The Safer California Universities study involved 14 large public universities, half of which were assigned randomly to the Safer intervention condition after baseline data collection in 2003. Environmental interventions took place in 2005 and 2006 after 1 year of planning with seven Safer intervention universities. Random cross-sectional samples of undergraduates completed online surveys in four consecutive fall semesters (2003-2006). Campuses and communities surrounding eight campuses of the University of California and six in the California State University system were utilized. The study used random samples of undergraduates (∼500-1000 per campus per year) attending the 14 public California universities. Safer environmental interventions included nuisance party enforcement operations, minor decoy operations, driving-under-the-influence checkpoints, social host ordinances, and use of campus and local media to increase the visibility of environmental strategies. Proportion of drinking occasions in which students drank to intoxication at six different settings during the fall semester (residence hall party, campus event, fraternity or sorority party, party at off-campus apartment or house, bar/restaurant, outdoor setting), any intoxication at each setting during the semester, and whether students drank to intoxication the last time they went to each setting. Significant reductions in the incidence and likelihood of intoxication at

Understanding barriers to safer sex practice in Zimbabwean marriages: implications for future HIV prevention interventions.

PubMed

Mugweni, Esther; Omar, Mayeh; Pearson, Stephen

2015-06-01

Against the backdrop of high human immunodeficiency virus (HIV) prevalence in stable relationships in Southern Africa, our study presents sociocultural barriers to safer sex practice in Zimbabwean marriages. We conducted 36 in-depth interviews and four focus group discussions with married men and women in Zimbabwe in 2008. Our aim was to identify barriers faced by married women when negotiating for safer sex. Participants identified individual, relational and community-level barriers. Individual level barriers made women voiceless to negotiate for safer sex. Being voiceless emanated from lack sexual decision-making power, economic dependence, low self-efficacy or fear of actual or perceived consequences of negotiating for safer sex. Relational barriers included trust and self-disclosure. At the community level, extended family members and religious leaders were said to explicitly or implicitly discourage women's safer sex negotiation. Given the complexity and multi-levelled nature of barriers affecting sexual behaviour in marriage, our findings suggest that HIV prevention interventions targeted at married women would benefit from empowering individual women, couples and also addressing the wider community. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Leveraging Publically Available Chemical Functional Use Data in Support of Exposure Prediction

EPA Science Inventory

The U.S. EPA Exposure Forecasting (ExpoCast) project aims to provide rapid screening-level exposure predictions for thousands of chemicals, most of which lack detailed exposure data. Chemical functional use - the role a chemical plays in processes or products (e.g. solvent, ant...

Parent-Adolescent Sexual Communication and Adolescent Safer Sex Behavior: A Meta-Analysis

PubMed Central

Widman, Laura; Choukas-Bradley, Sophia; Noar, Seth M.; Nesi, Jacqueline; Garrett, Kyla

2016-01-01

Importance Parent-adolescent sexual communication has received considerable attention as one factor that can positively impact safer sex among youth; however, the evidence linking communication to youth contraceptive and condom use has not been empirically synthesized. Objective This meta-analysis examined the effect of parent-adolescent sexual communication on youth safer sex behavior and explored potential moderators of this association. Data Sources A systematic search was conducted of studies published through June 2014 using Medline, PsycINFO, and Communication & Mass Media Complete databases and relevant review articles. Study Selection Studies were included if they: 1) sampled adolescents (mean sample age≤18); 2) included an adolescent report of sexual communication with parent(s); 3) measured safer sex behavior; and 4) were published in English. Data Extraction and Synthesis Correlation coefficients (r) and 95% confidence intervals (CIs) were computed from studies and meta-analyzed using random-effects models. Main Outcomes and Measures The primary outcome was safer sex behavior, including use of contraceptives/birth control or condoms. Results Seventy-one independent effects representing over three decades of research on 25,314 adolescents (mean age = 15.1) were synthesized. Across studies, there was a small, significant weighted mean effect (r = .10, [95% CI:0.08–0.13]) linking parent-adolescent sexual communication to safer sex behavior, which was statistically heterogeneous (Q = 203.50, p < .001, I2 = 65.60). Moderation analyses revealed larger effects for communication with girls (r = .12) than boys (r = .04), and among youth who discussed sex with mothers (r = .14) compared to fathers (r = .03). Effects did not differ for contraceptive versus condom use, or among longitudinal versus cross-sectional studies, indicating parent sexual communication had a similar impact across study designs and outcomes. Several methodological issues were identified

An expert system for prediction of chemical toxicity

USGS Publications Warehouse

Hickey, James P.; Aldridge, Andrew J.; Passino-Reader, Dora R.; Frank, Anthony M.

1992-01-01

The National Fisheries Research Center- Great Lakes has developed an interactive computer program that uses the structure of an organic molecule to predict its acute toxicity to four aquatic species. The expert system software, written in the muLISP language, identifies the skeletal structures and substituent groups of an organic molecule from a user-supplied standard chemical notation known as a SMILES string, and then generates values for four solvatochromic parameters. Multiple regression equations relate these parameters to the toxicities (expressed as log10LC50s and log10EC50s, along with 95% confidence intervals) for four species. The system is demonstrated by prediction of toxicity for anilide-type pesticides to the fathead minnow (Pimephales promelas). This software is designed for use on an IBM-compatible personal computer by personnel with minimal toxicology background for rapid estimation of chemical toxicity. The system has numerous applications, with much potential for use in the pharmaceutical industry

Predictive performance of the Vitrigel‐eye irritancy test method using 118 chemicals

PubMed Central

Yamaguchi, Hiroyuki; Kojima, Hajime

2015-01-01

Abstract We recently developed a novel Vitrigel‐eye irritancy test (EIT) method. The Vitrigel‐EIT method is composed of two parts, i.e., the construction of a human corneal epithelium (HCE) model in a collagen vitrigel membrane chamber and the prediction of eye irritancy by analyzing the time‐dependent profile of transepithelial electrical resistance values for 3 min after exposing a chemical to the HCE model. In this study, we estimated the predictive performance of Vitrigel‐EIT method by testing a total of 118 chemicals. The category determined by the Vitrigel‐EIT method in comparison to the globally harmonized system classification revealed that the sensitivity, specificity and accuracy were 90.1%, 65.9% and 80.5%, respectively. Here, five of seven false‐negative chemicals were acidic chemicals inducing the irregular rising of transepithelial electrical resistance values. In case of eliminating the test chemical solutions showing pH 5 or lower, the sensitivity, specificity and accuracy were improved to 96.8%, 67.4% and 84.4%, respectively. Meanwhile, nine of 16 false‐positive chemicals were classified irritant by the US Environmental Protection Agency. In addition, the disappearance of ZO‐1, a tight junction‐associated protein and MUC1, a cell membrane‐spanning mucin was immunohistologically confirmed in the HCE models after exposing not only eye irritant chemicals but also false‐positive chemicals, suggesting that such false‐positive chemicals have an eye irritant potential. These data demonstrated that the Vitrigel‐EIT method could provide excellent predictive performance to judge the widespread eye irritancy, including very mild irritant chemicals. We hope that the Vitrigel‐EIT method contributes to the development of safe commodity chemicals. Copyright © 2015 The Authors. Journal of Applied Toxicology published by John Wiley & Sons Ltd. PMID:26472347

Predictive performance of the Vitrigel-eye irritancy test method using 118 chemicals.

PubMed

Yamaguchi, Hiroyuki; Kojima, Hajime; Takezawa, Toshiaki

2016-08-01

We recently developed a novel Vitrigel-eye irritancy test (EIT) method. The Vitrigel-EIT method is composed of two parts, i.e., the construction of a human corneal epithelium (HCE) model in a collagen vitrigel membrane chamber and the prediction of eye irritancy by analyzing the time-dependent profile of transepithelial electrical resistance values for 3 min after exposing a chemical to the HCE model. In this study, we estimated the predictive performance of Vitrigel-EIT method by testing a total of 118 chemicals. The category determined by the Vitrigel-EIT method in comparison to the globally harmonized system classification revealed that the sensitivity, specificity and accuracy were 90.1%, 65.9% and 80.5%, respectively. Here, five of seven false-negative chemicals were acidic chemicals inducing the irregular rising of transepithelial electrical resistance values. In case of eliminating the test chemical solutions showing pH 5 or lower, the sensitivity, specificity and accuracy were improved to 96.8%, 67.4% and 84.4%, respectively. Meanwhile, nine of 16 false-positive chemicals were classified irritant by the US Environmental Protection Agency. In addition, the disappearance of ZO-1, a tight junction-associated protein and MUC1, a cell membrane-spanning mucin was immunohistologically confirmed in the HCE models after exposing not only eye irritant chemicals but also false-positive chemicals, suggesting that such false-positive chemicals have an eye irritant potential. These data demonstrated that the Vitrigel-EIT method could provide excellent predictive performance to judge the widespread eye irritancy, including very mild irritant chemicals. We hope that the Vitrigel-EIT method contributes to the development of safe commodity chemicals. Copyright © 2015 The Authors. Journal of Applied Toxicology published by John Wiley & Sons Ltd. Copyright © 2015 The Authors. Journal of Applied Toxicology published by John Wiley & Sons Ltd.

Prediction of novel synthetic pathways for the production of desired chemicals.

PubMed

Cho, Ayoun; Yun, Hongseok; Park, Jin Hwan; Lee, Sang Yup; Park, Sunwon

2010-03-28

There have been several methods developed for the prediction of synthetic metabolic pathways leading to the production of desired chemicals. In these approaches, novel pathways were predicted based on chemical structure changes, enzymatic information, and/or reaction mechanisms, but the approaches generating a huge number of predicted results are difficult to be applied to real experiments. Also, some of these methods focus on specific pathways, and thus are limited to expansion to the whole metabolism. In the present study, we propose a system framework employing a retrosynthesis model with a prioritization scoring algorithm. This new strategy allows deducing the novel promising pathways for the synthesis of a desired chemical together with information on enzymes involved based on structural changes and reaction mechanisms present in the system database. The prioritization scoring algorithm employing Tanimoto coefficient and group contribution method allows examination of structurally qualified pathways to recognize which pathway is more appropriate. In addition, new concepts of binding site covalence, estimation of pathway distance and organism specificity were taken into account to identify the best synthetic pathway. Parameters of these factors can be evolutionarily optimized when a newly proven synthetic pathway is registered. As the proofs of concept, the novel synthetic pathways for the production of isobutanol, 3-hydroxypropionate, and butyryl-CoA were predicted. The prediction shows a high reliability, in which experimentally verified synthetic pathways were listed within the top 0.089% of the identified pathway candidates. It is expected that the system framework developed in this study would be useful for the in silico design of novel metabolic pathways to be employed for the efficient production of chemicals, fuels and materials.

Under construction: building a safer industry.

PubMed Central

Tibbetts, John

2002-01-01

A revolution in the building industry over the past decade has spawned a new generation of safer materials and practices, decreasing some health risks for construction workers. Concerned consumers, builders, materials manufacturers, and government regulatory agencies have all contributed to a turn toward "green" building materials and practices, meaning that homeowners and office workers now are better able to live and work in healthier environments, and many construction workers are handling and installing less-toxic materials. PMID:11882489

Beyond HIV-serodiscordance: Partnership communication dynamics that affect engagement in safer conception care

PubMed Central

Burns, Bridget F.; Bajunirwe, Francis; Kabakyenga, Jerome; Bwana, Mwebesa; Ng, Courtney; Kastner, Jasmine; Kembabazi, Annet; Sanyu, Naomi; Kusasira, Adrine; Haberer, Jessica E.; Bangsberg, David R.; Kaida, Angela

2017-01-01

Introduction We explored acceptability and feasibility of safer conception methods among HIV-affected couples in Uganda. Methods We recruited HIV-positive men and women on antiretroviral therapy (ART) (‘index’) from the Uganda Antiretroviral Rural Treatment Outcomes cohort who reported an HIV-negative or unknown-serostatus partner (‘partner’), HIV-serostatus disclosure to partner, and personal or partner desire for a child within two years. We conducted in-depth interviews with 40 individuals from 20 couples, using a narrative approach with tailored images to assess acceptability of five safer conception strategies: ART for the infected partner, pre-exposure prophylaxis (PrEP) for the uninfected partner, condomless sex timed to peak fertility, manual insemination, and male circumcision. Translated and transcribed data were analyzed using thematic analysis. Results 11/20 index participants were women, median age of 32.5 years, median of 2 living children, and 80% had HIV-RNA <400 copies/mL. Awareness of HIV prevention strategies beyond condoms and abstinence was limited and precluded opportunity to explore or validly assess acceptability or feasibility of safer conception methods. Four key partnership communication challenges emerged as primary barriers to engagement in safer conception care, including: (1) HIV-serostatus disclosure: Although disclosure was an inclusion criterion, partners commonly reported not knowing the index partner’s HIV status. Similarly, the partner’s HIV-serostatus, as reported by the index, was frequently inaccurate. (2) Childbearing intention: Many couples had divergent childbearing intentions and made incorrect assumptions about their partner’s desires. (3) HIV risk perception: Participants had disparate understandings of HIV transmission and disagreed on the acceptable level of HIV risk to meet reproductive goals. (4) Partnership commitment: Participants revealed significant discord in perceptions of partnership commitment

Prediction Metrics for Chemical Detection in Long-Wave Infrared Hyperspectral Imagery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chilton, Marie C.; Walsh, Stephen J.; Daly, Don S.

2009-01-29

A natural or anthropogenic process often generates a signature gas plume whose chemical constituents may be identified using hyperspectral imagery. A hyperspectral image is a pixel-indexed set of spectra where each spectrum reflects the chemical constituents of the plume, the atmosphere, the bounding background surface, and instrument noise. This study explored the relationship between gas absorbance and background emissivity across the long-wave infrared (LWIR) spectrum and how they affect relative gas detection sensitivity. The physics-based model for the observed radiance shows that high gas absorbance coupled with low background emissivity at a single wavenumber results in a stronger recorded radiance.more » Two sensitivity measures were developed to predict relative probability of detection using chemical absorbance and background emissivity: one focused on a single wavenumber while another accounted for the entire spectrum. The predictive abilities of these measures were compared to synthetic image analysis. This study simulated images with 499 distinct gases at each of 6 concentrations over 6 different background surfaces with the atmosphere and level of instrument noise held constant. The Whitened Matched Filter was used to define gas detection from an image spectrum. The estimate of a chemical’s probability of detection at a given concentration over a specific background was the proportion of detections in 500 trials. Of the 499 chemicals used in the images, 276 had estimated probabilities of detection below 0.2 across all backgrounds and concentrations; these chemicals were removed from the study. For 92.8 percent of the remaining chemicals, the single channel measure correctly predicted the background over which the chemical had the largest relative probability of detection. Further, the measure which accounted for information across all wavenumbers predicted the background over which the chemical had the largest relative probability of detection for

Safer handling practice: influence of staff education on older people.

PubMed

Wilson, Christine Brown

The purpose of this small-scale survey was to explore the level of moving and handling training undertaken by nurses within private sector continuing care environments and the potential this training had to influence the care of older people. This study uses a definition of safer handling practice derived from existing literature to examine how nurses report the application of this training and whether they observe changes to the mobility of older people within their care. The limitations of this study indicate that generalizations must be made cautiously. However, this study tentatively suggests that potential exists to influence positively the use of safer handling practice as defined within this study. Recommendations for further study are made.

Predicting ready biodegradability of premanufacture notice chemicals.

PubMed

Boethling, Robert S; Lynch, David G; Thom, Gary C

2003-04-01

Chemical substances other than pesticides, drugs, and food additives are regulated by the U.S. Environmental Protection Agency (U.S. EPA) under the Toxic Substances Control Act (TSCA), but the United States does not require that new substances be tested automatically for such critical properties as biodegradability. The resulting lack of submitted data has fostered the development of estimation methods, and the BioWIN models for predicting biodegradability from chemical structure have played a prominent role in premanufacture notice (PMN) review. Until now, validation efforts have used only the Japanese Ministry of International Trade and Industry (MITI) test data and have not included all models. To assess BioWIN performance with PMN substances, we assembled a database of PMNs for which ready biodegradation data had been submitted over the period 1995 through 2001. The 305 PMN structures are highly varied and pose major challenges to chemical property estimation. Despite the variability of ready biodegradation tests, the use of at least six different test methods, and widely varying quality of submitted data, accuracy of four of six BioWIN models (MITI linear, MITI nonlinear, survey ultimate, survey primary) was in the 80+% range for predicting ready biodegradability. Greater accuracy (>90%) can be achieved by using model estimates only when the four models agree (true for 3/4 of the PMNs). The BioWIN linear and nonlinear probability models did not perform as well even when classification criteria were optimized. The results suggest that the MITI and survey BioWIN models are suitable for use in screening-level applications.

Pregnancy termination in Matlab, Bangladesh: trends and correlates of use of safer and less-safe methods.

PubMed

DaVanzo, Julie; Rahman, Mizanur

2014-09-01

Menstrual regulation (MR), a relatively safe form of pregnancy termination, is legal in Bangladesh during the early stages of pregnancy. However, little is known about the factors associated with whether women who terminate pregnancies choose this method or a less-safe one. Data from the Matlab Demographic Surveillance System on 122,691 pregnancies-5,221 (4.3%) of which were terminated-were used to examine trends between 1989 and 2008 in termination and in use of safer methods (MR or dilation and curettage) and less-safe (all other) methods of pregnancy termination. Logistic and multinomial logistic regressions were used to assess factors associated with whether women terminate pregnancies and whether they use safer methods. Sixty-seven percent of pregnancy terminations were by safer methods and 33% by less-safe means. The proportion of pregnancies that were terminated increased between 1989 and 2008; this increase was entirely due to increased use of safer methods. Women younger than 18 and those 25 or older were more likely than women aged 20-24 to terminate their pregnancies (odds ratios ranged from 1.5 among women aged 16-17 or 25-29 to 26.1 among those aged 45 or older). Among women who terminated their pregnancies, those aged 25-44 were more likely than those aged 20-24 to use a safer method. Compared with women who had no formal education, those with some education were more likely to terminate their pregnancies and to do so using safer methods. A growing proportion of pregnancies in Matlab are terminated, and these terminations are increasingly done using safer methods.

Steering Patients to Safer Hospitals? The Effect of a Tiered Hospital Network on Hospital Admissions

PubMed Central

Scanlon, Dennis P; Lindrooth, Richard C; Christianson, Jon B

2008-01-01

Objective To determine if a tiered hospital benefit and safety incentive shifted the distribution of admissions toward safer hospitals. Data Sources/Study Setting A large manufacturing company instituted the hospital safety incentive (HSI) for union employees. The HSI gave union patients a financial incentive to choose hospitals that met the Leapfrog Group's three patient safety “leaps.” The analysis merges data from four sources: claims and enrollment data from the company, the American Hospital Association, the AHRQ HCUP-SID, and a state Office of the Insurance Commissioner. Study Design Changes in hospital admissions’ patterns for union and nonunion employees using a difference-in-difference design. We estimate the probability of choosing a specific hospital from a set of available alternatives using conditional logistic regression. Principal Findings Patients affiliated with the engineers’ union and admitted for a medical diagnosis were 2.92 times more likely to select a hospital designated as safer in the postperiod than in the preperiod, while salaried nonunion (SNU) patients (not subject to the financial incentive) were 0.64 times as likely to choose a compliant hospital in the post- versus preperiod. The difference-in-difference estimate, which is based on the predictions of the conditional logit model, is 0.20. However, the machinists’ union was also exposed to the incentive and they were no more likely to choose a safer hospital than the SNU patients. The incentive did not have an effect on patients admitted for a surgical diagnosis, regardless of union status. All patients were averse to travel time, but those union patients selecting an incentive hospital were less averse to travel time. Conclusions Patient price incentives and quality/safety information may influence hospital selection decisions, particularly for medical admissions, though the optimal incentive level for financial return to the plan sponsor is not clear. PMID:18761676

Prediction of rodent carcinogenic potential of naturally occurring chemicals in the human diet using high-throughput QSAR predictive modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valerio, Luis G.; Arvidson, Kirk B.; Chanderbhan, Ronald F.

2007-07-01

Consistent with the U.S. Food and Drug Administration (FDA) Critical Path Initiative, predictive toxicology software programs employing quantitative structure-activity relationship (QSAR) models are currently under evaluation for regulatory risk assessment and scientific decision support for highly sensitive endpoints such as carcinogenicity, mutagenicity and reproductive toxicity. At the FDA's Center for Food Safety and Applied Nutrition's Office of Food Additive Safety and the Center for Drug Evaluation and Research's Informatics and Computational Safety Analysis Staff (ICSAS), the use of computational SAR tools for both qualitative and quantitative risk assessment applications are being developed and evaluated. One tool of current interest ismore » MDL-QSAR predictive discriminant analysis modeling of rodent carcinogenicity, which has been previously evaluated for pharmaceutical applications by the FDA ICSAS. The study described in this paper aims to evaluate the utility of this software to estimate the carcinogenic potential of small, organic, naturally occurring chemicals found in the human diet. In addition, a group of 19 known synthetic dietary constituents that were positive in rodent carcinogenicity studies served as a control group. In the test group of naturally occurring chemicals, 101 were found to be suitable for predictive modeling using this software's discriminant analysis modeling approach. Predictions performed on these compounds were compared to published experimental evidence of each compound's carcinogenic potential. Experimental evidence included relevant toxicological studies such as rodent cancer bioassays, rodent anti-carcinogenicity studies, genotoxic studies, and the presence of chemical structural alerts. Statistical indices of predictive performance were calculated to assess the utility of the predictive modeling method. Results revealed good predictive performance using this software's rodent carcinogenicity module of over 1200

Community Influences on Married Women's Safer Sex Negotiation Attitudes in Bangladesh: A Multilevel Analysis.

PubMed

Jesmin, Syeda S; Cready, Cynthia M

2016-02-01

The influence of disadvantaged or deprived community on individuals' health risk-behaviors is increasingly being documented in a growing body of literature. However, little is known about the effects of community characteristics on women's sexual attitudes and behaviors. To examine community effects on married women's safer sex negotiation attitudes, we analyzed cross-sectional data from the 2011 Bangladesh Demographic and Health Surveys on a sample of 15,134 married women in 600 communities. We estimated two multilevel logistic regression models. Model 1, which included only individual-level variables, showed that women's autonomy/empowerment, age, and HIV knowledge had significant associations with their safer sex negotiation attitudes. We did not find any socioeconomic status gradient in safer sex negotiation attitudes at the individual level. Adding community-level variables in Model 2 significantly improved the fit of the model. Strikingly, we found that higher community-level poverty was associated with greater positive safer sex negotiation attitudes. Prevailing gender norms and overall women's empowerment in the community also had significant effects. While research on community influences calls for focusing on disadvantaged communities, our research highlights the importance of not underestimating the challenges that married women in economically privileged communities may face in negotiating safer sex. To have sufficient and equitable impact on married women's sexual and reproductive health, sexual and reproductive health promotion policies and programs need to be directed to women in wealthier communities as well.

Parent-Adolescent Sexual Communication and Adolescent Safer Sex Behavior: A Meta-Analysis.

PubMed

Widman, Laura; Choukas-Bradley, Sophia; Noar, Seth M; Nesi, Jacqueline; Garrett, Kyla

2016-01-01

Parent-adolescent sexual communication has received considerable attention as a factor that can positively affect safer sex behavior among youth; however, the evidence linking such communication to youth contraceptive and condom use has not been empirically synthesized. To examine the effect of parent-adolescent sexual communication on safer sex behavior among youth and explore potential moderators of this association. A systematic search of studies published from database inception through June 30, 2014, using the MEDLINE, PsycINFO, and Communication & Mass Media Complete databases and relevant review articles yielded 5098 studies, of which 52 studies with 25,314 adolescents met the study eligibility criteria. Analysis was conducted from July 1, 2014, to July 27, 2015. Studies were included if they sampled adolescents (mean sample age ≤18 years), included an adolescent report of sexual communication with one or both parents, measured safer sex behavior, and were published in English. Correlation coefficients (r) and 95% CIs were computed from studies and meta-analyzed using random-effects models. Safer sex behavior, including use of contraceptives or condoms. Fifty-two articles, including 71 independent effects representing more than 3 decades of research on 25,314 adolescents (weighted mean age, 15.2 years) were synthesized. Across studies, there was a significant weighted mean effect (r = 0.10; 95% CI, 0.08-0.13) linking parent-adolescent sexual communication with safer sex behavior, which was statistically heterogeneous (Q = 203.50, P < .001, I2 = 65.60). Moderation analyses revealed larger effects for communication with girls (r = 0.12) than boys (r = 0.04) and among youth who discussed sex with their mothers (r = 0.14) compared with their fathers (r = 0.03). Effects did not differ for contraceptive vs condom use or among longitudinal vs cross-sectional studies, indicating that parent sexual communication had a similar effect

Using a Narrative to Spark Safer Sex Communication

ERIC Educational Resources Information Center

Donné, Lennie; Hoeks, John; Jansen, Carel

2017-01-01

Objective: College students are a group at risk for contracting sexually transmitted infections (STIs). While they are generally well informed about STIs, they do not consistently use condoms. An important element in preventing STIs is safer sex communication, especially with a sexual partner. This may be difficult, however, because of a lack of…

NREL, NASA, and UCL Team Up to Make Lithium-Ion Batteries Safer on Earth

Science.gov Websites

and in Space | News | NREL NREL, NASA, and UCL Team Up to Make Lithium-Ion Batteries Safer on Earth and in Space NREL, NASA, and UCL Team Up to Make Lithium-Ion Batteries Safer on Earth and in Space . NREL joined forces with NASA in finding new, more precise ways to trigger internal short circuits

AI AND SAR APPROACHES FOR PREDICTING CHEMICAL CARCINOGENICITY: SURVEY AND STATUS REPORT

EPA Science Inventory

A wide variety of artificial intelligence (AI) and structure-activity relationship (SAR approaches have been applied to tackling the general problem of predicting rodent chemical carcinogenicity. Given the diversity of chemical structures and mechanisms relative to this endpoin...

Chemical Safety Alert: Use Multiple Data Sources for Safer Emergency Response

EPA Pesticide Factsheets

Increases awareness of Material Safety Data Sheet (MSDS) limitations so that first responders to accidental releases can take proper precautions and identify additional sources of chemical information, such as reactivity and incompatibility.

A NOVEL SAFER CONCEPTION COUNSELING TOOLKIT FOR THE PREVENTION OF HIV: A MIXED-METHODS EVALUATION IN KISUMU, KENYA

PubMed Central

Brown, Joelle; Njoroge, Betty; Akama, Eliud; Breitnauer, Brooke; Leddy, Anna; Darbes, Lynae; Omondi, Richard; Mmeje, Okeoma

2017-01-01

Safer conception strategies can prevent HIV transmission between HIV-discordant partners while allowing them to conceive. However, HIV care providers in sub-Saharan Africa report they are not trained in safer conception, and patients are not routinely offered safer conception services. This mixed-methods pilot study evaluated the impact, acceptability, and feasibility of a novel Safer Conception Counseling Toolkit among providers and patients in Kenya. We enrolled 20 HIV-positive women, 10 HIV-discordant couples, and 10 providers from HIV care and treatment clinics. Providers completed questionnaires before/after training, and then counseled HIV-affected patients. Change in patient knowledge was assessed before/after counseling. Qualitative interviews were conducted among providers and patients. The Toolkit was associated with large, significant increases in patient knowledge, and provider confidence, knowledge, and favorable attitudes toward safer conception counseling; 20% felt confident before versus 100% after training (p < 0.01). PMID:27925487

Prediction of Hydrolysis Products of Organic Chemicals under Environmental pH Conditions.

PubMed

Tebes-Stevens, Caroline; Patel, Jay M; Jones, W Jack; Weber, Eric J

2017-05-02

Cheminformatics-based software tools can predict the molecular structure of transformation products using a library of transformation reaction schemes. This paper presents the development of such a library for abiotic hydrolysis of organic chemicals under environmentally relevant conditions. The hydrolysis reaction schemes in the library encode the process science gathered from peer-reviewed literature and regulatory reports. Each scheme has been ranked on a scale of one to six based on the median half-life in a data set compiled from literature-reported hydrolysis rates. These ranks are used to predict the most likely transformation route when more than one structural fragment susceptible to hydrolysis is present in a molecule of interest. Separate rank assignments are established for pH 5, 7, and 9 to represent standard conditions in hydrolysis studies required for registration of pesticides in Organisation for Economic Co-operation and Development (OECD) member countries. The library is applied to predict the likely hydrolytic transformation products for two lists of chemicals, one representative of chemicals used in commerce and the other specific to pesticides, to evaluate which hydrolysis reaction pathways are most likely to be relevant for organic chemicals found in the natural environment.

SAFER vehicle inspection: a multimodal robotic sensing platform

NASA Astrophysics Data System (ADS)

Page, David L.; Fougerolle, Yohan; Koschan, Andreas F.; Gribok, Andrei; Abidi, Mongi A.; Gorsich, David J.; Gerhart, Grant R.

2004-09-01

The current threats to U.S. security both military and civilian have led to an increased interest in the development of technologies to safeguard national facilities such as military bases, federal buildings, nuclear power plants, and national laboratories. As a result, the Imaging, Robotics, and Intelligent Systems (IRIS) Laboratory at The University of Tennessee (UT) has established a research consortium, known as SAFER (Security Automation and Future Electromotive Robotics), to develop, test, and deploy sensing and imaging systems for unmanned ground vehicles (UGV). The targeted missions for these UGV systems include -- but are not limited to --under vehicle threat assessment, stand-off check-point inspections, scout surveillance, intruder detection, obstacle-breach situations, and render-safe scenarios. This paper presents a general overview of the SAFER project. Beyond this general overview, we further focus on a specific problem where we collect 3D range scans of under vehicle carriages. These scans require appropriate segmentation and representation algorithms to facilitate the vehicle inspection process. We discuss the theory for these algorithms and present results from applying them to actual vehicle scans.

Motivational influences on the safer sex behavior of agency-based male sex workers.

PubMed

Smith, Michael D; Seal, David W

2008-10-01

Although indoor male sex workers (MSWs) have been found to engage in lower rates of HIV risk behavior with clients than street-based MSWs, few studies have examined the motivations behind such practices. We interviewed 30 MSWs working for the same escort agency regarding their safer sex practices with clients and their reasons for these. As in other research, MSWs reported little risk behavior with clients. Five motivational themes related to safer sex on the job emerged: health concerns, emotional intimacy, client attractiveness, relationships, and structural work factors. Results suggest that participants engaged in rational decision-making relative to sex with clients, facilitated by reduced economic incentive for riskier behavior and a supportive social context. MSWs desired a safe sexual work place, personal integrity, and minimal negative consequences to personal relationships. Collaborating with sex work employers to study their role in encouraging a safer workplace may be important to future research.

Negotiation for safer sex among married women in Cambodia: the role of women's autonomy.

PubMed

Ung, Mengieng; Boateng, Godfred O; Armah, Frederick A; Amoyaw, Jonathan A; Luginaah, Isaac; Kuuire, Vincent

2014-01-01

Negotiating safer sex among married women has been identified as an important determinant of vulnerability or resilience to new HIV infections. Using the Cambodia Demographic and Health Survey data of 2010, this paper examined negotiation for safer sex among 11,218 married women in the context of Cambodia's highly touted reduction in HIV/AIDS prevalence. The results from a complementary log-log regression model indicate that wealthier and highly educated married women were more likely to report that they can refuse sexual intercourse and ask their husbands to use a condom. Interestingly, while women who were fully involved in decision-making on their own health care were 19% more likely to refuse sex, they were 14% less likely to be able to ask their husbands to use a condom, compared with their counterparts who were not involved in this decision-making. Women who were partially involved in decision-making on family visits were 17% less likely to be able to ask their husbands to use a condom compared with those who were not involved. In this context, involvement in decision-making may have translated into trust and risk compensation. Those who believed in HIV transmission myths were less likely to negotiate safer sex relative to their counterparts who did not hold such myths to be true. Women's ability to negotiate for safer sex is, therefore, a function of their autonomy in terms of their full participation in decision-making in health care, household expenditure and mobility. Policy implications of the capacity of women to negotiate for safer sex are delineated.

Safer Schools in the UK--A Case Study

ERIC Educational Resources Information Center

Hayden, Carol; Holt, Amanda; Martin, Denise; Nee, Claire

2011-01-01

This article reports a research that is based on a European Safer Schools Partnership that included ten countries and specifically the UK case study which was located in London. The initiators of this partnership had been involved in early SSPs in the UK and the educationalists were very much focussed on work that would address problematic…

A hybrid method for prediction and repositioning of drug Anatomical Therapeutic Chemical classes.

PubMed

Chen, Lei; Lu, Jing; Zhang, Ning; Huang, Tao; Cai, Yu-Dong

2014-04-01

In the Anatomical Therapeutic Chemical (ATC) classification system, therapeutic drugs are divided into 14 main classes according to the organ or system on which they act and their chemical, pharmacological and therapeutic properties. This system, recommended by the World Health Organization (WHO), provides a global standard for classifying medical substances and serves as a tool for international drug utilization research to improve quality of drug use. In view of this, it is necessary to develop effective computational prediction methods to identify the ATC-class of a given drug, which thereby could facilitate further analysis of this system. In this study, we initiated an attempt to develop a prediction method and to gain insights from it by utilizing ontology information of drug compounds. Since only about one-fourth of drugs in the ATC classification system have ontology information, a hybrid prediction method combining the ontology information, chemical interaction information and chemical structure information of drug compounds was proposed for the prediction of drug ATC-classes. As a result, by using the Jackknife test, the 1st prediction accuracies for identifying the 14 main ATC-classes in the training dataset, the internal validation dataset and the external validation dataset were 75.90%, 75.70% and 66.36%, respectively. Analysis of some samples with false-positive predictions in the internal and external validation datasets indicated that some of them may even have a relationship with the false-positive predicted ATC-class, suggesting novel uses of these drugs. It was conceivable that the proposed method could be used as an efficient tool to identify ATC-classes of novel drugs or to discover novel uses of known drugs.

Three Conn. Companies Provide Public with Chemical Information under EPA Settlements

EPA Pesticide Factsheets

Three Connecticut companies will report publically on their use of required toxic chemicals, creating a safer environment for the public, under the terms of three separate recent settlements with the US Environmental Protection Agency. All three settlement

Chemical Facility Security: Reauthorization, Policy Issues, and Options for Congress

DTIC Science & Technology

2010-12-10

gaseous chlorine disinfection to chloramine disinfection —a change identified by some advocacy groups as being an inherently safer substitution—as being...chemicals, such as chlorine, for purposes such as disinfection .29 Advocates for their inclusion in security regulations cite the presence of such...Science and Technology (S& T ) Directorate is engaged in a Chemical Infrastructure Risk Assessment Project that, among other goals, will assess the

EPA's ToxCast Program for Predicting Hazard and Prioritizing the Toxicity Testing of Environmental Chemicals

EPA Science Inventory

An alternative is to perform a set of relatively inexpensive and rapid high throughput screening (HTS) assays, derive signatures predictive of effects or modes of chemical toxicity from the HTS data, then use these predictions to prioritize chemicals for more detailed analysis. T...

Motivational Influences on the Safer Sex Behavior of Agency-based Male Sex Workers

PubMed Central

Smith, Michael D.; Seal, David W.

2017-01-01

Although indoor male sex workers (MSWs) have been found to engage in lower rates of HIV risk behavior with clients than street-based MSWs, few studies have examined the motivations behind such practices. We interviewed 30 MSWs working for the same escort agency regarding their safer sex practices with clients and their reasons for these. As in other research, MSWs reported little risk behavior with clients. Five motivational themes related to safer sex on the job emerged: health concerns, emotional intimacy, client attractiveness, relationships, and structural work factors. Results suggest that participants engaged in rational decision-making relative to sex with clients, facilitated by reduced economic incentive for riskier behavior and a supportive social context. MSWs desired a safe sexual work place, personal integrity, and minimal negative consequences to personal relationships. Collaborating with sex work employers to study their role in encouraging a safer workplace may be important to future research. PMID:18288599

ToxCast: Developing Predictive Signatures of Chemically Induced Toxicity (S)

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry, bioactivity profiling and toxicogenomic data to predict potential for toxicity and prioritize limited testing resour...

Do Safer Sex Self-Efficacy, Attitudes toward Condoms, and HIV Transmission Risk Beliefs Differ among Men who have Sex with Men, Heterosexual Men, and Women Living with HIV?

PubMed Central

Widman, Laura; Golin, Carol E.; Grodensky, Catherine A.; Suchindran, Chirayath

2013-01-01

To understand sexual decision-making processes among people living with HIV, we compared safer sex self-efficacy, condom attitudes, sexual beliefs, and rates of unprotected anal or vaginal intercourse with at-risk partners (UAVI-AR) in the past 3 months among 476 people living with HIV: 185 men who have sex with men (MSM), 130 heterosexual men, and 161 heterosexual women. Participants were enrolled in SafeTalk, a randomized, controlled trial of a safer sex intervention. We found 15% of MSM, 9% of heterosexual men, and 12% of heterosexual women engaged in UAVI-AR. Groups did not differ in self-efficacy or sexual attitudes/beliefs. However, the associations between these variables and UAVI-AR varied within groups: greater self-efficacy predicted less UAVI-AR for MSM and women, whereas more positive condom attitudes – but not self-efficacy – predicted less UAVI-AR for heterosexual men. These results suggest HIV prevention programs should tailor materials to different subgroups. PMID:22252475

Enhanced NMR Discrimination of Pharmaceutically Relevant Molecular Crystal Forms through Fragment-Based Ab Initio Chemical Shift Predictions.

PubMed

Hartman, Joshua D; Day, Graeme M; Beran, Gregory J O

2016-11-02

Chemical shift prediction plays an important role in the determination or validation of crystal structures with solid-state nuclear magnetic resonance (NMR) spectroscopy. One of the fundamental theoretical challenges lies in discriminating variations in chemical shifts resulting from different crystallographic environments. Fragment-based electronic structure methods provide an alternative to the widely used plane wave gauge-including projector augmented wave (GIPAW) density functional technique for chemical shift prediction. Fragment methods allow hybrid density functionals to be employed routinely in chemical shift prediction, and we have recently demonstrated appreciable improvements in the accuracy of the predicted shifts when using the hybrid PBE0 functional instead of generalized gradient approximation (GGA) functionals like PBE. Here, we investigate the solid-state 13 C and 15 N NMR spectra for multiple crystal forms of acetaminophen, phenobarbital, and testosterone. We demonstrate that the use of the hybrid density functional instead of a GGA provides both higher accuracy in the chemical shifts and increased discrimination among the different crystallographic environments. Finally, these results also provide compelling evidence for the transferability of the linear regression parameters mapping predicted chemical shieldings to chemical shifts that were derived in an earlier study.

Enhanced NMR Discrimination of Pharmaceutically Relevant Molecular Crystal Forms through Fragment-Based Ab Initio Chemical Shift Predictions

PubMed Central

2016-01-01

Chemical shift prediction plays an important role in the determination or validation of crystal structures with solid-state nuclear magnetic resonance (NMR) spectroscopy. One of the fundamental theoretical challenges lies in discriminating variations in chemical shifts resulting from different crystallographic environments. Fragment-based electronic structure methods provide an alternative to the widely used plane wave gauge-including projector augmented wave (GIPAW) density functional technique for chemical shift prediction. Fragment methods allow hybrid density functionals to be employed routinely in chemical shift prediction, and we have recently demonstrated appreciable improvements in the accuracy of the predicted shifts when using the hybrid PBE0 functional instead of generalized gradient approximation (GGA) functionals like PBE. Here, we investigate the solid-state 13C and 15N NMR spectra for multiple crystal forms of acetaminophen, phenobarbital, and testosterone. We demonstrate that the use of the hybrid density functional instead of a GGA provides both higher accuracy in the chemical shifts and increased discrimination among the different crystallographic environments. Finally, these results also provide compelling evidence for the transferability of the linear regression parameters mapping predicted chemical shieldings to chemical shifts that were derived in an earlier study. PMID:27829821

Chemical combination effects predict connectivity in biological systems

PubMed Central

Lehár, Joseph; Zimmermann, Grant R; Krueger, Andrew S; Molnar, Raymond A; Ledell, Jebediah T; Heilbut, Adrian M; Short, Glenn F; Giusti, Leanne C; Nolan, Garry P; Magid, Omar A; Lee, Margaret S; Borisy, Alexis A; Stockwell, Brent R; Keith, Curtis T

2007-01-01

Efforts to construct therapeutically useful models of biological systems require large and diverse sets of data on functional connections between their components. Here we show that cellular responses to combinations of chemicals reveal how their biological targets are connected. Simulations of pathways with pairs of inhibitors at varying doses predict distinct response surface shapes that are reproduced in a yeast experiment, with further support from a larger screen using human tumour cells. The response morphology yields detailed connectivity constraints between nearby targets, and synergy profiles across many combinations show relatedness between targets in the whole network. Constraints from chemical combinations complement genetic studies, because they probe different cellular components and can be applied to disease models that are not amenable to mutagenesis. Chemical probes also offer increased flexibility, as they can be continuously dosed, temporally controlled, and readily combined. After extending this initial study to cover a wider range of combination effects and pathway topologies, chemical combinations may be used to refine network models or to identify novel targets. This response surface methodology may even apply to non-biological systems where responses to targeted perturbations can be measured. PMID:17332758

Comparative study of biodegradability prediction of chemicals using decision trees, functional trees, and logistic regression.

PubMed

Chen, Guangchao; Li, Xuehua; Chen, Jingwen; Zhang, Ya-Nan; Peijnenburg, Willie J G M

2014-12-01

Biodegradation is the principal environmental dissipation process of chemicals. As such, it is a dominant factor determining the persistence and fate of organic chemicals in the environment, and is therefore of critical importance to chemical management and regulation. In the present study, the authors developed in silico methods assessing biodegradability based on a large heterogeneous set of 825 organic compounds, using the techniques of the C4.5 decision tree, the functional inner regression tree, and logistic regression. External validation was subsequently carried out by 2 independent test sets of 777 and 27 chemicals. As a result, the functional inner regression tree exhibited the best predictability with predictive accuracies of 81.5% and 81.0%, respectively, on the training set (825 chemicals) and test set I (777 chemicals). Performance of the developed models on the 2 test sets was subsequently compared with that of the Estimation Program Interface (EPI) Suite Biowin 5 and Biowin 6 models, which also showed a better predictability of the functional inner regression tree model. The model built in the present study exhibits a reasonable predictability compared with existing models while possessing a transparent algorithm. Interpretation of the mechanisms of biodegradation was also carried out based on the models developed. © 2014 SETAC.

New approach to predict photoallergic potentials of chemicals based on murine local lymph node assay.

PubMed

Maeda, Yosuke; Hirosaki, Haruka; Yamanaka, Hidenori; Takeyoshi, Masahiro

2018-05-23

Photoallergic dermatitis, caused by pharmaceuticals and other consumer products, is a very important issue in human health. However, S10 guidelines of the International Conference on Harmonization do not recommend the existing prediction methods for photoallergy because of their low predictability in human cases. We applied local lymph node assay (LLNA), a reliable, quantitative skin sensitization prediction test, to develop a new photoallergy prediction method. This method involves a three-step approach: (1) ultraviolet (UV) absorption analysis; (2) determination of no observed adverse effect level for skin phototoxicity based on LLNA; and (3) photoallergy evaluation based on LLNA. Photoallergic potential of chemicals was evaluated by comparing lymph node cell proliferation among groups treated with chemicals with minimal effect levels of skin sensitization and skin phototoxicity under UV irradiation (UV+) or non-UV irradiation (UV-). A case showing significant difference (P < .05) in lymph node cell proliferation rates between UV- and UV+ groups was considered positive for photoallergic reaction. After testing 13 chemicals, seven human photoallergens tested positive and the other six, with no evidence of causing photoallergic dermatitis or UV absorption, tested negative. Among these chemicals, both doxycycline hydrochloride and minocycline hydrochloride were tetracycline antibiotics with different photoallergic properties, and the new method clearly distinguished between the photoallergic properties of these chemicals. These findings suggested high predictability of our method; therefore, it is promising and effective in predicting human photoallergens. Copyright © 2018 John Wiley & Sons, Ltd.

STRUCTURE-ACTIVITY RELATIONSHIP STUIDES AND THEIR ROLE IN PREDICTING AND INVESTIGATING CHEMICAL TOXICITY

EPA Science Inventory

Structure-Activity Relationship Studies and their Role in Predicting and Investigating Chemical Toxicity

Structure-activity relationships (SAR) represent attempts to generalize chemical information relative to biological activity for the twin purposes of generating insigh...

CADASTER QSPR Models for Predictions of Melting and Boiling Points of Perfluorinated Chemicals.

PubMed

Bhhatarai, Barun; Teetz, Wolfram; Liu, Tao; Öberg, Tomas; Jeliazkova, Nina; Kochev, Nikolay; Pukalov, Ognyan; Tetko, Igor V; Kovarich, Simona; Papa, Ester; Gramatica, Paola

2011-03-14

Quantitative structure property relationship (QSPR) studies on per- and polyfluorinated chemicals (PFCs) on melting point (MP) and boiling point (BP) are presented. The training and prediction chemicals used for developing and validating the models were selected from Syracuse PhysProp database and literatures. The available experimental data sets were split in two different ways: a) random selection on response value, and b) structural similarity verified by self-organizing-map (SOM), in order to propose reliable predictive models, developed only on the training sets and externally verified on the prediction sets. Individual linear and non-linear approaches based models developed by different CADASTER partners on 0D-2D Dragon descriptors, E-state descriptors and fragment based descriptors as well as consensus model and their predictions are presented. In addition, the predictive performance of the developed models was verified on a blind external validation set (EV-set) prepared using PERFORCE database on 15 MP and 25 BP data respectively. This database contains only long chain perfluoro-alkylated chemicals, particularly monitored by regulatory agencies like US-EPA and EU-REACH. QSPR models with internal and external validation on two different external prediction/validation sets and study of applicability-domain highlighting the robustness and high accuracy of the models are discussed. Finally, MPs for additional 303 PFCs and BPs for 271 PFCs were predicted for which experimental measurements are unknown. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Rapid prediction of chemical metabolism by human UDP-glucuronosyltransferase isoforms using quantum chemical descriptors derived with the electronegativity equalization method.

PubMed

Sorich, Michael J; McKinnon, Ross A; Miners, John O; Winkler, David A; Smith, Paul A

2004-10-07

This study aimed to evaluate in silico models based on quantum chemical (QC) descriptors derived using the electronegativity equalization method (EEM) and to assess the use of QC properties to predict chemical metabolism by human UDP-glucuronosyltransferase (UGT) isoforms. Various EEM-derived QC molecular descriptors were calculated for known UGT substrates and nonsubstrates. Classification models were developed using support vector machine and partial least squares discriminant analysis. In general, the most predictive models were generated with the support vector machine. Combining QC and 2D descriptors (from previous work) using a consensus approach resulted in a statistically significant improvement in predictivity (to 84%) over both the QC and 2D models and the other methods of combining the descriptors. EEM-derived QC descriptors were shown to be both highly predictive and computationally efficient. It is likely that EEM-derived QC properties will be generally useful for predicting ADMET and physicochemical properties during drug discovery.

McArthur conducts SAFER onboard training during Expedition 12

NASA Image and Video Library

2005-10-21

ISS012-E-06035 (21 October 2005) --- Astronaut William S. McArthur Jr., Expedition 12 commander and NASA science officer, holds a Hand Control Module (HCM) while looking at laptop computer graphics during a Simplified Aid for EVA Rescue (SAFER) training session in the Unity node of the international space station.

McArthur conducts SAFER onboard training during Expedition 12

NASA Image and Video Library

2005-10-21

ISS012-E-06030 (21 October 2005) --- Astronaut William S. McArthur Jr., Expedition 12 commander and NASA science officer, holds a Hand Control Module (HCM) while looking at laptop computer graphics during a Simplified Aid for EVA Rescue (SAFER) training session in the Unity node of the international space station.

Immobilizer-assisted management of metal-contaminated agricultural soils for safer food production.

PubMed

Kim, Kwon-Rae; Kim, Jeong-Gyu; Park, Jeong-Sik; Kim, Min-Suk; Owens, Gary; Youn, Gyu-Hoon; Lee, Jin-Su

2012-07-15

Production of food crops on metal contaminated agricultural soils is of concern because consumers are potentially exposed to hazardous metals via dietary intake of such crops or crop derived products. Therefore, the current study was conducted to develop management protocols for crop cultivation to allow safer food production. Metal uptake, as influenced by pH change-induced immobilizing agents (dolomite, steel slag, and agricultural lime) and sorption agents (zeolite and compost), was monitored in three common plants representative of leafy (Chinese cabbage), root (spring onion) and fruit (red pepper) vegetables, in a field experiment. The efficiency of the immobilizing agents was assessed by their ability to decrease the phytoavailability of metals (Cd, Pb, and Zn). The fruit vegetable (red pepper) showed the least accumulation of Cd (0.16-0.29 mgkg(-1) DW) and Pb (0.2-0.9 mgkg(-1) DW) in edible parts regardless of treatment, indicating selection of low metal accumulating crops was a reasonable strategy for safer food production. However, safer food production was more likely to be achievable by combining crop selection with immobilizing agent amendment of soils. Among the immobilizing agents, pH change-induced immobilizers were more effective than sorption agents, showing decreases in Cd and Pb concentrations in each plant well below standard limits. The efficiency of pH change-induced immobilizers was also comparable to reductions obtained by 'clean soil cover' where the total metal concentrations of the plow layer was reduced via capping the surface with uncontaminated soil, implying that pH change-induced immobilizers can be practically applied to metal contaminated agricultural soils for safer food production. Copyright © 2012 Elsevier Ltd. All rights reserved.

A framework for an alternatives assessment dashboard for evaluating chemical alternatives applied to flame retardants for electronic applications

EPA Science Inventory

The goal of alternatives assessment (AA) is to facilitate a comparison of alternatives to a chemical of concern, resulting in the identification of safer alternatives. A two-stage methodology for comparing chemical alternatives was developed. In the first stage, alternatives are ...

Predictive Structure-Based Toxicology Approaches To Assess the Androgenic Potential of Chemicals.

PubMed

Trisciuzzi, Daniela; Alberga, Domenico; Mansouri, Kamel; Judson, Richard; Novellino, Ettore; Mangiatordi, Giuseppe Felice; Nicolotti, Orazio

2017-11-27

We present a practical and easy-to-run in silico workflow exploiting a structure-based strategy making use of docking simulations to derive highly predictive classification models of the androgenic potential of chemicals. Models were trained on a high-quality chemical collection comprising 1689 curated compounds made available within the CoMPARA consortium from the US Environmental Protection Agency and were integrated with a two-step applicability domain whose implementation had the effect of improving both the confidence in prediction and statistics by reducing the number of false negatives. Among the nine androgen receptor X-ray solved structures, the crystal 2PNU (entry code from the Protein Data Bank) was associated with the best performing structure-based classification model. Three validation sets comprising each 2590 compounds extracted by the DUD-E collection were used to challenge model performance and the effectiveness of Applicability Domain implementation. Next, the 2PNU model was applied to screen and prioritize two collections of chemicals. The first is a small pool of 12 representative androgenic compounds that were accurately classified based on outstanding rationale at the molecular level. The second is a large external blind set of 55450 chemicals with potential for human exposure. We show how the use of molecular docking provides highly interpretable models and can represent a real-life option as an alternative nontesting method for predictive toxicology.

Learning to Predict Chemical Reactions

PubMed Central

Kayala, Matthew A.; Azencott, Chloé-Agathe; Chen, Jonathan H.

2011-01-01

Being able to predict the course of arbitrary chemical reactions is essential to the theory and applications of organic chemistry. Approaches to the reaction prediction problems can be organized around three poles corresponding to: (1) physical laws; (2) rule-based expert systems; and (3) inductive machine learning. Previous approaches at these poles respectively are not high-throughput, are not generalizable or scalable, or lack sufficient data and structure to be implemented. We propose a new approach to reaction prediction utilizing elements from each pole. Using a physically inspired conceptualization, we describe single mechanistic reactions as interactions between coarse approximations of molecular orbitals (MOs) and use topological and physicochemical attributes as descriptors. Using an existing rule-based system (Reaction Explorer), we derive a restricted chemistry dataset consisting of 1630 full multi-step reactions with 2358 distinct starting materials and intermediates, associated with 2989 productive mechanistic steps and 6.14 million unproductive mechanistic steps. And from machine learning, we pose identifying productive mechanistic steps as a statistical ranking, information retrieval, problem: given a set of reactants and a description of conditions, learn a ranking model over potential filled-to-unfilled MO interactions such that the top ranked mechanistic steps yield the major products. The machine learning implementation follows a two-stage approach, in which we first train atom level reactivity filters to prune 94.00% of non-productive reactions with a 0.01% error rate. Then, we train an ensemble of ranking models on pairs of interacting MOs to learn a relative productivity function over mechanistic steps in a given system. Without the use of explicit transformation patterns, the ensemble perfectly ranks the productive mechanism at the top 89.05% of the time, rising to 99.86% of the time when the top four are considered. Furthermore, the system

Learning to predict chemical reactions.

PubMed

Kayala, Matthew A; Azencott, Chloé-Agathe; Chen, Jonathan H; Baldi, Pierre

2011-09-26

Being able to predict the course of arbitrary chemical reactions is essential to the theory and applications of organic chemistry. Approaches to the reaction prediction problems can be organized around three poles corresponding to: (1) physical laws; (2) rule-based expert systems; and (3) inductive machine learning. Previous approaches at these poles, respectively, are not high throughput, are not generalizable or scalable, and lack sufficient data and structure to be implemented. We propose a new approach to reaction prediction utilizing elements from each pole. Using a physically inspired conceptualization, we describe single mechanistic reactions as interactions between coarse approximations of molecular orbitals (MOs) and use topological and physicochemical attributes as descriptors. Using an existing rule-based system (Reaction Explorer), we derive a restricted chemistry data set consisting of 1630 full multistep reactions with 2358 distinct starting materials and intermediates, associated with 2989 productive mechanistic steps and 6.14 million unproductive mechanistic steps. And from machine learning, we pose identifying productive mechanistic steps as a statistical ranking, information retrieval problem: given a set of reactants and a description of conditions, learn a ranking model over potential filled-to-unfilled MO interactions such that the top-ranked mechanistic steps yield the major products. The machine learning implementation follows a two-stage approach, in which we first train atom level reactivity filters to prune 94.00% of nonproductive reactions with a 0.01% error rate. Then, we train an ensemble of ranking models on pairs of interacting MOs to learn a relative productivity function over mechanistic steps in a given system. Without the use of explicit transformation patterns, the ensemble perfectly ranks the productive mechanism at the top 89.05% of the time, rising to 99.86% of the time when the top four are considered. Furthermore, the system

Significance of vapor phase chemical reactions on CVD rates predicted by chemically frozen and local thermochemical equilibrium boundary layer theories

NASA Technical Reports Server (NTRS)

Gokoglu, Suleyman A.

1988-01-01

This paper investigates the role played by vapor-phase chemical reactions on CVD rates by comparing the results of two extreme theories developed to predict CVD mass transport rates in the absence of interfacial kinetic barrier: one based on chemically frozen boundary layer and the other based on local thermochemical equilibrium. Both theories consider laminar convective-diffusion boundary layers at high Reynolds numbers and include thermal (Soret) diffusion and variable property effects. As an example, Na2SO4 deposition was studied. It was found that gas phase reactions have no important role on Na2SO4 deposition rates and on the predictions of the theories. The implications of the predictions of the two theories to other CVD systems are discussed.

Predicting acute aquatic toxicity of structurally diverse chemicals in fish using artificial intelligence approaches.

PubMed

Singh, Kunwar P; Gupta, Shikha; Rai, Premanjali

2013-09-01

The research aims to develop global modeling tools capable of categorizing structurally diverse chemicals in various toxicity classes according to the EEC and European Community directives, and to predict their acute toxicity in fathead minnow using set of selected molecular descriptors. Accordingly, artificial intelligence approach based classification and regression models, such as probabilistic neural networks (PNN), generalized regression neural networks (GRNN), multilayer perceptron neural network (MLPN), radial basis function neural network (RBFN), support vector machines (SVM), gene expression programming (GEP), and decision tree (DT) were constructed using the experimental toxicity data. Diversity and non-linearity in the chemicals' data were tested using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. Predictive and generalization abilities of various models constructed here were compared using several statistical parameters. PNN and GRNN models performed relatively better than MLPN, RBFN, SVM, GEP, and DT. Both in two and four category classifications, PNN yielded a considerably high accuracy of classification in training (95.85 percent and 90.07 percent) and validation data (91.30 percent and 86.96 percent), respectively. GRNN rendered a high correlation between the measured and model predicted -log LC50 values both for the training (0.929) and validation (0.910) data and low prediction errors (RMSE) of 0.52 and 0.49 for two sets. Efficiency of the selected PNN and GRNN models in predicting acute toxicity of new chemicals was adequately validated using external datasets of different fish species (fathead minnow, bluegill, trout, and guppy). The PNN and GRNN models showed good predictive and generalization abilities and can be used as tools for predicting toxicities of structurally diverse chemical compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

Self-rescue strategies for EVA crewmembers equipped with the SAFER backpack

NASA Technical Reports Server (NTRS)

Williams, Trevor; Baughman, David

1994-01-01

An extravehicular astronaut who becomes separated from a space station has three options available: grappling the station immediately by means of a 'shepherd's crook' device; rescue by either a second crewmember flying an MMU or a robotic-controlled MMU; or self-rescue by means of a propulsive system. The first option requires very fast response by a tumbling astronaut; the second requires constant availability of an MMU, as well as a rendezvous procedure thousands of feet from the station. This paper will consider the third option, propulsive self-rescue. In particular, the capability of the new Simplified Aid for EVA Rescue (SAFER) propulsive backpack, which is to be tested on STS-64 in Sep. 1994, will be studied. This system possesses an attitude hold function that can automatically detumble an astronaut after separation. On-orbit tests of candidate self-rescue systems have demonstrated the need for such a feature. SAFER has a total delta(v) capability of about 10 fps, to cover both rotations and translations, compared with a possible separation rate of 2.5 fps. But the delta(v) required for self-rescue is critically dependent on the delay before return can be initiated, as a consequence of orbital effects. A very important practical question is then whether the total delta(v) of SAFER is adequate to perform self-rescue for worst case values of separation speed, time to detumble, and time for the astronaut to visually acquire the station. This paper shows that SAFER does indeed have sufficient propellant to carry out self-rescue in all realistic separation cases, as well as in cases which are considerably more severe than anything likely to be encountered in practice. The return trajectories and total delta(v)'s discussed are obtained by means of an 'inertial line-of-sight targeting' scheme, derived in the paper, which allows orbital effects to be corrected by making use of the visual information available to the pilot, namely the line-of-sight direction to the

Development and Validation of Decision Forest Model for Estrogen Receptor Binding Prediction of Chemicals Using Large Data Sets.

PubMed

Ng, Hui Wen; Doughty, Stephen W; Luo, Heng; Ye, Hao; Ge, Weigong; Tong, Weida; Hong, Huixiao

2015-12-21

Some chemicals in the environment possess the potential to interact with the endocrine system in the human body. Multiple receptors are involved in the endocrine system; estrogen receptor α (ERα) plays very important roles in endocrine activity and is the most studied receptor. Understanding and predicting estrogenic activity of chemicals facilitates the evaluation of their endocrine activity. Hence, we have developed a decision forest classification model to predict chemical binding to ERα using a large training data set of 3308 chemicals obtained from the U.S. Food and Drug Administration's Estrogenic Activity Database. We tested the model using cross validations and external data sets of 1641 chemicals obtained from the U.S. Environmental Protection Agency's ToxCast project. The model showed good performance in both internal (92% accuracy) and external validations (∼ 70-89% relative balanced accuracies), where the latter involved the validations of the model across different ER pathway-related assays in ToxCast. The important features that contribute to the prediction ability of the model were identified through informative descriptor analysis and were related to current knowledge of ER binding. Prediction confidence analysis revealed that the model had both high prediction confidence and accuracy for most predicted chemicals. The results demonstrated that the model constructed based on the large training data set is more accurate and robust for predicting ER binding of chemicals than the published models that have been developed using much smaller data sets. The model could be useful for the evaluation of ERα-mediated endocrine activity potential of environmental chemicals.

PREDICTION METRICS FOR CHEMICAL DETECTION IN LONG-WAVE INFRARED HYPERSPECTRAL IMAGERY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chilton, M.; Walsh, S.J.; Daly, D.S.

2009-01-01

Natural and man-made chemical processes generate gaseous plumes that may be detected by hyperspectral imaging, which produces a matrix of spectra affected by the chemical constituents of the plume, the atmosphere, the bounding background surface and instrument noise. A physics-based model of observed radiance shows that high chemical absorbance and low background emissivity result in a larger chemical signature. Using simulated hyperspectral imagery, this study investigated two metrics which exploited this relationship. The objective was to explore how well the chosen metrics predicted when a chemical would be more easily detected when comparing one background type to another. The twomore » predictor metrics correctly rank ordered the backgrounds for about 94% of the chemicals tested as compared to the background rank orders from Whitened Matched Filtering (a detection algorithm) of the simulated spectra. These results suggest that the metrics provide a reasonable summary of how the background emissivity and chemical absorbance interact to produce the at-sensor chemical signal. This study suggests that similarly effective predictors that account for more general physical conditions may be derived.« less

Identifying Subtypes of Spousal Assaulters Using the B-SAFER

ERIC Educational Resources Information Center

Thijssen, Jill; de Ruiter, Corine

2011-01-01

In the present study, a structured risk assessment instrument for intimate partner violence, the Brief Spousal Assault Form for the Evaluation of Risk (B-SAFER), was coded for 146 files of spousal assault cases from the Dutch probation service, dating from 2004 and 2005. The aim of the study was twofold: (a) to validate Holtzworth-Munroe and…

A Pilot Model for the NASA Simplified Aid for EVA Rescue (SAFER) (Single-Axis Pitch Task)

NASA Astrophysics Data System (ADS)

Handley, Patrick Mark

This thesis defines, tests, and validates a descriptive pilot model for a single-axis pitch control task of the Simplified Aid for EVA Rescue (SAFER). SAFER is a small propulsive jetpack used by astronauts for self-rescue. Pilot model research supports development of improved self-rescue strategies and technologies through insights into pilot behavior.This thesis defines a multi-loop pilot model. The innermost loop controls the hand controller, the middle loop controls pitch rate, and the outer loop controls pitch angle. A human-in-the-loop simulation was conducted to gather data from a human pilot. Quantitative and qualitative metrics both indicate that the model is an acceptable fit to the human data. Fuel consumption was nearly identical; time to task completion matched very well. There is some evidence that the model responds faster to initial pitch rates than the human, artificially decreasing the model's time to task completion. This pilot model is descriptive, not predictive, of the human pilot. Insights are made into pilot behavior from this research. Symmetry implies that the human responds to positive and negative initial conditions with the same strategy. The human pilot appears indifferent to pitch angles within 0.5 deg, coasts at a constant pitch rate 1.09 deg/s, and has a reaction delay of 0.1 s.

Minority Stress and Safer Sex Practices Among Sexual Minority Women in Toronto, Canada: Results from a Cross-Sectional Internet-Based Survey.

PubMed

Logie, Carmen H; Lacombe-Duncan, Ashley; MacKenzie, Rachel K; Poteat, Tonia

2016-12-01

Sexual stigma is a chronic stressor that enhances vulnerability to mental health disparities among lesbian, gay, bisexual, and queer people. Sexual stigma has also been associated with reduced uptake of safer sex practices, such as condom use, among gay and bisexual men. Scant research has examined the relationship between sexual stigma and safer sex practices among sexual minority women (SMW), including lesbian, bisexual, and queer women. We explored associations between sexual stigma and safer sex practices among SMW. We also tested the interaction between sexual stigma, social support, and resilient coping in this relationship. A cross-sectional internet-based survey was administered to SMW in Toronto, Canada. Among 388 participants with complete measurement data, simple linear regression indicated both perceived and enacted sexual stigma were positively associated with uptake of safer sex practices. In multivariable analyses, significant interactions were found between perceived sexual stigma and resilient coping, and between enacted sexual stigma and social support. At low levels of resilient coping, higher levels of perceived sexual stigma were associated with fewer safer sex practices, while at high levels of resilient coping the relationship was reversed. At low levels of social support, higher levels of enacted sexual stigma were associated with fewer safer sex practices, while at high levels of social support the relationship was reversed. These findings document complex relationships between sexual stigma dimensions, coping, social support, and safer sex practices. Understanding the role these variables play in uptake of safer sex practices can inform sexual health interventions tailored for SMW.

CDC Vital Signs: Making Health Care Safer -- Think Sepsis. Time Matters.

MedlinePlus

... Press Kit Read the MMWR Science Clips Making Health Care Safer Think sepsis. Time matters. Language: English (US) ... the antibiotic type, dose, and duration are correct. Health care facility CEOs/administrators can Make infection control a ...

Similarity-based prediction for Anatomical Therapeutic Chemical classification of drugs by integrating multiple data sources.

PubMed

Liu, Zhongyang; Guo, Feifei; Gu, Jiangyong; Wang, Yong; Li, Yang; Wang, Dan; Lu, Liang; Li, Dong; He, Fuchu

2015-06-01

Anatomical Therapeutic Chemical (ATC) classification system, widely applied in almost all drug utilization studies, is currently the most widely recognized classification system for drugs. Currently, new drug entries are added into the system only on users' requests, which leads to seriously incomplete drug coverage of the system, and bioinformatics prediction is helpful during this process. Here we propose a novel prediction model of drug-ATC code associations, using logistic regression to integrate multiple heterogeneous data sources including chemical structures, target proteins, gene expression, side-effects and chemical-chemical associations. The model obtains good performance for the prediction not only on ATC codes of unclassified drugs but also on new ATC codes of classified drugs assessed by cross-validation and independent test sets, and its efficacy exceeds previous methods. Further to facilitate the use, the model is developed into a user-friendly web service SPACE ( S: imilarity-based P: redictor of A: TC C: od E: ), which for each submitted compound, will give candidate ATC codes (ranked according to the decreasing probability_score predicted by the model) together with corresponding supporting evidence. This work not only contributes to knowing drugs' therapeutic, pharmacological and chemical properties, but also provides clues for drug repositioning and side-effect discovery. In addition, the construction of the prediction model also provides a general framework for similarity-based data integration which is suitable for other drug-related studies such as target, side-effect prediction etc. The web service SPACE is available at http://www.bprc.ac.cn/space. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Near elimination of ventricular pacing in SafeR mode compared to DDD modes: a randomized study of 422 patients.

PubMed

Davy, Jean-Marc; Hoffmann, Ellen; Frey, Axel; Jocham, Kurt; Rossi, Stefano; Dupuis, Jean-Marc; Frabetti, Lorenzo; Ducloux, Pascale; Prades, Emmanuel; Jauvert, Gaël

2012-04-01

SafeR performance versus DDD/automatic mode conversion (DDD/AMC) and DDD with a 250-ms atrioventricular (AV) delay (DDD/LD) modes was assessed toward ventricular pacing (Vp) reduction. After a 1-month run-in phase, recipients of dual-chamber pacemakers without persistent AV block and persistent atrial fibrillation (AF) were randomly assigned to SafeR, DDD/AMC, or DDD/LD in a 1:1:1 design. The main endpoint was the percentage of Vp (%Vp) at 2 months and 1 year after randomization, ascertained from device memories. Secondary endpoints include %Vp at 1 year according to pacing indication and 1-year AF incidence based on automatic mode switch device stored episodes. Among 422 randomized patients (73.2±10.6 years, 50% men, sinus node dysfunction 47.4%, paroxysmal AV block 30.3%, bradycardia-tachycardia syndrome 21.8%), 141 were assigned to SafeR versus 146 to DDD/AMC and 135 to DDD/LD modes. Mean %Vp at 2 months was 3.4±12.6% in SafeR versus 33.6±34.7% and 14.0±26.0% in DDD/AMC and DDD/LD modes, respectively (P<0.0001 for both). At 1 year, mean %Vp in SafeR was 4.5±15.3% versus 37.9±34.4% and 16.7±28.0% in DDD/AMC and DDD/LD modes, respectively (P<0.0001 for both). The proportion of patients in whom Vp was completely eliminated was significantly higher in SafeR (69%) versus DDD/AMC (15%) and DDD/LD (45%) modes (P<0.0001 for both), regardless of pacing indication. The absolute risk of developing permanent AF or of remaining in AF for >30% of the time was 5.4% lower in SafeR than in the DDD pacing group (ns). In this selected patient population, SafeR markedly suppressed unnecessary Vp compared with DDD modes. ©2012, The Authors. Journal compilation ©2012 Wiley Periodicals, Inc.

Molecular Structure-Based Large-Scale Prediction of Chemical-Induced Gene Expression Changes.

PubMed

Liu, Ruifeng; AbdulHameed, Mohamed Diwan M; Wallqvist, Anders

2017-09-25

The quantitative structure-activity relationship (QSAR) approach has been used to model a wide range of chemical-induced biological responses. However, it had not been utilized to model chemical-induced genomewide gene expression changes until very recently, owing to the complexity of training and evaluating a very large number of models. To address this issue, we examined the performance of a variable nearest neighbor (v-NN) method that uses information on near neighbors conforming to the principle that similar structures have similar activities. Using a data set of gene expression signatures of 13 150 compounds derived from cell-based measurements in the NIH Library of Integrated Network-based Cellular Signatures program, we were able to make predictions for 62% of the compounds in a 10-fold cross validation test, with a correlation coefficient of 0.61 between the predicted and experimentally derived signatures-a reproducibility rivaling that of high-throughput gene expression measurements. To evaluate the utility of the predicted gene expression signatures, we compared the predicted and experimentally derived signatures in their ability to identify drugs known to cause specific liver, kidney, and heart injuries. Overall, the predicted and experimentally derived signatures had similar receiver operating characteristics, whose areas under the curve ranged from 0.71 to 0.77 and 0.70 to 0.73, respectively, across the three organ injury models. However, detailed analyses of enrichment curves indicate that signatures predicted from multiple near neighbors outperformed those derived from experiments, suggesting that averaging information from near neighbors may help improve the signal from gene expression measurements. Our results demonstrate that the v-NN method can serve as a practical approach for modeling large-scale, genomewide, chemical-induced, gene expression changes.

Efficient first-principles prediction of solid stability: Towards chemical accuracy

NASA Astrophysics Data System (ADS)

Zhang, Yubo; Kitchaev, Daniil A.; Yang, Julia; Chen, Tina; Dacek, Stephen T.; Sarmiento-Pérez, Rafael A.; Marques, Maguel A. L.; Peng, Haowei; Ceder, Gerbrand; Perdew, John P.; Sun, Jianwei

2018-03-01

The question of material stability is of fundamental importance to any analysis of system properties in condensed matter physics and materials science. The ability to evaluate chemical stability, i.e., whether a stoichiometry will persist in some chemical environment, and structure selection, i.e. what crystal structure a stoichiometry will adopt, is critical to the prediction of materials synthesis, reactivity and properties. Here, we demonstrate that density functional theory, with the recently developed strongly constrained and appropriately normed (SCAN) functional, has advanced to a point where both facets of the stability problem can be reliably and efficiently predicted for main group compounds, while transition metal compounds are improved but remain a challenge. SCAN therefore offers a robust model for a significant portion of the periodic table, presenting an opportunity for the development of novel materials and the study of fine phase transformations even in largely unexplored systems with little to no experimental data.

Efficient first-principles prediction of solid stability: Towards chemical accuracy

DOE PAGES

Zhang, Yubo; Kitchaev, Daniil A.; Yang, Julia; ...

2018-03-09

The question of material stability is of fundamental importance to any analysis of system properties in condensed matter physics and materials science. The ability to evaluate chemical stability, i.e., whether a stoichiometry will persist in some chemical environment, and structure selection, i.e. what crystal structure a stoichiometry will adopt, is critical to the prediction of materials synthesis, reactivity and properties. In this paper, we demonstrate that density functional theory, with the recently developed strongly constrained and appropriately normed (SCAN) functional, has advanced to a point where both facets of the stability problem can be reliably and efficiently predicted for mainmore » group compounds, while transition metal compounds are improved but remain a challenge. SCAN therefore offers a robust model for a significant portion of the periodic table, presenting an opportunity for the development of novel materials and the study of fine phase transformations even in largely unexplored systems with little to no experimental data.« less

Efficient first-principles prediction of solid stability: Towards chemical accuracy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yubo; Kitchaev, Daniil A.; Yang, Julia

The question of material stability is of fundamental importance to any analysis of system properties in condensed matter physics and materials science. The ability to evaluate chemical stability, i.e., whether a stoichiometry will persist in some chemical environment, and structure selection, i.e. what crystal structure a stoichiometry will adopt, is critical to the prediction of materials synthesis, reactivity and properties. In this paper, we demonstrate that density functional theory, with the recently developed strongly constrained and appropriately normed (SCAN) functional, has advanced to a point where both facets of the stability problem can be reliably and efficiently predicted for mainmore » group compounds, while transition metal compounds are improved but remain a challenge. SCAN therefore offers a robust model for a significant portion of the periodic table, presenting an opportunity for the development of novel materials and the study of fine phase transformations even in largely unexplored systems with little to no experimental data.« less

Predicting bioconcentration of chemicals into vegetation from soil or air using the molecular connectivity index

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dowdy, D.L.; McKone, T.E.; Hsieh, D.P.H.

1995-12-31

Bioconcentration factors (BCFs) are the ratio of chemical concentration found in an exposed organism (in this case a plant) to the concentration in an air or soil exposure medium. The authors examine here the use of molecular connectivity indices (MCIs) as quantitative structure-activity relationships (QSARS) for predicting BCFs for organic chemicals between plants and air or soil. The authors compare the reliability of the octanol-air partition coefficient (K{sub oa}) to the MC based prediction method for predicting plant/air partition coefficients. The authors also compare the reliability of the octanol/water partition coefficient (K{sub ow}) to the MC based prediction method formore » predicting plant/soil partition coefficients. The results here indicate that, relative to the use of K{sub ow} or K{sub oa} as predictors of BCFs the MC can substantially increase the reliability with which BCFs can be estimated. The authors find that the MC provides a relatively precise and accurate method for predicting the potential biotransfer of a chemical from environmental media into plants. In addition, the MC is much faster and more cost effective than direct measurements.« less

Novel naïve Bayes classification models for predicting the carcinogenicity of chemicals.

PubMed

Zhang, Hui; Cao, Zhi-Xing; Li, Meng; Li, Yu-Zhi; Peng, Cheng

2016-11-01

The carcinogenicity prediction has become a significant issue for the pharmaceutical industry. The purpose of this investigation was to develop a novel prediction model of carcinogenicity of chemicals by using a naïve Bayes classifier. The established model was validated by the internal 5-fold cross validation and external test set. The naïve Bayes classifier gave an average overall prediction accuracy of 90 ± 0.8% for the training set and 68 ± 1.9% for the external test set. Moreover, five simple molecular descriptors (e.g., AlogP, Molecular weight (M W ), No. of H donors, Apol and Wiener) considered as important for the carcinogenicity of chemicals were identified, and some substructures related to the carcinogenicity were achieved. Thus, we hope the established naïve Bayes prediction model could be applied to filter early-stage molecules for this potential carcinogenicity adverse effect; and the identified five simple molecular descriptors and substructures of carcinogens would give a better understanding of the carcinogenicity of chemicals, and further provide guidance for medicinal chemists in the design of new candidate drugs and lead optimization, ultimately reducing the attrition rate in later stages of drug development. Copyright © 2016 Elsevier Ltd. All rights reserved.

Safety in the Chemical Laboratory: Learning How to Run Safer Undergraduate Laboratories.

ERIC Educational Resources Information Center

Mohrig, Jerry R.

1983-01-01

Discusses responsibilities for providing safe experiments and for teaching about safety. Provides lists of references on chemical safety and regulated/potential carcinogens. Also discusses general laboratory safety procedures including waste disposal and recycling of solvents. (JM)

QSAR classification models for the prediction of endocrine disrupting activity of brominated flame retardants.

PubMed

Kovarich, Simona; Papa, Ester; Gramatica, Paola

2011-06-15

The identification of potential endocrine disrupting (ED) chemicals is an important task for the scientific community due to their diffusion in the environment; the production and use of such compounds will be strictly regulated through the authorization process of the REACH regulation. To overcome the problem of insufficient experimental data, the quantitative structure-activity relationship (QSAR) approach is applied to predict the ED activity of new chemicals. In the present study QSAR classification models are developed, according to the OECD principles, to predict the ED potency for a class of emerging ubiquitary pollutants, viz. brominated flame retardants (BFRs). Different endpoints related to ED activity (i.e. aryl hydrocarbon receptor agonism and antagonism, estrogen receptor agonism and antagonism, androgen and progesterone receptor antagonism, T4-TTR competition, E2SULT inhibition) are modeled using the k-NN classification method. The best models are selected by maximizing the sensitivity and external predictive ability. We propose simple QSARs (based on few descriptors) characterized by internal stability, good predictive power and with a verified applicability domain. These models are simple tools that are applicable to screen BFRs in relation to their ED activity, and also to design safer alternatives, in agreement with the requirements of REACH regulation at the authorization step. Copyright © 2011 Elsevier B.V. All rights reserved.

Stigma to Sage: Learning and Teaching Safer Sex Practices Among Canadian Sex Trade Workers. NALL Working Paper.

ERIC Educational Resources Information Center

Meaghan, Diane

A study interviewed 37 Canadian sex workers in 4 cities to determine how they acquire a working knowledge of safer sex practices and what that knowledge constituted. Findings indicated the vast majority exhibited high levels of knowledge and efficacy regarding safer sex practices; sex workers took the initiative to obtain information and engage in…

NMRDSP: an accurate prediction of protein shape strings from NMR chemical shifts and sequence data.

PubMed

Mao, Wusong; Cong, Peisheng; Wang, Zhiheng; Lu, Longjian; Zhu, Zhongliang; Li, Tonghua

2013-01-01

Shape string is structural sequence and is an extremely important structure representation of protein backbone conformations. Nuclear magnetic resonance chemical shifts give a strong correlation with the local protein structure, and are exploited to predict protein structures in conjunction with computational approaches. Here we demonstrate a novel approach, NMRDSP, which can accurately predict the protein shape string based on nuclear magnetic resonance chemical shifts and structural profiles obtained from sequence data. The NMRDSP uses six chemical shifts (HA, H, N, CA, CB and C) and eight elements of structure profiles as features, a non-redundant set (1,003 entries) as the training set, and a conditional random field as a classification algorithm. For an independent testing set (203 entries), we achieved an accuracy of 75.8% for S8 (the eight states accuracy) and 87.8% for S3 (the three states accuracy). This is higher than only using chemical shifts or sequence data, and confirms that the chemical shift and the structure profile are significant features for shape string prediction and their combination prominently improves the accuracy of the predictor. We have constructed the NMRDSP web server and believe it could be employed to provide a solid platform to predict other protein structures and functions. The NMRDSP web server is freely available at http://cal.tongji.edu.cn/NMRDSP/index.jsp.

Incorporating High-Throughput Exposure Predictions With Dosimetry-Adjusted In Vitro Bioactivity to Inform Chemical Toxicity Testing

PubMed Central

Wetmore, Barbara A.; Wambaugh, John F.; Allen, Brittany; Ferguson, Stephen S.; Sochaski, Mark A.; Setzer, R. Woodrow; Houck, Keith A.; Strope, Cory L.; Cantwell, Katherine; Judson, Richard S.; LeCluyse, Edward; Clewell, Harvey J.; Thomas, Russell S.; Andersen, Melvin E.

2015-01-01

We previously integrated dosimetry and exposure with high-throughput screening (HTS) to enhance the utility of ToxCast HTS data by translating in vitro bioactivity concentrations to oral equivalent doses (OEDs) required to achieve these levels internally. These OEDs were compared against regulatory exposure estimates, providing an activity-to-exposure ratio (AER) useful for a risk-based ranking strategy. As ToxCast efforts expand (ie, Phase II) beyond food-use pesticides toward a wider chemical domain that lacks exposure and toxicity information, prediction tools become increasingly important. In this study, in vitro hepatic clearance and plasma protein binding were measured to estimate OEDs for a subset of Phase II chemicals. OEDs were compared against high-throughput (HT) exposure predictions generated using probabilistic modeling and Bayesian approaches generated by the U.S. Environmental Protection Agency (EPA) ExpoCast program. This approach incorporated chemical-specific use and national production volume data with biomonitoring data to inform the exposure predictions. This HT exposure modeling approach provided predictions for all Phase II chemicals assessed in this study whereas estimates from regulatory sources were available for only 7% of chemicals. Of the 163 chemicals assessed in this study, 3 or 13 chemicals possessed AERs < 1 or < 100, respectively. Diverse bioactivities across a range of assays and concentrations were also noted across the wider chemical space surveyed. The availability of HT exposure estimation and bioactivity screening tools provides an opportunity to incorporate a risk-based strategy for use in testing prioritization. PMID:26251325

Simultaneous virtual prediction of anti-Escherichia coli activities and ADMET profiles: A chemoinformatic complementary approach for high-throughput screening.

PubMed

Speck-Planche, Alejandro; Cordeiro, M N D S

2014-02-10

Escherichia coli remains one of the principal pathogens that cause nosocomial infections, medical conditions that are increasingly common in healthcare facilities. E. coli is intrinsically resistant to many antibiotics, and multidrug-resistant strains have emerged recently. Chemoinformatics has been a great ally of experimental methodologies such as high-throughput screening, playing an important role in the discovery of effective antibacterial agents. However, there is no approach that can design safer anti-E. coli agents, because of the multifactorial nature and complexity of bacterial diseases and the lack of desirable ADMET (absorption, distribution, metabolism, elimination, and toxicity) profiles as a major cause of disapproval of drugs. In this work, we introduce the first multitasking model based on quantitative-structure biological effect relationships (mtk-QSBER) for simultaneous virtual prediction of anti-E. coli activities and ADMET properties of drugs and/or chemicals under many experimental conditions. The mtk-QSBER model was developed from a large and heterogeneous data set of more than 37800 cases, exhibiting overall accuracies of >95% in both training and prediction (validation) sets. The utility of our mtk-QSBER model was demonstrated by performing virtual prediction of properties for the investigational drug avarofloxacin (AVX) under 260 different experimental conditions. Results converged with the experimental evidence, confirming the remarkable anti-E. coli activities and safety of AVX. Predictions also showed that our mtk-QSBER model can be a promising computational tool for virtual screening of desirable anti-E. coli agents, and this chemoinformatic approach could be extended to the search for safer drugs with defined pharmacological activities.

Use of QSARs in international decision-making frameworks to predict ecologic effects and environmental fate of chemical substances.

PubMed Central

Cronin, Mark T D; Walker, John D; Jaworska, Joanna S; Comber, Michael H I; Watts, Christopher D; Worth, Andrew P

2003-01-01

This article is a review of the use, by regulatory agencies and authorities, of quantitative structure-activity relationships (QSARs) to predict ecologic effects and environmental fate of chemicals. For many years, the U.S. Environmental Protection Agency has been the most prominent regulatory agency using QSARs to predict the ecologic effects and environmental fate of chemicals. However, as increasing numbers of standard QSAR methods are developed and validated to predict ecologic effects and environmental fate of chemicals, it is anticipated that more regulatory agencies and authorities will find them to be acceptable alternatives to chemical testing. PMID:12896861

Students' Predictions about the Sensory Properties of Chemical Compounds: Additive versus Emergent Frameworks

ERIC Educational Resources Information Center

Talanquer, Vicente

2008-01-01

We investigated general chemistry students' intuitive ideas about the expected properties of the products of a chemical reaction. In particular, we analyzed college chemistry students' predictions about the color, smell, and taste of the products of chemical reactions represented at the molecular level. The study was designed to explore the extent…

In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattle.

PubMed

Castilhos, A M; Francisco, C L; Branco, R H; Bonilha, S F M; Mercadante, M E Z; Meirelles, P R L; Pariz, C M; Jorge, A M

2018-05-04

Evaluation of the body chemical composition of beef cattle can only be measured postmortem and those data cannot be used in real production scenarios to adjust nutritional plans. The objective of this study was to develop multiple linear regression equations from in vivo measurements, such as ultrasound parameters [backfat thickness (uBFT, mm), rump fat thickness (uRF, mm), and ribeye area (uLMA, cm2)], shrunk body weight (SBW, kg), age (AG, d), hip height (HH, m), as well as from postmortem measurements (composition of the 9th to 11th rib section) to predict the empty body and carcass chemical composition for Nellore cattle. Thirty-three young bulls were used (339 ± 36.15 kg and 448 ± 17.78 d for initial weight and age, respectively). Empty body chemical composition (protein, fat, water, and ash in kg) was obtained by combining noncarcass and carcass components. Data were analyzed using the PROC REG procedure of SAS software. Mallows' Cp values were close to the ideal value of number of independent variables in the prediction equations plus one. Equations to predict chemical components of both empty body and carcass using in vivo measurements presented higher R2 values than those determined by postmortem measurements. Chemical composition of the empty body using in vivo measurements was predicted with R2 > 0.73. Equations to predict chemical composition of the carcass from in vivo measurements showed R2 lower (R2< 0.68) than observed for empty body, except for the water (R2 = 0.84). The independent variables SBW, uRF, and AG were sufficient to predict the fat, water, energy components of the empty body, whereas for estimation of protein content the uRF, HH, and SBW were satisfactory. For the calculation of the ash, the SBW variable in the equation was sufficient. Chemical compounds from components of the empty body of Nellore cattle can be calculated by the following equations: protein (kg) = 47.92 + 0.18 × SBW - 1.46 × uRF - 30.72 × HH (R2 = 0.94, RMSPE = 1

Does motivational interviewing counseling time influence HIV-positive persons' self-efficacy to practice safer sex?

PubMed

Chariyeva, Zulfiya; Golin, Carol E; Earp, Jo Anne; Suchindran, Chirayath

2012-04-01

This study examined the impact of motivational interviewing (MI) counseling time on self-efficacy to practice safer sex for people living with HIV/AIDS (PLWHA). In 4 month intervals we followed a cohort of 490 PLWHA for 12 months. We conducted hierarchical linear regression models to examine changes in safer sex self-efficacy when participants received zero, low to moderate (5-131 min) and high (132-320 min) doses of MI time. We conducted a similar analysis using number of counseling sessions as the predictor variable. Participants with low to moderate doses of MI counseling had 0.26 higher self-efficacy scores than participants with zero MI time (p=0.01). Also, they had 0.26 lower self-efficacy scores than participants with high amounts of MI time (p=0.04). Participants with high doses of MI had a 0.5 higher self-efficacy score than participants with zero amount of MI time (p<0.0001). Participants who received 3-4 counseling sessions had 0.41 greater self-efficacy scores than participants who did not receive any sessions (p<0.0001) but did not differ from participants receiving 1-2 sessions. MI time is a key to enhancing safer sex self-efficacy among PLWHA. Safer sex self-efficacy improves the more MI counseling time and sessions PLWHA receive. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Developing a predictive model for the chemical composition of soot nanoparticles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Violi, Angela; Michelsen, Hope; Hansen, Nils

In order to provide the scientific foundation to enable technology breakthroughs in transportation fuel, it is important to develop a combustion modeling capability to optimize the operation and design of evolving fuels in advanced engines for transportation applications. The goal of this proposal is to develop a validated predictive model to describe the chemical composition of soot nanoparticles in premixed and diffusion flames. Atomistic studies in conjunction with state-of-the-art experiments are the distinguishing characteristics of this unique interdisciplinary effort. The modeling effort has been conducted at the University of Michigan by Prof. A. Violi. The experimental work has entailed amore » series of studies using different techniques to analyze gas-phase soot precursor chemistry and soot particle production in premixed and diffusion flames. Measurements have provided spatial distributions of polycyclic aromatic hydrocarbons and other gas-phase species and size and composition of incipient soot nanoparticles for comparison with model results. The experimental team includes Dr. N. Hansen and H. Michelsen at Sandia National Labs' Combustion Research Facility, and Dr. K. Wilson as collaborator at Lawrence Berkeley National Lab's Advanced Light Source. Our results show that the chemical and physical properties of nanoparticles affect the coagulation behavior in soot formation, and our results on an experimentally validated, predictive model for the chemical composition of soot nanoparticles will not only enhance our understanding of soot formation since but will also allow the prediction of particle size distributions under combustion conditions. These results provide a novel description of soot formation based on physical and chemical properties of the particles for use in the next generation of soot models and an enhanced capability for facilitating the design of alternative fuels and the engines they will power.« less

Predicting in vivo effect levels for repeat-dose systemic toxicity using chemical, biological, kinetic and study covariates.

PubMed

Truong, Lisa; Ouedraogo, Gladys; Pham, LyLy; Clouzeau, Jacques; Loisel-Joubert, Sophie; Blanchet, Delphine; Noçairi, Hicham; Setzer, Woodrow; Judson, Richard; Grulke, Chris; Mansouri, Kamel; Martin, Matthew

2018-02-01

In an effort to address a major challenge in chemical safety assessment, alternative approaches for characterizing systemic effect levels, a predictive model was developed. Systemic effect levels were curated from ToxRefDB, HESS-DB and COSMOS-DB from numerous study types totaling 4379 in vivo studies for 1247 chemicals. Observed systemic effects in mammalian models are a complex function of chemical dynamics, kinetics, and inter- and intra-individual variability. To address this complex problem, systemic effect levels were modeled at the study-level by leveraging study covariates (e.g., study type, strain, administration route) in addition to multiple descriptor sets, including chemical (ToxPrint, PaDEL, and Physchem), biological (ToxCast), and kinetic descriptors. Using random forest modeling with cross-validation and external validation procedures, study-level covariates alone accounted for approximately 15% of the variance reducing the root mean squared error (RMSE) from 0.96 log 10 to 0.85 log 10  mg/kg/day, providing a baseline performance metric (lower expectation of model performance). A consensus model developed using a combination of study-level covariates, chemical, biological, and kinetic descriptors explained a total of 43% of the variance with an RMSE of 0.69 log 10  mg/kg/day. A benchmark model (upper expectation of model performance) was also developed with an RMSE of 0.5 log 10  mg/kg/day by incorporating study-level covariates and the mean effect level per chemical. To achieve a representative chemical-level prediction, the minimum study-level predicted and observed effect level per chemical were compared reducing the RMSE from 1.0 to 0.73 log 10  mg/kg/day, equivalent to 87% of predictions falling within an order-of-magnitude of the observed value. Although biological descriptors did not improve model performance, the final model was enriched for biological descriptors that indicated xenobiotic metabolism gene expression, oxidative stress, and

Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs.

PubMed

Liu, Mei; Wu, Yonghui; Chen, Yukun; Sun, Jingchun; Zhao, Zhongming; Chen, Xue-wen; Matheny, Michael Edwin; Xu, Hua

2012-06-01

Adverse drug reaction (ADR) is one of the major causes of failure in drug development. Severe ADRs that go undetected until the post-marketing phase of a drug often lead to patient morbidity. Accurate prediction of potential ADRs is required in the entire life cycle of a drug, including early stages of drug design, different phases of clinical trials, and post-marketing surveillance. Many studies have utilized either chemical structures or molecular pathways of the drugs to predict ADRs. Here, the authors propose a machine-learning-based approach for ADR prediction by integrating the phenotypic characteristics of a drug, including indications and other known ADRs, with the drug's chemical structures and biological properties, including protein targets and pathway information. A large-scale study was conducted to predict 1385 known ADRs of 832 approved drugs, and five machine-learning algorithms for this task were compared. This evaluation, based on a fivefold cross-validation, showed that the support vector machine algorithm outperformed the others. Of the three types of information, phenotypic data were the most informative for ADR prediction. When biological and phenotypic features were added to the baseline chemical information, the ADR prediction model achieved significant improvements in area under the curve (from 0.9054 to 0.9524), precision (from 43.37% to 66.17%), and recall (from 49.25% to 63.06%). Most importantly, the proposed model successfully predicted the ADRs associated with withdrawal of rofecoxib and cerivastatin. The results suggest that phenotypic information on drugs is valuable for ADR prediction. Moreover, they demonstrate that different models that combine chemical, biological, or phenotypic information can be built from approved drugs, and they have the potential to detect clinically important ADRs in both preclinical and post-marketing phases.

PRISM 3: expanded prediction of natural product chemical structures from microbial genomes

PubMed Central

Skinnider, Michael A.; Merwin, Nishanth J.; Johnston, Chad W.

2017-01-01

Abstract Microbial natural products represent a rich resource of pharmaceutically and industrially important compounds. Genome sequencing has revealed that the majority of natural products remain undiscovered, and computational methods to connect biosynthetic gene clusters to their corresponding natural products therefore have the potential to revitalize natural product discovery. Previously, we described PRediction Informatics for Secondary Metabolomes (PRISM), a combinatorial approach to chemical structure prediction for genetically encoded nonribosomal peptides and type I and II polyketides. Here, we present a ground-up rewrite of the PRISM structure prediction algorithm to derive prediction of natural products arising from non-modular biosynthetic paradigms. Within this new version, PRISM 3, natural product scaffolds are modeled as chemical graphs, permitting structure prediction for aminocoumarins, antimetabolites, bisindoles and phosphonate natural products, and building upon the addition of ribosomally synthesized and post-translationally modified peptides. Further, with the addition of cluster detection for 11 new cluster types, PRISM 3 expands to detect 22 distinct natural product cluster types. Other major modifications to PRISM include improved sequence input and ORF detection, user-friendliness and output. Distribution of PRISM 3 over a 300-core server grid improves the speed and capacity of the web application. PRISM 3 is available at http://magarveylab.ca/prism/. PMID:28460067

Safety and fitness electronic records (SAFER) system : logical architecture document : working draft

DOT National Transportation Integrated Search

1997-01-31

This Logical Architecture Document includes the products developed during the functional analysis of the Safety and Fitness Electronic Records (SAFER) System. This document, along with the companion Operational Concept and Physical Architecture Docum...

ToxCast: Developing Predictive Signatures of Chemically Induced Toxicity (Developing Predictive Bioactivity Signatures from ToxCasts HTS Data)

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry, bioactivity profiling and toxicogenomic data to predict potential for toxicity and prioritize limited testing resour...

A unified algorithm for predicting partition coefficients for PBPK modeling of drugs and environmental chemicals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peyret, Thomas; Poulin, Patrick; Krishnan, Kannan, E-mail: kannan.krishnan@umontreal.ca

The algorithms in the literature focusing to predict tissue:blood PC (P{sub tb}) for environmental chemicals and tissue:plasma PC based on total (K{sub p}) or unbound concentration (K{sub pu}) for drugs differ in their consideration of binding to hemoglobin, plasma proteins and charged phospholipids. The objective of the present study was to develop a unified algorithm such that P{sub tb}, K{sub p} and K{sub pu} for both drugs and environmental chemicals could be predicted. The development of the unified algorithm was accomplished by integrating all mechanistic algorithms previously published to compute the PCs. Furthermore, the algorithm was structured in such amore » way as to facilitate predictions of the distribution of organic compounds at the macro (i.e. whole tissue) and micro (i.e. cells and fluids) levels. The resulting unified algorithm was applied to compute the rat P{sub tb}, K{sub p} or K{sub pu} of muscle (n = 174), liver (n = 139) and adipose tissue (n = 141) for acidic, neutral, zwitterionic and basic drugs as well as ketones, acetate esters, alcohols, aliphatic hydrocarbons, aromatic hydrocarbons and ethers. The unified algorithm reproduced adequately the values predicted previously by the published algorithms for a total of 142 drugs and chemicals. The sensitivity analysis demonstrated the relative importance of the various compound properties reflective of specific mechanistic determinants relevant to prediction of PC values of drugs and environmental chemicals. Overall, the present unified algorithm uniquely facilitates the computation of macro and micro level PCs for developing organ and cellular-level PBPK models for both chemicals and drugs.« less

Integrative Approaches for Predicting in vivo Effects of Chemicals from their Structural Descriptors and the Results of Short-term Biological Assays

PubMed Central

Low, Yen S.; Sedykh, Alexander; Rusyn, Ivan; Tropsha, Alexander

2017-01-01

Cheminformatics approaches such as Quantitative Structure Activity Relationship (QSAR) modeling have been used traditionally for predicting chemical toxicity. In recent years, high throughput biological assays have been increasingly employed to elucidate mechanisms of chemical toxicity and predict toxic effects of chemicals in vivo. The data generated in such assays can be considered as biological descriptors of chemicals that can be combined with molecular descriptors and employed in QSAR modeling to improve the accuracy of toxicity prediction. In this review, we discuss several approaches for integrating chemical and biological data for predicting biological effects of chemicals in vivo and compare their performance across several data sets. We conclude that while no method consistently shows superior performance, the integrative approaches rank consistently among the best yet offer enriched interpretation of models over those built with either chemical or biological data alone. We discuss the outlook for such interdisciplinary methods and offer recommendations to further improve the accuracy and interpretability of computational models that predict chemical toxicity. PMID:24805064

A Safer Formulation Concept for Flame-Generated Engineered Nanomaterials

PubMed Central

Gass, Samuel; Cohen, Joel M.; Pyrgiotakis, Georgios; Sotiriou, Georgios A.; Pratsinis, Sotiris E.; Demokritou, Philip

2013-01-01

The likely success or failure of the nanotechnology industry depends on the environmental health and safety of engineered nanomaterials (ENMs). While efforts toward engineering safer ENMs are sparse, such efforts are considered crucial to the sustainability of the nanotech industry. A promising approach in this regard is to coat potentially toxic nanomaterials with a biologically inert layer of amorphous SiO2. Core-shell particles exhibit the surface properties of their amorphous SiO2 shell while maintaining specific functional properties of their core material. A major challenge in the development of functional core-shell particles is the design of scalable high-yield processes that can meet large-scale industrial demand. Here, we present a safer formulation concept for flame-generated ENMs based on a one-step, in flight SiO2 encapsulation process, which was recently introduced by the authors as a means for a scalable manufacturing of SiO2 coated ENMs. Firstly, the versatility of the SiO2-coating process is demonstrated by applying it to four ENMs (CeO2, ZnO, Fe2O3, Ag) marked by their prevalence in consumer products as well as their range in toxicity. The ENM-dependent coating fundamentals are assessed and process parameters are optimized for each ENM investigated. The effects of the SiO2-coating on core material structure, composition and morphology, as well as the coating efficiency on each nanostructured material, are evaluated using state-of-the-art analytical methods (XRD, N2 adsorption, TEM, XPS, isopropanol chemisorption). Finally, the biological interactions of SiO2-coated vs. uncoated ENMs are evaluated using cellular bioassays, providing valuable evidence for reduced toxicity for the SiO2-coated ENMs. Results indicate that the proposed ‘safer by design’ concept bears great promise for scaled-up application in industry in order to reduce the toxicological profile of ENMs for certain applications. PMID:23961338

Accurate prediction of acute fish toxicity of fragrance chemicals with the RTgill-W1 cell assay.

PubMed

Natsch, Andreas; Laue, Heike; Haupt, Tina; von Niederhäusern, Valentin; Sanders, Gordon

2018-03-01

Testing for acute fish toxicity is an integral part of the environmental safety assessment of chemicals. A true replacement of primary fish tissue was recently proposed using cell viability in a fish gill cell line (RTgill-W1) as a means of predicting acute toxicity, showing good predictivity on 35 chemicals. To promote regulatory acceptance, the predictivity and applicability domain of novel tests need to be carefully evaluated on chemicals with existing high-quality in vivo data. We applied the RTgill-W1 cell assay to 38 fragrance chemicals with a wide range of both physicochemical properties and median lethal concentration (LC50) values and representing a diverse range of chemistries. A strong correlation (R 2  = 0.90-0.94) between the logarithmic in vivo LC50 values, based on fish mortality, and the logarithmic in vitro median effect concentration (EC50) values based on cell viability was observed. A leave-one-out analysis illustrates a median under-/overprediction from in vitro EC50 values to in vivo LC50 values by a factor of 1.5. This assay offers a simple, accurate, and reliable alternative to in vivo acute fish toxicity testing for chemicals, presumably acting mainly by a narcotic mode of action. Furthermore, the present study provides validation of the predictivity of the RTgill-W1 assay on a completely independent set of chemicals that had not been previously tested and indicates that fragrance chemicals are clearly within the applicability domain. Environ Toxicol Chem 2018;37:931-941. © 2017 SETAC. © 2017 SETAC.

Development of Methods to Evaluate Safer Flight Characteristics

NASA Technical Reports Server (NTRS)

Basciano, Thomas E., Jr.; Erickson, Jon D.

1997-01-01

The goal of the proposed research is to begin development of a simulation that models the flight characteristics of the Simplified Aid For EVA Rescue (SAFER) pack. Development of such a simulation was initiated to ultimately study the effect an Orbital Replacement Unit (ORU) has on SAFER dynamics. A major function of this program will be to calculate fuel consumption for many ORUs with different masses and locations. This will ultimately determine the maximum ORU mass an astronaut can carry and still perform a self-rescue without jettisoning the unit. A second primary goal is to eventually simulate relative motion (vibration) between the ORU and astronaut. After relative motion is accurately modeled it will be possible to evaluate the robustness of the control system and optimize performance as needed. The first stage in developing the simulation is the ability to model a standardized, total, self-rescue scenario, making it possible to accurately compare different program runs. In orbit an astronaut has only limited data and will not be able to follow the most fuel efficient trajectory; therefore, it is important to correctly model the procedures an astronaut would use in orbit so that good fuel consumption data can be obtained. Once this part of the program is well tested and verified, the vibration (relative motion) of the ORU with respect to the astronaut can be studied.

Characterization and prediction of chemical functions and weight fractions in consumer products.

PubMed

Isaacs, Kristin K; Goldsmith, Michael-Rock; Egeghy, Peter; Phillips, Katherine; Brooks, Raina; Hong, Tao; Wambaugh, John F

2016-01-01

Assessing exposures from the thousands of chemicals in commerce requires quantitative information on the chemical constituents of consumer products. Unfortunately, gaps in available composition data prevent assessment of exposure to chemicals in many products. Here we propose filling these gaps via consideration of chemical functional role. We obtained function information for thousands of chemicals from public sources and used a clustering algorithm to assign chemicals into 35 harmonized function categories (e.g., plasticizers, antimicrobials, solvents). We combined these functions with weight fraction data for 4115 personal care products (PCPs) to characterize the composition of 66 different product categories (e.g., shampoos). We analyzed the combined weight fraction/function dataset using machine learning techniques to develop quantitative structure property relationship (QSPR) classifier models for 22 functions and for weight fraction, based on chemical-specific descriptors (including chemical properties). We applied these classifier models to a library of 10196 data-poor chemicals. Our predictions of chemical function and composition will inform exposure-based screening of chemicals in PCPs for combination with hazard data in risk-based evaluation frameworks. As new information becomes available, this approach can be applied to other classes of products and the chemicals they contain in order to provide essential consumer product data for use in exposure-based chemical prioritization.

Safer staining method for acid fast bacilli.

PubMed Central

Ellis, R C; Zabrowarny, L A

1993-01-01

To develop a method for staining acid fast bacilli which excluded highly toxic phenol from the staining solution. A lipophilic agent, a liquid organic detergent, LOC High Studs, distributed by Amway, was substituted. The acid fast bacilli stained red; nuclei, cytoplasm, and cytoplasmic elements stained blue on a clear background. These results compare very favourably with acid fast bacilli stained by the traditional method. Detergents are efficient lipophilic agents and safer to handle than phenol. The method described here stains acid fast bacilli as efficiently as traditional carbol fuchsin methods. LOC High Suds is considerably cheaper than phenol. Images PMID:7687254

Safer staining method for acid fast bacilli.

PubMed

Ellis, R C; Zabrowarny, L A

1993-06-01

To develop a method for staining acid fast bacilli which excluded highly toxic phenol from the staining solution. A lipophilic agent, a liquid organic detergent, LOC High Studs, distributed by Amway, was substituted. The acid fast bacilli stained red; nuclei, cytoplasm, and cytoplasmic elements stained blue on a clear background. These results compare very favourably with acid fast bacilli stained by the traditional method. Detergents are efficient lipophilic agents and safer to handle than phenol. The method described here stains acid fast bacilli as efficiently as traditional carbol fuchsin methods. LOC High Suds is considerably cheaper than phenol.

Predictive performance of the human Cell Line Activation Test (h-CLAT) for lipophilic chemicals with high octanol-water partition coefficients.

PubMed

Takenouchi, Osamu; Miyazawa, Masaaki; Saito, Kazutoshi; Ashikaga, Takao; Sakaguchi, Hitoshi

2013-01-01

To meet the urgent need for a reliable alternative test for predicting skin sensitizing potential of many chemicals, we have developed a cell-based in vitro test, human Cell Line Activation Test (h-CLAT). However, the predictive performance for lipophilic chemicals in the h-CLAT still remains relatively unknown. Moreover, it's suggested that low water solubility of chemicals might induce false negative outcomes. Thus, in this study, we tested relatively low water soluble 37 chemicals with log Kow values above and below 3.5 in the h-CLAT. The small-scale assessment resulted in nine false negative outcomes for chemicals with log Kow values greater than 3.5. We then created a dataset of 143 chemicals by combining the existing dataset of 106 chemicals and examined the predictive performance of the h-CLAT for chemicals with a log Kow of less than 3.5; a total of 112 chemicals from the 143 chemicals in the dataset. The sensitivity and overall accuracy for the 143 chemicals were 83% and 80%, respectively. In contrast, sensitivity and overall accuracy for the 112 chemicals with log Kow values below 3.5 improved to 94% and 88%, respectively. These data suggested that the h-CLAT could successfully detect sensitizers with log Kow values up to 3.5. When chemicals with log Kow values greater than 3.5 that were deemed positive by h-CLAT were included with the 112 chemicals, the sensitivity and accuracy in terms of the resulting applicable 128 chemicals out of the 143 chemicals became 95% and 88%, respectively. The use of log Kow values gave the h-CLAT a higher predictive performance. Our results demonstrated that the h-CLAT could predict sensitizing potential of various chemicals, which contain lipophilic chemicals using a large-scale chemical dataset.

Sexually active older Australian's knowledge of sexually transmitted infections and safer sexual practices.

PubMed

Lyons, Anthony; Heywood, Wendy; Fileborn, Bianca; Minichiello, Victor; Barrett, Catherine; Brown, Graham; Hinchliff, Sharron; Malta, Sue; Crameri, Pauline

2017-06-01

Rates of sexually transmitted infections (STIs) are rising among older Australians. We conducted a large survey of older people's knowledge of STIs and safer sexual practices. A total of 2,137 Australians aged 60 years and older completed the survey, which included 15 questions assessing knowledge of STIs and safer sexual practices. We examined both levels of knowledge and factors associated with an overall knowledge score. In total, 1,652 respondents reported having sex in the past five years and answered all knowledge questions. This group had good general knowledge but poorer knowledge in areas such as the protection offered by condoms and potential transmission modes for specific STIs. Women had better knowledge than men. Men in their 60s, men with higher education levels, and men who thought they were at risk of STIs reported better knowledge than other men. Knowledge was also better among men and women who had been tested for STIs or reported 'other' sources of knowledge on STIs. Many older Australians lack knowledge of STIs and safer sexual practices. Implications for public health: To reverse current trends toward increasing STI diagnoses in this population, policies and education campaigns aimed at improving knowledge levels may need to be considered. © 2017 The Authors.

Experiences Using Pre-Exposure Prophylaxis for Safer Conception Among HIV Serodiscordant Heterosexual Couples in the United States.

PubMed

Bazzi, Angela R; Leech, Ashley A; Biancarelli, Dea L; Sullivan, Meg; Drainoni, Mari-Lynn

2017-08-01

Antiretroviral pre-exposure prophylaxis (PrEP) is a promising HIV prevention strategy for HIV serodiscordant couples (HIV-infected male, uninfected female) seeking safer conception. However, most research on PrEP for safer conception has focused on couples in sub-Saharan Africa; little is known about the perspectives or experiences of heterosexual couples in the United States. We conducted qualitative interviews with six couples (six women and five of their male partners) receiving PrEP for conception services at an urban safety net hospital in the US Northeast. In-depth interview guides explored couple relationships and contextual factors and attitudes, perceptions, and decision-making processes surrounding PrEP for safer conception. Thematic analyses focused on identifying the following emergent themes. We found that couple relationships were situated within broader social and cultural contexts of immigration, family, and community that shaped their experiences with HIV and serodiscordant relationship status. Despite strong partner support within relationships, HIV stigma and disapproval of serodiscordant relationships contributed to couples' feelings of social isolation and subsequent aspirations to have "normal" families. By enabling "natural" conception through condomless sex, PrEP for safer conception provided a sense of enhanced relationship intimacy. Couples called for increasing public awareness of PrEP through positive messaging as a way to combat HIV stigma. Findings suggest that relationship dynamics and broader social contexts appear to shape HIV serodiscordant couples' fertility desires and motivations to use PrEP. However, increased public awareness of PrEP for safer conception may be needed to combat HIV stigma at the community level.

The OSHA hazardous chemical occupational exposure standard for laboratories.

PubMed

Armbruster, D A

1991-01-01

OSHA's chemical occupational exposure standard for laboratories is an outgrowth of the previously issued Hazard Communication Standard. The standard relieves laboratories from complying with general industry standards but does require compliance with specific laboratory guidelines. The heart of the standard is the creation of a Chemical Hygiene Plan (CHP). The CHP addresses major issues such as safety equipment and procedures, work practices, training, the designation of a chemical hygiene officer, and the provision of medical consultation and examination for affected employees. This new standard, in full effect as of January 31, 1991, presents yet another regulatory challenge to laboratory managers but also ensures a safer environment for laboratory workers.

PRISM 3: expanded prediction of natural product chemical structures from microbial genomes.

PubMed

Skinnider, Michael A; Merwin, Nishanth J; Johnston, Chad W; Magarvey, Nathan A

2017-07-03

Microbial natural products represent a rich resource of pharmaceutically and industrially important compounds. Genome sequencing has revealed that the majority of natural products remain undiscovered, and computational methods to connect biosynthetic gene clusters to their corresponding natural products therefore have the potential to revitalize natural product discovery. Previously, we described PRediction Informatics for Secondary Metabolomes (PRISM), a combinatorial approach to chemical structure prediction for genetically encoded nonribosomal peptides and type I and II polyketides. Here, we present a ground-up rewrite of the PRISM structure prediction algorithm to derive prediction of natural products arising from non-modular biosynthetic paradigms. Within this new version, PRISM 3, natural product scaffolds are modeled as chemical graphs, permitting structure prediction for aminocoumarins, antimetabolites, bisindoles and phosphonate natural products, and building upon the addition of ribosomally synthesized and post-translationally modified peptides. Further, with the addition of cluster detection for 11 new cluster types, PRISM 3 expands to detect 22 distinct natural product cluster types. Other major modifications to PRISM include improved sequence input and ORF detection, user-friendliness and output. Distribution of PRISM 3 over a 300-core server grid improves the speed and capacity of the web application. PRISM 3 is available at http://magarveylab.ca/prism/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Pathways from Resilient Coping to Safer Sex Communication Among African, Caribbean, and Black Women in Toronto, Canada: Results from a Cross-sectional Survey.

PubMed

Logie, Carmen H; Okumu, Moses; Ryan, Shannon; Yehdego, Mary

2018-05-22

African, Caribbean, and Black (ACB) women in Canada are disproportionately impacted by HIV and other sexually transmitted infections. Although there is reported suboptimal consistent condom use with ACB women, limited research has explored safer sex communication among this population. Coping frameworks highlight the role that resilient coping and condom use self-efficacy may play in facilitating safer sex communication. Structural perspectives stress the need to explore associations between HIV vulnerabilities and food insecurity. We examined pathways from resilient coping to safer sex communication through the mediator of condom use self-efficacy among ACB women in Toronto. We conducted a cross-sectional survey with a purposive sample of ACB women aged 16 and older across Toronto, Canada. We conducted path analysis to test the direct effects of resilient coping on safer sex communication, and indirect pathways through the mediator (condom use self-efficacy) while controlling for food insecurity. Participant (n = 80; mean age 27, SD 7.93) ethnicities included African (58.8%, n = 47), Caribbean (30%, n = 24), and others (11.3%, n = 9). Participants with food security reported significantly higher safer sex communication. We found no direct effect of resilient coping on safer sex communication. Findings support the hypothesized mediation process; resilient coping was associated with condom use self-efficacy, which in turn was associated with safer sex communication. Findings that condom use self-efficacy mediated the association between resilient coping and safer sex communication align with theoretical assertions of the protective role of adaptive coping strategies. Findings can inform tailored HIV and STI preventive interventions with ACB women.

Predictive spectroscopy and chemical imaging based on novel optical systems

NASA Astrophysics Data System (ADS)

Nelson, Matthew Paul

1998-10-01

This thesis describes two futuristic optical systems designed to surpass contemporary spectroscopic methods for predictive spectroscopy and chemical imaging. These systems are advantageous to current techniques in a number of ways including lower cost, enhanced portability, shorter analysis time, and improved S/N. First, a novel optical approach to predicting chemical and physical properties based on principal component analysis (PCA) is proposed and evaluated. A regression vector produced by PCA is designed into the structure of a set of paired optical filters. Light passing through the paired filters produces an analog detector signal directly proportional to the chemical/physical property for which the regression vector was designed. Second, a novel optical system is described which takes a single-shot approach to chemical imaging with high spectroscopic resolution using a dimension-reduction fiber-optic array. Images are focused onto a two- dimensional matrix of optical fibers which are drawn into a linear distal array with specific ordering. The distal end is imaged with a spectrograph equipped with an ICCD camera for spectral analysis. Software is used to extract the spatial/spectral information contained in the ICCD images and deconvolute them into wave length-specific reconstructed images or position-specific spectra which span a multi-wavelength space. This thesis includes a description of the fabrication of two dimension-reduction arrays as well as an evaluation of the system for spatial and spectral resolution, throughput, image brightness, resolving power, depth of focus, and channel cross-talk. PCA is performed on the images by treating rows of the ICCD images as spectra and plotting the scores of each PC as a function of reconstruction position. In addition, iterative target transformation factor analysis (ITTFA) is performed on the spectroscopic images to generate ``true'' chemical maps of samples. Univariate zero-order images, univariate first

Building social capital in healthcare organizations: thinking ecologically for safer care.

PubMed

Hofmeyer, Anne; Marck, Patricia B

2008-01-01

Research on patient safety and health human resources, 2 critical issues for 21st century healthcare, converges on similar findings. Specifically, it is apparent that along with the patients, families, and communities we serve, nurses and other healthcare professionals navigate a volatile health care system where persistent restructuring, market pressures, and workforce instability present ongoing threats to the delivery of safer care. Drawing from the fields of nursing, healthcare ethics, health systems management, and ecological restoration, we outline the role of social capital for organizational integrity, healthy workplace cultures, sustainable resource management, improved nurse retention, effective knowledge translation, and safer patient care. Nursing leaders can use ecological thinking to build the vital resource of social capital by taking concrete steps to commit the necessary human and material resources to: (1) forge relations to foster bonding, bridging and linking social capital; (2) build solidarity and trust; (3) foster collective action and cooperation; (4) strengthen communication and knowledge exchange; and (5) create capacity for social cohesion and inclusion.

CURRENT STATE OF PREDICTING THE RESPIRATORY ALLERGY POTENTIAL OF CHEMICALS: WHAT ARE THE ISSUES?

EPA Science Inventory

Current State of Predicting the Respiratory Allergy Potential of Chemicals: What Are the Issues? M I. Gilmour1 and S. E. Loveless2, 1USEPA, Research Triangle Park, NC and 2DuPont Haskell Laboratory, Newark, DE.

Many chemicals are clearly capable of eliciting immune respon...

In search of a psychology of safer-sex promotion; beyond beliefs and texts.

PubMed

Abraham, C; Sheeran, P

1993-06-01

Belief and attitudinal change are important to the promotion of safer sexual behaviour. However, the individual decision-making psychology implicit in belief-change models provides only a partial picture of the determinants of sexual behaviour. A broader psychological understanding emphasizing the complex social skills involved in regulating sexual interaction is advocated. A discourse analysis critique of the viability of characterizing individuals' psychology on the basis of verbal responses is discussed and it is noted that psychological models linking such responses to underlying beliefs and cognitions must be based on measures which accurately predict health behaviour. It is concluded that an interactive model incorporating personal, interpersonal and situational constraints on sexual behaviour could be used to design effective programmes addressing barriers to HIV protection. Such interventions would promote communication and sexual negotiating skills and could be included in school curricula. This would have radical implications for sex education, shifting its theoretical basis from biology to social psychology and its methods from information-giving to participation and practice.

An Energy Balance Model to Predict Chemical Partitioning in a Photosynthetic Microbial Mat

NASA Technical Reports Server (NTRS)

Hoehler, Tori M.; Albert, Daniel B.; DesMarais, David J.

2006-01-01

Studies of biosignature formation in photosynthetic microbial mat communities offer potentially useful insights with regards to both solar and extrasolar astrobiology. Biosignature formation in such systems results from the chemical transformation of photosynthetically fixed carbon by accessory microorganisms. This fixed carbon represents a source not only of reducing power, but also energy, to these organisms, so that chemical and energy budgets should be coupled. We tested this hypothesis by applying an energy balance model to predict the fate of photosynthetic productivity under dark, anoxic conditions. Fermentation of photosynthetically fixed carbon is taken to be the only source of energy available to cyanobacteria in the absence of light and oxygen, and nitrogen fixation is the principal energy demand. The alternate fate for fixed carbon is to build cyanobacterial biomass with Redfield C:N ratio. The model predicts that, under completely nitrogen-limited conditions, growth is optimized when 78% of fixed carbon stores are directed into fermentative energy generation, with the remainder allocated to growth. These predictions were compared to measurements made on microbial mats that are known to be both nitrogen-limited and populated by actively nitrogen-fixing cyanobacteria. In these mats, under dark, anoxic conditions, 82% of fixed carbon stores were diverted into fermentation. The close agreement between these independent approaches suggests that energy balance models may provide a quantitative means of predicting chemical partitioning within such systems - an important step towards understanding how biological productivity is ultimately partitioned into biosignature compounds.

A Rat α-Fetoprotein Binding Activity Prediction Model to Facilitate Assessment of the Endocrine Disruption Potential of Environmental Chemicals.

PubMed

Hong, Huixiao; Shen, Jie; Ng, Hui Wen; Sakkiah, Sugunadevi; Ye, Hao; Ge, Weigong; Gong, Ping; Xiao, Wenming; Tong, Weida

2016-03-25

Endocrine disruptors such as polychlorinated biphenyls (PCBs), diethylstilbestrol (DES) and dichlorodiphenyltrichloroethane (DDT) are agents that interfere with the endocrine system and cause adverse health effects. Huge public health concern about endocrine disruptors has arisen. One of the mechanisms of endocrine disruption is through binding of endocrine disruptors with the hormone receptors in the target cells. Entrance of endocrine disruptors into target cells is the precondition of endocrine disruption. The binding capability of a chemical with proteins in the blood affects its entrance into the target cells and, thus, is very informative for the assessment of potential endocrine disruption of chemicals. α-fetoprotein is one of the major serum proteins that binds to a variety of chemicals such as estrogens. To better facilitate assessment of endocrine disruption of environmental chemicals, we developed a model for α-fetoprotein binding activity prediction using the novel pattern recognition method (Decision Forest) and the molecular descriptors calculated from two-dimensional structures by Mold² software. The predictive capability of the model has been evaluated through internal validation using 125 training chemicals (average balanced accuracy of 69%) and external validations using 22 chemicals (balanced accuracy of 71%). Prediction confidence analysis revealed the model performed much better at high prediction confidence. Our results indicate that the model is useful (when predictions are in high confidence) in endocrine disruption risk assessment of environmental chemicals though improvement by increasing number of training chemicals is needed.

Sexual communication, safer sex self-efficacy, and condom use among young Chinese migrants in Beijing, China.

PubMed

Xiao, Zhiwen; Li, Xiaoming; Lin, Danhua; Jiang, Shulin; Liu, Yingjie; Li, Shuming

2013-12-01

Mediation effect of sexual communication on the relationship between safer sex self-efficacy and condom use was tested among 307 homosexually active migrant men, 376 heterosexually active migrant men, and 265 heterosexually active migrant women. The study found certain aspects of sexual communication mediated the effect of self-efficacy on condom use among the three samples. The findings underscored the importance of including components that promote safer sex self-efficacy and sexual communication in HIV prevention interventions for Chinese migrants.

Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space

DOE PAGES

Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; ...

2015-06-04

Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstratemore » prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies.« less

Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space

PubMed Central

2015-01-01

Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. In addition, the same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies. PMID:26113956

Prediction of the true digestible amino acid contents from the chemical composition of sorghum grain for poultry.

PubMed

Ebadi, M R; Sedghi, M; Golian, A; Ahmadi, H

2011-10-01

Accurate knowledge of true digestible amino acid (TDAA) contents of feedstuffs is necessary to accurately formulate poultry diets for profitable production. Several experimental approaches that are highly expensive and time consuming have been used to determine available amino acids. Prediction of the nutritive value of a feed ingredient from its chemical composition via regression methodology has been attempted for many years. The artificial neural network (ANN) model is a powerful method that may describe the relationship between digestible amino acid contents and chemical composition. Therefore, multiple linear regressions (MLR) and ANN models were developed for predicting the TDAA contents of sorghum grain based on chemical composition. A precision-fed assay trial using cecectomized roosters was performed to determine the TDAA contents in 48 sorghum samples from 12 sorghum varieties differing in chemical composition. The input variables for both MLR and ANN models were CP, ash, crude fiber, ether extract, and total phenols whereas the output variable was each individual TDAA for every sample. The results of this study revealed that it is possible to satisfactorily estimate the TDAA of sorghum grain through its chemical composition. The chemical composition of sorghum grain seems to highly influence the TDAA contents when considering components such as CP, crude fiber, ether extract, ash and total phenols. It is also possible to estimate the TDAA contents through multiple regression equations with reasonable accuracy depending on composition. However, a more satisfactory prediction may be achieved via ANN for all amino acids. The R(2) values for the ANN model corresponding to testing and training parameters showed a higher accuracy of prediction than equations established by the MLR method. In addition, the current data confirmed that chemical composition, often considered in total amino acid prediction, could be also a useful predictor of true digestible values

Prediction of contaminant persistence in aqueous phase: a quantum chemical approach.

PubMed

Blotevogel, Jens; Mayeno, Arthur N; Sale, Tom C; Borch, Thomas

2011-03-15

At contaminated field sites where active remediation measures are not feasible, monitored natural attenuation is sometimes the only alternative for surface water or groundwater decontamination. However, due to slow degradation rates of some contaminants under natural conditions, attenuation processes and their performance assessment can take several years to decades to complete. Here, we apply quantum chemical calculations to predict contaminant persistence in the aqueous phase. For the test compound hexamethylphosphoramide (HMPA), P-N bond hydrolysis is the only thermodynamically favorable reaction that may lead to its degradation under reducing conditions. Through calculation of aqueous Gibbs free energies of activation for all potential reaction mechanisms, it is predicted that HMPA hydrolyzes via an acid-catalyzed mechanism at pH < 8.2, and an uncatalyzed mechanism at pH 8.2-8.5. The estimated half-lives of thousands to hundreds of thousands of years over the groundwater-typical pH range of 6.0 to 8.5 indicate that HMPA will be persistent in the absence of suitable oxidants. At pH 0, where the hydrolysis reaction is rapid enough to enable measurement, the experimentally determined rate constant and half-life are in excellent agreement with the predicted values. Since the quantum chemical methodology described herein can be applied to virtually any contaminant or reaction of interest, it is especially valuable for the prediction of persistence when slow reaction rates impede experimental investigations and appropriate QSARs are unavailable.

Prediction of Hydrolysis Products of Organic Chemicals under Environmental pH Conditions

EPA Science Inventory

Cheminformatics-based software tools can predict the molecular structure of transformation products using a library of transformation reaction schemes. This paper presents the development of such a library for abiotic hydrolysis of organic chemicals under environmentally relevant...

Predictive In Vitro Screening of Environmental Chemicals – The ToxCast Project

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry and bioactivity profiling to predict potential for toxicity and prioritize limited testing resources (www.epa.gov/toc...

Pregnancy Intentions and Safer Pregnancy Knowledge Among Female Sex Workers in Port Elizabeth, South Africa.

PubMed

Rao, Amrita; Baral, Stefan; Phaswana-Mafuya, Nancy; Lambert, Andrew; Kose, Zamakayise; Mcingana, Mfezi; Holland, Claire; Ketende, Sosthenes; Schwartz, Sheree

2016-07-01

To assess the association between human immunodeficiency virus (HIV) and pregnancy intentions and safer conception knowledge among female sex workers in Port Elizabeth, South Africa. This cross-sectional study recruited female sex workers in Port Elizabeth using respondent-driven sampling and completed an interviewer-administered questionnaire alongside HIV testing and counseling. In this secondary analysis, robust Poisson regression was used to model prevalence ratios for positive fertility intentions in this cross-sectional study. Knowledge of safer conception methods by HIV status was compared using Fisher exact tests. Overall 391 women were represented in the analyses. More than 50% had a prior HIV diagnosis, and an additional 12% were diagnosed with HIV during the study. Approximately half (n=185) of the women reported future pregnancy intentions. In univariate analysis, a prior HIV diagnosis was negatively associated with pregnancy intentions as compared with HIV-negative women (prevalence ratio 0.68, 95% confidence interval 0.55-0.85). Only parity remained independently associated with future pregnancy intentions in multivariate regression after controlling for HIV status, age, race, relationship status, and years selling sex. Knowledge of safer conception methods such as timed sex without a condom, preexposure prophylaxis, or self-insemination was low and similar between those with and without future pregnancy plans. Pregnancy intentions did not significantly vary according to HIV status. Fertility intentions were high, however, and knowledge of safer conception methods low, suggesting a need to provide female sex workers with advice around options to conceive safely in the context of high HIV prevalence.

Novel naïve Bayes classification models for predicting the chemical Ames mutagenicity.

PubMed

Zhang, Hui; Kang, Yan-Li; Zhu, Yuan-Yuan; Zhao, Kai-Xia; Liang, Jun-Yu; Ding, Lan; Zhang, Teng-Guo; Zhang, Ji

2017-06-01

Prediction of drug candidates for mutagenicity is a regulatory requirement since mutagenic compounds could pose a toxic risk to humans. The aim of this investigation was to develop a novel prediction model of mutagenicity by using a naïve Bayes classifier. The established model was validated by the internal 5-fold cross validation and external test sets. For comparison, the recursive partitioning classifier prediction model was also established and other various reported prediction models of mutagenicity were collected. Among these methods, the prediction performance of naïve Bayes classifier established here displayed very well and stable, which yielded average overall prediction accuracies for the internal 5-fold cross validation of the training set and external test set I set were 89.1±0.4% and 77.3±1.5%, respectively. The concordance of the external test set II with 446 marketed drugs was 90.9±0.3%. In addition, four simple molecular descriptors (e.g., Apol, No. of H donors, Num-Rings and Wiener) related to mutagenicity and five representative substructures of mutagens (e.g., aromatic nitro, hydroxyl amine, nitroso, aromatic amine and N-methyl-N-methylenemethanaminum) produced by ECFP_14 fingerprints were identified. We hope the established naïve Bayes prediction model can be applied to risk assessment processes; and the obtained important information of mutagenic chemicals can guide the design of chemical libraries for hit and lead optimization. Copyright © 2017 Elsevier B.V. All rights reserved.

Prediction of the sorption capacities and affinities of organic chemicals by XAD-7.

PubMed

Yang, Kun; Qi, Long; Wei, Wei; Wu, Wenhao; Lin, Daohui

2016-01-01

Macro-porous resins are widely used as adsorbents for the treatment of organic contaminants in wastewater and for the pre-concentration of organic solutes from water. However, the sorption mechanisms for organic contaminants on such adsorbents have not been systematically investigated so far. Therefore, in this study, the sorption capacities and affinities of 24 organic chemicals by XAD-7 were investigated and the experimentally obtained sorption isotherms were fitted to the Dubinin-Ashtakhov model. Linear positive correlations were observed between the sorption capacities and the solubilities (SW) of the chemicals in water or octanol and between the sorption affinities and the solvatochromic parameters of the chemicals, indicating that the sorption of various organic compounds by XAD-7 occurred by non-linear partitioning into XAD-7, rather than by adsorption on XAD-7 surfaces. Both specific interactions (i.e., hydrogen-bonding interactions) as well as nonspecific interactions were considered to be responsible for the non-linear partitioning. The correlation equations obtained in this study allow the prediction of non-linear partitioning using well-known chemical parameters, namely SW, octanol-water partition coefficients (KOW), and the hydrogen-bonding donor parameter (αm). The effect of pH on the sorption of ionizable organic compounds (IOCs) could also be predicted by combining the correlation equations with additional equations developed from the estimation of IOC dissociation rates. The prediction equations developed in this study and the proposed non-linear partition mechanism shed new light on the selective removal and pre-concentration of organic solutes from water and on the regeneration of exhausted XAD-7 using solvent extraction.

Chemical genomic profiling via barcode sequencing to predict compound mode of action

PubMed Central

Piotrowski, Jeff S.; Simpkins, Scott W.; Li, Sheena C.; Deshpande, Raamesh; McIlwain, Sean; Ong, Irene; Myers, Chad L.; Boone, Charlie; Andersen, Raymond J.

2015-01-01

Summary Chemical genomics is an unbiased, whole-cell approach to characterizing novel compounds to determine mode of action and cellular target. Our version of this technique is built upon barcoded deletion mutants of Saccharomyces cerevisiae and has been adapted to a high-throughput methodology using next-generation sequencing. Here we describe the steps to generate a chemical genomic profile from a compound of interest, and how to use this information to predict molecular mechanism and targets of bioactive compounds. PMID:25618354

Achieving Safety: Safer Sex, Communication, and Desire among Young Gay Men

ERIC Educational Resources Information Center

Eisenberg, Anna; Bauermeister, Jose A.; Pingel, Emily; Johns, Michelle Marie; Santana, Matthew Leslie

2011-01-01

Conceptualizations of safer sex practices among young gay men (YGM) are frequently structured around communication between partners and the subsequent utilization or absence of condoms in a sexual encounter. Drawing on a sample of 34 in-depth interviews with YGM, ages 18 to 24, the authors explore the ways in which conceptualizations and…

PREDICTION OF CHEMICAL RESIDUES IN AQUATIC ORGANISMS FOR A FIELD DISCHARGE SITUATION.

EPA Science Inventory

A field study was performed which compared predicted and measured concentrations of chemicals in receiving water organisms from three sampling locations on Five Mile Creek, Birmingham, Al. Two point source discharges, both from coke manufacturing facilities, were included in the ...

Married women's negotiation for safer sexual intercourse in Kenya: Does experience of female genital mutilation matter?

PubMed

Chai, Xiangnan; Sano, Yujiro; Kansanga, Moses; Baada, Jemima; Antabe, Roger

2017-12-01

Married women's ability to negotiate for safer sex is important for HIV prevention in sub-Saharan Africa, including Kenya. Yet, its relationship to female genital mutilation is rarely explored, although female genital mutilation has been described as a social norm and marker of womanhood that can control women's sexuality. Drawing on the social normative influence theory, this study addressed this void in the literature. We analysed data from the 2014 Kenya Demographic and Health Survey using logistic regression. Our sample included 8,602 married women. Two indicators of safer sex, namely the ability to refuse sex and the ability to ask for condom use, were explored. We found that women who had undergone genital mutilation were significantly less likely to report that they can refuse sex (OR=0.87; p<.05) and that they can ask for condom use during sexual intercourse (OR=0.62; p<.001) than their counterparts who had not undergone genital mutilation, while controlling for theoretically relevant variables. Our findings indicate that the experience of female genital mutilation may influence married women's ability to negotiate for safer sex through gendered socialization and expectations. Based on these findings, several policy implications are suggested. For instance, culturally sensitive programmes are needed that target both married women who have undergone genital mutilation and their husbands to understand the importance of safer sexual practices within marriage. Copyright © 2017. Published by Elsevier B.V.

WISDOM GPR investigations in a Mars-analog environment during the SAFER rover operation simulation

NASA Astrophysics Data System (ADS)

Dorizon, S.; Ciarletti, V.; Plettemeier, D.; Vieau, A.-J.; Benedix, W.-S.; Mütze, M.; Hassen-Kodja, R.; Humeau, O.

2014-04-01

The WISDOM (Water Ice Subsurface Deposits Observations on Mars) Ground Penetrating Radar has been selected to be onboard the ExoMars 2018 rover mission [1]. This instrument will investigate the Martian shallow subsurface and provide the geological context of the mission, by characterizing the subsurface in terms of structure, stratigraphy and potential buried objects. It will also quantify the geoelectrical properties of the medium, which are directly related to its nature, its water or salts content and its hardness [2]. WISDOM data will provide important clues to guide the drilling operations to location of potential exobiological interest. A prototype available in LATMOS, France, is currently tested in a wide range of natural environments. In this context, the WISDOM team participated in the SAFER (Sample Acquisition Field Experiment with a Rover) field trial that occurred from 7th to 13th October 2013 in the Atacama Desert, Chile. Designed to gather together scientists and engineers in a context of a real Martian mission with a rover, the SAFER trial was the opportunity to use three onboard ExoMars instruments, namely CLUPI (Close- UP Imager), PANCAM (Panoramic Camera) and WISDOM, to investigate the chosen area. We present the results derived from WISDOM data acquired over the SAFER trial site to characterize the shallow subsurface of the area.

Dryden Flight Research Center Chemical Pharmacy Program

NASA Technical Reports Server (NTRS)

Davis, Bette

1997-01-01

The Dryden Flight Research Center (DFRC) Chemical Pharmacy "Crib" is a chemical sharing system which loans chemicals to users, rather than issuing them or having each individual organization or group purchasing the chemicals. This cooperative system of sharing chemicals eliminates multiple ownership of the same chemicals and also eliminates stockpiles. Chemical management duties are eliminated for each of the participating organizations. The chemical storage issues, hazards and responsibilities are eliminated. The system also ensures safe storage of chemicals and proper disposal practices. The purpose of this program is to reduce the total releases and transfers of toxic chemicals. The initial cost of the program to DFRC was $585,000. A savings of $69,000 per year has been estimated for the Center. This savings includes the reduced costs in purchasing, disposal and chemical inventory/storage responsibilities. DFRC has chemicals stored in 47 buildings and at 289 locations. When the program is fully implemented throughout the Center, there will be three chemical locations at this facility. The benefits of this program are the elimination of chemical management duties; elimination of the hazard associated with chemical storage; elimination of stockpiles; assurance of safe storage; assurance of proper disposal practices; assurance of a safer workplace; and more accurate emissions reports.

Assessment of quantitative structure-activity relationship of toxicity prediction models for Korean chemical substance control legislation

PubMed Central

Kim, Kwang-Yon; Shin, Seong Eun; No, Kyoung Tai

2015-01-01

Objectives For successful adoption of legislation controlling registration and assessment of chemical substances, it is important to obtain sufficient toxicological experimental evidence and other related information. It is also essential to obtain a sufficient number of predicted risk and toxicity results. Particularly, methods used in predicting toxicities of chemical substances during acquisition of required data, ultimately become an economic method for future dealings with new substances. Although the need for such methods is gradually increasing, the-required information about reliability and applicability range has not been systematically provided. Methods There are various representative environmental and human toxicity models based on quantitative structure-activity relationships (QSAR). Here, we secured the 10 representative QSAR-based prediction models and its information that can make predictions about substances that are expected to be regulated. We used models that predict and confirm usability of the information expected to be collected and submitted according to the legislation. After collecting and evaluating each predictive model and relevant data, we prepared methods quantifying the scientific validity and reliability, which are essential conditions for using predictive models. Results We calculated predicted values for the models. Furthermore, we deduced and compared adequacies of the models using the Alternative non-testing method assessed for Registration, Evaluation, Authorization, and Restriction of Chemicals Substances scoring system, and deduced the applicability domains for each model. Additionally, we calculated and compared inclusion rates of substances expected to be regulated, to confirm the applicability. Conclusions We evaluated and compared the data, adequacy, and applicability of our selected QSAR-based toxicity prediction models, and included them in a database. Based on this data, we aimed to construct a system that can be used

A safer alternative: Cannabis substitution as harm reduction.

PubMed

Lau, Nicholas; Sales, Paloma; Averill, Sheigla; Murphy, Fiona; Sato, Sye-Ok; Murphy, Sheigla

2015-11-01

Substitution is operationalised as a conscious choice made by users to use one drug instead of, or in conjunction with another based on: perceived safety, level of addiction potential, effectiveness in relieving symptoms, access and level of acceptance. Harm reduction is a set of strategies that aim to minimise problems associated with drug use while recognising that for some users, abstinence may be neither a realistic nor a desirable goal. In this paper, we aim for deeper understandings of older adult cannabis users' beliefs and substitution practices as part of the harm reduction framework. We present selected findings from our qualitative study of Baby Boomer (born 1946-1964) marijuana users in the San Francisco Bay Area. Although the sample consisted of primary cannabis users, many had personal experience with other drugs throughout their lifetimes. Data collection consisted of an audio-recorded, semi-structured in-depth life history interview followed by a questionnaire and health survey. Qualitative interviews were analysed to discover users' harm reduction beliefs and cannabis substitution practices. Study participants described using cannabis as a safer alternative for alcohol, illicit drugs and pharmaceuticals based on their perceptions of less adverse side effects, low-risk for addiction and greater effectiveness at relieving symptoms, such as chronic pain. Cannabis substitution can be an effective harm reduction method for those who are unable or unwilling to stop using drugs completely. More research is needed on cannabis as a safer alternative. © 2015 Australasian Professional Society on Alcohol and other Drugs.

75 FR 71123 - Agency Information Collection Activities; Proposed Collection; Comment Request; Safer Detergent...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-22

...-HQ-OPPT-2010-0874. The DCO is open from 8 a.m. to 4 p.m., Monday through Friday, excluding legal..., cleaners, airplane deicers, and fire-fighting foams. Safer surfactants are those that break down quickly to...

NREL Blows Up Batteries to Make the World Safer | News | NREL

Science.gov Websites

lithium-ion batteries safer for earthlings and astronauts is something NREL excels at. In this video . Matt and his team study battery failure using innovative technologies, such as the award-winning Battery Internal Short Circuit (ISC) Device that can precisely identify weak spots in battery cells. This

In vitro perturbations of targets in cancer hallmark processes predict rodent chemical carcinogenesis.

PubMed

Kleinstreuer, Nicole C; Dix, David J; Houck, Keith A; Kavlock, Robert J; Knudsen, Thomas B; Martin, Matthew T; Paul, Katie B; Reif, David M; Crofton, Kevin M; Hamilton, Kerry; Hunter, Ronald; Shah, Imran; Judson, Richard S

2013-01-01

Thousands of untested chemicals in the environment require efficient characterization of carcinogenic potential in humans. A proposed solution is rapid testing of chemicals using in vitro high-throughput screening (HTS) assays for targets in pathways linked to disease processes to build models for priority setting and further testing. We describe a model for predicting rodent carcinogenicity based on HTS data from 292 chemicals tested in 672 assays mapping to 455 genes. All data come from the EPA ToxCast project. The model was trained on a subset of 232 chemicals with in vivo rodent carcinogenicity data in the Toxicity Reference Database (ToxRefDB). Individual HTS assays strongly associated with rodent cancers in ToxRefDB were linked to genes, pathways, and hallmark processes documented to be involved in tumor biology and cancer progression. Rodent liver cancer endpoints were linked to well-documented pathways such as peroxisome proliferator-activated receptor signaling and TP53 and novel targets such as PDE5A and PLAUR. Cancer hallmark genes associated with rodent thyroid tumors were found to be linked to human thyroid tumors and autoimmune thyroid disease. A model was developed in which these genes/pathways function as hypothetical enhancers or promoters of rat thyroid tumors, acting secondary to the key initiating event of thyroid hormone disruption. A simple scoring function was generated to identify chemicals with significant in vitro evidence that was predictive of in vivo carcinogenicity in different rat tissues and organs. This scoring function was applied to an external test set of 33 compounds with carcinogenicity classifications from the EPA's Office of Pesticide Programs and successfully (p = 0.024) differentiated between chemicals classified as "possible"/"probable"/"likely" carcinogens and those designated as "not likely" or with "evidence of noncarcinogenicity." This model represents a chemical carcinogenicity prioritization tool supporting targeted

Genomic Models of Short-Term Exposure Accurately Predict Long-Term Chemical Carcinogenicity and Identify Putative Mechanisms of Action

PubMed Central

Gusenleitner, Daniel; Auerbach, Scott S.; Melia, Tisha; Gómez, Harold F.; Sherr, David H.; Monti, Stefano

2014-01-01

Background Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity. Results In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical's carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors. Conclusion Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure. PMID:25058030

Oral LD50 toxicity modeling and prediction of per- and polyfluorinated chemicals on rat and mouse.

PubMed

Bhhatarai, Barun; Gramatica, Paola

2011-05-01

Quantitative structure-activity relationship (QSAR) analyses were performed using the LD(50) oral toxicity data of per- and polyfluorinated chemicals (PFCs) on rodents: rat and mouse. PFCs are studied under the EU project CADASTER which uses the available experimental data for prediction and prioritization of toxic chemicals for risk assessment by using the in silico tools. The methodology presented here applies chemometrical analysis on the existing experimental data and predicts the toxicity of new compounds. QSAR analyses were performed on the available 58 mouse and 50 rat LD(50) oral data using multiple linear regression (MLR) based on theoretical molecular descriptors selected by genetic algorithm (GA). Training and prediction sets were prepared a priori from available experimental datasets in terms of structure and response. These sets were used to derive statistically robust and predictive (both internally and externally) models. The structural applicability domain (AD) of the models were verified on 376 per- and polyfluorinated chemicals including those in REACH preregistration list. The rat and mouse endpoints were predicted by each model for the studied compounds, and finally 30 compounds, all perfluorinated, were prioritized as most important for experimental toxicity analysis under the project. In addition, cumulative study on compounds within the AD of all four models, including two earlier published models on LC(50) rodent analysis was studied and the cumulative toxicity trend was observed using principal component analysis (PCA). The similarities and the differences observed in terms of descriptors and chemical/mechanistic meaning encoded by descriptors to prioritize the most toxic compounds are highlighted.

Safer sex practices among newly diagnosed HIV-positive men who have sex with men in China: results from an ethnographic study

PubMed Central

Li, Haochu; Sankar, Andrea; Holroyd, Eleanor; Jiang, Baofa

2017-01-01

ABSTRACT The study reported here sought to understand the rationales of safer sex practices adopted by newly diagnosed HIV-positive men who have sex with men (MSM). Guided by a socio-ecological framework, an ethnography was conducted among newly diagnosed HIV-positive MSM. In-depth interviews and participant observation were employed to produce an account of the social and cultural settings that was faithful to the perspectives of participants. A total of 31 participants with diverse backgrounds were recruited in a southern city of China. Participant observation was conducted in local healthcare settings, MSM venues, and NGO offices. Most participants (24/31) reported stopping unprotected anal intercourse (UAI) immediately after being diagnosed as HIV-positive. Factors associated with safer sex practices were identified at both individual and environmental levels, including self-protection, establishment of self-esteem, dignity, altruism and reciprocity, disease experience as a source of personal growth, and organizational culture and values. Newly diagnosed HIV-positive MSM navigate their sexual practices within the context of multiple competing factors. Implications for sustained behaviour change enabling safer sex practices include stimulating survival instinct, facilitating safer sex decision making, motivating and facilitating personal growth, and encouraging volunteerism to promote intentional activities for safer sex practices. PMID:29284374

Safer sex practices among newly diagnosed HIV-positive men who have sex with men in China: results from an ethnographic study.

PubMed

Li, Haochu; Sankar, Andrea; Holroyd, Eleanor; Jiang, Baofa

2017-12-01

The study reported here sought to understand the rationales of safer sex practices adopted by newly diagnosed HIV-positive men who have sex with men (MSM). Guided by a socio-ecological framework, an ethnography was conducted among newly diagnosed HIV-positive MSM. In-depth interviews and participant observation were employed to produce an account of the social and cultural settings that was faithful to the perspectives of participants. A total of 31 participants with diverse backgrounds were recruited in a southern city of China. Participant observation was conducted in local healthcare settings, MSM venues, and NGO offices. Most participants (24/31) reported stopping unprotected anal intercourse (UAI) immediately after being diagnosed as HIV-positive. Factors associated with safer sex practices were identified at both individual and environmental levels, including self-protection, establishment of self-esteem, dignity, altruism and reciprocity, disease experience as a source of personal growth, and organizational culture and values. Newly diagnosed HIV-positive MSM navigate their sexual practices within the context of multiple competing factors. Implications for sustained behaviour change enabling safer sex practices include stimulating survival instinct, facilitating safer sex decision making, motivating and facilitating personal growth, and encouraging volunteerism to promote intentional activities for safer sex practices.

Fragment-based 13C nuclear magnetic resonance chemical shift predictions in molecular crystals: An alternative to planewave methods

NASA Astrophysics Data System (ADS)

Hartman, Joshua D.; Monaco, Stephen; Schatschneider, Bohdan; Beran, Gregory J. O.

2015-09-01

We assess the quality of fragment-based ab initio isotropic 13C chemical shift predictions for a collection of 25 molecular crystals with eight different density functionals. We explore the relative performance of cluster, two-body fragment, combined cluster/fragment, and the planewave gauge-including projector augmented wave (GIPAW) models relative to experiment. When electrostatic embedding is employed to capture many-body polarization effects, the simple and computationally inexpensive two-body fragment model predicts both isotropic 13C chemical shifts and the chemical shielding tensors as well as both cluster models and the GIPAW approach. Unlike the GIPAW approach, hybrid density functionals can be used readily in a fragment model, and all four hybrid functionals tested here (PBE0, B3LYP, B3PW91, and B97-2) predict chemical shifts in noticeably better agreement with experiment than the four generalized gradient approximation (GGA) functionals considered (PBE, OPBE, BLYP, and BP86). A set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided based on these benchmark calculations. Statistical cross-validation procedures are used to demonstrate the robustness of these fits.

Fragment-based (13)C nuclear magnetic resonance chemical shift predictions in molecular crystals: An alternative to planewave methods.

PubMed

Hartman, Joshua D; Monaco, Stephen; Schatschneider, Bohdan; Beran, Gregory J O

2015-09-14

We assess the quality of fragment-based ab initio isotropic (13)C chemical shift predictions for a collection of 25 molecular crystals with eight different density functionals. We explore the relative performance of cluster, two-body fragment, combined cluster/fragment, and the planewave gauge-including projector augmented wave (GIPAW) models relative to experiment. When electrostatic embedding is employed to capture many-body polarization effects, the simple and computationally inexpensive two-body fragment model predicts both isotropic (13)C chemical shifts and the chemical shielding tensors as well as both cluster models and the GIPAW approach. Unlike the GIPAW approach, hybrid density functionals can be used readily in a fragment model, and all four hybrid functionals tested here (PBE0, B3LYP, B3PW91, and B97-2) predict chemical shifts in noticeably better agreement with experiment than the four generalized gradient approximation (GGA) functionals considered (PBE, OPBE, BLYP, and BP86). A set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided based on these benchmark calculations. Statistical cross-validation procedures are used to demonstrate the robustness of these fits.

Chemical Facility Security: Reauthorization, Policy Issues, and Options for Congress

DTIC Science & Technology

2009-11-10

chlorine disinfection to chloramine disinfection —a change identified by some advocacy groups as being an inherently safer substitution—as being...Congressional Research Service 9 such as chlorine, for purposes such as disinfection .22 Advocates for their inclusion in security regulations cite the...Science and Technology (S& T ) Directorate is engaged in a Chemical Infrastructure Risk Assessment Project that, among other goals, will assess the

EPA'S TOXCAST PROGRAM FOR PREDICTING HAZARD AND PRIORITIZING TOXICITY TESTING OF ENVIRONMENTAL CHEMICALS

EPA Science Inventory

EPA is developing methods for utilizing computational chemistry, high-throughput screening (HTS) and various toxicogenomic technologies to predict potential for toxicity and prioritize limited testing resources towards chemicals that likely represent the greatest hazard to human ...

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alves, Vinicius M.; Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599; Muratov, Eugene

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putativemore » sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. �

Computational neural networks in chemistry: Model free mapping devices for predicting chemical reactivity from molecular structure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elrod, D.W.

1992-01-01

Computational neural networks (CNNs) are a computational paradigm inspired by the brain's massively parallel network of highly interconnected neurons. The power of computational neural networks derives not so much from their ability to model the brain as from their ability to learn by example and to map highly complex, nonlinear functions, without the need to explicitly specify the functional relationship. Two central questions about CNNs were investigated in the context of predicting chemical reactions: (1) the mapping properties of neural networks and (2) the representation of chemical information for use in CNNs. Chemical reactivity is here considered an example ofmore » a complex, nonlinear function of molecular structure. CNN's were trained using modifications of the back propagation learning rule to map a three dimensional response surface similar to those typically observed in quantitative structure-activity and structure-property relationships. The computational neural network's mapping of the response surface was found to be robust to the effects of training sample size, noisy data and intercorrelated input variables. The investigation of chemical structure representation led to the development of a molecular structure-based connection-table representation suitable for neural network training. An extension of this work led to a BE-matrix structure representation that was found to be general for several classes of reactions. The CNN prediction of chemical reactivity and regiochemistry was investigated for electrophilic aromatic substitution reactions, Markovnikov addition to alkenes, Saytzeff elimination from haloalkanes, Diels-Alder cycloaddition, and retro Diels-Alder ring opening reactions using these connectivity-matrix derived representations. The reaction predictions made by the CNNs were more accurate than those of an expert system and were comparable to predictions made by chemists.« less

From consumption to harvest: Environmental fate prediction of excreted ionizable trace organic chemicals.

PubMed

Polesel, Fabio; Plósz, Benedek Gy; Trapp, Stefan

2015-11-01

Excreted trace organic chemicals, e.g., pharmaceuticals and biocides, typically undergo incomplete elimination in municipal wastewater treatment plants (WWTPs) and are released to surface water via treated effluents and to agricultural soils through sludge amendment and/or irrigation with freshwater or reclaimed wastewater. Recent research has shown the tendency for these substances to accumulate in food crops. In this study, we developed and applied a simulation tool to predict the fate of three ionizable trace chemicals (triclosan-TCS, furosemide-FUR, ciprofloxacin-CIP) from human consumption/excretion up to the accumulation in soil and plant, following field amendment with sewage sludge or irrigation with river water (assuming dilution of WWTP effluent). The simulation tool combines the SimpleTreat model modified for fate prediction of ionizable chemicals in a generic WWTP and a recently developed dynamic soil-plant uptake model. The simulation tool was tested using country-specific (e.g., consumption/emission rates, precipitation and temperature) input data. A Monte Carlo-based approach was adopted to account for the uncertainty associated to physico-chemical and biokinetic model parameters. Results obtained in this study suggest significant accumulation of TCS and CIP in sewage sludge (1.4-2.8 mg kgDW(-1)) as compared to FUR (0.02-0.11 mg kgDW(-1)). For the latter substance, more than half of the influent load (60.1%-72.5%) was estimated to be discharged via WWTP effluent. Specific emission rates (g ha(-1) a(-1)) of FUR to soil via either sludge application or irrigation were up to 300 times lower than for TCS and CIP. Nevertheless, high translocation potential to wheat was predicted for FUR, reaching concentrations up to 4.3 μg kgDW(-1) in grain. Irrigation was found to enhance the relative translocation of FUR to plant (45.3%-48.9% of emission to soil), as compared to sludge application (21.9%-27.6%). A comparison with peer-reviewed literature showed

‘It is not expected for married couples’: a qualitative study on challenges to safer sex communication among polygamous and monogamous partners in southeastern Tanzania

PubMed Central

Mtenga, Sally Mmanyi; Geubbels, Eveline; Tanner, Marcel; Merten, Sonja; Pfeiffer, Constanze

2016-01-01

Background Behavioral change approaches for human immunodeficiency virus (HIV) prevention in Tanzania encourage married partners to observe safe sex practices (condom use, avoidance of, or safe sex with multiple partners). To implement this advice, partners need to communicate with each other about safer sex, which is often challenging. Although social-structural factors are crucial in understanding sexual behavior, only a few studies focus on understanding safer sex dialogue in a broader social context. Design Drawing on the WHO-Commission on the Social Determinants of Health (WHO-CSDH) framework, this study explored key social-structural constructs for studying health in the context of improving safer sex dialogue between polygamous and monogamous partners. Twenty-four in-depth interviews (IDIs) and six focus group discussions (FGDs) with 38 men and women aged 18–60 years were conducted in Ifakara town located in Kilombero district, Tanzania. The study was nested within the community health surveillance project MZIMA (Kiswahili: ‘being healthy’). Partners’ experiences of safer sex dialogue in polygamous and monogamous relations were investigated and the challenges to safer sex dialogue explored. Results The study revealed that open safer sex dialogue in marriage is limited and challenged by social norms about marriage (a view that safer sex dialogue imply that partners are ‘not really’ married); marital status (a belief that safer sex dialogue is not practical in polygamous marriages, the elder wife should be exempted from the dialogue since she is at lower risk of engaging in extramarital affairs); relationship quality (marital conflicts, extramarital affairs, trust, and sexual dissatisfaction); and gender power relations (the notion that females’ initiative to discuss condom use and HIV couple counseling and testing may lead to conflict or divorce). Conclusions Implementing safer sex practices requires interventions beyond promotion messages. HIV

Quantum Chemical Prediction of Equilibrium Acidities of Ureas, Deltamides, Squaramides, and Croconamides.

PubMed

Ho, Junming; Zwicker, Vincent E; Yuen, Karen K Y; Jolliffe, Katrina A

2017-10-06

Robust quantum chemical methods are employed to predict the pK a 's of several families of dual hydrogen-bonding organocatalysts/anion receptors, including deltamides and croconamides as well as their thio derivatives. The average accuracy of these predictions is ∼1 pK a unit and allows for a comparison of the acidity between classes of receptors and for quantitative studies of substituent effects. These computational insights further explain the relationship between pK a and chloride anion affinity of these receptors that will be important for designing future anion receptors and organocatalysts.

Assessing deep and shallow learning methods for quantitative prediction of acute chemical toxicity.

PubMed

Liu, Ruifeng; Madore, Michael; Glover, Kyle P; Feasel, Michael G; Wallqvist, Anders

2018-05-02

Animal-based methods for assessing chemical toxicity are struggling to meet testing demands. In silico approaches, including machine-learning methods, are promising alternatives. Recently, deep neural networks (DNNs) were evaluated and reported to outperform other machine-learning methods for quantitative structure-activity relationship modeling of molecular properties. However, most of the reported performance evaluations relied on global performance metrics, such as the root mean squared error (RMSE) between the predicted and experimental values of all samples, without considering the impact of sample distribution across the activity spectrum. Here, we carried out an in-depth analysis of DNN performance for quantitative prediction of acute chemical toxicity using several datasets. We found that the overall performance of DNN models on datasets of up to 30,000 compounds was similar to that of random forest (RF) models, as measured by the RMSE and correlation coefficients between the predicted and experimental results. However, our detailed analyses demonstrated that global performance metrics are inappropriate for datasets with a highly uneven sample distribution, because they show a strong bias for the most populous compounds along the toxicity spectrum. For highly toxic compounds, DNN and RF models trained on all samples performed much worse than the global performance metrics indicated. Surprisingly, our variable nearest neighbor method, which utilizes only structurally similar compounds to make predictions, performed reasonably well, suggesting that information of close near neighbors in the training sets is a key determinant of acute toxicity predictions.

Test battery with the human cell line activation test, direct peptide reactivity assay and DEREK based on a 139 chemical data set for predicting skin sensitizing potential and potency of chemicals.

PubMed

Takenouchi, Osamu; Fukui, Shiho; Okamoto, Kenji; Kurotani, Satoru; Imai, Noriyasu; Fujishiro, Miyuki; Kyotani, Daiki; Kato, Yoshinao; Kasahara, Toshihiko; Fujita, Masaharu; Toyoda, Akemi; Sekiya, Daisuke; Watanabe, Shinichi; Seto, Hirokazu; Hirota, Morihiko; Ashikaga, Takao; Miyazawa, Masaaki

2015-11-01

To develop a testing strategy incorporating the human cell line activation test (h-CLAT), direct peptide reactivity assay (DPRA) and DEREK, we created an expanded data set of 139 chemicals (102 sensitizers and 37 non-sensitizers) by combining the existing data set of 101 chemicals through the collaborative projects of Japan Cosmetic Industry Association. Of the additional 38 chemicals, 15 chemicals with relatively low water solubility (log Kow > 3.5) were selected to clarify the limitation of testing strategies regarding the lipophilic chemicals. Predictivities of the h-CLAT, DPRA and DEREK, and the combinations thereof were evaluated by comparison to results of the local lymph node assay. When evaluating 139 chemicals using combinations of three methods based on integrated testing strategy (ITS) concept (ITS-based test battery) and a sequential testing strategy (STS) weighing the predictive performance of the h-CLAT and DPRA, overall similar predictivities were found as before on the 101 chemical data set. An analysis of false negative chemicals suggested a major limitation of our strategies was the testing of low water-soluble chemicals. When excluded the negative results for chemicals with log Kow > 3.5, the sensitivity and accuracy of ITS improved to 97% (91 of 94 chemicals) and 89% (114 of 128). Likewise, the sensitivity and accuracy of STS to 98% (92 of 94) and 85% (111 of 129). Moreover, the ITS and STS also showed good correlation with local lymph node assay on three potency classifications, yielding accuracies of 74% (ITS) and 73% (STS). Thus, the inclusion of log Kow in analysis could give both strategies a higher predictive performance. Copyright © 2015 John Wiley & Sons, Ltd.

Statistics-based model for prediction of chemical biosynthesis yield from Saccharomyces cerevisiae

PubMed Central

2011-01-01

Background The robustness of Saccharomyces cerevisiae in facilitating industrial-scale production of ethanol extends its utilization as a platform to synthesize other metabolites. Metabolic engineering strategies, typically via pathway overexpression and deletion, continue to play a key role for optimizing the conversion efficiency of substrates into the desired products. However, chemical production titer or yield remains difficult to predict based on reaction stoichiometry and mass balance. We sampled a large space of data of chemical production from S. cerevisiae, and developed a statistics-based model to calculate production yield using input variables that represent the number of enzymatic steps in the key biosynthetic pathway of interest, metabolic modifications, cultivation modes, nutrition and oxygen availability. Results Based on the production data of about 40 chemicals produced from S. cerevisiae, metabolic engineering methods, nutrient supplementation, and fermentation conditions described therein, we generated mathematical models with numerical and categorical variables to predict production yield. Statistically, the models showed that: 1. Chemical production from central metabolic precursors decreased exponentially with increasing number of enzymatic steps for biosynthesis (>30% loss of yield per enzymatic step, P-value = 0); 2. Categorical variables of gene overexpression and knockout improved product yield by 2~4 folds (P-value < 0.1); 3. Addition of notable amount of intermediate precursors or nutrients improved product yield by over five folds (P-value < 0.05); 4. Performing the cultivation in a well-controlled bioreactor enhanced the yield of product by three folds (P-value < 0.05); 5. Contribution of oxygen to product yield was not statistically significant. Yield calculations for various chemicals using the linear model were in fairly good agreement with the experimental values. The model generally underestimated the ethanol production as

Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks

PubMed Central

Shen, Yang; Bax, Ad

2013-01-01

A new program, TALOS-N, is introduced for predicting protein backbone torsion angles from NMR chemical shifts. The program relies far more extensively on the use of trained artificial neural networks than its predecessor, TALOS+. Validation on an independent set of proteins indicates that backbone torsion angles can be predicted for a larger, ≥ 90% fraction of the residues, with an error rate smaller than ca 3.5%, using an acceptance criterion that is nearly two-fold tighter than that used previously, and a root mean square difference between predicted and crystallographically observed (φ,ψ) torsion angles of ca 12°. TALOS-N also reports sidechain χ1 rotameric states for about 50% of the residues, and a consistency with reference structures of 89%. The program includes a neural network trained to identify secondary structure from residue sequence and chemical shifts. PMID:23728592

Concept of REACH and impact on evaluation of chemicals.

PubMed

Foth, H; Hayes, Aw

2008-01-01

Industrial chemicals have been in use for many decades and new products are regularly invented and introduced to the market. Also for decades, many different chemical laws have been introduced to regulate safe handling of chemicals in different use patterns. The patchwork of current regulation in the European Union is to be replaced by the new regulation on industrial chemical control, REACH. REACH stands for registration, evaluation, and authorization of chemicals. REACH entered force on June 1, 2007. REACH aims to overcome limitations in testing requirements of former regulation on industrial chemicals to enhance competitiveness and innovation with regard to manufacture safer substances and to promote the development of alternative testing methods. A main task of REACH is to address data gaps regarding the properties and uses of industrial chemicals. Producers, importers, and downstream users will have to compile and communicate standard information for all chemicals. Information sets to be prepared include safety data sheets (SDS), chemical safety reports (CSR), and chemical safety assessments (CSA). These are designed to guarantee adequate handling in the production chain, in transport and in use and to prevent the substances from being released to and distributed within the environment. Another important aim is to identify the most harmful chemicals and to set incentives to substitute them with safer alternatives. On one hand, REACH will have substantial impact on the basic understanding of the evaluation of chemicals. However, the toxicological sciences can also substantially influence the workability of REACH that supports the transformation of data to the information required to understand and manage acceptable and non acceptable risks in the use of industrial chemicals. The REACH regulation has been laid down in the main document and 17 Annexes of more than 849 pages. Even bigger technical guidance documents will follow and will inform about the rules for

Chemical Composition of a New Taxon, Seseli gummiferum subsp. ilgazense, and its Larvicidal Activity against Aedes aegypti.

USDA-ARS?s Scientific Manuscript database

There has been renewed interest in finding the use of natural plant extracts as alternative sources for public health pesticides since these extracts and their constituent compounds are normally considered safer than chemicals for human health and the environment. Mosquitoes are vectors for many pat...

SAFER, an Analysis Method of Quantitative Proteomic Data, Reveals New Interactors of the C. elegans Autophagic Protein LGG-1.

PubMed

Yi, Zhou; Manil-Ségalen, Marion; Sago, Laila; Glatigny, Annie; Redeker, Virginie; Legouis, Renaud; Mucchielli-Giorgi, Marie-Hélène

2016-05-06

Affinity purifications followed by mass spectrometric analysis are used to identify protein-protein interactions. Because quantitative proteomic data are noisy, it is necessary to develop statistical methods to eliminate false-positives and identify true partners. We present here a novel approach for filtering false interactors, named "SAFER" for mass Spectrometry data Analysis by Filtering of Experimental Replicates, which is based on the reproducibility of the replicates and the fold-change of the protein intensities between bait and control. To identify regulators or targets of autophagy, we characterized the interactors of LGG1, a ubiquitin-like protein involved in autophagosome formation in C. elegans. LGG-1 partners were purified by affinity, analyzed by nanoLC-MS/MS mass spectrometry, and quantified by a label-free proteomic approach based on the mass spectrometric signal intensity of peptide precursor ions. Because the selection of confident interactions depends on the method used for statistical analysis, we compared SAFER with several statistical tests and different scoring algorithms on this set of data. We show that SAFER recovers high-confidence interactors that have been ignored by the other methods and identified new candidates involved in the autophagy process. We further validated our method on a public data set and conclude that SAFER notably improves the identification of protein interactors.

Chemical Facility Security: Issues and Options for the 112th Congress

DTIC Science & Technology

2011-03-08

between two approved disinfectants —chlorine and chloramine —as correlated with an unexpected increase in levels of lead in drinking water due to increased...for purposes such as disinfection .50 Advocates for their inclusion in security regulations cite the presence of such potentially hazardous... T ) Directorate is engaged in a Chemical Infrastructure Risk Assessment Project that, among other goals, will assess the potential for safer

Chemical Potentials, Activity Coefficients, and Solubility in Aqueous NaCl Solutions: Prediction by Polarizable Force Fields.

PubMed

Moučka, Filip; Nezbeda, Ivo; Smith, William R

2015-04-14

We describe a computationally efficient molecular simulation methodology for calculating the concentration dependence of the chemical potentials of both solute and solvent in aqueous electrolyte solutions, based on simulations of the salt chemical potential alone. We use our approach to study the predictions for aqueous NaCl solutions at ambient conditions of these properties by the recently developed polarizable force fields (FFs) AH/BK3 of Kiss and Baranyai (J. Chem. Phys. 2013, 138, 204507) and AH/SWM4-DP of Lamoureux and Roux (J. Phys. Chem. B 2006, 110, 3308 - 3322) and by the nonpolarizable JC FF of Joung and Cheatham tailored to SPC/E water (J. Phys. Chem. B 2008, 112, 9020 - 9041). We also consider their predictions of the concentration dependence of the electrolyte activity coefficient, the crystalline solid chemical potential, the electrolyte solubility, and the solution specific volume. We first highlight the disagreement in the literature concerning calculations of solubility by means of molecular simulation in the case of the JC FF and provide strong evidence of the correctness of our methodology based on recent independently obtained results for this important test case. We then compare the predictions of the three FFs with each other and with experiment and draw conclusions concerning their relative merits, with particular emphasis on the salt chemical potential and activity coefficient vs concentration curves and their derivatives. The latter curves have only previously been available from Kirkwood-Buff integrals, which require approximate numerical integrations over system pair correlation functions at each concentration. Unlike the case of the other FFs, the AH/BK3 curves are nearly parallel to the corresponding experimental curves at moderate and higher concentrations. This leads to an excellent prediction of the water chemical potential via the Gibbs-Duhem equation and enables the activity coefficient curve to be brought into excellent agreement

Effects of a Televised Two-City Safer Sex Mass Media Campaign Targeting High-Sensation-Seeking and Impulsive-Decision-Making Young Adults

ERIC Educational Resources Information Center

Zimmerman, Rick S.; Palmgreen, Philip M.; Noar, Seth M.; Lustria, Mia Liza A.; Lu, Hung-Yi; Horosewski, Mary Lee

2007-01-01

This study evaluates the ability of a safer sex televised public service announcement (PSA) campaign to increase safer sexual behavior among at-risk young adults. Independent, monthly random samples of 100 individuals were surveyed in each city for 21 months as part of an interrupted-time-series design with a control community. The 3-month…

Reforming state-level chemicals management policies in the United States: status, challenges, and opportunities.

PubMed

Geiser, Ken; Tickner, Joel; Torrie, Yve

2009-01-01

During the last several years there has been increasing public concern about chemicals in everyday products. Scientific studies are increasingly revealing the build-up of some substances in ecosystems and in our bodies and new findings are linking exposures to hazardous chemicals to a range of adverse human health effects. Despite these trends, there has been little federal initiative in the United States on reforming chemicals management policies for well over two decades, even though a variety of analyses have identified significant gaps in the regulatory structure. As has historically been the case, states are beginning to fill the holes in federal leadership. This article explores this emerging state leadership and establishes a vision for and elements of policies to reduce hazardous chemicals in the products we buy and the places we go. It examines international efforts to reform chemicals management policies, such as the European REACH legislation and corporate leadership in advancing safer products. Finally, it outlines specific challenges states face in developing integrated, comprehensive chemicals management policies. We conclude that while there are plenty of challenges to implementation of chemicals policy reforms, it is a propitious time for states to become leaders in policy innovation that can help achieve safer production systems and products for future generations. This article is part of a Lowell Center for Sustainable Production report entitled "Options for State Chemicals Policy Reform" that provides in-depth analysis of the pros and cons of policy options to address a range of aspects of state-level chemicals policy reform. The article has been edited slightly for use in New Solutions. The report has been widely distributed to policy-makers, advocates, and others across the United States.

Simultaneous prediction of enzyme orthologs from chemical transformation patterns for de novo metabolic pathway reconstruction

PubMed Central

Tabei, Yasuo; Yamanishi, Yoshihiro; Kotera, Masaaki

2016-01-01

Motivation: Metabolic pathways are an important class of molecular networks consisting of compounds, enzymes and their interactions. The understanding of global metabolic pathways is extremely important for various applications in ecology and pharmacology. However, large parts of metabolic pathways remain unknown, and most organism-specific pathways contain many missing enzymes. Results: In this study we propose a novel method to predict the enzyme orthologs that catalyze the putative reactions to facilitate the de novo reconstruction of metabolic pathways from metabolome-scale compound sets. The algorithm detects the chemical transformation patterns of substrate–product pairs using chemical graph alignments, and constructs a set of enzyme-specific classifiers to simultaneously predict all the enzyme orthologs that could catalyze the putative reactions of the substrate–product pairs in the joint learning framework. The originality of the method lies in its ability to make predictions for thousands of enzyme orthologs simultaneously, as well as its extraction of enzyme-specific chemical transformation patterns of substrate–product pairs. We demonstrate the usefulness of the proposed method by applying it to some ten thousands of metabolic compounds, and analyze the extracted chemical transformation patterns that provide insights into the characteristics and specificities of enzymes. The proposed method will open the door to both primary (central) and secondary metabolism in genomics research, increasing research productivity to tackle a wide variety of environmental and public health matters. Availability and Implementation: Contact: maskot@bio.titech.ac.jp PMID:27307627

Essential Set of Molecular Descriptors for ADME Prediction in Drug and Environmental Chemical Space

EPA Science Inventory

Historically, the disciplines of pharmacology and toxicology have embraced quantitative structure-activity relationships (QSAR) and quantitative structure-property relationships (QSPR) to predict ADME properties or biological activities of untested chemicals. The question arises ...

Fragment-based {sup 13}C nuclear magnetic resonance chemical shift predictions in molecular crystals: An alternative to planewave methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hartman, Joshua D.; Beran, Gregory J. O., E-mail: gregory.beran@ucr.edu; Monaco, Stephen

2015-09-14

We assess the quality of fragment-based ab initio isotropic {sup 13}C chemical shift predictions for a collection of 25 molecular crystals with eight different density functionals. We explore the relative performance of cluster, two-body fragment, combined cluster/fragment, and the planewave gauge-including projector augmented wave (GIPAW) models relative to experiment. When electrostatic embedding is employed to capture many-body polarization effects, the simple and computationally inexpensive two-body fragment model predicts both isotropic {sup 13}C chemical shifts and the chemical shielding tensors as well as both cluster models and the GIPAW approach. Unlike the GIPAW approach, hybrid density functionals can be used readilymore » in a fragment model, and all four hybrid functionals tested here (PBE0, B3LYP, B3PW91, and B97-2) predict chemical shifts in noticeably better agreement with experiment than the four generalized gradient approximation (GGA) functionals considered (PBE, OPBE, BLYP, and BP86). A set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided based on these benchmark calculations. Statistical cross-validation procedures are used to demonstrate the robustness of these fits.« less

Chemical production in electrocautery smoke by a novel predictive model.

PubMed

Wu, Y-C; Tang, C-S; Huang, H-Y; Liu, C-H; Chen, Y-L; Chen, D-R; Lin, Y-W

2011-01-01

The hazards of electrocautery smoke have been known for decades. However, few clinical studies have been conducted to analyze the responsible variables of the smoke production. This study collected clinical smoke samples and systematically analyzed all possible factors. Thirty diathermy smoke samples were collected during mastectomy and abdominal cavity operations. Samples were analyzed using a gas chromatographer with a flame ionization detector. Data were applied to construct prediction models for chemical production from electrosurgeries to identify all possible factors that impact chemical production during electrosurgery. Toluene was detected in 27 smoke samples (90%) with concentrations of 0.003-0.463 mg/m(3) and production of 176.0-2,780.0 ng. Ethyl benzene and styrene were identified in very few cases. General linear regression analysis demonstrates that surgery type, patient age, electrocautery duration and imparted coagulation energy explained 67.63% of the variation in toluene production. Surgery type and patient age are known prior to surgery. In terms of risk precaution, the operating team should pay close attention to exposure when certain positive factors of increasing the chemical production are known in advance. Copyright © 2011 S. Karger AG, Basel.

High-Throughput Predictive Approaches to Evaluating Chemicals in Food Contact Materials: Migration, Exposure, and Alternatives Identification

EPA Science Inventory

This is a presentation describing CSS research on HT predictive methods to modeling exposure and predicting functional substitutes. It will be presented at a forum co-sponsored by the State of California and UC Berekeley on evaluation of chemical alternatives for food contact ch...

ZEBRAFISH AS AN IN VIVO MODEL FOR SUSTAINABLE CHEMICAL DESIGN.

PubMed

Noyes, Pamela D; Garcia, Gloria R; Tanguay, Robert L

2016-12-21

Heightened public awareness about the many thousands of chemicals in use and present as persistent contaminants in the environment has increased the demand for safer chemicals and more rigorous toxicity testing. There is a growing recognition that the use of traditional test models and empirical approaches is impractical for screening for toxicity the many thousands of chemicals in the environment and the hundreds of new chemistries introduced each year. These realities coupled with the green chemistry movement have prompted efforts to implement more predictive-based approaches to evaluate chemical toxicity early in product development. While used for many years in environmental toxicology and biomedicine, zebrafish use has accelerated more recently in genetic toxicology, high throughput screening (HTS), and behavioral testing. This review describes major advances in these testing methods that have positioned the zebrafish as a highly applicable model in chemical safety evaluations and sustainable chemistry efforts. Many toxic responses have been shown to be shared among fish and mammals owing to their generally well-conserved development, cellular networks, and organ systems. These shared responses have been observed for chemicals that impair endocrine functioning, development, and reproduction, as well as those that elicit cardiotoxicity and carcinogenicity, among other diseases. HTS technologies with zebrafish enable screening large chemical libraries for bioactivity that provide opportunities for testing early in product development. A compelling attribute of the zebrafish centers on being able to characterize toxicity mechanisms across multiple levels of biological organization from the genome to receptor interactions and cellular processes leading to phenotypic changes such as developmental malformations. Finally, there is a growing recognition of the links between human and wildlife health and the need for approaches that allow for assessment of real world

ZEBRAFISH AS AN IN VIVO MODEL FOR SUSTAINABLE CHEMICAL DESIGN

PubMed Central

Noyes, Pamela D.; Garcia, Gloria R.; Tanguay, Robert L.

2016-01-01

Heightened public awareness about the many thousands of chemicals in use and present as persistent contaminants in the environment has increased the demand for safer chemicals and more rigorous toxicity testing. There is a growing recognition that the use of traditional test models and empirical approaches is impractical for screening for toxicity the many thousands of chemicals in the environment and the hundreds of new chemistries introduced each year. These realities coupled with the green chemistry movement have prompted efforts to implement more predictive-based approaches to evaluate chemical toxicity early in product development. While used for many years in environmental toxicology and biomedicine, zebrafish use has accelerated more recently in genetic toxicology, high throughput screening (HTS), and behavioral testing. This review describes major advances in these testing methods that have positioned the zebrafish as a highly applicable model in chemical safety evaluations and sustainable chemistry efforts. Many toxic responses have been shown to be shared among fish and mammals owing to their generally well-conserved development, cellular networks, and organ systems. These shared responses have been observed for chemicals that impair endocrine functioning, development, and reproduction, as well as those that elicit cardiotoxicity and carcinogenicity, among other diseases. HTS technologies with zebrafish enable screening large chemical libraries for bioactivity that provide opportunities for testing early in product development. A compelling attribute of the zebrafish centers on being able to characterize toxicity mechanisms across multiple levels of biological organization from the genome to receptor interactions and cellular processes leading to phenotypic changes such as developmental malformations. Finally, there is a growing recognition of the links between human and wildlife health and the need for approaches that allow for assessment of real world

Advanced and safer lithium-ion battery based on sustainable electrodes

NASA Astrophysics Data System (ADS)

Ding, Xiang; Huang, Xiaobing; Jin, Junling; Ming, Hai; Wang, Limin; Ming, Jun

2018-03-01

Seeking advanced and safer lithium-ion battery with sustainable characteristic is significant for the development of electronic devices and electric vehicles. Herein, a new porous TiO2 nanobundles (PTNBs) is synthesized though a scalable and green hydrothermal strategy from the TiO2 powders without using any high-cost and harmful organic titanium-based compounds. The PTNBs exhibits an extremely high lithium storage capacity of 296 mAh g-1 at 100 mA g-1, where the capacity can maintain over 146 mAh g-1 even after 500 cycles at 1000 mA g-1. To pursue more reliable Li-ion batteries, full batteries of PTNBs/LiNixMn1-xO4 (x = 0, 0.5) using spinel structured cathode are constructed. The batteries have the features of sustainability and deliver high capacities of 112 mAh gcathode-1 and 102 mAh gcathode-1 with stable capacity retentions of 99% and 90% over 140 cycles. Note that the energy densities can achieve as high as 267 and 270 Wh kgcathode-1 (535 and 540 Wh kganode-1) respectively, which is feasible to satisfy diverse requirements for energy storage products. We believe that the universal synthetic strategy, appealing structure and intriguing properties of PTNBs is applicable for wider applications, while the concept of sustainable strategy seeking reliable and safer Li-ion battery can attract broad interest.

Species-Specific Predictive Signatures of Developmental Toxicity Using the ToxCast Chemical Library

EPA Science Inventory

EPA’s ToxCastTM project is profiling the in vitro bioactivity of chemicals to generate predictive signatures that correlate with observed in vivo toxicity. In vitro profiling methods from ToxCast data consist of over 600 high-throughput screening (HTS) and high-content screening ...

Evaluation of in silico tools to predict the skin sensitization potential of chemicals.

PubMed

Verheyen, G R; Braeken, E; Van Deun, K; Van Miert, S

2017-01-01

Public domain and commercial in silico tools were compared for their performance in predicting the skin sensitization potential of chemicals. The packages were either statistical based (Vega, CASE Ultra) or rule based (OECD Toolbox, Toxtree, Derek Nexus). In practice, several of these in silico tools are used in gap filling and read-across, but here their use was limited to make predictions based on presence/absence of structural features associated to sensitization. The top 400 ranking substances of the ATSDR 2011 Priority List of Hazardous Substances were selected as a starting point. Experimental information was identified for 160 chemically diverse substances (82 positive and 78 negative). The prediction for skin sensitization potential was compared with the experimental data. Rule-based tools perform slightly better, with accuracies ranging from 0.6 (OECD Toolbox) to 0.78 (Derek Nexus), compared with statistical tools that had accuracies ranging from 0.48 (Vega) to 0.73 (CASE Ultra - LLNA weak model). Combining models increased the performance, with positive and negative predictive values up to 80% and 84%, respectively. However, the number of substances that were predicted positive or negative for skin sensitization in both models was low. Adding more substances to the dataset will increase the confidence in the conclusions reached. The insights obtained in this evaluation are incorporated in a web database www.asopus.weebly.com that provides a potential end user context for the scope and performance of different in silico tools with respect to a common dataset of curated skin sensitization data.

Prediction of the effect of formulation on the toxicity of chemicals.

PubMed

Mistry, Pritesh; Neagu, Daniel; Sanchez-Ruiz, Antonio; Trundle, Paul R; Vessey, Jonathan D; Gosling, John Paul

2017-01-01

Two approaches for the prediction of which of two vehicles will result in lower toxicity for anticancer agents are presented. Machine-learning models are developed using decision tree, random forest and partial least squares methodologies and statistical evidence is presented to demonstrate that they represent valid models. Separately, a clustering method is presented that allows the ordering of vehicles by the toxicity they show for chemically-related compounds.

Engineering safer-by-design, transparent, silica-coated ZnO nanorods with reduced DNA damage potential

PubMed Central

Sotiriou, Georgios A.; Watson, Christa; Murdaugh, Kimberly M.; Darrah, Thomas H.; Pyrgiotakis, Georgios; Elder, Alison; Brain, Joseph D.; Demokritou, Philip

2014-01-01

Zinc oxide (ZnO) nanoparticles absorb UV light efficiently while remaining transparent in the visible light spectrum rendering them attractive in cosmetics and polymer films. Their broad use, however, raises concerns regarding potential environmental health risks and it has been shown that ZnO nanoparticles can induce significant DNA damage and cytotoxicity. Even though research on ZnO nanoparticle synthesis has made great progress, efforts on developing safer ZnO nanoparticles that maintain their inherent optoelectronic properties while exhibiting minimal toxicity are limited. Here, a safer-by-design concept was pursued by hermetically encapsulating ZnO nanorods in a biologically inert, nanothin amorphous SiO2 coating during their gas-phase synthesis. It is demonstrated that the SiO2 nanothin layer hermetically encapsulates the core ZnO nanorods without altering their optoelectronic properties. Furthermore, the effect of SiO2 on the toxicological profile of the core ZnO nanorods was assessed using the Nano-Cometchip assay by monitoring DNA damage at a cellular level using human lymphoblastoid cells (TK6). Results indicate significantly lower DNA damage (>3 times) for the SiO2-coated ZnO nanorods compared to uncoated ones. Such an industry-relevant, scalable, safer-by-design formulation of nanostructured materials can liberate their employment in nano-enabled products and minimize risks to the environment and human health. PMID:24955241

Species-specific predictive models of developmental toxicity using the ToxCast chemical library

EPA Science Inventory

EPA’s ToxCastTM project is profiling the in vitro bioactivity of chemicals to generate predictive models that correlate with observed in vivo toxicity. In vitro profiling methods are based on ToxCast data, consisting of over 600 high-throughput screening (HTS) and high-content sc...

Inferences of drug responses in cancer cells from cancer genomic features and compound chemical and therapeutic properties

PubMed Central

Wang, Yongcui; Fang, Jianwen; Chen, Shilong

2016-01-01

Accurately predicting the response of a cancer patient to a therapeutic agent is a core goal of precision medicine. Existing approaches were mainly relied primarily on genomic alterations in cancer cells that have been treated with different drugs. Here we focus on predicting drug response based on integration of the heterogeneously pharmacogenomics data from both cell and drug sides. Through a systematical approach, named as PDRCC (Predict Drug Response in Cancer Cells), the cancer genomic alterations and compound chemical and therapeutic properties were incorporated to determine the chemotherapeutic response in cancer patients. Using the Cancer Cell Line Encyclopedia (CCLE) study as the benchmark dataset, all pharmacogenomics data exhibited their roles in inferring the relationships between cancer cells and drugs. When integrating both genomic resources and compound information, the prediction coverage was significantly increased. The validity of PDRCC was also supported by its effective in uncovering the unknown cell-drug associations with database and literature evidences. It set the stage for clinical testing of novel therapeutic strategies, such as the sensitive association between cancer cell ‘A549_LUNG’ and compound ‘Topotecan’. In conclusion, PDRCC offers the possibility for faster, safer, and cheaper the development of novel anti-cancer therapeutics in the early-stage clinical trails. PMID:27645580

Inferences of drug responses in cancer cells from cancer genomic features and compound chemical and therapeutic properties

NASA Astrophysics Data System (ADS)

Wang, Yongcui; Fang, Jianwen; Chen, Shilong

2016-09-01

Accurately predicting the response of a cancer patient to a therapeutic agent is a core goal of precision medicine. Existing approaches were mainly relied primarily on genomic alterations in cancer cells that have been treated with different drugs. Here we focus on predicting drug response based on integration of the heterogeneously pharmacogenomics data from both cell and drug sides. Through a systematical approach, named as PDRCC (Predict Drug Response in Cancer Cells), the cancer genomic alterations and compound chemical and therapeutic properties were incorporated to determine the chemotherapeutic response in cancer patients. Using the Cancer Cell Line Encyclopedia (CCLE) study as the benchmark dataset, all pharmacogenomics data exhibited their roles in inferring the relationships between cancer cells and drugs. When integrating both genomic resources and compound information, the prediction coverage was significantly increased. The validity of PDRCC was also supported by its effective in uncovering the unknown cell-drug associations with database and literature evidences. It set the stage for clinical testing of novel therapeutic strategies, such as the sensitive association between cancer cell ‘A549_LUNG’ and compound ‘Topotecan’. In conclusion, PDRCC offers the possibility for faster, safer, and cheaper the development of novel anti-cancer therapeutics in the early-stage clinical trails.

Inferences of drug responses in cancer cells from cancer genomic features and compound chemical and therapeutic properties.

PubMed

Wang, Yongcui; Fang, Jianwen; Chen, Shilong

2016-09-20

Accurately predicting the response of a cancer patient to a therapeutic agent is a core goal of precision medicine. Existing approaches were mainly relied primarily on genomic alterations in cancer cells that have been treated with different drugs. Here we focus on predicting drug response based on integration of the heterogeneously pharmacogenomics data from both cell and drug sides. Through a systematical approach, named as PDRCC (Predict Drug Response in Cancer Cells), the cancer genomic alterations and compound chemical and therapeutic properties were incorporated to determine the chemotherapeutic response in cancer patients. Using the Cancer Cell Line Encyclopedia (CCLE) study as the benchmark dataset, all pharmacogenomics data exhibited their roles in inferring the relationships between cancer cells and drugs. When integrating both genomic resources and compound information, the prediction coverage was significantly increased. The validity of PDRCC was also supported by its effective in uncovering the unknown cell-drug associations with database and literature evidences. It set the stage for clinical testing of novel therapeutic strategies, such as the sensitive association between cancer cell 'A549_LUNG' and compound 'Topotecan'. In conclusion, PDRCC offers the possibility for faster, safer, and cheaper the development of novel anti-cancer therapeutics in the early-stage clinical trails.

Designing Safer Analgesics via μ-Opioid Receptor Pathways.

PubMed

Chan, H C Stephen; McCarthy, Dillon; Li, Jianing; Palczewski, Krzysztof; Yuan, Shuguang

2017-11-01

Pain is both a major clinical and economic problem, affecting more people than diabetes, heart disease, and cancer combined. While a variety of prescribed or over-the-counter (OTC) medications are available for pain management, opioid medications, especially those acting on the μ-opioid receptor (μOR) and related pathways, have proven to be the most effective, despite some serious side effects including respiration depression, pruritus, dependence, and constipation. It is therefore imperative that both academia and industry develop novel μOR analgesics which retain their opioid analgesic properties but with fewer or no adverse effects. In this review we outline recent progress towards the discovery of safer opioid analgesics. Copyright © 2017 Elsevier Ltd. All rights reserved.

Designing Safer Analgesics via μ-Opioid Receptor Pathways

PubMed Central

Chan, H.C. Stephen; McCarthy, Dillon; Li, Jianing; Palczewski, Krzysztof; Yuan, Shuguang

2017-01-01

Pain is both a major clinical and economic problem, affecting more people than diabetes, heart disease, and cancer combined. While a variety of prescribed or over-the-counter (OTC) medications are available for pain management, opioid medications, especially those acting on the μ-opioid receptor (μOR) and related pathways, have proven to be the most effective, despite some serious side effects including respiration depression, pruritus, dependence, and constipation. It is therefore imperative that both academia and industry develop novel μOR analgesics which retain their opioid analgesic properties but with fewer or no adverse effects. In this review we outline recent progress towards the discovery of safer opioid analgesics. PMID:28935293

Prediction of cancer cell sensitivity to natural products based on genomic and chemical properties.

PubMed

Yue, Zhenyu; Zhang, Wenna; Lu, Yongming; Yang, Qiaoyue; Ding, Qiuying; Xia, Junfeng; Chen, Yan

2015-01-01

Natural products play a significant role in cancer chemotherapy. They are likely to provide many lead structures, which can be used as templates for the construction of novel drugs with enhanced antitumor activity. Traditional research approaches studied structure-activity relationship of natural products and obtained key structural properties, such as chemical bond or group, with the purpose of ascertaining their effect on a single cell line or a single tissue type. Here, for the first time, we develop a machine learning method to comprehensively predict natural products responses against a panel of cancer cell lines based on both the gene expression and the chemical properties of natural products. The results on two datasets, training set and independent test set, show that this proposed method yields significantly better prediction accuracy. In addition, we also demonstrate the predictive power of our proposed method by modeling the cancer cell sensitivity to two natural products, Curcumin and Resveratrol, which indicate that our method can effectively predict the response of cancer cell lines to these two natural products. Taken together, the method will facilitate the identification of natural products as cancer therapies and the development of precision medicine by linking the features of patient genomes to natural product sensitivity.

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

PubMed Central

Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

2015-01-01

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using random forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers were 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the ScoreCard database of possible skin or sense organ toxicants as primary candidates for experimental validation. PMID:25560674

Predicting In Vivo Effect Levels for Repeat Dose Systemic Toxicity using Chemical, Biological, Kinetic and Study Covariates

EPA Science Inventory

In an effort to ensure chemical safety while reducing reliance on animal testing, USEPA and L’Oréal have collaborated to address a major challenge in chemical safety assessment using alternative approaches: the prediction of points-of-departure (POD) of systemic effects. Systemic...

Use of statistical and neural net approaches in predicting toxicity of chemicals.

PubMed

Basak, S C; Grunwald, G D; Gute, B D; Balasubramanian, K; Opitz, D

2000-01-01

Hierarchical quantitative structure-activity relationships (H-QSAR) have been developed as a new approach in constructing models for estimating physicochemical, biomedicinal, and toxicological properties of interest. This approach uses increasingly more complex molecular descriptors in a graduated approach to model building. In this study, statistical and neural network methods have been applied to the development of H-QSAR models for estimating the acute aquatic toxicity (LC50) of 69 benzene derivatives to Pimephales promelas (fathead minnow). Topostructural, topochemical, geometrical, and quantum chemical indices were used as the four levels of the hierarchical method. It is clear from both the statistical and neural network models that topostructural indices alone cannot adequately model this set of congeneric chemicals. Not surprisingly, topochemical indices greatly increase the predictive power of both statistical and neural network models. Quantum chemical indices also add significantly to the modeling of this set of acute aquatic toxicity data.

Applications of integrated human error identification techniques on the chemical cylinder change task.

PubMed

Cheng, Ching-Min; Hwang, Sheue-Ling

2015-03-01

This paper outlines the human error identification (HEI) techniques that currently exist to assess latent human errors. Many formal error identification techniques have existed for years, but few have been validated to cover latent human error analysis in different domains. This study considers many possible error modes and influential factors, including external error modes, internal error modes, psychological error mechanisms, and performance shaping factors, and integrates several execution procedures and frameworks of HEI techniques. The case study in this research was the operational process of changing chemical cylinders in a factory. In addition, the integrated HEI method was used to assess the operational processes and the system's reliability. It was concluded that the integrated method is a valuable aid to develop much safer operational processes and can be used to predict human error rates on critical tasks in the plant. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

HIV-Positive Mothers' Communication about Safer Sex and Std Prevention with Their Children

ERIC Educational Resources Information Center

Murphy, Debra A.; Roberts, Kathleen Johnston; Herbeck, Diane M.

2012-01-01

Mothers play an important role in promoting the sexual health of their adolescent children. Fifty-seven HIV-positive mothers with adolescent children participated in an in-depth, qualitative interview regarding whether they have talked to their children about safer sex and sexually transmitted disease (STD) prevention, including at what age they…

Are Schools Making the Grade? School Districts Nationwide Adopt Safer Pest Management Policies.

ERIC Educational Resources Information Center

Piper, Cortney; Owens, Kagan

2002-01-01

This report documents school districts that have adopted safer pest management policies, such as integrated pest management (IPM), in response to state requirements or as a voluntary measure that exceeds state law. It also documents the state of local school pest management policies and illustrates the opportunities that exist for better…

Predictive Models and Tools for Assessing Chemicals under the Toxic Substances Control Act (TSCA)

EPA Pesticide Factsheets

EPA has developed databases and predictive models to help evaluate the hazard, exposure, and risk of chemicals released to the environment and how workers, the general public, and the environment may be exposed to and affected by them.

Prediction of aged red wine aroma properties from aroma chemical composition. Partial least squares regression models.

PubMed

Aznar, Margarita; López, Ricardo; Cacho, Juan; Ferreira, Vicente

2003-04-23

Partial least squares regression (PLSR) models able to predict some of the wine aroma nuances from its chemical composition have been developed. The aromatic sensory characteristics of 57 Spanish aged red wines were determined by 51 experts from the wine industry. The individual descriptions given by the experts were recorded, and the frequency with which a sensory term was used to define a given wine was taken as a measurement of its intensity. The aromatic chemical composition of the wines was determined by already published gas chromatography (GC)-flame ionization detector and GC-mass spectrometry methods. In the whole, 69 odorants were analyzed. Both matrixes, the sensory and chemical data, were simplified by grouping and rearranging correlated sensory terms or chemical compounds and by the exclusion of secondary aroma terms or of weak aroma chemicals. Finally, models were developed for 18 sensory terms and 27 chemicals or groups of chemicals. Satisfactory models, explaining more than 45% of the original variance, could be found for nine of the most important sensory terms (wood-vanillin-cinnamon, animal-leather-phenolic, toasted-coffee, old wood-reduction, vegetal-pepper, raisin-flowery, sweet-candy-cacao, fruity, and berry fruit). For this set of terms, the correlation coefficients between the measured and predicted Y (determined by cross-validation) ranged from 0.62 to 0.81. Models confirmed the existence of complex multivariate relationships between chemicals and odors. In general, pleasant descriptors were positively correlated to chemicals with pleasant aroma, such as vanillin, beta damascenone, or (E)-beta-methyl-gamma-octalactone, and negatively correlated to compounds showing less favorable odor properties, such as 4-ethyl and vinyl phenols, 3-(methylthio)-1-propanol, or phenylacetaldehyde.

Measurement Noninvariance of Safer Sex Self-Efficacy Between Heterosexual and Sexual Minority Black Youth.

PubMed

Gerke, Donald; Budd, Elizabeth L; Plax, Kathryn

2016-01-01

Black and lesbian, gay, bisexual, or questioning (LGBQ) youth in the United States are disproportionately affected by HIV and other sexually transmitted diseases (STDs). Although self-efficacy is strongly, positively associated with safer sex behaviors, no studies have examined the validity of a safer sex self-efficacy scale used by many federally funded HIV/STD prevention programs. This study aims to test factor validity of the Sexual Self-Efficacy Scale by using confirmatory factor analysis (CFA) to determine if scale validity varies between heterosexual and LGBQ Black youth. The study uses cross-sectional data collected through baseline surveys with 226 Black youth (15 to 24 years) enrolled in community-based HIV-prevention programs. Participants use a 4-point Likert-type scale to report their confidence in performing 6 healthy sexual behaviors. CFAs are conducted on 2 factor structures of the scale. Using the best-fitting model, the scale is tested for measurement invariance between the 2 groups. A single-factor model with correlated errors of condom-specific items fits the sample well and, when tested with the heterosexual group, the model demonstrates good fit. However, when tested with the LGBQ group, the same model yields poor fit, indicating factorial noninvariance between the groups. The Sexual Self-Efficacy Scale does not perform equally well among Black heterosexual and LGBQ youth. Study findings suggest additional research is needed to inform development of measures for safer sex self-efficacy among Black LGBQ youth to ensure validity of conceptual understanding and to accurately assess effectiveness of HIV/STD prevention interventions among this population.

Assessment of Fecal Near-infrared Spectroscopy to Predict Feces Chemical Composition and Apparent Total Tract Digestibility of Nutrients in Pigs.

PubMed

Nirea, K G; Pérez de Nanclares, M; Skugor, A; Afseth, N K; Meuwissen, T H E; Hansen, J Ø; Mydland, L T; Øverland, M

2018-05-08

Apparent total tract digestibility (ATTD) of nutrients could be an alternative measure of feed efficiency when breeding for robust animals that are fed fiber-rich diets. Apparent total tract digestibility of nutrients requires measuring individual feed intake of a large number of animals which is expensive and complex. Alternatively, ATTD of nutrients and feces chemical composition can be predicted using fecal near-infrared spectroscopy (FNIRS). The objective of this study was to assess if the feces chemical composition and ATTD of nutrients can be predicted using FNIRS that originate from various pig experimental datasets. Fecal samples together with detailed information on the feces chemical composition and ATTD of nutrients were obtained from four different pig experiments. Feces near-infrared spectroscopy were analyzed from fecal samples of a complete dataset. The model was calibrated using the FNIRS and reference samples of feces chemical composition and ATTD of nutrients. The robustness and predictability of the model was evaluated by the r2 and the closeness between SE of calibration (SEC) and SE of cross-validation (SECV). Prediction of the feces chemical components and ATTD of nutrients was successful as SEC and SECV were equivalent. Calibration model was developed to estimate the ATTD of nutrients and fecal chemical composition from the FNIRS and worked well for OM (r2 = 0.94; SEC = 48.5; SECV = 56.6), CP ( r2 = 0.89; SEC = 18.1; SECV = 18.8), GE ( r2 = 0.92; SEC = 1.2; SECV = 1.4), NDF (r2 = 0.94 ; SEC = 55; SECV = 60.2), OM digestibility (r2 = 0.94; SEC = 5.5; SECV = 6.7), GE digestibility (r2 = 0.88; SEC = 2.3; SECV = 2.6) and fat digestibility (r2 = 0.79 ; SEC = 6, SECV = 6.8). However, the SE of prediction was slightly higher than what has been reported in another study. The prediction of feces chemical composition for fat (r2 = 0.69; SEC = 11.7, SECV = 12.3), CP digestibility (r2 = 0.63; SEC = 2.3; SECV = 2.7) and NDF digestibility (r2 = 0.64, SEC

HIV knowledge, risk perception, and safer sex practices among female sex workers in Port Moresby, Papua New Guinea

PubMed Central

Bruce, Eunice; Bauai, Ludwina; Sapuri, Mathias; Kaldor, John M; Fairley, Christopher K; Keogh, Louise A

2011-01-01

Sex workers are considered a high-risk group for sexually transmitted infections, including human immunodeficiency virus (HIV), and are often targeted by prevention interventions with safer sex messages. The purpose of this study was to explore the extent to which knowledge of HIV and perception of risk influence safer sex practices among female sex workers (FSWs) in Port Moresby, Papua New Guinea. FSWs (n = 174) were recruited from 19 sites to participate in the study. Qualitative data were collected using semistructured interviews with FSWs (n = 142) through focus group discussions and (n = 32) individual interviews. In addition, quantitative data were collected from all FSWs using a short structured, demographic questionnaire. Data were analyzed using recurring themes and calculations of confidence intervals. Despite some common misperceptions, overall, most FSWs were basically aware of the risks of HIV and informed about transmission and prevention modalities but used condoms inconsistently. Most reported using condoms ‘sometimes’, almost one-sixth ‘never’ used condoms, only a fraction used condoms ‘always’ with clients, and none used condoms ‘always’ with regular sexual partners (RSPs). Among these FSWs, being knowledgeable about the risks, transmission, and prevention of HIV did not translate into safe sex. The findings suggest that certain contextual barriers to safer sex practices exist. These barriers could heighten HIV vulnerability and possibly may be responsible for infection in FSWs. Specific interventions that focus on improving condom self-efficacy in FSWs and simultaneously target clients and RSPs with safer sex messages are recommended. PMID:21445375

A Novel Two-Step Hierarchical Quantitative Structure–Activity Relationship Modeling Work Flow for Predicting Acute Toxicity of Chemicals in Rodents

PubMed Central

Zhu, Hao; Ye, Lin; Richard, Ann; Golbraikh, Alexander; Wright, Fred A.; Rusyn, Ivan; Tropsha, Alexander

2009-01-01

Background Accurate prediction of in vivo toxicity from in vitro testing is a challenging problem. Large public–private consortia have been formed with the goal of improving chemical safety assessment by the means of high-throughput screening. Objective A wealth of available biological data requires new computational approaches to link chemical structure, in vitro data, and potential adverse health effects. Methods and results A database containing experimental cytotoxicity values for in vitro half-maximal inhibitory concentration (IC50) and in vivo rodent median lethal dose (LD50) for more than 300 chemicals was compiled by Zentralstelle zur Erfassung und Bewertung von Ersatz- und Ergaenzungsmethoden zum Tierversuch (ZEBET; National Center for Documentation and Evaluation of Alternative Methods to Animal Experiments). The application of conventional quantitative structure–activity relationship (QSAR) modeling approaches to predict mouse or rat acute LD50 values from chemical descriptors of ZEBET compounds yielded no statistically significant models. The analysis of these data showed no significant correlation between IC50 and LD50. However, a linear IC50 versus LD50 correlation could be established for a fraction of compounds. To capitalize on this observation, we developed a novel two-step modeling approach as follows. First, all chemicals are partitioned into two groups based on the relationship between IC50 and LD50 values: One group comprises compounds with linear IC50 versus LD50 relationships, and another group comprises the remaining compounds. Second, we built conventional binary classification QSAR models to predict the group affiliation based on chemical descriptors only. Third, we developed k-nearest neighbor continuous QSAR models for each subclass to predict LD50 values from chemical descriptors. All models were extensively validated using special protocols. Conclusions The novelty of this modeling approach is that it uses the relationships

A novel two-step hierarchical quantitative structure-activity relationship modeling work flow for predicting acute toxicity of chemicals in rodents.

PubMed

Zhu, Hao; Ye, Lin; Richard, Ann; Golbraikh, Alexander; Wright, Fred A; Rusyn, Ivan; Tropsha, Alexander

2009-08-01

Accurate prediction of in vivo toxicity from in vitro testing is a challenging problem. Large public-private consortia have been formed with the goal of improving chemical safety assessment by the means of high-throughput screening. A wealth of available biological data requires new computational approaches to link chemical structure, in vitro data, and potential adverse health effects. A database containing experimental cytotoxicity values for in vitro half-maximal inhibitory concentration (IC(50)) and in vivo rodent median lethal dose (LD(50)) for more than 300 chemicals was compiled by Zentralstelle zur Erfassung und Bewertung von Ersatz- und Ergaenzungsmethoden zum Tierversuch (ZEBET; National Center for Documentation and Evaluation of Alternative Methods to Animal Experiments). The application of conventional quantitative structure-activity relationship (QSAR) modeling approaches to predict mouse or rat acute LD(50) values from chemical descriptors of ZEBET compounds yielded no statistically significant models. The analysis of these data showed no significant correlation between IC(50) and LD(50). However, a linear IC(50) versus LD(50) correlation could be established for a fraction of compounds. To capitalize on this observation, we developed a novel two-step modeling approach as follows. First, all chemicals are partitioned into two groups based on the relationship between IC(50) and LD(50) values: One group comprises compounds with linear IC(50) versus LD(50) relationships, and another group comprises the remaining compounds. Second, we built conventional binary classification QSAR models to predict the group affiliation based on chemical descriptors only. Third, we developed k-nearest neighbor continuous QSAR models for each subclass to predict LD(50) values from chemical descriptors. All models were extensively validated using special protocols. The novelty of this modeling approach is that it uses the relationships between in vivo and in vitro data only

[Improvement and prediction of intestinal drug absorption].

PubMed

Miyake, Masateru

2013-01-01

The suppository preparation, which can improve the absorption of poorly absorbable drugs safer than commercially available suppositories, was developed by utilizing sodium laurate and taurine. Additionally, the novel oral absorption-improving system was also established by utilizing polyamines and bile acids. Furthermore, to evaluate the efficacy of these new formulations and estimate the absorbability of new drug candidates in humans, the in vitro prediction system utilizing an isolated human intestinal tissues was developed and successfully predicted the fraction of dose absorbed for several model drugs. These findings would contribute to the development of new dosage forms and new drugs for oral administration.

ADMET Evaluation in Drug Discovery. 18. Reliable Prediction of Chemical-Induced Urinary Tract Toxicity by Boosting Machine Learning Approaches.

PubMed

Lei, Tailong; Sun, Huiyong; Kang, Yu; Zhu, Feng; Liu, Hui; Zhou, Wenfang; Wang, Zhe; Li, Dan; Li, Youyong; Hou, Tingjun

2017-11-06

Xenobiotic chemicals and their metabolites are mainly excreted out of our bodies by the urinary tract through the urine. Chemical-induced urinary tract toxicity is one of the main reasons that cause failure during drug development, and it is a common adverse event for medications, natural supplements, and environmental chemicals. Despite its importance, there are only a few in silico models for assessing urinary tract toxicity for a large number of compounds with diverse chemical structures. Here, we developed a series of qualitative and quantitative structure-activity relationship (QSAR) models for predicting urinary tract toxicity. In our study, the recursive feature elimination method incorporated with random forests (RFE-RF) was used for dimension reduction, and then eight machine learning approaches were used for QSAR modeling, i.e., relevance vector machine (RVM), support vector machine (SVM), regularized random forest (RRF), C5.0 trees, eXtreme gradient boosting (XGBoost), AdaBoost.M1, SVM boosting (SVMBoost), and RVM boosting (RVMBoost). For building classification models, the synthetic minority oversampling technique was used to handle the imbalance data set problem. Among all the machine learning approaches, SVMBoost based on the RBF kernel achieves both the best quantitative (q ext 2 = 0.845) and qualitative predictions for the test set (MCC of 0.787, AUC of 0.893, sensitivity of 89.6%, specificity of 94.1%, and global accuracy of 90.8%). The application domains were then analyzed, and all of the tested chemicals fall within the application domain coverage. We also examined the structure features of the chemicals with large prediction errors. In brief, both the regression and classification models developed by the SVMBoost approach have reliable prediction capability for assessing chemical-induced urinary tract toxicity.

Guidance Notes on Safer School Construction: Global Facility for Disaster Reduction and Recovery

ERIC Educational Resources Information Center

World Bank Publications, 2009

2009-01-01

This document provides a framework of guiding principles and general steps addressing the construction of safer and more disaster resilient education facilities. It is aimed to be adapted to the local context and used to develop a context-specific plan to address a critical gap to reaching the Education for All (EFA) and Millennium Development…

A Safer and Convenient Synthesis of Sulfathiazole for Undergraduate Organic and Medicinal Chemistry Classes

ERIC Educational Resources Information Center

Boyle, Jeff; Otty, Sandra; Sarojini, Vijayalekshmi

2012-01-01

A safer method for the synthesis of the sulfonamide drug sulfathiazole, for undergraduate classes, is described. This method improves upon procedures currently followed in several undergraduate teaching laboratories for the synthesis of sulfathiazole. Key features of this procedure include the total exclusion of pyridine, which has potential…

Summary of findings from the evaluation of a pilot medically supervised safer injecting facility

PubMed Central

Wood, Evan; Tyndall, Mark W.; Montaner, Julio S.; Kerr, Thomas

2006-01-01

In many cities, infectious disease and overdose epidemics are occurring among illicit injection drug users (IDUs). To reduce these concerns, Vancouver opened a supervised safer injecting facility in September 2003. Within the facility, people inject pre-obtained illicit drugs under the supervision of medical staff. The program was granted a legal exemption by the Canadian government on the condition that a 3-year scientific evaluation of its impacts be conducted. In this review, we summarize the findings from evaluations in those 3 years, including characteristics of IDUs at the facility, public injection drug use and publicly discarded syringes, HIV risk behaviour, use of addiction treatment services and other community resources, and drug-related crime rates. Vancouver's safer injecting facility has been associated with an array of community and public health benefits without evidence of adverse impacts. These findings should be useful to other cities considering supervised injecting facilities and to governments considering regulating their use. PMID:17116909

3D flexible alignment using 2D maximum common substructure: dependence of prediction accuracy on target-reference chemical similarity.

PubMed

Kawabata, Takeshi; Nakamura, Haruki

2014-07-28

A protein-bound conformation of a target molecule can be predicted by aligning the target molecule on the reference molecule obtained from the 3D structure of the compound-protein complex. This strategy is called "similarity-based docking". For this purpose, we develop the flexible alignment program fkcombu, which aligns the target molecule based on atomic correspondences with the reference molecule. The correspondences are obtained by the maximum common substructure (MCS) of 2D chemical structures, using our program kcombu. The prediction performance was evaluated using many target-reference pairs of superimposed ligand 3D structures on the same protein in the PDB, with different ranges of chemical similarity. The details of atomic correspondence largely affected the prediction success. We found that topologically constrained disconnected MCS (TD-MCS) with the simple element-based atomic classification provides the best prediction. The crashing potential energy with the receptor protein improved the performance. We also found that the RMSD between the predicted and correct target conformations significantly correlates with the chemical similarities between target-reference molecules. Generally speaking, if the reference and target compounds have more than 70% chemical similarity, then the average RMSD of 3D conformations is <2.0 Å. We compared the performance with a rigid-body molecular alignment program based on volume-overlap scores (ShaEP). Our MCS-based flexible alignment program performed better than the rigid-body alignment program, especially when the target and reference molecules were sufficiently similar.

Safer Electrolytes for Lithium-Ion Cells

NASA Technical Reports Server (NTRS)

Kejha, Joe; Smith, Novis; McCloseky, Joel

2004-01-01

A number of nonvolatile, low-flammability liquid oligomers and polymers based on aliphatic organic carbonate molecular structures have been found to be suitable to be blended with ethylene carbonate to make electrolytes for lithium-ion electrochemical cells. Heretofore, such electrolytes have often been made by blending ethylene carbonate with volatile, flammable organic carbonates. The present nonvolatile electrolytes have been found to have adequate conductivity (about 2 mS/cm) for lithium ions and to remain liquid at temperatures down to -5 C. At normal charge and discharge rates, lithiumion cells containing these nonvolatile electrolytes but otherwise of standard design have been found to operate at current and energy densities comparable to those of cells now in common use. They do not perform well at high charge and discharge rates -- an effect probably attributable to electrolyte viscosity. Cells containing the nonvolatile electrolytes have also been found to be, variously, nonflammable or at least self-extinguishing. Hence, there appears to be a basis for the development of safer high-performance lithium-ion cells.

Ecological Models to Predict and Test the Effects of Chemical Stressors: Integration across 2 EPA STAR cooperative agreements

EPA Science Inventory

Accessible tools to quantify adverse outcomes pathways (AOPs) that can predict the ecological effects of chemicals and other stressors are a major goal of Chemical Safety and Sustainability research within US EPA’s Office of Research and Development. To address this goal, w...

Can Computer-Mediated Interventions Change Theoretical Mediators of Safer Sex? A Meta-Analysis

ERIC Educational Resources Information Center

Noar, Seth M.; Pierce, Larson B.; Black, Hulda G.

2010-01-01

The purpose of this study was to conduct a meta-analysis of computer-mediated interventions (CMIs) aimed at changing theoretical mediators of safer sex. Meta-analytic aggregation of effect sizes from k = 20 studies indicated that CMIs significantly improved HIV/AIDS knowledge, d = 0.276, p less than 0.001, k = 15, N = 6,625; sexual/condom…

Seriously Mentally Ill Women's Safer Sex Behaviors and the Theory of Reasoned Action

ERIC Educational Resources Information Center

Randolph, Mary E.; Pinkerton, Steven D.; Somlai, Anton M.; Kelly, Jeffrey A.; McAuliffe, Timothy L.; Gibson, Richard H.; Hackl, Kristin

2009-01-01

Seriously mentally ill women at risk for HIV infection (n = 96) participated in structured interviews assessing sexual and substance-use behavior over a 3-month period. The majority of the women (63.5%) did not use condoms. Consistent with the theory of reasoned action, attitudes toward condom use and perceived social norms about safer sex were…

Development of a category approach to predict the testicular toxicity of chemical substances structurally related to ethylene glycol methyl ether.

PubMed

Yamada, Takashi; Tanaka, Yushiro; Hasegawa, Ryuichi; Sakuratani, Yuki; Yamazoe, Yasushi; Ono, Atsushi; Hirose, Akihiko; Hayashi, Makoto

2014-12-01

We propose a category approach to assessing the testicular toxicity of chemicals with a similar structure to ethylene glycol methyl ether (EGME). Based on toxicity information for EGME and related chemicals and accompanied by adverse outcome pathway information on the testicular toxicity of EGME, this category was defined as chemicals that are metabolized to methoxy- or ethoxyacetic acid, a substance responsible for testicular toxicity. A Japanese chemical inventory was screened using the Hazard Evaluation Support System, which we have developed to support a category approach for predicting the repeated-dose toxicity of chemical substances. Quantitative metabolic information on the related chemicals was then considered, and seventeen chemicals were finally obtained from the inventory as a shortlist for the category. Available data in the literature shows that chemicals for which information is available on the metabolic formation of EGME, ethylene glycol ethyl ether, methoxy- or ethoxyacetic acid do in fact possess testicular toxicity, suggesting that testicular toxicity is a concern, due to metabolic activation, for the remaining chemicals. Our results clearly demonstrate practical utility of AOP-based category approach for predicting repeated-dose toxicity of chemicals. Copyright © 2014 Elsevier Inc. All rights reserved.

Using different assumptions of aerosol mixing state and chemical composition to predict CCN concentrations based on field measurements in urban Beijing

NASA Astrophysics Data System (ADS)

Ren, Jingye; Zhang, Fang; Wang, Yuying; Collins, Don; Fan, Xinxin; Jin, Xiaoai; Xu, Weiqi; Sun, Yele; Cribb, Maureen; Li, Zhanqing

2018-05-01

Understanding the impacts of aerosol chemical composition and mixing state on cloud condensation nuclei (CCN) activity in polluted areas is crucial for accurately predicting CCN number concentrations (NCCN). In this study, we predict NCCN under five assumed schemes of aerosol chemical composition and mixing state based on field measurements in Beijing during the winter of 2016. Our results show that the best closure is achieved with the assumption of size dependent chemical composition for which sulfate, nitrate, secondary organic aerosols, and aged black carbon are internally mixed with each other but externally mixed with primary organic aerosol and fresh black carbon (external-internal size-resolved, abbreviated as EI-SR scheme). The resulting ratios of predicted-to-measured NCCN (RCCN_p/m) were 0.90 - 0.98 under both clean and polluted conditions. Assumption of an internal mixture and bulk chemical composition (INT-BK scheme) shows good closure with RCCN_p/m of 1.0 -1.16 under clean conditions, implying that it is adequate for CCN prediction in continental clean regions. On polluted days, assuming the aerosol is internally mixed and has a chemical composition that is size dependent (INT-SR scheme) achieves better closure than the INT-BK scheme due to the heterogeneity and variation in particle composition at different sizes. The improved closure achieved using the EI-SR and INT-SR assumptions highlight the importance of measuring size-resolved chemical composition for CCN predictions in polluted regions. NCCN is significantly underestimated (with RCCN_p/m of 0.66 - 0.75) when using the schemes of external mixtures with bulk (EXT-BK scheme) or size-resolved composition (EXT-SR scheme), implying that primary particles experience rapid aging and physical mixing processes in urban Beijing. However, our results show that the aerosol mixing state plays a minor role in CCN prediction when the κorg exceeds 0.1.

Alternatives Assessment Frameworks: Research Needs for the Informed Substitution of Hazardous Chemicals

PubMed Central

Jacobs, Molly M.; Malloy, Timothy F.; Tickner, Joel A.; Edwards, Sally

2015-01-01

Background Given increasing pressures for hazardous chemical replacement, there is growing interest in alternatives assessment to avoid substituting a toxic chemical with another of equal or greater concern. Alternatives assessment is a process for identifying, comparing, and selecting safer alternatives to chemicals of concern (including those used in materials, processes, or technologies) on the basis of their hazards, performance, and economic viability. Objectives The purposes of this substantive review of alternatives assessment frameworks are to identify consistencies and differences in methods and to outline needs for research and collaboration to advance science policy practice. Methods This review compares methods used in six core components of these frameworks: hazard assessment, exposure characterization, life-cycle impacts, technical feasibility evaluation, economic feasibility assessment, and decision making. Alternatives assessment frameworks published from 1990 to 2014 were included. Results Twenty frameworks were reviewed. The frameworks were consistent in terms of general process steps, but some differences were identified in the end points addressed. Methodological gaps were identified in the exposure characterization, life-cycle assessment, and decision–analysis components. Methods for addressing data gaps remain an issue. Discussion Greater consistency in methods and evaluation metrics is needed but with sufficient flexibility to allow the process to be adapted to different decision contexts. Conclusion Although alternatives assessment is becoming an important science policy field, there is a need for increased cross-disciplinary collaboration to refine methodologies in support of the informed substitution and design of safer chemicals, materials, and products. Case studies can provide concrete lessons to improve alternatives assessment. Citation Jacobs MM, Malloy TF, Tickner JA, Edwards S. 2016. Alternatives assessment frameworks: research

Promoting safer sexual practices among young adults: a survey of health workers in Moshi Rural District, Tanzania.

PubMed

Ngomuo, E T; Klepp, K I; Rise, J; Mnyika, K S

1995-01-01

As part of the national effort to prevent further spread of HIV/AIDS, rural health workers in Tanzania are asked to promote safer sex practices among the sexually active population. We conducted a survey among health workers in Moshi Rural District, Kilimanjaro, designed to assess their attitudes, perceived norms and self-efficacy with respect to the promotion of safer sexual practices among young adults 15-35 years old. Health workers at all private and governmental health facilities were included (n = 342; participation rate of 68.4%). We observed relatively strong associations between the frequency and quality of reported counselling behaviour and perceived norms, attitudes and self-efficacy (standardized regression coefficients (beta) of 0.329, 0.252 and 0.159 respectively). In addition, exposure to behaviour change strategies during formal training and marital status of the health workers were associated with counselling behaviour (beta of 0.133 and 0.118 respectively). Overall, these factors accounted for 40.8% of the observed variance in reported counselling behaviour. It is recommended that continued education for health workers focus on providing normative support for promoting safer sex, provide information which may help foster positive attitudes and teach practical counselling skills to further increase the self-efficacy regarding counselling young people.

Midlife safer sex challenges for heterosexual New Zealand women re-partnering or in casual relationships.

PubMed

Morison, Trish; Cook, Catherine M

2015-06-01

The rate of sexually transmitted infections (STIs) amongst midlife and older heterosexual women in New Zealand is rising. Popular culture celebrates a heightened sexuality for this population group. However, depictions of sexually savvy 'cougars' are at odds with reality for many women. International literature highlights that these women are often ill-equipped to negotiate safer sex and condom use, instead focusing on pleasing men and attributing their silence to spontaneity. The study aimed to explore barriers to safer heterosexual sex as perceived by midlife and older New Zealand women who are re-partnering or in casual relationships. This qualitative study utilised Interpretive Phenomenology Analysis, supported by the theory of gender and power, to examine the gender-normative assumptions and behaviours in women's accounts of unprotected sex. Eight single women aged 40-69 participated in individual, in-depth interviews. This exploration included eliciting women's accounts of potential information resources, such as clinical consultations. Analysis indicated that these women held misconceptions about STI transmission but had not sought educational material, nor discussed their sexual health with health professionals. Results highlighted women's ambivalence about prioritising safer sex, preferring to comply with partners' wishes, particularly when under the influence of alcohol. Women described valuing their own pleasure and their distaste for condom use, but data emphasised that women predominantly aligned their choices with men's preferences. This study highlights that the women were both ill-informed and vulnerable with regards to sexual health. General practitioners are well placed to provide education and sexual health advice.

NREL Blows Up Batteries to Make the World Safer

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

Making lithium-ion batteries safer for earthlings and astronauts is something NREL excels at. In this video you’ll meet Matt Keyser, a senior energy storage engineer who is on a mission to improve the thermal performance of batteries for electric vehicles, consumer gadgets, and technology used by NASA in outer space. Matt and his team study battery failure using innovative technologies, such as the award-winning Battery Internal Short Circuit (ISC) Device that can precisely identify weak spots in battery cells. This cutting-edge research helps battery manufacturers develop advanced materials that can deliver superior results. Who benefits from all of this ingenuitymore » rooted in fundamental science? We all do!« less

Reality and responsibility revisited: Stakeholder accountability in the effort to develop safer opioids.

PubMed

Passik, Steven D; Heit, Howard A; DeGeorge, Michael

This supplement is dedicated to an exploration of the science, potential utility, and the current state of abuse-deterrent formulations (ADF) of opioid analgesics. There are many stakeholders in the search for safer pain treatments in general, and safer opioid therapy in particular. Healthcare providers, patients, third-party payors, law enforcement and government regulators, the pharmaceutical industry, and the media all have a stake in seeing pain treated and addiction and overdose avoided. As it applies to ADFs, obviously not everyone has a stake in seeing that ADFs succeed commercially; but all stakeholders certainly have a responsibility to see that any potential advance, including ADFs, in protecting the public health is fairly and thoroughly evaluated. Particularly at a time of crisis. In this article, we revisit the framework used by Passik, Heit, and Kirsh (2006) to evaluate stakeholders' responsibilities with regard to both the opioid abuse and chronic pain epidemics. After evaluating the present status of aspirations delineated over a decade ago, we discuss the updated roles and responsibilities of each stakeholder, with emphasis on the role of ADFs as this technology was unavailable when the original manuscript was written.

Understanding the resistance to creating safer ice hockey: essential points for injury prevention.

PubMed

Todd, Ryan A; Soklaridis, Sophie; Treen, Alice K; Bhalerao, Shree U; Cusimano, Michael D

2017-11-27

Despite the known negative health outcomes of concussions in minor level boys' hockey, there has been significant resistance to creating a safer game with less body checking. To better understand cultural barriers that prevent making the sport safer for youth and adolescents, semistructured interviews, with 20 ice hockey stakeholders, were conducted and analysed using thematic analysis. Through this analysis, two primary concepts arose from respondents. The first concept is that body checking, despite the harm it can cause, should be done in a respectful sportsmanlike fashion. The second concept is the contradiction that the game of ice hockey is both dynamic and unchangeable. Using structural functionalist theory, we propose an argument that the unfortunate perpetuation of violence and body checking in youth ice hockey serves to maintain the social order of the game and its culture. Any strategies aimed at modifying and promoting healthy behaviour in the game should take these concepts into account. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Computational Prediction and Validation of an Expert's Evaluation of Chemical Probes

PubMed Central

Litterman, Nadia K.; Lipinski, Christopher A.; Bunin, Barry A.; Ekins, Sean

2016-01-01

In a decade with over half a billion dollars of investment, more than 300 chemical probes have been identified to have biological activity through NIH funded screening efforts. We have collected the evaluations of an experienced medicinal chemist on the likely chemistry quality of these probes based on a number of criteria including literature related to the probe and potential chemical reactivity. Over 20% of these probes were found to be undesirable. Analysis of the molecular properties of these compounds scored as desirable suggested higher pKa, molecular weight, heavy atom count and rotatable bond number. We were particularly interested whether the human evaluation aspect of medicinal chemistry due diligence could be computationally predicted. We used a process of sequential Bayesian model building and iterative testing as we included additional probes. Following external validation of these methods and comparing different machine learning methods we identified Bayesian models with accuracy comparable to other measures of drug-likeness and filtering rules created to date. PMID:25244007

Effects of a Televised Two-City Safer Sex Mass Media Campaign Targeting High-Sensation-Seeking and Impulsive-Decision-Making Young Adults

PubMed Central

Zimmerman, Rick S.; Palmgreen, Philip M.; Noar, Seth M.; Lustria, Mia Liza A.; Lu, Hung-Yi; Horosewski, Mary Lee

2015-01-01

This study evaluates the ability of a safer sex televised public service announcement (PSA) campaign to increase safer sexual behavior among at-risk young adults. Independent, monthly random samples of 100 individuals were surveyed in each city for 21 months as part of an interrupted-time-series design with a control community. The 3-month high-audience-saturation campaign took place in Lexington, KY, with Knoxville, TN, as a comparison city. Messages were especially designed and selected for the target audience (those above the median on a composite sensation-seeking/impulsive-decision-making scale). Data indicate high campaign exposure among the target audience, with 85%–96% reporting viewing one or more PSAs. Analyses indicate significant 5-month increases in condom use, condom-use self-efficacy, and behavioral intentions among the target group in the campaign city with no changes in the comparison city. The results suggest that a carefully targeted, intensive mass media campaign using televised PSAs can change safer sexual behaviors. PMID:17602097

BitterSweetForest: A Random Forest Based Binary Classifier to Predict Bitterness and Sweetness of Chemical Compounds

PubMed Central

Banerjee, Priyanka; Preissner, Robert

2018-01-01

Taste of a chemical compound present in food stimulates us to take in nutrients and avoid poisons. However, the perception of taste greatly depends on the genetic as well as evolutionary perspectives. The aim of this work was the development and validation of a machine learning model based on molecular fingerprints to discriminate between sweet and bitter taste of molecules. BitterSweetForest is the first open access model based on KNIME workflow that provides platform for prediction of bitter and sweet taste of chemical compounds using molecular fingerprints and Random Forest based classifier. The constructed model yielded an accuracy of 95% and an AUC of 0.98 in cross-validation. In independent test set, BitterSweetForest achieved an accuracy of 96% and an AUC of 0.98 for bitter and sweet taste prediction. The constructed model was further applied to predict the bitter and sweet taste of natural compounds, approved drugs as well as on an acute toxicity compound data set. BitterSweetForest suggests 70% of the natural product space, as bitter and 10% of the natural product space as sweet with confidence score of 0.60 and above. 77% of the approved drug set was predicted as bitter and 2% as sweet with a confidence score of 0.75 and above. Similarly, 75% of the total compounds from acute oral toxicity class were predicted only as bitter with a minimum confidence score of 0.75, revealing toxic compounds are mostly bitter. Furthermore, we applied a Bayesian based feature analysis method to discriminate the most occurring chemical features between sweet and bitter compounds using the feature space of a circular fingerprint. PMID:29696137

BitterSweetForest: A random forest based binary classifier to predict bitterness and sweetness of chemical compounds

NASA Astrophysics Data System (ADS)

Banerjee, Priyanka; Preissner, Robert

2018-04-01

Taste of a chemical compounds present in food stimulates us to take in nutrients and avoid poisons. However, the perception of taste greatly depends on the genetic as well as evolutionary perspectives. The aim of this work was the development and validation of a machine learning model based on molecular fingerprints to discriminate between sweet and bitter taste of molecules. BitterSweetForest is the first open access model based on KNIME workflow that provides platform for prediction of bitter and sweet taste of chemical compounds using molecular fingerprints and Random Forest based classifier. The constructed model yielded an accuracy of 95% and an AUC of 0.98 in cross-validation. In independent test set, BitterSweetForest achieved an accuracy of 96 % and an AUC of 0.98 for bitter and sweet taste prediction. The constructed model was further applied to predict the bitter and sweet taste of natural compounds, approved drugs as well as on an acute toxicity compound data set. BitterSweetForest suggests 70% of the natural product space, as bitter and 10 % of the natural product space as sweet with confidence score of 0.60 and above. 77 % of the approved drug set was predicted as bitter and 2% as sweet with a confidence scores of 0.75 and above. Similarly, 75% of the total compounds from acute oral toxicity class were predicted only as bitter with a minimum confidence score of 0.75, revealing toxic compounds are mostly bitter. Furthermore, we applied a Bayesian based feature analysis method to discriminate the most occurring chemical features between sweet and bitter compounds from the feature space of a circular fingerprint.

Safer Conception for Couples Affected by HIV: Structural and Cultural Considerations in the Delivery of Safer Conception Care in Uganda.

PubMed

Mindry, Deborah; Wanyenze, Rhoda K; Beyeza-Kashesya, Jolly; Woldetsadik, Mahlet A; Finocchario-Kessler, Sarah; Goggin, Kathy; Wagner, Glenn

2017-08-01

In countries with high HIV prevalence and high fertility desires, the rights of HIV-affected couples to have children are a pressing issue. Conception among people living with HIV carries risks for both horizontal and vertical HIV transmission. In Uganda ~100,000 HIV-infected women become pregnant annually. Providers face a number of challenges to preventing HIV transmission, reducing unplanned pregnancies, and ensuring safer conception. We report findings from interviews with 27 HIV-affected couples (54 individuals) in Uganda. We explored key cultural and structural factors shaping couples' childbearing decisions. Our data reveal a complex intersection of gender norms, familial expectations, relationship dynamics, and HIV stigma influencing their decisions. Participants provided insights regarding provider bias, stigma, and the gendering of reproductive healthcare. To reduce horizontal transmission HIV and family planning clinics must address men's and women's concerns regarding childbearing with specific attention to cultural and structural challenges.

Mapping Proteome-Wide Interactions of Reactive Chemicals Using Chemoproteomic Platforms

PubMed Central

Counihan, Jessica L.; Ford, Breanna; Nomura, Daniel K.

2015-01-01

A large number of pharmaceuticals, endogenous metabolites, and environmental chemicals act through covalent mechanisms with protein targets. Yet, their specific interactions with the proteome still remain poorly defined for most of these reactive chemicals. Deciphering direct protein targets of reactive small-molecules is critical in understanding their biological action, off-target effects, potential toxicological liabilities, and development of safer and more selective agents. Chemoproteomic technologies have arisen as a powerful strategy that enable the assessment of proteome-wide interactions of these irreversible agents directly in complex biological systems. We review here several chemoproteomic strategies that have facilitated our understanding of specific protein interactions of irreversibly-acting pharmaceuticals, endogenous metabolites, and environmental electrophiles to reveal novel pharmacological, biological, and toxicological mechanisms. PMID:26647369

Zebrafish Whole-Adult-Organism Chemogenomics for Large-Scale Predictive and Discovery Chemical Biology

PubMed Central

Lam, Siew Hong; Mathavan, Sinnakarupan; Tong, Yan; Li, Haixia; Karuturi, R. Krishna Murthy; Wu, Yilian; Vega, Vinsensius B.; Liu, Edison T.; Gong, Zhiyuan

2008-01-01

The ability to perform large-scale, expression-based chemogenomics on whole adult organisms, as in invertebrate models (worm and fly), is highly desirable for a vertebrate model but its feasibility and potential has not been demonstrated. We performed expression-based chemogenomics on the whole adult organism of a vertebrate model, the zebrafish, and demonstrated its potential for large-scale predictive and discovery chemical biology. Focusing on two classes of compounds with wide implications to human health, polycyclic (halogenated) aromatic hydrocarbons [P(H)AHs] and estrogenic compounds (ECs), we generated robust prediction models that can discriminate compounds of the same class from those of different classes in two large independent experiments. The robust expression signatures led to the identification of biomarkers for potent aryl hydrocarbon receptor (AHR) and estrogen receptor (ER) agonists, respectively, and were validated in multiple targeted tissues. Knowledge-based data mining of human homologs of zebrafish genes revealed highly conserved chemical-induced biological responses/effects, health risks, and novel biological insights associated with AHR and ER that could be inferred to humans. Thus, our study presents an effective, high-throughput strategy of capturing molecular snapshots of chemical-induced biological states of a whole adult vertebrate that provides information on biomarkers of effects, deregulated signaling pathways, and possible affected biological functions, perturbed physiological systems, and increased health risks. These findings place zebrafish in a strategic position to bridge the wide gap between cell-based and rodent models in chemogenomics research and applications, especially in preclinical drug discovery and toxicology. PMID:18618001

Acceptability and preferences for safer conception HIV prevention strategies: a qualitative study.

PubMed

Schwartz, Sheree R; West, Nora; Phofa, Rebecca; Yende, Nompumelelo; Sanne, Ian; Bassett, Jean; Van Rie, Annelies

2016-10-01

Safer conception strategies to reduce the HIV transmission risk include antiretroviral therapy for HIV-positive partners, pre-exposure prophylaxis for HIV-negative partners, condomless sex limited to fertile periods, and home-based self-insemination. Resistance to taking treatment or cultural concerns may limit uptake of strategies and intervention success. Understanding the acceptability and preferences between different approaches is important to optimise service delivery. Between February and July 2013, 42 adults (21 HIV-positive and 21 HIV-negative) receiving primary care at Witkoppen Health and Welfare Centre in Johannesburg, South Africa, participated in focus group discussions or in-depth interviews. Themes were analysed using a grounded theory approach. Acceptability of antiretroviral-based strategies varied. Concerns over side effects, antiretroviral treatment duration and beliefs that treatment is only for the sick were common barriers; however, desperation for a child was noted as a facilitator for uptake. HIV-negative men and HIV-positive women had favourable attitudes towards self-insemination, though paternity and safety concerns were raised. Self-insemination was generally preferred over pre-exposure prophylaxis by HIV-negative men, and antiretroviral-based strategies were preferred by couples with HIV-negative female partners, despite concerns raised about condomless sex while virally suppressed. Knowledge about the fertile window was low. A strong counselling component will be required for effective uptake and adherence to safer conception services. © The Author(s) 2016.

Acceptability and preferences for safer conception HIV prevention strategies: A qualitative study

PubMed Central

Schwartz, Sheree; West, Nora; Phofa, Rebecca; Yende, Nompumelelo; Sanne, Ian; Bassett, Jean; Van Rie, Annelies

2016-01-01

Safer conception strategies to reduce HIV transmission risk include antiretroviral therapy (ART) for HIV-positive partners, pre-exposure prophylaxis (PrEP) for HIV-negative partners, condomless sex limited to fertile periods, and home-based self-insemination. Resistance to taking treatment or cultural concerns may limit uptake of strategies and intervention success. Understanding the acceptability and preferences between different approaches is important to optimize service delivery. Between February-July 2013, 42 adults (21 HIV-positive and 21 HIV-negative) receiving primary care at Witkoppen Health and Welfare Centre in Johannesburg, South Africa, participated in focus group discussions or in-depth interviews. Themes were analyzed using a grounded theory approach. Acceptability of antiretroviral-based (ARV) strategies varied. Concerns over side effects, ARV treatment duration, and beliefs that treatment is only for the sick were common barriers, however desperation for a child was noted as a facilitator for uptake. HIV-negative men and HIV-positive women had favorable attitudes towards self-insemination, though paternity and safety concerns were raised. Self-insemination was generally preferred over PrEP by HIV-negative men, and ARV-based strategies were preferred by couples with HIV-negative female partners, despite concerns raised about condomless sex while virally suppressed. Knowledge about the fertile window was low. A strong counselling component will be required for effective uptake and adherence to safer conception services. PMID:26384950

Exploratory multivariate modeling and prediction of the physico-chemical properties of surface water and groundwater

NASA Astrophysics Data System (ADS)

Ayoko, Godwin A.; Singh, Kirpal; Balerea, Steven; Kokot, Serge

2007-03-01

SummaryPhysico-chemical properties of surface water and groundwater samples from some developing countries have been subjected to multivariate analyses by the non-parametric multi-criteria decision-making methods, PROMETHEE and GAIA. Complete ranking information necessary to select one source of water in preference to all others was obtained, and this enabled relationships between the physico-chemical properties and water quality to be assessed. Thus, the ranking of the quality of the water bodies was found to be strongly dependent on the total dissolved solid, phosphate, sulfate, ammonia-nitrogen, calcium, iron, chloride, magnesium, zinc, nitrate and fluoride contents of the waters. However, potassium, manganese and zinc composition showed the least influence in differentiating the water bodies. To model and predict the water quality influencing parameters, partial least squares analyses were carried out on a matrix made up of the results of water quality assessment studies carried out in Nigeria, Papua New Guinea, Egypt, Thailand and India/Pakistan. The results showed that the total dissolved solid, calcium, sulfate, sodium and chloride contents can be used to predict a wide range of physico-chemical characteristics of water. The potential implications of these observations on the financial and opportunity costs associated with elaborate water quality monitoring are discussed.

EFFECTS OF USING THE CB05 VERSUS THE CB4 CHEMICAL MECHANISMS ON MODEL PREDICTIONS

EPA Science Inventory

The Carbon Bond 4 (CB4) chemical mechanism has been widely used for many years in box and air quality models to predict the effect of atmospheric chemistry on pollutant concentrations. Because of the importance of this mechanism and the length of time since its original developm...

EFFECTS OF USING THE CB05 VERSUS THE CB4 CHEMICAL MECHANISM ON MODEL PREDICTIONS

EPA Science Inventory

The Carbon Bond 4 (CB4) chemical mechanism has been widely used for many years in box and air quality models to predict the effect of atmospheric chemistry on pollutant concentrations. Because of the importance of this mechanism and the length of time since its original developm...

Prediction of Chemical Carcinogenicity in Rodents from in vitro Genetic Toxicity Assays

NASA Astrophysics Data System (ADS)

Tennant, Raymond W.; Margolin, Barry H.; Shelby, Michael D.; Zeiger, Errol; Haseman, Joseph K.; Spalding, Judson; Caspary, William; Resnick, Michael; Stasiewicz, Stanley; Anderson, Beth; Minor, Robert

1987-05-01

Four widely used in vitro assays for genetic toxicity were evaluated for their ability to predict the carcinogenicity of selected chemicals in rodents. These assays were mutagenesis in Salmonella and mouse lymphoma cells and chromosome aberrations and sister chromatid exchanges in Chinese hamster ovary cells. Seventy-three chemicals recently tested in 2-year carcinogenicity studies conducted by the National Cancer Institute and the National Toxicology Program were used in this evaluation. Test results from the four in vitro assays did not show significant differences in individual concordance with the rodent carcinogenicity results; the concordance of each assay was approximately 60 percent. Within the limits of this study there was no evidence of complementarity among the four assays, and no battery of tests constructed from these assays improved substantially on the overall performance of the Salmonella assay. The in vitro assays which represented a range of three cell types and four end points did show substantial agreement among themselves, indicating that chemicals positive in one in vitro assay tended to be positive in the other in vitro assays. To help put this project into its proper context, we emphasize certain features of the study: 1) Standard protocols were used to mimic the major use of STTs worldwide--screening for mutagens and carcinogens; no attempt was made to optimize protocols for specific chemicals. 2) The 73 NTP chemicals and their 60% incidence of carcinogenicity are probably not representative of the universe of chemicals but rather reflect the recent chemical selection process for the NTP carcinogenicity assay. 3) The small, diverse group of chemicals precludes a meaningful evaluation of the predictive utility of chemical structure information. 4) The NTP is currently testing these same 73 chemicals in two in vivo STTs for chromosomal effects. 5) Complete data for an additional group of 30 to 40 NTP chemicals will be gathered on

‘On the same level’: facilitators’ experiences running a drug user-led safer injecting education campaign

PubMed Central

2013-01-01

Background Unsafe injection practices play a major role in elevated rates of morbidity and mortality among people who inject drugs (IDU). There is growing interest in the direct involvement of IDU in interventions that seek to address unsafe injecting. This study describes a drug user-led safer injecting education campaign, and explores facilitators’ experiences delivering educational workshops. Methods We conducted semi-structured qualitative interviews with 8 members of the Injection Support (IS) Team who developed and facilitated a series of safer injecting education workshops. Interviews explored facilitator’s perceptions of the workshops, experiences being a facilitator, and perspectives on the educational campaign. Interviews were transcribed verbatim and a thematic analysis was conducted. Results IS Team facilitators described how the workshop’s structure and content enabled effective communication of information about safer injecting practices, while targeting the unsafe practices of workshop participants. Facilitators’ identity as IDU enhanced their ability to relate to workshop participants and communicate educational messages in language accessible to workshop participants. Facilitators reported gaining knowledge and skills from their involvement in the campaign, as well as positive feelings about themselves from the realization that they were helping people to protect their health. Overall, facilitators felt that this campaign provided IDU with valuable information, although facilitators also critiqued the campaign and suggested improvements for future efforts. Conclusions This study demonstrates the feasibility of involving IDU in educational initiatives targeting unsafe injecting. Findings illustrate how IDU involvement in prevention activities improves relevance and cultural appropriateness of interventions while providing individual, social, and professional benefits to those IDU delivering education. PMID:23497293

New research discovery may mean less radioactive contamination, safer nuclear power plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murph, S.

Murph has now made another nanoparticle breakthrough that could benefit various work environments such as nuclear power plants. Murph and her team have created nanoparticle treated stainless steel filters that are capable to capturing radioactive vapor materials. Just like air filters capture dust and dirt, these filters are capable of capturing large amounts of radioactive vapors. The new research may one day mean that nuclear power plant workers, and other workers in related fields, will have a safer working environment.

Integrative Chemical-Biological Read-Across Approach for Chemical Hazard Classification

PubMed Central

Low, Yen; Sedykh, Alexander; Fourches, Denis; Golbraikh, Alexander; Whelan, Maurice; Rusyn, Ivan; Tropsha, Alexander

2013-01-01

Traditional read-across approaches typically rely on the chemical similarity principle to predict chemical toxicity; however, the accuracy of such predictions is often inadequate due to the underlying complex mechanisms of toxicity. Here we report on the development of a hazard classification and visualization method that draws upon both chemical structural similarity and comparisons of biological responses to chemicals measured in multiple short-term assays (”biological” similarity). The Chemical-Biological Read-Across (CBRA) approach infers each compound's toxicity from those of both chemical and biological analogs whose similarities are determined by the Tanimoto coefficient. Classification accuracy of CBRA was compared to that of classical RA and other methods using chemical descriptors alone, or in combination with biological data. Different types of adverse effects (hepatotoxicity, hepatocarcinogenicity, mutagenicity, and acute lethality) were classified using several biological data types (gene expression profiling and cytotoxicity screening). CBRA-based hazard classification exhibited consistently high external classification accuracy and applicability to diverse chemicals. Transparency of the CBRA approach is aided by the use of radial plots that show the relative contribution of analogous chemical and biological neighbors. Identification of both chemical and biological features that give rise to the high accuracy of CBRA-based toxicity prediction facilitates mechanistic interpretation of the models. PMID:23848138

Understanding Barriers to Safer Sex Practice in Zimbabwean Marriages: Implications for Future HIV Prevention Interventions

ERIC Educational Resources Information Center

Mugweni, Esther; Omar, Mayeh; Pearson, Stephen

2015-01-01

Against the backdrop of high human immunodeficiency virus (HIV) prevalence in stable relationships in Southern Africa, our study presents sociocultural barriers to safer sex practice in Zimbabwean marriages. We conducted 36 in-depth interviews and four focus group discussions with married men and women in Zimbabwe in 2008. Our aim was to identify…

Developing predictive models for toxicity of organic chemicals to green algae based on mode of action.

PubMed

Bakire, Serge; Yang, Xinya; Ma, Guangcai; Wei, Xiaoxuan; Yu, Haiying; Chen, Jianrong; Lin, Hongjun

2018-01-01

Organic chemicals in the aquatic ecosystem may inhibit algae growth and subsequently lead to the decline of primary productivity. Growth inhibition tests are required for ecotoxicological assessments for regulatory purposes. In silico study is playing an important role in replacing or reducing animal tests and decreasing experimental expense due to its efficiency. In this work, a series of theoretical models was developed for predicting algal growth inhibition (log EC 50 ) after 72 h exposure to diverse chemicals. In total 348 organic compounds were classified into five modes of toxic action using the Verhaar Scheme. Each model was established by using molecular descriptors that characterize electronic and structural properties. The external validation and leave-one-out cross validation proved the statistical robustness of the derived models. Thus they can be used to predict log EC 50 values of chemicals that lack authorized algal growth inhibition values (72 h). This work systematically studied algal growth inhibition according to toxic modes and the developed model suite covers all five toxic modes. The outcome of this research will promote toxic mechanism analysis and be made applicable to structural diversity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Developing predictions of in vivo developmental toxicity of ToxCast chemicals using mouse embryonic stem cells.

EPA Science Inventory

Developing predictions of in vivo developmental toxicity of ToxCast chemicals using mouse embryonic stem cells S. Hunter, M. Rosen, M. Hoopes, H. Nichols, S. Jeffay, K. Chandler1, Integrated Systems Toxicology Division, National Health and Environmental Effects Research Labor...

Can phylogeny predict chemical diversity and potential medicinal activity of plants? A case study of Amaryllidaceae

USDA-ARS?s Scientific Manuscript database

During evolution, plants and other organisms have developed a diversity of chemical defences, leading to the evolution of various groups of specialized metabolites selected for their endogenous biological function. A correlation between phylogeny and biosynthetic pathways could offer a predictive ap...

Retrofitting existing chemical scrubbers to biotrickling filters for H2S emission control

PubMed Central

Gabriel, David; Deshusses, Marc A.

2003-01-01

Biological treatment is a promising alternative to conventional air-pollution control methods, but thus far biotreatment processes for odor control have always required much larger reactor volumes than chemical scrubbers. We converted an existing full-scale chemical scrubber to a biological trickling filter and showed that effective treatment of hydrogen sulfide (H2S) in the converted scrubber was possible even at gas contact times as low as 1.6 s. That is 8–20 times shorter than previous biotrickling filtration reports and comparable to usual contact times in chemical scrubbers. Significant removal of reduced sulfur compounds, ammonia, and volatile organic compounds present in traces in the air was also observed. Continuous operation for >8 months showed stable performance and robust behavior for H2S treatment, with pollutant-removal performance comparable to that achieved by using a chemical scrubber. Our study demonstrates that biotrickling filters can replace chemical scrubbers and be a safer, more economical technique for odor control. PMID:12740445

Retrofitting existing chemical scrubbers to biotrickling filters for H2S emission control.

PubMed

Gabriel, David; Deshusses, Marc A

2003-05-27

Biological treatment is a promising alternative to conventional air-pollution control methods, but thus far biotreatment processes for odor control have always required much larger reactor volumes than chemical scrubbers. We converted an existing full-scale chemical scrubber to a biological trickling filter and showed that effective treatment of hydrogen sulfide (H2S) in the converted scrubber was possible even at gas contact times as low as 1.6 s. That is 8-20 times shorter than previous biotrickling filtration reports and comparable to usual contact times in chemical scrubbers. Significant removal of reduced sulfur compounds, ammonia, and volatile organic compounds present in traces in the air was also observed. Continuous operation for >8 months showed stable performance and robust behavior for H2S treatment, with pollutant-removal performance comparable to that achieved by using a chemical scrubber. Our study demonstrates that biotrickling filters can replace chemical scrubbers and be a safer, more economical technique for odor control.

Humanized mouse lines and their application for prediction of human drug metabolism and toxicological risk assessment

PubMed Central

Cheung, Connie; Gonzalez, Frank J

2008-01-01

Cytochrome P450s (P450s) are important enzymes involved in the metabolism of xenobiotics, particularly clinically used drugs, and are also responsible for metabolic activation of chemical carcinogens and toxins. Many xenobiotics can activate nuclear receptors that in turn induce the expression of genes encoding xenobiotic metabolizing enzymes and drug transporters. Marked species differences in the expression and regulation of cytochromes P450 and xenobiotic nuclear receptors exist. Thus obtaining reliable rodent models to accurately reflect human drug and carcinogen metabolism is severely limited. Humanized transgenic mice were developed in an effort to create more reliable in vivo systems to study and predict human responses to xenobiotics. Human P450s or human xenobiotic-activated nuclear receptors were introduced directly or replaced the corresponding mouse gene, thus creating “humanized” transgenic mice. Mice expressing human CYP1A1/CYP1A2, CYP2E1, CYP2D6, CYP3A4, CY3A7, PXR, PPARα were generated and characterized. These humanized mouse models offers a broad utility in the evaluation and prediction of toxicological risk that may aid in the development of safer drugs. PMID:18682571

Endocrine disrupting chemicals in fish: developing exposure indicators and predictive models of effects based on mechanism of action.

PubMed

Ankley, Gerald T; Bencic, David C; Breen, Michael S; Collette, Timothy W; Conolly, Rory B; Denslow, Nancy D; Edwards, Stephen W; Ekman, Drew R; Garcia-Reyero, Natalia; Jensen, Kathleen M; Lazorchak, James M; Martinović, Dalma; Miller, David H; Perkins, Edward J; Orlando, Edward F; Villeneuve, Daniel L; Wang, Rong-Lin; Watanabe, Karen H

2009-05-05

Knowledge of possible toxic mechanisms (or modes) of action (MOA) of chemicals can provide valuable insights as to appropriate methods for assessing exposure and effects, thereby reducing uncertainties related to extrapolation across species, endpoints and chemical structure. However, MOA-based testing seldom has been used for assessing the ecological risk of chemicals. This is in part because past regulatory mandates have focused more on adverse effects of chemicals (reductions in survival, growth or reproduction) than the pathways through which these effects are elicited. A recent departure from this involves endocrine-disrupting chemicals (EDCs), where there is a need to understand both MOA and adverse outcomes. To achieve this understanding, advances in predictive approaches are required whereby mechanistic changes caused by chemicals at the molecular level can be translated into apical responses meaningful to ecological risk assessment. In this paper we provide an overview and illustrative results from a large, integrated project that assesses the effects of EDCs on two small fish models, the fathead minnow (Pimephales promelas) and zebrafish (Danio rerio). For this work a systems-based approach is being used to delineate toxicity pathways for 12 model EDCs with different known or hypothesized toxic MOA. The studies employ a combination of state-of-the-art genomic (transcriptomic, proteomic, metabolomic), bioinformatic and modeling approaches, in conjunction with whole animal testing, to develop response linkages across biological levels of organization. This understanding forms the basis for predictive approaches for species, endpoint and chemical extrapolation. Although our project is focused specifically on EDCs in fish, we believe that the basic conceptual approach has utility for systematically assessing exposure and effects of chemicals with other MOA across a variety of biological systems.

In silico site-directed mutagenesis informs species-specific predictions of chemical susceptibility derived from the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool

EPA Science Inventory

The Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed to address needs for rapid, cost effective methods of species extrapolation of chemical susceptibility. Specifically, the SeqAPASS tool compares the primary sequence (Level 1), functiona...

Chemical and biological extraction of metals present in E waste: A hybrid technology.

PubMed

Pant, Deepak; Joshi, Deepika; Upreti, Manoj K; Kotnala, Ravindra K

2012-05-01

Management of metal pollution associated with E-waste is widespread across the globe. Currently used techniques for the extraction of metals from E-waste by using either chemical or biological leaching have their own limitations. Chemical leaching is much rapid and efficient but has its own environmental consequences, even the future prospects of associated nanoremediation are also uncertain. Biological leaching on the other hand is comparatively a cost effective technique but at the same moment it is time consuming and the complete recovery of the metal, alone by biological leaching is not possible in most of the cases. The current review addresses the individual issues related to chemical and biological extraction techniques and proposes a hybrid-methodology which incorporates both, along with safer chemicals and compatible microbes for better and efficient extraction of metals from the E-waste. Copyright © 2011 Elsevier Ltd. All rights reserved.

Better learning in schools to improve attitudes toward abstinence and intentions for safer sex among adolescents in urban Nepal.

PubMed

Shrestha, Rachana Manandhar; Otsuka, Keiko; Poudel, Krishna C; Yasuoka, Junko; Lamichhane, Medin; Jimba, Masamine

2013-03-20

School-based sex education is an effective medium to convey health information and skills about preventing sexually transmitted infections (STIs) and unwanted pregnancies among adolescents. However, research on school-based sex education is limited in many developing countries, including Nepal. This study thus had two main objectives: (1) to assess students' evaluation of school-based sex education, and (2) to examine the associations between students' evaluations of school-based sex education and their (a) attitudes toward abstinence and (b) intentions for safer sex. This cross-sectional study was conducted among 634 students from six schools in the Kathmandu Valley during May-June 2010. We used a self-administered questionnaire to assess students' evaluations of school-based sex education, attitudes toward abstinence, and intentions for safer sex. The data were then analyzed using multiple linear regression models. Regarding "information on HIV and sexual health", many students perceived that they received the least amount of information on HIV counseling and testing centers (mean 2.29, SD 1.00) through their schools. In terms of "support and involvement of teachers and parents" in sex education, parents' participation ranked as the lowest (mean 1.81, SD 1.01). Audiotapes were reported as the least used among the listed "teaching aids for sexual health education" (mean 1.54, SD 0.82). In multivariate analysis, receiving more "information on HIV and sexual health" was positively associated with more positive "attitudes toward abstinence" (β = 0.11, p = <0.018) and greater "intentions for safer sex" (β = 0.17, p = <0.001) among students. Similarly, increased "support and involvement from teachers and parents" was also positively associated with more positive "attitudes toward abstinence" (β = 0.16, p = <0.001) and greater "intentions for safer sex" (β = 0.15, p = <0.002). Our results suggest that students' needs and expectations

Better learning in schools to improve attitudes toward abstinence and intentions for safer sex among adolescents in urban Nepal

PubMed Central

2013-01-01

Background School-based sex education is an effective medium to convey health information and skills about preventing sexually transmitted infections (STIs) and unwanted pregnancies among adolescents. However, research on school-based sex education is limited in many developing countries, including Nepal. This study thus had two main objectives: (1) to assess students’ evaluation of school-based sex education, and (2) to examine the associations between students’ evaluations of school-based sex education and their (a) attitudes toward abstinence and (b) intentions for safer sex. Methods This cross-sectional study was conducted among 634 students from six schools in the Kathmandu Valley during May–June 2010. We used a self-administered questionnaire to assess students’ evaluations of school-based sex education, attitudes toward abstinence, and intentions for safer sex. The data were then analyzed using multiple linear regression models. Results Regarding “information on HIV and sexual health”, many students perceived that they received the least amount of information on HIV counseling and testing centers (mean 2.29, SD 1.00) through their schools. In terms of “support and involvement of teachers and parents” in sex education, parents’ participation ranked as the lowest (mean 1.81, SD 1.01). Audiotapes were reported as the least used among the listed “teaching aids for sexual health education” (mean 1.54, SD 0.82). In multivariate analysis, receiving more “information on HIV and sexual health” was positively associated with more positive “attitudes toward abstinence” (β = 0.11, p = <0.018) and greater “intentions for safer sex” (β = 0.17, p = <0.001) among students. Similarly, increased “support and involvement from teachers and parents” was also positively associated with more positive “attitudes toward abstinence” (β = 0.16, p = <0.001) and greater “intentions for safer sex” (β = 0.15, p�

Identification of Chemical Vascular Disruptors During Development Using An Integrative Predictive Toxicity Model and Zebrafish and in Vitro Functional Angiogenesis Assays.

EPA Science Inventory

Identification of chemical vascular disruptors during development using an integrative predictive toxicity model and zebrafish and in vitro functional angiogenesis assays Chemically-induced vascular toxicity during embryonic development can result in a wide range of adverse pre...

Are Charter Schools Safer in Deindustrialized Cities with High Rates of Crime? Testing Hypotheses in Detroit

ERIC Educational Resources Information Center

Hamlin, Daniel

2017-01-01

Families in deindustrialized cities with high crime rates report prioritizing school safety when opting for charter schools. Yet, very little research has investigated whether charter schools are safer than traditional public schools. This study compares charter and traditional public schools in Detroit, Michigan, on perceived school safety by…

Structure-biodegradability study and computer-automated prediction of aerobic biodegradation of chemicals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klopman, G.; Tu, M.

1997-09-01

It is shown that a combination of two programs, MultiCASE and META, can help assess the biodegradability of industrial organic materials in the ecosystem. MultiCASE is an artificial intelligence computer program that had been trained to identify molecular substructures believed to cause or inhibit biodegradation and META is an expert system trained to predict the aerobic biodegradation products of organic molecules. These two programs can be used to help evaluate the fate of disposed chemicals by estimating their biodegradability and the nature of their biodegradation products under conditions that may model the environment.

Predicting Formation Damage in Aquifer Thermal Energy Storage Systems Utilizing a Coupled Hydraulic-Thermal-Chemical Reservoir Model

NASA Astrophysics Data System (ADS)

Müller, Daniel; Regenspurg, Simona; Milsch, Harald; Blöcher, Guido; Kranz, Stefan; Saadat, Ali

2014-05-01

In aquifer thermal energy storage (ATES) systems, large amounts of energy can be stored by injecting hot water into deep or intermediate aquifers. In a seasonal production-injection cycle, water is circulated through a system comprising the porous aquifer, a production well, a heat exchanger and an injection well. This process involves large temperature and pressure differences, which shift chemical equilibria and introduce or amplify mechanical processes. Rock-fluid interaction such as dissolution and precipitation or migration and deposition of fine particles will affect the hydraulic properties of the porous medium and may lead to irreversible formation damage. In consequence, these processes determine the long-term performance of the ATES system and need to be predicted to ensure the reliability of the system. However, high temperature and pressure gradients and dynamic feedback cycles pose challenges on predicting the influence of the relevant processes. Within this study, a reservoir model comprising a coupled hydraulic-thermal-chemical simulation was developed based on an ATES demonstration project located in the city of Berlin, Germany. The structural model was created with Petrel, based on data available from seismic cross-sections and wellbores. The reservoir simulation was realized by combining the capabilities of multiple simulation tools. For the reactive transport model, COMSOL Multiphysics (hydraulic-thermal) and PHREEQC (chemical) were combined using the novel interface COMSOL_PHREEQC, developed by Wissmeier & Barry (2011). It provides a MATLAB-based coupling interface between both programs. Compared to using COMSOL's built-in reactive transport simulator, PHREEQC additionally calculates adsorption and reaction kinetics and allows the selection of different activity coefficient models in the database. The presented simulation tool will be able to predict the most important aspects of hydraulic, thermal and chemical transport processes relevant to

Informing the Human Plasma Protein Binding of Environmental Chemicals by Machine Learning in the Pharmaceutical Space: Applicability Domain and Limits of Predictability.

PubMed

Ingle, Brandall L; Veber, Brandon C; Nichols, John W; Tornero-Velez, Rogelio

2016-11-28

The free fraction of a xenobiotic in plasma (F ub ) is an important determinant of chemical adsorption, distribution, metabolism, elimination, and toxicity, yet experimental plasma protein binding data are scarce for environmentally relevant chemicals. The presented work explores the merit of utilizing available pharmaceutical data to predict F ub for environmentally relevant chemicals via machine learning techniques. Quantitative structure-activity relationship (QSAR) models were constructed with k nearest neighbors (kNN), support vector machines (SVM), and random forest (RF) machine learning algorithms from a training set of 1045 pharmaceuticals. The models were then evaluated with independent test sets of pharmaceuticals (200 compounds) and environmentally relevant ToxCast chemicals (406 total, in two groups of 238 and 168 compounds). The selection of a minimal feature set of 10-15 2D molecular descriptors allowed for both informative feature interpretation and practical applicability domain assessment via a bounded box of descriptor ranges and principal component analysis. The diverse pharmaceutical and environmental chemical sets exhibit similarities in terms of chemical space (99-82% overlap), as well as comparable bias and variance in constructed learning curves. All the models exhibit significant predictability with mean absolute errors (MAE) in the range of 0.10-0.18F ub . The models performed best for highly bound chemicals (MAE 0.07-0.12), neutrals (MAE 0.11-0.14), and acids (MAE 0.14-0.17). A consensus model had the highest accuracy across both pharmaceuticals (MAE 0.151-0.155) and environmentally relevant chemicals (MAE 0.110-0.131). The inclusion of the majority of the ToxCast test sets within the AD of the consensus model, coupled with high prediction accuracy for these chemicals, indicates the model provides a QSAR for F ub that is broadly applicable to both pharmaceuticals and environmentally relevant chemicals.

Microorganisms in inorganic chemical analysis.

PubMed

Godlewska-Zyłkiewicz, Beata

2006-01-01

There are innumerable strains of microbes (bacteria, yeast and fungi) that degrade or transform chemicals and compounds into simpler, safer or less toxic substances. These bioprocesses have been used for centuries in the treatment of municipal wastes, in wine, cheese and bread making, and in bioleaching and metal recovery processes. Recent literature shows that microorganisms can be also used as effective sorbents for solid phase extraction procedures. This review reveals that fundamental nonanalytical studies on the parameters and conditions of biosorption processes and on metal-biomass interactions often result in efficient analytical procedures and biotechnological applications. Some selected examples illustrate the latest developments in the biosorption of metals by microbial biomass, which have opened the door to the application of microorganisms to analyte preconcentration, matrix separation and speciation analysis.

Human Pluripotent Stem Cell-Based Assay Predicts Developmental Toxicity Potential of ToxCast Chemicals (ACT meeting)

EPA Science Inventory

Worldwide initiatives to screen for toxicity potential among the thousands of chemicals currently in use require inexpensive and high-throughput in vitro models to meet their goals. The devTOX quickPredict platform is an in vitro human pluripotent stem cell-based assay used to as...

Application of bioelectrical impedance analysis in prediction of light kid carcass and muscle chemical composition.

PubMed

Silva, S R; Afonso, J; Monteiro, A; Morais, R; Cabo, A; Batista, A C; Guedes, C M; Teixeira, A

2018-06-01

Carcass data were collected from 24 kids (average live weight of 12.5±5.5 kg; range 4.5 to 22.4 kg) of Jarmelista Portuguese native breed, to evaluate bioelectrical impedance analysis (BIA) as a technique for prediction of light kid carcass and muscle chemical composition. Resistance (Rs, Ω) and reactance (Xc, Ω), were measured in the cold carcasses with a single frequency bioelectrical impedance analyzer and, together with impedance (Z, Ω), two electrical volume measurements (VolA and VolB, cm2/Ω), carcass cold weight (CCW), carcass compactness and several carcass linear measurements were fitted as independent variables to predict carcass composition by stepwise regression analysis. The amount of variation explained by VolA and VolB only reached a significant level (P<0.01 and P<0.05, respectively) for muscle weight, moisture, protein and fat-free soft tissue content, even so with low accuracy, with VolA providing the best results (0.326⩽R 2⩽0.366). Quite differently, individual BIA parameters (Rs, Xc and Z) explained a very large amount of variation in dissectible carcass fat weight (0.814⩽R 2⩽0.862; P<0.01). These individual BIA parameters also explained a large amount of variation in subcutaneous and intermuscular fat weights (respectively 0.749⩽R 2⩽0.793 and 0.718⩽R 2⩽0.760; P<0.01), and in muscle chemical fat weight (0.663⩽R 2⩽0.684; P<0.01). Still significant but much lower was the variation in muscle, moisture, protein and fat-free soft tissue weights (0.344⩽R 2⩽0.393; P<0.01) explained by BIA parameters. Still, the best models for estimation of muscle, moisture, protein and fat-free soft tissue weights included Rs in addition to CCW, and accounted for 97.1% to 99.8% (P<0.01) of the variation observed, with CCW by itself accounting for 97.0% to 99.6% (P<0.01) of that variation. Resistance was the only independent variable selected for the best model predicting subcutaneous fat weight. It was also selected for the best models

Prediction of the contact sensitizing potential of chemicals using analysis of gene expression changes in human THP-1 monocytes.

PubMed

Arkusz, Joanna; Stępnik, Maciej; Sobala, Wojciech; Dastych, Jarosław

2010-11-10

The aim of this study was to find differentially regulated genes in THP-1 monocytic cells exposed to sensitizers and nonsensitizers and to investigate if such genes could be reliable markers for an in vitro predictive method for the identification of skin sensitizing chemicals. Changes in expression of 35 genes in the THP-1 cell line following treatment with chemicals of different sensitizing potential (from nonsensitizers to extreme sensitizers) were assessed using real-time PCR. Verification of 13 candidate genes by testing a large number of chemicals (an additional 22 sensitizers and 8 nonsensitizers) revealed that prediction of contact sensitization potential was possible based on evaluation of changes in three genes: IL8, HMOX1 and PAIMP1. In total, changes in expression of these genes allowed correct detection of sensitization potential of 21 out of 27 (78%) test sensitizers. The gene expression levels inside potency groups varied and did not allow estimation of sensitization potency of test chemicals. Results of this study indicate that evaluation of changes in expression of proposed biomarkers in THP-1 cells could be a valuable model for preliminary screening of chemicals to discriminate an appreciable majority of sensitizers from nonsensitizers. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Safer work clothing for fishermen.

PubMed

Geving, Ingunn Holmen; Reitan, Jarl; Sandsund, Mariann; Faerevik, Hilde; Reinertsen, Randi Eidsmo; Aasjord, Halvard

2006-01-01

The fisherman's work environment consists of many potential risks. A study of occupational accidents in the Norwegian fishing industry in the nine-year period from 1998 to 2006 shows that more than 3/4 of the deaths were caused by loss of fishing vessel or man-overboard accidents. Furthermore, the greatest risk of drowning is found in the smallest fleet. The aim of our project was to develop safer work clothing and through this contribute to a reduction in work accidents and injuries in the fishing fleet. We considered that it is possible to produce protective work clothing that satisfies a specification of requirements covering the fishermen's needs for protection and comfort during work. An end user-centred process including twenty-three personal interviews and a questionnaire was used to clarify the fishermen's needs and wishes before detailed design and product development. We identified an overview of all the fishermen's needs for protection during work, and produced a prioritised list of functional requirements for the clothing. The results show that the clothing previously preferred by fishermen does not satisfy all the users' demands for safety, functionality and comfort. These demands have been taken into consideration when designing improved work clothing for the fishing fleet. A selected number of prototypes were developed on the basis of the established specification of requirements. The prototypes were evaluated according to the users' requirements through tests in SINTEF's Work Physiology Laboratory and on board fishing vessels. The results demonstrate that the new protective clothing satisfies the fishermen's requirements.

A chemical reactor network for oxides of nitrogen emission prediction in gas turbine combustor

NASA Astrophysics Data System (ADS)

Hao, Nguyen Thanh

2014-06-01

This study presents the use of a new chemical reactor network (CRN) model and non-uniform injectors to predict the NOx emission pollutant in gas turbine combustor. The CRN uses information from Computational Fluid Dynamics (CFD) combustion analysis with two injectors of CH4-air mixture. The injectors of CH4-air mixture have different lean equivalence ratio, and they control fuel flow to stabilize combustion and adjust combustor's equivalence ratio. Non-uniform injector is applied to improve the burning process of the turbine combustor. The results of the new CRN for NOx prediction in the gas turbine combustor show very good agreement with the experimental data from Korea Electric Power Research Institute.

Screening for Chemical Contributions to Breast Cancer Risk: A Case Study for Chemical Safety Evaluation

PubMed Central

Ackerman, Janet M.; Dairkee, Shanaz H.; Fenton, Suzanne E.; Johnson, Dale; Navarro, Kathleen M.; Osborne, Gwendolyn; Rudel, Ruthann A.; Solomon, Gina M.; Zeise, Lauren; Janssen, Sarah

2015-01-01

Background Current approaches to chemical screening, prioritization, and assessment are being reenvisioned, driven by innovations in chemical safety testing, new chemical regulations, and demand for information on human and environmental impacts of chemicals. To conceptualize these changes through the lens of a prevalent disease, the Breast Cancer and Chemicals Policy project convened an interdisciplinary expert panel to investigate methods for identifying chemicals that may increase breast cancer risk. Methods Based on a review of current evidence, the panel identified key biological processes whose perturbation may alter breast cancer risk. We identified corresponding assays to develop the Hazard Identification Approach for Breast Carcinogens (HIA-BC), a method for detecting chemicals that may raise breast cancer risk. Finally, we conducted a literature-based pilot test of the HIA-BC. Results The HIA-BC identifies assays capable of detecting alterations to biological processes relevant to breast cancer, including cellular and molecular events, tissue changes, and factors that alter susceptibility. In the pilot test of the HIA-BC, chemicals associated with breast cancer all demonstrated genotoxic or endocrine activity, but not necessarily both. Significant data gaps persist. Conclusions This approach could inform the development of toxicity testing that targets mechanisms relevant to breast cancer, providing a basis for identifying safer chemicals. The study identified important end points not currently evaluated by federal testing programs, including altered mammary gland development, Her2 activation, progesterone receptor activity, prolactin effects, and aspects of estrogen receptor β activity. This approach could be extended to identify the biological processes and screening methods relevant for other common diseases. Citation Schwarzman MR, Ackerman JM, Dairkee SH, Fenton SE, Johnson D, Navarro KM, Osborne G, Rudel RA, Solomon GM, Zeise L, Janssen S. 2015

A mechanism-mediated model for carcinogenicity: Model content and prediction of the outcome of rodent carcinogenicity bioassays currently being conducted on 25 organic chemicals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Purdy, R.

A hierarchical model consisting of quantitative structure-activity relationships based mainly on chemical reactivity was developed to predict the carcinogenicity of organic chemicals to rodents. The model is comprised of quantitative structure-activity relationships, QSARs based on hypothesized mechanisms of action, metabolism, and partitioning. Predictors included octanol/water partition coefficient, molecular size, atomic partial charge, bond angle strain, atomic acceptor delocalizibility, atomic radical superdelocalizibility, the lowest unoccupied molecular orbital (LUMO) energy of hypothesized intermediate nitrenium ion of primary aromatic amines, difference in charge of ionized and unionized carbon-chlorine bonds, substituent size and pattern on polynuclear aromatic hydrocarbons, the distance between lone electron pairsmore » over a rigid structure, and the presence of functionalities such as nitroso and hydrazine. The model correctly classified 96% of the carcinogens in the training set of 306 chemicals, and 90% of the carcinogens in the test set of 301 chemicals. The test set by chance contained 84% of the positive thiocontaining chemicals. A QSAR for these chemicals was developed. This posttest set modified model correctly predicted 94% of the carcinogens in the test set. This model was used to predict the carcinogenicity of the 25 organic chemicals the U.S. National Toxicology Program was testing at the writing of this article. 12 refs., 3 tabs.« less

Are nuclear ships environmentally safer than conventionally powered ships

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bone, C.A.; Molgaard, C.A.; Helmkamp, J.C.

1988-03-01

An epidemiologic analysis was conducted to determine if risk of hospitalization varied by age, ship type, or occupation between nuclear and conventional powered ship crews in the U.S. Navy. Study cohorts consisted of all male enlisted personnel who served exclusively aboard conventional or nuclear powered aircraft carriers and cruisers during the years 1975-1979; cases were those men hospitalized during this period (N = 48,242). Conventional ship personnel showed significantly elevated rates of injury and disease when compared to nuclear ship personnel. The largest relative risks by age occurred for conventional ship crewmen less than 30 years old. Seaman, logistics (supply),more » and healthcare personnel serving aboard conventional ships comprised the occupational groups exhibiting the highest hospitalization rate differentials. The results strongly suggest that nuclear ships provide a healthier, safer working and living environment than conventional ships.« less

Cocaine-dependent adults and recreational cocaine users are more likely than controls to choose immediate unsafe sex over delayed safer sex.

PubMed

Koffarnus, Mikhail N; Johnson, Matthew W; Thompson-Lake, Daisy G Y; Wesley, Michael J; Lohrenz, Terry; Montague, P Read; Bickel, Warren K

2016-08-01

Cocaine users have a higher incidence of risky sexual behavior and HIV infection than nonusers. Our aim was to measure whether safer sex discount rates-a measure of the likelihood of having immediate unprotected sex versus waiting to have safer sex-differed between controls and cocaine users of varying severity. Of the 162 individuals included in the primary data analyses, 69 met the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR) criteria for cocaine dependence, 29 were recreational cocaine users who did not meet the dependence criteria, and 64 were controls. Participants completed the Sexual Discounting Task, which measures a person's likelihood of using a condom when one is immediately available and how that likelihood decreases as a function of delay to condom availability with regard to 4 images chosen by the participants of hypothetical sexual partners differing in perceived desirability and likelihood of having a sexually transmitted infection. When a condom was immediately available, the stated likelihood of condom use sometimes differed between cocaine users and controls, which depended on the image condition. Even after controlling for rates of condom use when one is immediately available, the cocaine-dependent and recreational users groups were more sensitive to delay to condom availability than controls. Safer sex discount rates were also related to intelligence scores. The Sexual Discounting Task identifies delay as a key variable that impacts the likelihood of using a condom among these groups and suggests that HIV prevention efforts may be differentially effective based on an individual's safer sex discount rate. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Gender power control, sexual experiences, safer sex practices, and potential HIV risk behaviors among young Asian-American women.

PubMed

Hahm, Hyeouk Chris; Lee, Jieha; Rough, Kathryn; Strathdee, Steffanie A

2012-01-01

We examined the prevalence of three domains of sexual behaviors among young Asian-American women: sexual experiences, safer sex practices, and potential HIV risk behaviors. We also investigated the impact of gender power control on these domains. Among sexually experienced women, 51% reported using condoms during their most recent sex act, 63% reported inconsistent condom use, and 18% reported ever having forced sex. Multiple logistic regression analyses revealed that women's perceived lower relationship power control was not associated with vaginal sex or safer sex practices, but it was powerfully associated with forced sex and all three potential HIV risk behaviors. This study demonstrates that control within young Asian-American women's intimate relationships exerts different associations depending on the type of sexual behavior. The application of the Theory of Gender and Power should be employed with prudence when designing HIV interventions for this population.

Predicting dermal penetration for Expocast chemicals using in silico approaches – should dermal metabolism be considered?

EPA Science Inventory

There are thousands of consumer product chemicals to which humans may be exposed to via direct (e.g. product use) or indirect (e.g. contact with contaminated media) pathways. The US EPA has developed a research program known as ExpoCast to predict exposures to give real-world con...

Contextual influences on safer sex negotiation among female sex workers (FSWs) in Hong Kong: the role of non-governmental organizations (NGOs), FSWs' managers, and clients.

PubMed

Cheng, Shannon S Y; Mak, Winnie W S

2010-05-01

Despite social-cognitive interventions to increase safer sex awareness, condom use among female sex workers (FSWs) continued to be inconsistent. To account for the possible influences of contextual factors that may hinder or promote FSWs' safer sex negotiation and condom use, the present study examined the effects of non-governmental organizations (NGOs), FSWs' managers, and clients on FSWs' negotiation efficacy and condom-use efficacy, and the effects of efficacy on condom use. One hundred and nineteen FSWs in Hong Kong completed a questionnaire that focused on their perceived influences of NGOs, managers, and clients toward safer sex negotiation and condom use. Hierarchical regression results showed that whereas NGOs' influence and clients' support were positively related to negotiation self-efficacy, managers' pressure, and clients' pressure were negatively related to negotiation self-efficacy. Managers' pressure was negatively related to condom-use self-efficacy. Logistic regression results showed that FSWs with high condom-use self-efficacy was 24 times more likely to use condom in the previous six months than their counterparts. The present study indicated the importance of social contexts in affecting FSWs' safer sex negotiation and condom-use self-efficacy. Implications on preventive programs for FSWs, managers, and clients were discussed.

Predictive Analytics for Safer Food Supply

USDA-ARS?s Scientific Manuscript database

Science based risk analysis improves the USDA Food Safety Inspection Service’s ability to combat threats to public health from food-borne illness by allowing the Agency to focus resources on hazards that pose the greatest risk. Innovative algorithms enable detection and containment of threat by an...

Multi-level Correlates of Safer Conception Methods Awareness and Attitudes Among Ugandan HIV Clients with Fertility Intentions.

PubMed

Wagner, Glenn J; Woldetsadik, Mahlet A; Beyeza-Kashesya, Jolly; Goggin, Kathy; Mindry, Deborah; Finocchario-Kessler, Sarah; Khanakwa, Sarah; Wanyenze, Rhoda K

2016-03-01

Many people living with HIV desire childbearing, but low cost safer conception methods (SCM) such as timed unprotected intercourse (TUI) and manual self-insemination (MSI) are rarely used. We examined awareness and attitudes towards SCM, and the correlates of these constructs among 400 HIV clients with fertility intentions in Uganda. Measures included awareness, self-efficacy, and motivation regarding SCM, as well as demographics, health management, partner and provider characteristics. Just over half knew that MSI (53%) and TUI (51%) reduced transmission risk during conception, and 15% knew of sperm washing and pre-exposure prophylaxis. In separate regression models for SCM awareness, motivation, and self-efficacy, nearly all independent correlates were related to the partner, including perceived willingness to use SCM, knowledge of respondent's HIV status, HIV-seropositivity, marriage and equality in decision making within the relationship. These findings suggest the importance of partners in promoting SCM use and partner inclusion in safer conception counselling.

Safer sex negotiation and its association with condom use among clients of female sex workers in Bangladesh.

PubMed

Kamal, S M Mostafa; Hassan, Che Hashim; Salikon, Roslan Hj

2015-03-01

This study examines safer sex negotiation and its association with condom use among clients of female sex workers (FSWs) in Bangladesh. Data were collected from 484 FSWs living in Dhaka city following a convenient sampling procedure. Overall, 47% of the clients were suggested to use condom during last sexual intercourse and 21% did so. Both bivariate and multivariable binary logistic regression analyses yielded significantly increased risk of negotiation for safer sex with clients among FSWs with higher education. The power bargaining significantly (P < .001) increased the risk of condom use by 2.15 times (95% confidence interval = 1.28-3.59). The odds of condom use were significantly higher among the FSWs with higher education, unmarried, hotel-based, and among those with higher level of HIV/AIDS-related knowledge. The Bangladeshi FSWs have little control over their profession. HIV prevention programs should aim to encourage FSWs through information, education, and communication program to insist on condom use among clients. © 2013 APJPH.

Prediction of Chemical Respiratory Sensitizers Using GARD, a Novel In Vitro Assay Based on a Genomic Biomarker Signature

PubMed Central

Albrekt, Ann-Sofie; Borrebaeck, Carl A. K.; Lindstedt, Malin

2015-01-01

Background Repeated exposure to certain low molecular weight (LMW) chemical compounds may result in development of allergic reactions in the skin or in the respiratory tract. In most cases, a certain LMW compound selectively sensitize the skin, giving rise to allergic contact dermatitis (ACD), or the respiratory tract, giving rise to occupational asthma (OA). To limit occurrence of allergic diseases, efforts are currently being made to develop predictive assays that accurately identify chemicals capable of inducing such reactions. However, while a few promising methods for prediction of skin sensitization have been described, to date no validated method, in vitro or in vivo, exists that is able to accurately classify chemicals as respiratory sensitizers. Results Recently, we presented the in vitro based Genomic Allergen Rapid Detection (GARD) assay as a novel testing strategy for classification of skin sensitizing chemicals based on measurement of a genomic biomarker signature. We have expanded the applicability domain of the GARD assay to classify also respiratory sensitizers by identifying a separate biomarker signature containing 389 differentially regulated genes for respiratory sensitizers in comparison to non-respiratory sensitizers. By using an independent data set in combination with supervised machine learning, we validated the assay, showing that the identified genomic biomarker is able to accurately classify respiratory sensitizers. Conclusions We have identified a genomic biomarker signature for classification of respiratory sensitizers. Combining this newly identified biomarker signature with our previously identified biomarker signature for classification of skin sensitizers, we have developed a novel in vitro testing strategy with a potent ability to predict both skin and respiratory sensitization in the same sample. PMID:25760038

Secrets and safety in the age of AIDS: does HIV disclosure lead to safer sex?

PubMed

Simoni, Jane M; Pantalone, David W

2004-01-01

To fuel the HIV/AIDS epidemic, HIV-seropositive individuals must interact unsafely with HIV-seronegative individuals. Research indicates that up to one third of individuals diagnosed with HIV continue to have unprotected sex, at times without informing partners, who may be of negative or unknown serostatus. Some research and public health interventions have focused on encouraging HIV-positive individuals to reveal their serostatus to their sexual partners, predicated upon the assumption that disclosure will increase the safety of subsequent sexual activity with informed partners. This review examines the empirical literature on disclosure of HIV status and subsequent sexual risk behaviors of HIV-positive individuals. Only 15 of the 23 studies reviewed provided data that allowed us to examine the association between disclosure and safer sex. Fewer still provided a methodologically sound analysis, and those that did provided conflicting results, often with significant effects limited to only 1 subgroup of participants. However, this failure to demonstrate a consistent association does not necessarily mean that disclosure is irrelevant to the practice of safer sex. We discuss limitations of the research to date and implications for policy and practice.

Toxicokinetic Triage for Environmental Chemicals.

PubMed

Wambaugh, John F; Wetmore, Barbara A; Pearce, Robert; Strope, Cory; Goldsmith, Rocky; Sluka, James P; Sedykh, Alexander; Tropsha, Alex; Bosgra, Sieto; Shah, Imran; Judson, Richard; Thomas, Russell S; Setzer, R Woodrow

2015-09-01

Toxicokinetic (TK) models link administered doses to plasma, blood, and tissue concentrations. High-throughput TK (HTTK) performs in vitro to in vivo extrapolation to predict TK from rapid in vitro measurements and chemical structure-based properties. A significant toxicological application of HTTK has been "reverse dosimetry," in which bioactive concentrations from in vitro screening studies are converted into in vivo doses (mg/kg BW/day). These doses are predicted to produce steady-state plasma concentrations that are equivalent to in vitro bioactive concentrations. In this study, we evaluate the impact of the approximations and assumptions necessary for reverse dosimetry and develop methods to determine whether HTTK tools are appropriate or may lead to false conclusions for a particular chemical. Based on literature in vivo data for 87 chemicals, we identified specific properties (eg, in vitro HTTK data, physico-chemical descriptors, and predicted transporter affinities) that correlate with poor HTTK predictive ability. For 271 chemicals we developed a generic HT physiologically based TK (HTPBTK) model that predicts non-steady-state chemical concentration time-courses for a variety of exposure scenarios. We used this HTPBTK model to find that assumptions previously used for reverse dosimetry are usually appropriate, except most notably for highly bioaccumulative compounds. For the thousands of man-made chemicals in the environment that currently have no TK data, we propose a 4-element framework for chemical TK triage that can group chemicals into 7 different categories associated with varying levels of confidence in HTTK predictions. For 349 chemicals with literature HTTK data, we differentiated those chemicals for which HTTK approaches are likely to be sufficient, from those that may require additional data. Published by Oxford University Press on behalf of Society of Toxicology 2015. This work is written by US Government employees and is in the public

Toxicokinetic Triage for Environmental Chemicals

PubMed Central

Wambaugh, John F.; Wetmore, Barbara A.; Pearce, Robert; Strope, Cory; Goldsmith, Rocky; Sluka, James P.; Sedykh, Alexander; Tropsha, Alex; Bosgra, Sieto; Shah, Imran; Judson, Richard; Thomas, Russell S.; Woodrow Setzer, R.

2015-01-01

Toxicokinetic (TK) models link administered doses to plasma, blood, and tissue concentrations. High-throughput TK (HTTK) performs in vitro to in vivo extrapolation to predict TK from rapid in vitro measurements and chemical structure-based properties. A significant toxicological application of HTTK has been “reverse dosimetry,” in which bioactive concentrations from in vitro screening studies are converted into in vivo doses (mg/kg BW/day). These doses are predicted to produce steady-state plasma concentrations that are equivalent to in vitro bioactive concentrations. In this study, we evaluate the impact of the approximations and assumptions necessary for reverse dosimetry and develop methods to determine whether HTTK tools are appropriate or may lead to false conclusions for a particular chemical. Based on literature in vivo data for 87 chemicals, we identified specific properties (eg, in vitro HTTK data, physico-chemical descriptors, and predicted transporter affinities) that correlate with poor HTTK predictive ability. For 271 chemicals we developed a generic HT physiologically based TK (HTPBTK) model that predicts non-steady-state chemical concentration time-courses for a variety of exposure scenarios. We used this HTPBTK model to find that assumptions previously used for reverse dosimetry are usually appropriate, except most notably for highly bioaccumulative compounds. For the thousands of man-made chemicals in the environment that currently have no TK data, we propose a 4-element framework for chemical TK triage that can group chemicals into 7 different categories associated with varying levels of confidence in HTTK predictions. For 349 chemicals with literature HTTK data, we differentiated those chemicals for which HTTK approaches are likely to be sufficient, from those that may require additional data. PMID:26085347

Chemical engineering challenges and investment opportunities in sustainable energy.

PubMed

Heller, Adam

2008-01-01

The chemical and energy industries are transforming as they adjust to the new era of high-priced petroleum and severe global warming. As a result of the transformation, engineering challenges and investment opportunities abound. Rapid evolution and fast growth are expected in cathode and anode materials as well as polymeric electrolytes for vehicular batteries and in high-performance polymer-ceramic composites for wind turbines, fuel-efficient aircraft, and lighter and safer cars. Unique process-engineering opportunities exist in sand-oil, coal, and possibly also shale liquefaction to produce transportation fuel; and also in genetic engineering of photosynthesizing plants and other organisms for their processing into high-performance biodegradable polymers and high-value-added environmentally friendly chemicals. Also, research on the feasibility of mitigation of global warming through enhancement of CO(2) uptake by the southern oceans by fertilization with trace amounts of iron is progressing. Because chemical engineers are uniquely well trained in mathematical modeling of mass transport, flow, and mixing, and also in cost analysis, they are likely to join the oceanographers and marine biologists in this important endeavor.

Development and evaluation of predictive model for bovine serum albumin-water partition coefficients of neutral organic chemicals.

PubMed

Ma, Guangcai; Yuan, Quan; Yu, Haiying; Lin, Hongjun; Chen, Jianrong; Hong, Huachang

2017-04-01

The binding of organic chemicals to serum albumin can significantly reduce their unbound concentration in blood and affect their biological reactions. In this study, we developed a new QSAR model for bovine serum albumin (BSA) - water partition coefficients (K BSA/W ) of neutral organic chemicals with large structural variance, logK BSA/W values covering 3.5 orders of magnitude (1.19-4.76). All chemical geometries were optimized by semi-empirical PM6 algorithm. Several quantum chemical parameters that reflect various intermolecular interactions as well as hydrophobicity were selected to develop QSAR model. The result indicates the regression model derived from logK ow , the most positive net atomic charges on an atom, Connolly solvent excluded volume, polarizability, and Abraham acidity could explain the partitioning mechanism of organic chemicals between BSA and water. The simulated external validation and cross validation verifies the developed model has good statistical robustness and predictive ability, thus can be used to estimate the logK BSA/W values for chemicals in application domain, accordingly to provide basic data for the toxicity assessment of the chemicals. Copyright © 2016 Elsevier Inc. All rights reserved.

On Demand Internal Short Circuit Device Enables Verification of Safer, Higher Performing Battery Designs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Darcy, Eric; Keyser, Matthew

The Internal Short Circuit (ISC) device enables critical battery safety verification. With the aluminum interstitial heat sink between the cells, normal trigger cells cannot be driven into thermal runaway without excessive temperature bias of adjacent cells. With an implantable, on-demand ISC device, thermal runaway tests show that the conductive heat sinks protected adjacent cells from propagation. High heat dissipation and structural support of Al heat sinks show high promise for safer, higher performing batteries.

Discovery of optimal zeolites for challenging separations and chemical conversions through predictive materials modeling

NASA Astrophysics Data System (ADS)

Siepmann, J. Ilja; Bai, Peng; Tsapatsis, Michael; Knight, Chris; Deem, Michael W.

2015-03-01

Zeolites play numerous important roles in modern petroleum refineries and have the potential to advance the production of fuels and chemical feedstocks from renewable resources. The performance of a zeolite as separation medium and catalyst depends on its framework structure and the type or location of active sites. To date, 213 framework types have been synthesized and >330000 thermodynamically accessible zeolite structures have been predicted. Hence, identification of optimal zeolites for a given application from the large pool of candidate structures is attractive for accelerating the pace of materials discovery. Here we identify, through a large-scale, multi-step computational screening process, promising zeolite structures for two energy-related applications: the purification of ethanol beyond the ethanol/water azeotropic concentration in a single separation step from fermentation broths and the hydroisomerization of alkanes with 18-30 carbon atoms encountered in petroleum refining. These results demonstrate that predictive modeling and data-driven science can now be applied to solve some of the most challenging separation problems involving highly non-ideal mixtures and highly articulated compounds. Financial support from the Department of Energy Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences under Award DE-FG02-12ER16362 is gratefully acknowledged.

Use of QR and EAN-13 codes by older patients taking multiple medications for a safer use of medication.

PubMed

Mira, José Joaquín; Guilabert, Mercedes; Carrillo, Irene; Fernández, César; Vicente, Ma Asunción; Orozco-Beltrán, Domingo; Gil-Guillen, Vicente F

2015-06-01

Older persons following a prolonged complex drug regimen often make mistakes when taking their medication. Currently, the widespread use of tablets and smartphones has encouraged the development of applications to support self-management of medication. The aim of this study was to design, develop and assess an app that transforms medication-associated ean-13 (barcodes) and Quick Response codes (QR) into verbal instructions, to enable safer use of medication by the elderly patients taking multiple medications. Meetings were held in which participated a total of 61 patients. The results showed that patients appreciated the application and found it useful for safer use of medicines. The study results support the use of such technology to increase patient safety taking multiple medications safety. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Predicting bioavailability of PAHs in soils to wheat roots with triolein-embedded cellulose acetate membranes and comparison with chemical extraction.

PubMed

Tao, Yuqiang; Zhang, Shuzhen; Wang, Zijian; Christie, Peter

2008-11-26

Triolein-embedded cellulose acetate membrane (TECAM) was buried in 15 field-contaminated soils in parallel with the cultivation of wheat to predict bioavailability of naphthalene, phenanthrene, pyrene, and benzo[a]pyrene to wheat roots, and the method was compared with chemical extraction methods. Although a good linear relationship was found between PAH concentrations in chemical extractants and wheat roots, the percentage of PAH in soil removed by chemical extraction was much higher than the corresponding percentage removed by wheat roots. In contrast to chemical extraction, a nearly 1:1 relationship was found between the amount of each PAH taken up by TECAMs and wheat roots (r(2) = 0.798-0.925, P < 0.01). Furthermore, the uptake of PAHs by TECAMs and wheat roots had the same pathway of passive transport via the soil solution. Moreover, TECAM caused minimal disturbance to the soil and was easy to deploy. Therefore, TECAM is believed to be a useful tool to predict bioavailability of PAHs to wheat roots grown in contaminated soils.

Predicting human skin absorption of chemicals: development of a novel quantitative structure activity relationship.

PubMed

Luo, Wen; Medrek, Sarah; Misra, Jatin; Nohynek, Gerhard J

2007-02-01

The objective of this study was to construct and validate a quantitative structure-activity relationship model for skin absorption. Such models are valuable tools for screening and prioritization in safety and efficacy evaluation, and risk assessment of drugs and chemicals. A database of 340 chemicals with percutaneous absorption was assembled. Two models were derived from the training set consisting 306 chemicals (90/10 random split). In addition to the experimental K(ow) values, over 300 2D and 3D atomic and molecular descriptors were analyzed using MDL's QsarIS computer program. Subsequently, the models were validated using both internal (leave-one-out) and external validation (test set) procedures. Using the stepwise regression analysis, three molecular descriptors were determined to have significant statistical correlation with K(p) (R2 = 0.8225): logK(ow), X0 (quantification of both molecular size and the degree of skeletal branching), and SsssCH (count of aromatic carbon groups). In conclusion, two models to estimate skin absorption were developed. When compared to other skin absorption QSAR models in the literature, our model incorporated more chemicals and explored a large number of descriptors. Additionally, our models are reasonably predictive and have met both internal and external statistical validations.

Prediction of Radical Scavenging Activities of Anthocyanins Applying Adaptive Neuro-Fuzzy Inference System (ANFIS) with Quantum Chemical Descriptors

PubMed Central

Jhin, Changho; Hwang, Keum Taek

2014-01-01

Radical scavenging activity of anthocyanins is well known, but only a few studies have been conducted by quantum chemical approach. The adaptive neuro-fuzzy inference system (ANFIS) is an effective technique for solving problems with uncertainty. The purpose of this study was to construct and evaluate quantitative structure-activity relationship (QSAR) models for predicting radical scavenging activities of anthocyanins with good prediction efficiency. ANFIS-applied QSAR models were developed by using quantum chemical descriptors of anthocyanins calculated by semi-empirical PM6 and PM7 methods. Electron affinity (A) and electronegativity (χ) of flavylium cation, and ionization potential (I) of quinoidal base were significantly correlated with radical scavenging activities of anthocyanins. These descriptors were used as independent variables for QSAR models. ANFIS models with two triangular-shaped input fuzzy functions for each independent variable were constructed and optimized by 100 learning epochs. The constructed models using descriptors calculated by both PM6 and PM7 had good prediction efficiency with Q-square of 0.82 and 0.86, respectively. PMID:25153627

Benchmark fragment-based 1H, 13C, 15N and 17O chemical shift predictions in molecular crystals†

PubMed Central

Hartman, Joshua D.; Kudla, Ryan A.; Day, Graeme M.; Mueller, Leonard J.; Beran, Gregory J. O.

2016-01-01

The performance of fragment-based ab initio 1H, 13C, 15N and 17O chemical shift predictions is assessed against experimental NMR chemical shift data in four benchmark sets of molecular crystals. Employing a variety of commonly used density functionals (PBE0, B3LYP, TPSSh, OPBE, PBE, TPSS), we explore the relative performance of cluster, two-body fragment, and combined cluster/fragment models. The hybrid density functionals (PBE0, B3LYP and TPSSh) generally out-perform their generalized gradient approximation (GGA)-based counterparts. 1H, 13C, 15N, and 17O isotropic chemical shifts can be predicted with root-mean-square errors of 0.3, 1.5, 4.2, and 9.8 ppm, respectively, using a computationally inexpensive electrostatically embedded two-body PBE0 fragment model. Oxygen chemical shieldings prove particularly sensitive to local many-body effects, and using a combined cluster/fragment model instead of the simple two-body fragment model decreases the root-mean-square errors to 7.6 ppm. These fragment-based model errors compare favorably with GIPAW PBE ones of 0.4, 2.2, 5.4, and 7.2 ppm for the same 1H, 13C, 15N, and 17O test sets. Using these benchmark calculations, a set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided and their robustness assessed using statistical cross-validation. We demonstrate the utility of these approaches and the reported scaling parameters on applications to 9-tertbutyl anthracene, several histidine co-crystals, benzoic acid and the C-nitrosoarene SnCl2(CH3)2(NODMA)2. PMID:27431490

Benchmark fragment-based (1)H, (13)C, (15)N and (17)O chemical shift predictions in molecular crystals.

PubMed

Hartman, Joshua D; Kudla, Ryan A; Day, Graeme M; Mueller, Leonard J; Beran, Gregory J O

2016-08-21

The performance of fragment-based ab initio(1)H, (13)C, (15)N and (17)O chemical shift predictions is assessed against experimental NMR chemical shift data in four benchmark sets of molecular crystals. Employing a variety of commonly used density functionals (PBE0, B3LYP, TPSSh, OPBE, PBE, TPSS), we explore the relative performance of cluster, two-body fragment, and combined cluster/fragment models. The hybrid density functionals (PBE0, B3LYP and TPSSh) generally out-perform their generalized gradient approximation (GGA)-based counterparts. (1)H, (13)C, (15)N, and (17)O isotropic chemical shifts can be predicted with root-mean-square errors of 0.3, 1.5, 4.2, and 9.8 ppm, respectively, using a computationally inexpensive electrostatically embedded two-body PBE0 fragment model. Oxygen chemical shieldings prove particularly sensitive to local many-body effects, and using a combined cluster/fragment model instead of the simple two-body fragment model decreases the root-mean-square errors to 7.6 ppm. These fragment-based model errors compare favorably with GIPAW PBE ones of 0.4, 2.2, 5.4, and 7.2 ppm for the same (1)H, (13)C, (15)N, and (17)O test sets. Using these benchmark calculations, a set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided and their robustness assessed using statistical cross-validation. We demonstrate the utility of these approaches and the reported scaling parameters on applications to 9-tert-butyl anthracene, several histidine co-crystals, benzoic acid and the C-nitrosoarene SnCl2(CH3)2(NODMA)2.

An Assessment of the Model of Concentration Addition for Predicting the Estrogenic Activity of Chemical Mixtures in Wastewater Treatment Works Effluents

PubMed Central

Thorpe, Karen L.; Gross-Sorokin, Melanie; Johnson, Ian; Brighty, Geoff; Tyler, Charles R.

2006-01-01

The effects of simple mixtures of chemicals, with similar mechanisms of action, can be predicted using the concentration addition model (CA). The ability of this model to predict the estrogenic effects of more complex mixtures such as effluent discharges, however, has yet to be established. Effluents from 43 U.K. wastewater treatment works were analyzed for the presence of the principal estrogenic chemical contaminants, estradiol, estrone, ethinylestradiol, and nonylphenol. The measured concentrations were used to predict the estrogenic activity of each effluent, employing the model of CA, based on the relative potencies of the individual chemicals in an in vitro recombinant yeast estrogen screen (rYES) and a short-term (14-day) in vivo rainbow trout vitellogenin induction assay. Based on the measured concentrations of the four chemicals in the effluents and their relative potencies in each assay, the calculated in vitro and in vivo responses compared well and ranged between 3.5 and 87 ng/L of estradiol equivalents (E2 EQ) for the different effluents. In the rYES, however, the measured E2 EQ concentrations in the effluents ranged between 0.65 and 43 ng E2 EQ/L, and they varied against those predicted by the CA model. Deviations in the estimation of the estrogenic potency of the effluents by the CA model, compared with the measured responses in the rYES, are likely to have resulted from inaccuracies associated with the measurement of the chemicals in the extracts derived from the complex effluents. Such deviations could also result as a consequence of interactions between chemicals present in the extracts that disrupted the activation of the estrogen response elements in the rYES. E2 EQ concentrations derived from the vitellogenic response in fathead minnows exposed to a series of effluent dilutions were highly comparable with the E2 EQ concentrations derived from assessments of the estrogenic potency of these dilutions in the rYES. Together these data support the

Gender Power Control, Sexual Experiences, Safer Sex Practices, and Potential HIV Risk Behaviors Among Young Asian-American Women

PubMed Central

Lee, Jieha; Rough, Kathryn; Strathdee, Steffanie A.

2012-01-01

We examined the prevalence of three domains of sexual behaviors among young Asian-American women: sexual experiences, safer sex practices, and potential HIV risk behaviors. We also investigated the impact of gender power control on these domains. Among sexually experienced women, 51% reported using condoms during their most recent sex act, 63% reported inconsistent condom use, and 18% reported ever having forced sex. Multiple logistic regression analyses revealed that women’s perceived lower relationship power control was not associated with vaginal sex or safer sex practices, but it was powerfully associated with forced sex and all three potential HIV risk behaviors. This study demonstrates that control within young Asian-American women’s intimate relationships exerts different associations depending on the type of sexual behavior. The application of the Theory of Gender and Power should be employed with prudence when designing HIV interventions for this population. PMID:21259042

PREDICTING CHRONIC LETHALITY OF CHEMICALS TO FISHES FROM ACUTE TOXICITY TEST DATA: THEORY OF ACCELERATED LIFE TESTING

EPA Science Inventory

A method for modeling aquatic toxicity date based on the theory of accelerated life testing and a procedure for maximum likelihood fitting the proposed model is presented. he procedure is computerized as software, which can predict chronic lethality of chemicals using data from a...

EFFECTS OF USING THE CB05 VS SAPRC 99 VS CB4 CHEMICAL MECHANISMS ON MODEL PREDICTIONS

EPA Science Inventory

In this study, we examine differences in predictions of ozone, other oxidants, and ozone precursors for 3 chemical mechanisms: the CB4, CB05 and SAPRC99 mechanism (CMAQ/Models3 version). We present results for current conditions and differences among the mechanisms with emission...

Use of fish embryo toxicity tests for the prediction of acute fish toxicity to chemicals.

PubMed

Belanger, Scott E; Rawlings, Jane M; Carr, Gregory J

2013-08-01

The fish embryo test (FET) is a potential animal alternative for the acute fish toxicity (AFT) test. A comprehensive validation program assessed 20 different chemicals to understand intra- and interlaboratory variability for the FET. The FET had sufficient reproducibility across a range of potencies and modes of action. In the present study, the suitability of the FET as an alternative model is reviewed by relating FET and AFT. In total, 985 FET studies and 1531 AFT studies were summarized. The authors performed FET-AFT regressions to understand potential relationships based on physical-chemical properties, species choices, duration of exposure, chemical classes, chemical functional uses, and modes of action. The FET-AFT relationships are very robust (slopes near 1.0, intercepts near 0) across 9 orders of magnitude in potency. A recommendation for the predictive regression relationship is based on 96-h FET and AFT data: log FET median lethal concentration (LC50) = (0.989 × log fish LC50) - 0.195; n = 72 chemicals, r = 0.95, p < 0.001, LC50 in mg/L. A similar, not statistically different regression was developed for the entire data set (n = 144 chemicals, unreliable studies deleted). The FET-AFT regressions were robust for major chemical classes with suitably large data sets. Furthermore, regressions were similar to those for large groups of functional chemical categories such as pesticides, surfactants, and industrial organics. Pharmaceutical regressions (n = 8 studies only) were directionally correct. The FET-AFT relationships were not quantitatively different from acute fish-acute fish toxicity relationships with the following species: fathead minnow, rainbow trout, bluegill sunfish, Japanese medaka, and zebrafish. The FET is scientifically supportable as a rational animal alternative model for ecotoxicological testing of acute toxicity of chemicals to fish. Copyright © 2013 SETAC.

Misperceptions regarding protective barrier method use for safer sex among African-American women who have sex with women.

PubMed

Muzny, Christina A; Harbison, Hanne S; Pembleton, Elizabeth S; Hook, Edward W; Austin, Erika L

2013-05-01

Barrier methods for HIV and sexually transmissible infection (STI) prevention among women who have sex with women (WSW) are available, although their effectiveness has not been systematically investigated. These methods are infrequently used by WSW. As part of a larger study on STI risk perceptions and safer sex among African-American WSW, we discovered several misperceptions regarding barrier methods that may be associated with their limited use. Participants were recruited from the Jefferson County Health Department STI Clinic and through word of mouth in Birmingham, Alabama, for focus group discussions exploring perceptions of STI risk and safer sex. Seven focus groups with 29 participants were conducted (age range: 19-43 years). Several misperceptions regarding barrier methods were identified, notably the conflation of dental dams and female condoms. Descriptions of the use of barrier methods were qualified with phrases suggesting their hypothetical, rather than actual, use. Additional evidence that barrier methods are not actually used came from beliefs that dental dams and female condoms are available in major grocery stores or department store chains. Those providing sexual health services to WSW should be cautious in assuming that WSW have accurate information regarding barrier methods for safer sex. Sexual health services provided to WSW should include an accurate description of what barrier methods are, how to distinguish them from barrier methods more commonly used during heterosexual sex (female and male condoms), and how to use them correctly. Future studies are needed to address how effectively these measures reduce transmission of STIs among WSW.

A Peer-Led, Social Media-Delivered, Safer Sex Intervention for Chinese College Students: Randomized Controlled Trial

PubMed Central

Sun, Wai Han; Wong, Carlos King Ho

2017-01-01

Background The peer-led, social media-delivered intervention is an emerging method in sexual health promotion. However, no research has yet investigated its effectiveness as compared with other online channels or in an Asian population. Objective The objective of this study is to compare a peer-led, social media-delivered, safer sex intervention with a sexual health website. Both conditions target Chinese college students in Hong Kong. Methods A randomized controlled trial was conducted with a peer-led, safer sex Facebook group as the intervention and an existing online sexual health website as the control. The intervention materials were developed with peer input and followed the information-motivation-behavioral skills model; the intervention was moderated by peer educators. The participants filled out the online questionnaires before and after the 6-week intervention period. Outcome evaluations included safer sex attitudes, behavioral skills, and behaviors, while process evaluation focused on online experience, online-visiting frequency, and online engagement. The effect of online-visiting frequency and online engagement on outcome variables was investigated. Results Of 196 eligible participants—100 in the control group and 96 in the intervention group—who joined the study, 2 (1.0%) control participants joined the Facebook group and 24 of the remaining 194 participants (12.4%) were lost to follow-up. For the process evaluation, participants in the intervention group reported more satisfying online experiences (P<.001) and a higher level of online-visiting frequency (P<.001). They also had more positive comments when compared with the control group. For outcome evaluation, within-group analysis showed significant improvement in condom use attitude (P=.02) and behavioral skills (P<.001) in the intervention group, but not in the control group. No significant between-group difference was found. After adjusting for demographic data, increased online

InP/ZnS as a safer alternative to CdSe/ZnS core/shell quantum dots: in vitro and in vivo toxicity assessment

NASA Astrophysics Data System (ADS)

Brunetti, Virgilio; Chibli, Hicham; Fiammengo, Roberto; Galeone, Antonio; Malvindi, Maria Ada; Vecchio, Giuseppe; Cingolani, Roberto; Nadeau, Jay L.; Pompa, Pier Paolo

2012-12-01

We show that water soluble InP/ZnS core/shell QDs are a safer alternative to CdSe/ZnS QDs for biological applications, by comparing their toxicity in vitro (cell culture) and in vivo (animal model Drosophila). By choosing QDs with comparable physical and chemical properties, we find that cellular uptake and localization are practically identical for these two nanomaterials. Toxicity of CdSe/ZnS QDs appears to be related to the release of poisonous Cd2+ ions and indeed we show that there is leaching of Cd2+ ions from the particle core despite the two-layer ZnS shell. Since an almost identical amount of In(iii) ions is observed to leach from the core of InP/ZnS QDs, their very low toxicity as revealed in this study hints at a much lower intrinsic toxicity of indium compared to cadmium.

InP/ZnS as a safer alternative to CdSe/ZnS core/shell quantum dots: in vitro and in vivo toxicity assessment.

PubMed

Brunetti, Virgilio; Chibli, Hicham; Fiammengo, Roberto; Galeone, Antonio; Malvindi, Maria Ada; Vecchio, Giuseppe; Cingolani, Roberto; Nadeau, Jay L; Pompa, Pier Paolo

2013-01-07

We show that water soluble InP/ZnS core/shell QDs are a safer alternative to CdSe/ZnS QDs for biological applications, by comparing their toxicity in vitro (cell culture) and in vivo (animal model Drosophila). By choosing QDs with comparable physical and chemical properties, we find that cellular uptake and localization are practically identical for these two nanomaterials. Toxicity of CdSe/ZnS QDs appears to be related to the release of poisonous Cd(2+) ions and indeed we show that there is leaching of Cd(2+) ions from the particle core despite the two-layer ZnS shell. Since an almost identical amount of In(III) ions is observed to leach from the core of InP/ZnS QDs, their very low toxicity as revealed in this study hints at a much lower intrinsic toxicity of indium compared to cadmium.

Using ToxCast in vitro Assays in the Hierarchical Quantitative Structure-Activity Relationship (QSAR) Modeling for Predicting in vivo Toxicity of Chemicals

EPA Science Inventory

The goal of chemical toxicology research is utilizing short term bioassays and/or robust computational methods to predict in vivo toxicity endpoints for chemicals. The ToxCast program established at the US Environmental Protection Agency (EPA) is addressing this goal by using ca....

Antiretrovirals and safer conception for HIV-serodiscordant couples

PubMed Central

Matthews, Lynn T.; Smit, Jennifer A.; Cu-Uvin, Susan; Cohan, Deborah

2013-01-01

Purpose of review Many men and women living with HIV and their uninfected partners attempt to conceive children. HIV-prevention science can be applied to reduce sexual transmission risk while respecting couples’ reproductive goals. Here we discuss antiretrovirals as prevention in the context of safer conception for HIV-serodiscordant couples. Recent findings Antiretroviral therapy (ART) for the infected partner and pre-exposure prophylaxis (PrEP) for the uninfected partner reduce the risk of heterosexual HIV transmission. Several demonstration projects suggest the feasibility and acceptability of antiretroviral (ARV)s as periconception HIV-prevention for HIV-serodiscordant couples. The application of ARVs to periconception risk reduction may be limited by adherence. Summary For male-infected (M+F−) couples who cannot access sperm processing and female-infected (F+M−) couples unwilling to carry out insemination without intercourse, ART for the infected partner, PrEP for the uninfected partner, combined with treatment for sexually transmitted infections, sex limited to peak fertility, and medical male circumcision (for F+M couples) provide excellent, well tolerated options for reducing the risk of periconception HIV sexual transmission. PMID:23032734

Classification and prediction of toxicity of chemicals using an automated phenotypic profiling of Caenorhabditis elegans.

PubMed

Gao, Shan; Chen, Weiyang; Zeng, Yingxin; Jing, Haiming; Zhang, Nan; Flavel, Matthew; Jois, Markandeya; Han, Jing-Dong J; Xian, Bo; Li, Guojun

2018-04-18

Traditional toxicological studies have relied heavily on various animal models to understand the effect of various compounds in a biological context. Considering the great cost, complexity and time involved in experiments using higher order organisms. Researchers have been exploring alternative models that avoid these disadvantages. One example of such a model is the nematode Caenorhabditis elegans. There are some advantages of C. elegans, such as small size, short life cycle, well defined genome, ease of maintenance and efficient reproduction. As these benefits allow large scale studies to be initiated with relative ease, the problem of how to efficiently capture, organize and analyze the resulting large volumes of data must be addressed. We have developed a new method for quantitative screening of chemicals using C. elegans. 33 features were identified for each chemical treatment. The compounds with different toxicities were shown to alter the phenotypes of C. elegans in distinct and detectable patterns. We found that phenotypic profiling revealed conserved functions to classify and predict the toxicity of different chemicals. Our results demonstrate the power of phenotypic profiling in C. elegans under different chemical environments.

Toxicity challenges in environmental chemicals: Prediction of human plasma protein binding through quantitative structure-activity relationship (QSAR) models

EPA Science Inventory

The present study explores the merit of utilizing available pharmaceutical data to construct a quantitative structure-activity relationship (QSAR) for prediction of the fraction of a chemical unbound to plasma protein (Fub) in environmentally relevant compounds. Independent model...

Efficient Phosphorus Cycling in Food Production: Predicting the Phosphorus Fertilization Effect of Sludge from Chemical Wastewater Treatment.

PubMed

Falk Øgaard, Anne; Brod, Eva

2016-06-22

This study examined the P fertilization effects of 11 sewage sludges obtained from sewage treated with Al and/or Fe salts to remove P by a pot experiment with ryegrass (Lolium multiflorum) and a nutrient-deficient sand-peat mixture. Also it investigated whether fertilization effects could be predicted by chemical sludge characteristics and/or by P extraction. The mineral fertilizer equivalent (MFE) value varied significantly but was low for all sludges. MFE was best predicted by a negative correlation with ox-Al and ox-Fe in sludge, or by a positive correlation with P extracted with 2% citric acid. Ox-Al had a greater negative impact on MFE than ox-Fe, indicating that Fe salts are preferable as a coagulant when aiming to increase the plant availability of P in sludge. The results also indicate that sludge liming after chemical wastewater treatment with Al and/or Fe salts increases the P fertilization effect.

Room-temperature and temperature-dependent QSRR modelling for predicting the nitrate radical reaction rate constants of organic chemicals using ensemble learning methods.

PubMed

Gupta, S; Basant, N; Mohan, D; Singh, K P

2016-07-01

Experimental determinations of the rate constants of the reaction of NO3 with a large number of organic chemicals are tedious, and time and resource intensive; and the development of computational methods has widely been advocated. In this study, we have developed room-temperature (298 K) and temperature-dependent quantitative structure-reactivity relationship (QSRR) models based on the ensemble learning approaches (decision tree forest (DTF) and decision treeboost (DTB)) for predicting the rate constant of the reaction of NO3 radicals with diverse organic chemicals, under OECD guidelines. Predictive powers of the developed models were established in terms of statistical coefficients. In the test phase, the QSRR models yielded a correlation (r(2)) of >0.94 between experimental and predicted rate constants. The applicability domains of the constructed models were determined. An attempt has been made to provide the mechanistic interpretation of the selected features for QSRR development. The proposed QSRR models outperformed the previous reports, and the temperature-dependent models offered a much wider applicability domain. This is the first report presenting a temperature-dependent QSRR model for predicting the nitrate radical reaction rate constant at different temperatures. The proposed models can be useful tools in predicting the reactivities of chemicals towards NO3 radicals in the atmosphere, hence, their persistence and exposure risk assessment.

Uniting Cheminformatics and Chemical Theory To Predict the Intrinsic Aqueous Solubility of Crystalline Druglike Molecules

PubMed Central

2014-01-01

We present four models of solution free-energy prediction for druglike molecules utilizing cheminformatics descriptors and theoretically calculated thermodynamic values. We make predictions of solution free energy using physics-based theory alone and using machine learning/quantitative structure–property relationship (QSPR) models. We also develop machine learning models where the theoretical energies and cheminformatics descriptors are used as combined input. These models are used to predict solvation free energy. While direct theoretical calculation does not give accurate results in this approach, machine learning is able to give predictions with a root mean squared error (RMSE) of ∼1.1 log S units in a 10-fold cross-validation for our Drug-Like-Solubility-100 (DLS-100) dataset of 100 druglike molecules. We find that a model built using energy terms from our theoretical methodology as descriptors is marginally less predictive than one built on Chemistry Development Kit (CDK) descriptors. Combining both sets of descriptors allows a further but very modest improvement in the predictions. However, in some cases, this is a statistically significant enhancement. These results suggest that there is little complementarity between the chemical information provided by these two sets of descriptors, despite their different sources and methods of calculation. Our machine learning models are also able to predict the well-known Solubility Challenge dataset with an RMSE value of 0.9–1.0 log S units. PMID:24564264

In silico assessment of the acute toxicity of chemicals: recent advances and new model for multitasking prediction of toxic effect.

PubMed

Kleandrova, Valeria V; Luan, Feng; Speck-Planche, Alejandro; Cordeiro, M Natália D S

2015-01-01

The assessment of acute toxicity is one of the most important stages to ensure the safety of chemicals with potential applications in pharmaceutical sciences, biomedical research, or any other industrial branch. A huge and indiscriminate number of toxicity assays have been carried out on laboratory animals. In this sense, computational approaches involving models based on quantitative-structure activity/toxicity relationships (QSAR/QSTR) can help to rationalize time and financial costs. Here, we discuss the most significant advances in the last 6 years focused on the use of QSAR/QSTR models to predict acute toxicity of drugs/chemicals in laboratory animals, employing large and heterogeneous datasets. The advantages and drawbacks of the different QSAR/QSTR models are analyzed. As a contribution to the field, we introduce the first multitasking (mtk) QSTR model for simultaneous prediction of acute toxicity of compounds by considering different routes of administration, diverse breeds of laboratory animals, and the reliability of the experimental conditions. The mtk-QSTR model was based on artificial neural networks (ANN), allowing the classification of compounds as toxic or non-toxic. This model correctly classified more than 94% of the 1646 cases present in the whole dataset, and its applicability was demonstrated by performing predictions of different chemicals such as drugs, dietary supplements, and molecules which could serve as nanocarriers for drug delivery. The predictions given by the mtk-QSTR model are in very good agreement with the experimental results.

Does the real-time ultrasound guidance provide safer venipuncture in implantable venous port implantation?

PubMed

Yıldırım, İlknur; Tütüncü, Ayşe Çiğdem; Bademler, Süleyman; Özgür, İlker; Demiray, Mukaddes; Karanlık, Hasan

2018-03-01

To examine whether the real-time ultrasound-guided venipuncture for implantable venous port placement is safer than the traditional venipuncture. The study analyzed the results of 2153 venous ports placed consecutively from January 2009 to January 2016. A total of 922 patients in group 1 and 1231 patients in group 2 were admitted with venous port placed using the traditional landmark subclavian approach and real-time ultrasound-guided axillary approach, respectively. Sociodemographic characteristics of patients, early (pneumothorax, pinch-off syndrome, arterial puncture, hematoma, and malposition arrhythmia) and late (deep vein thrombosis, obstruction, infection, erosion-dehiscence, and rotation of the port chamber) complications and the association of these complications with the implantation method were evaluated. There were no significant differences in the sociodemographic characteristics of the patients between the two groups. The overall and early complications in group 2 were significantly lower than those in group 1. Pinch-off syndrome only developed in group 1. Seven patients and two patients had pneumothorax in groups 1 and 2, respectively. Puncture number was significantly associated with the development of the overall complications. The ultrasound-guided axillary approach may be preferred as a method to reduce the risk of both early and late complications. Large, randomized, controlled prospective trials will be helpful in determining a safer implantable venous port implantation technique.

Toward a Public Toxicogenomics Capability for Supporting Predictive Toxicology: Survey of Current Resources and Chemical Indexing of Experiments in GEO and ArrayExpress

EPA Science Inventory

A publicly available toxicogenomics capability for supporting predictive toxicology and meta-analysis depends on availability of gene expression data for chemical treatment scenarios, the ability to locate and aggregate such information by chemical, and broad data coverage within...

Development of a model for predicting reaction rate constants of organic chemicals with ozone at different temperatures.

PubMed

Li, Xuehua; Zhao, Wenxing; Li, Jing; Jiang, Jingqiu; Chen, Jianji; Chen, Jingwen

2013-08-01

To assess the persistence and fate of volatile organic compounds in the troposphere, the rate constants for the reaction with ozone (kO3) are needed. As kO3 values are only available for hundreds of compounds, and experimental determination of kO3 is costly and time-consuming, it is of importance to develop predictive models on kO3. In this study, a total of 379 logkO3 values at different temperatures were used to develop and validate a model for the prediction of kO3, based on quantum chemical descriptors, Dragon descriptors and structural fragments. Molecular descriptors were screened by stepwise multiple linear regression, and the model was constructed by partial least-squares regression. The cross validation coefficient QCUM(2) of the model is 0.836, and the external validation coefficient Qext(2) is 0.811, indicating that the model has high robustness and good predictive performance. The most significant descriptor explaining logkO3 is the BELm2 descriptor with connectivity information weighted atomic masses. kO3 increases with increasing BELm2, and decreases with increasing ionization potential. The applicability domain of the proposed model was visualized by the Williams plot. The developed model can be used to predict kO3 at different temperatures for a wide range of organic chemicals, including alkenes, cycloalkenes, haloalkenes, alkynes, oxygen-containing compounds, nitrogen-containing compounds (except primary amines) and aromatic compounds. Copyright © 2013 Elsevier Ltd. All rights reserved.

In Silico Prediction for Intestinal Absorption and Brain Penetration of Chemical Pesticides in Humans.

PubMed

Chedik, Lisa; Mias-Lucquin, Dominique; Bruyere, Arnaud; Fardel, Olivier

2017-06-30

Intestinal absorption and brain permeation constitute key parameters of toxicokinetics for pesticides, conditioning their toxicity, including neurotoxicity. However, they remain poorly characterized in humans. The present study was therefore designed to evaluate human intestine and brain permeation for a large set of pesticides ( n = 338) belonging to various chemical classes, using an in silico graphical BOILED-Egg/SwissADME online method based on lipophilicity and polarity that was initially developed for drugs. A high percentage of the pesticides (81.4%) was predicted to exhibit high intestinal absorption, with a high accuracy (96%), whereas a lower, but substantial, percentage (38.5%) displayed brain permeation. Among the pesticide classes, organochlorines ( n = 30) constitute the class with the lowest percentage of intestine-permeant members (40%), whereas that of the organophosphorus compounds ( n = 99) has the lowest percentage of brain-permeant chemicals (9%). The predictions of the permeations for the pesticides were additionally shown to be significantly associated with various molecular descriptors well-known to discriminate between permeant and non-permeant drugs. Overall, our in silico data suggest that human exposure to pesticides through the oral way is likely to result in an intake of these dietary contaminants for most of them and brain permeation for some of them, thus supporting the idea that they have toxic effects on human health, including neurotoxic effects.

In Silico Prediction for Intestinal Absorption and Brain Penetration of Chemical Pesticides in Humans

PubMed Central

Chedik, Lisa; Mias-Lucquin, Dominique; Bruyere, Arnaud; Fardel, Olivier

2017-01-01

Intestinal absorption and brain permeation constitute key parameters of toxicokinetics for pesticides, conditioning their toxicity, including neurotoxicity. However, they remain poorly characterized in humans. The present study was therefore designed to evaluate human intestine and brain permeation for a large set of pesticides (n = 338) belonging to various chemical classes, using an in silico graphical BOILED-Egg/SwissADME online method based on lipophilicity and polarity that was initially developed for drugs. A high percentage of the pesticides (81.4%) was predicted to exhibit high intestinal absorption, with a high accuracy (96%), whereas a lower, but substantial, percentage (38.5%) displayed brain permeation. Among the pesticide classes, organochlorines (n = 30) constitute the class with the lowest percentage of intestine-permeant members (40%), whereas that of the organophosphorus compounds (n = 99) has the lowest percentage of brain-permeant chemicals (9%). The predictions of the permeations for the pesticides were additionally shown to be significantly associated with various molecular descriptors well-known to discriminate between permeant and non-permeant drugs. Overall, our in silico data suggest that human exposure to pesticides through the oral way is likely to result in an intake of these dietary contaminants for most of them and brain permeation for some of them, thus supporting the idea that they have toxic effects on human health, including neurotoxic effects. PMID:28665355

Toward a public toxicogenomics capability for supporting predictive toxicology: survey of current resources and chemical indexing of experiments in GEO and ArrayExpress.

PubMed

Williams-Devane, ClarLynda R; Wolf, Maritja A; Richard, Ann M

2009-06-01

A publicly available toxicogenomics capability for supporting predictive toxicology and meta-analysis depends on availability of gene expression data for chemical treatment scenarios, the ability to locate and aggregate such information by chemical, and broad data coverage within chemical, genomics, and toxicological information domains. This capability also depends on common genomics standards, protocol description, and functional linkages of diverse public Internet data resources. We present a survey of public genomics resources from these vantage points and conclude that, despite progress in many areas, the current state of the majority of public microarray databases is inadequate for supporting these objectives, particularly with regard to chemical indexing. To begin to address these inadequacies, we focus chemical annotation efforts on experimental content contained in the two primary public genomic resources: ArrayExpress and Gene Expression Omnibus. Automated scripts and extensive manual review were employed to transform free-text experiment descriptions into a standardized, chemically indexed inventory of experiments in both resources. These files, which include top-level summary annotations, allow for identification of current chemical-associated experimental content, as well as chemical-exposure-related (or "Treatment") content of greatest potential value to toxicogenomics investigation. With these chemical-index files, it is possible for the first time to assess the breadth and overlap of chemical study space represented in these databases, and to begin to assess the sufficiency of data with shared protocols for chemical similarity inferences. Chemical indexing of public genomics databases is a first important step toward integrating chemical, toxicological and genomics data into predictive toxicology.

Biological networks for predicting chemical hepatocarcinogenicity using gene expression data from treated mice and relevance across human and rat species.

PubMed

Thomas, Reuben; Thomas, Russell S; Auerbach, Scott S; Portier, Christopher J

2013-01-01

Several groups have employed genomic data from subchronic chemical toxicity studies in rodents (90 days) to derive gene-centric predictors of chronic toxicity and carcinogenicity. Genes are annotated to belong to biological processes or molecular pathways that are mechanistically well understood and are described in public databases. To develop a molecular pathway-based prediction model of long term hepatocarcinogenicity using 90-day gene expression data and to evaluate the performance of this model with respect to both intra-species, dose-dependent and cross-species predictions. Genome-wide hepatic mRNA expression was retrospectively measured in B6C3F1 mice following subchronic exposure to twenty-six (26) chemicals (10 were positive, 2 equivocal and 14 negative for liver tumors) previously studied by the US National Toxicology Program. Using these data, a pathway-based predictor model for long-term liver cancer risk was derived using random forests. The prediction model was independently validated on test sets associated with liver cancer risk obtained from mice, rats and humans. Using 5-fold cross validation, the developed prediction model had reasonable predictive performance with the area under receiver-operator curve (AUC) equal to 0.66. The developed prediction model was then used to extrapolate the results to data associated with rat and human liver cancer. The extrapolated model worked well for both extrapolated species (AUC value of 0.74 for rats and 0.91 for humans). The prediction models implied a balanced interplay between all pathway responses leading to carcinogenicity predictions. Pathway-based prediction models estimated from sub-chronic data hold promise for predicting long-term carcinogenicity and also for its ability to extrapolate results across multiple species.

Chemical reaction vector embeddings: towards predicting drug metabolism in the human gut microbiome.

PubMed

Mallory, Emily K; Acharya, Ambika; Rensi, Stefano E; Turnbaugh, Peter J; Bright, Roselie A; Altman, Russ B

2018-01-01

Bacteria in the human gut have the ability to activate, inactivate, and reactivate drugs with both intended and unintended effects. For example, the drug digoxin is reduced to the inactive metabolite dihydrodigoxin by the gut Actinobacterium E. lenta, and patients colonized with high levels of drug metabolizing strains may have limited response to the drug. Understanding the complete space of drugs that are metabolized by the human gut microbiome is critical for predicting bacteria-drug relationships and their effects on individual patient response. Discovery and validation of drug metabolism via bacterial enzymes has yielded >50 drugs after nearly a century of experimental research. However, there are limited computational tools for screening drugs for potential metabolism by the gut microbiome. We developed a pipeline for comparing and characterizing chemical transformations using continuous vector representations of molecular structure learned using unsupervised representation learning. We applied this pipeline to chemical reaction data from MetaCyc to characterize the utility of vector representations for chemical reaction transformations. After clustering molecular and reaction vectors, we performed enrichment analyses and queries to characterize the space. We detected enriched enzyme names, Gene Ontology terms, and Enzyme Consortium (EC) classes within reaction clusters. In addition, we queried reactions against drug-metabolite transformations known to be metabolized by the human gut microbiome. The top results for these known drug transformations contained similar substructure modifications to the original drug pair. This work enables high throughput screening of drugs and their resulting metabolites against chemical reactions common to gut bacteria.

Camel Milk Is a Safer Choice than Goat Milk for Feeding Children with Cow Milk Allergy

PubMed Central

Ehlayel, Mohammad; Bener, Abdulbari; Abu Hazeima, Khalid; Al-Mesaifri, Fatima

2011-01-01

Background. Various sources of mammalian milk have been tried in CMA. Objectives. To determine whether camel milk is safer than goat milk in CMA. Methods. Prospective study conducted at Hamad Medical Corporation between April 2007 and April 2010, on children with CMA. Each child had medical examination, CBC, total IgE, cow milk-specific IgE and SPT. CMA children were tested against fresh camel and goat milks. Results. Of 38 children (median age 21.5 months), 21 (55.3%) presented with urticaria, 17 (39.5%) atopic dermatitis, 10 (26.3%) anaphylaxis. WBC was 10, 039 ± 4, 735 cells/μL, eosinophil 1, 143 ± 2, 213 cells/μL, IgE 694 ± 921 IU/mL, cow's milk-specific-IgE 23.5 ± 35.6 KU/L. Only 7 children (18.4%) tested positive to camel milk and 24 (63.2%) to goat milk. 6 (15.8%) were positive to camel, goat, and cow milks. Patients with negative SPT tolerated well camel and goat milks. Conclusions. In CMA, SPT indicates low cross-reactivity between camel milk and cow milk, and camel milk is a safer alternative than goat milk. PMID:23724227

Predicted Biological Activity of Purchasable Chemical Space

PubMed Central

2017-01-01

Whereas 400 million distinct compounds are now purchasable within the span of a few weeks, the biological activities of most are unknown. To facilitate access to new chemistry for biology, we have combined the Similarity Ensemble Approach (SEA) with the maximum Tanimoto similarity to the nearest bioactive to predict activity for every commercially available molecule in ZINC. This method, which we label SEA+TC, outperforms both SEA and a naïve-Bayesian classifier via predictive performance on a 5-fold cross-validation of ChEMBL’s bioactivity data set (version 21). Using this method, predictions for over 40% of compounds (>160 million) have either high significance (pSEA ≥ 40), high similarity (ECFP4MaxTc ≥ 0.4), or both, for one or more of 1382 targets well described by ligands in the literature. Using a further 1347 less-well-described targets, we predict activities for an additional 11 million compounds. To gauge whether these predictions are sensible, we investigate 75 predictions for 50 drugs lacking a binding affinity annotation in ChEMBL. The 535 million predictions for over 171 million compounds at 2629 targets are linked to purchasing information and evidence to support each prediction and are freely available via https://zinc15.docking.org and https://files.docking.org. PMID:29193970

Identifying Safer Anti-Wear Triaryl Phosphate Additives for Jet Engine Lubricants

PubMed Central

Baker, Paul E.; Cole, Toby B.; Cartwright, Megan; Suzuki, Stephanie M.; Thummel, Kenneth E.; Lin, Yvonne S.; Co, Aila L.; Rettie, Allan E.; Kim, Jerry H.; Furlong, Clement E.

2013-01-01

Individuals aboard jet aircraft may be exposed to potentially toxic triaryl organophosphate anti-wear lubricant additives (TAPs) that are converted by cytochromes P450 into toxic metabolites. Consequences of exposure could be reduced by using less toxic TAPs. Our goal was to determine whether an in vitro assay for inhibition of butyrylcholinesterase (BChE) by bioactivated TAPs would be predictive of inhibition of serine active-site enzymes in vivo. The in vitro assay involved TAP bioactivation with liver microsomes and NADPH, followed by incubation with human BChE and measurement of BChE activity. Of 19 TAPs tested, tert-butylated isomers produced the least BChE inhibition. To determine the relevance of these results in vivo, mice were exposed to Durad 125 (D125; a commercial mixture of TAP esters) or to TAPs demonstrating low or no BChE inhibition when assayed in vitro. Inhibition of BChE by bioactivated TAPs in vitro correlated well with inhibition of other serine active-site enzymes in vivo, with the exception of brain acetylcholinesterase and neuropathy target esterase (NTE), which were not inhibited by any TAP tested following single exposures. A recombinant catalytic domain of NTE (rNEST) exhibited classical kinetic properties of NTE. The metabolite of tri-(o-cresyl) phosphate (ToCP), 2-(o-cresyl)-4H-1,3,2-benzodioxaphosphoran-2-one (CBDP), inhibited rNEST in vitro, but with an IC50 value almost 6-times higher than for inhibition of BChE. Physiologically-relevant concentrations of the flavonoid, naringenin, dramatically reduced D125 bioconversion in vitro. The in vitro assay should provide a valuable tool for prescreening candidate TAP anti-wear additives, identifying safer additives and reducing the number of animals required for in vivo toxicity testing. PMID:23085349

Identifying safer anti-wear triaryl phosphate additives for jet engine lubricants.

PubMed

Baker, Paul E; Cole, Toby B; Cartwright, Megan; Suzuki, Stephanie M; Thummel, Kenneth E; Lin, Yvonne S; Co, Aila L; Rettie, Allan E; Kim, Jerry H; Furlong, Clement E

2013-03-25

Individuals aboard jet aircraft may be exposed to potentially toxic triaryl organophosphate anti-wear lubricant additives (TAPs) that are converted by cytochromes P450 into toxic metabolites. Consequences of exposure could be reduced by using less toxic TAPs. Our goal was to determine whether an in vitro assay for inhibition of butyrylcholinesterase (BChE) by bioactivated TAPs would be predictive of inhibition of serine active-site enzymes in vivo. The in vitro assay involved TAP bioactivation with liver microsomes and NADPH, followed by incubation with human BChE and measurement of BChE activity. Of 19 TAPs tested, tert-butylated isomers produced the least BChE inhibition. To determine the relevance of these results in vivo, mice were exposed to Durad 125 (D125; a commercial mixture of TAP esters) or to TAPs demonstrating low or no BChE inhibition when assayed in vitro. Inhibition of BChE by bioactivated TAPs in vitro correlated well with inhibition of other serine active-site enzymes in vivo, with the exception of brain acetylcholinesterase and neuropathy target esterase (NTE), which were not inhibited by any TAP tested following single exposures. A recombinant catalytic domain of NTE (rNEST) exhibited classical kinetic properties of NTE. The metabolite of tri-(o-cresyl) phosphate (ToCP), 2-(o-cresyl)-4H-1,3,2-benzodioxaphosphoran-2-one (CBDP), inhibited rNEST in vitro, but with an IC(50) value almost 6-times higher than for inhibition of BChE. Physiologically-relevant concentrations of the flavonoid naringenin dramatically reduced D125 bioconversion in vitro. The in vitro assay should provide a valuable tool for prescreening candidate TAP anti-wear additives, identifying safer additives and reducing the number of animals required for in vivo toxicity testing. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Quantitative structure-activity relationships for predicting potential ecological hazard of organic chemicals for use in regulatory risk assessments.

PubMed

Comber, Mike H I; Walker, John D; Watts, Chris; Hermens, Joop

2003-08-01

The use of quantitative structure-activity relationships (QSARs) for deriving the predicted no-effect concentration of discrete organic chemicals for the purposes of conducting a regulatory risk assessment in Europe and the United States is described. In the United States, under the Toxic Substances Control Act (TSCA), the TSCA Interagency Testing Committee and the U.S. Environmental Protection Agency (U.S. EPA) use SARs to estimate the hazards of existing and new chemicals. Within the Existing Substances Regulation in Europe, QSARs may be used for data evaluation, test strategy indications, and the identification and filling of data gaps. To illustrate where and when QSARs may be useful and when their use is more problematic, an example, methyl tertiary-butyl ether (MTBE), is given and the predicted and experimental data are compared. Improvements needed for new QSARs and tools for developing and using QSARs are discussed.

Predicting physical properties of emerging compounds with limited physical and chemical data: QSAR model uncertainty and applicability to military munitions.

PubMed

Bennett, Erin R; Clausen, Jay; Linkov, Eugene; Linkov, Igor

2009-11-01

Reliable, up-front information on physical and biological properties of emerging materials is essential before making a decision and investment to formulate, synthesize, scale-up, test, and manufacture a new material for use in both military and civilian applications. Multiple quantitative structure-activity relationships (QSARs) software tools are available for predicting a material's physical/chemical properties and environmental effects. Even though information on emerging materials is often limited, QSAR software output is treated without sufficient uncertainty analysis. We hypothesize that uncertainty and variability in material properties and uncertainty in model prediction can be too large to provide meaningful results. To test this hypothesis, we predicted octanol water partitioning coefficients (logP) for multiple, similar compounds with limited physical-chemical properties using six different commercial logP calculators (KOWWIN, MarvinSketch, ACD/Labs, ALogP, CLogP, SPARC). Analysis was done for materials with largely uncertain properties that were similar, based on molecular formula, to military compounds (RDX, BTTN, TNT) and pharmaceuticals (Carbamazepine, Gemfibrizol). We have also compared QSAR modeling results for a well-studied pesticide and pesticide breakdown product (Atrazine, DDE). Our analysis shows variability due to structural variations of the emerging chemicals may be several orders of magnitude. The model uncertainty across six software packages was very high (10 orders of magnitude) for emerging materials while it was low for traditional chemicals (e.g. Atrazine). Thus the use of QSAR models for emerging materials screening requires extensive model validation and coupling QSAR output with available empirical data and other relevant information.

A Randomised Controlled Trial Using Mobile Advertising to Promote Safer Sex and Sun Safety to Young People

ERIC Educational Resources Information Center

Gold, J.; Aitken, C. K.; Dixon, H. G.; Lim, M. S. C.; Gouillou, M.; Spelman, T.; Wakefield, M.; Hellard, M. E.

2011-01-01

Mobile phone text messages (SMS) are a promising method of health promotion, but a simple and low cost way to obtain phone numbers is required to reach a wide population. We conducted a randomised controlled trial with simultaneous brief interventions to (i) evaluate effectiveness of messages related to safer sex and sun safety and (ii) pilot the…

Comprehensive and Automated Linear Interaction Energy Based Binding-Affinity Prediction for Multifarious Cytochrome P450 Aromatase Inhibitors

PubMed Central

2017-01-01

Cytochrome P450 aromatase (CYP19A1) plays a key role in the development of estrogen dependent breast cancer, and aromatase inhibitors have been at the front line of treatment for the past three decades. The development of potent, selective and safer inhibitors is ongoing with in silico screening methods playing a more prominent role in the search for promising lead compounds in bioactivity-relevant chemical space. Here we present a set of comprehensive binding affinity prediction models for CYP19A1 using our automated Linear Interaction Energy (LIE) based workflow on a set of 132 putative and structurally diverse aromatase inhibitors obtained from a typical industrial screening study. We extended the workflow with machine learning methods to automatically cluster training and test compounds in order to maximize the number of explained compounds in one or more predictive LIE models. The method uses protein–ligand interaction profiles obtained from Molecular Dynamics (MD) trajectories to help model search and define the applicability domain of the resolved models. Our method was successful in accounting for 86% of the data set in 3 robust models that show high correlation between calculated and observed values for ligand-binding free energies (RMSE < 2.5 kJ mol–1), with good cross-validation statistics. PMID:28776988

LC-MS-based characterization of the peptide reactivity of chemicals to improve the in vitro prediction of the skin sensitization potential.

PubMed

Natsch, Andreas; Gfeller, Hans

2008-12-01

A key step in the skin sensitization process is the formation of a covalent adduct between skin sensitizers and endogenous proteins and/or peptides in the skin. Based on this mechanistic understanding, there is a renewed interest in in vitro assays to determine the reactivity of chemicals toward peptides in order to predict their sensitization potential. A standardized peptide reactivity assay yielded a promising predictivity. This published assay is based on high-performance liquid chromatography with ultraviolet detection to quantify peptide depletion after incubation with test chemicals. We had observed that peptide depletion may be due to either adduct formation or peptide oxidation. Here we report a modified assay based on both liquid chromatography-mass spectrometry (LC-MS) analysis and detection of free thiol groups. This approach allows simultaneous determination of (1) peptide depletion, (2) peptide oxidation (dimerization), (3) adduct formation, and (4) thiol reactivity and thus generates a more detailed characterization of the reactivity of a molecule. Highly reactive molecules are further discriminated with a kinetic measure. The assay was validated on 80 chemicals. Peptide depletion could accurately be quantified both with LC-MS detection and depletion of thiol groups. The majority of the moderate/strong/extreme sensitizers formed detectable peptide adducts, but many sensitizers were also able to catalyze peptide oxidation. Whereas adduct formation was only observed for sensitizers, this oxidation reaction was also observed for two nonsensitizing fragrance aldehydes, indicating that peptide depletion might not always be regarded as sufficient evidence for rating a chemical as a sensitizer. Thus, this modified assay gives a more informed view of the peptide reactivity of chemicals to better predict their sensitization potential.

Chemical and biological extraction of metals present in E waste: A hybrid technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pant, Deepak, E-mail: deepakpant1@rediffmail.com; Joshi, Deepika; Upreti, Manoj K.

2012-05-15

Highlights: Black-Right-Pointing-Pointer Hybrid methodology for E waste management. Black-Right-Pointing-Pointer Efficient extraction of metals. Black-Right-Pointing-Pointer Trace metal extraction is possible. - Abstract: Management of metal pollution associated with E-waste is widespread across the globe. Currently used techniques for the extraction of metals from E-waste by using either chemical or biological leaching have their own limitations. Chemical leaching is much rapid and efficient but has its own environmental consequences, even the future prospects of associated nanoremediation are also uncertain. Biological leaching on the other hand is comparatively a cost effective technique but at the same moment it is time consuming and themore » complete recovery of the metal, alone by biological leaching is not possible in most of the cases. The current review addresses the individual issues related to chemical and biological extraction techniques and proposes a hybrid-methodology which incorporates both, along with safer chemicals and compatible microbes for better and efficient extraction of metals from the E-waste.« less

A Peer-Led, Social Media-Delivered, Safer Sex Intervention for Chinese College Students: Randomized Controlled Trial.

PubMed

Sun, Wai Han; Wong, Carlos King Ho; Wong, William Chi Wai

2017-08-09

The peer-led, social media-delivered intervention is an emerging method in sexual health promotion. However, no research has yet investigated its effectiveness as compared with other online channels or in an Asian population. The objective of this study is to compare a peer-led, social media-delivered, safer sex intervention with a sexual health website. Both conditions target Chinese college students in Hong Kong. A randomized controlled trial was conducted with a peer-led, safer sex Facebook group as the intervention and an existing online sexual health website as the control. The intervention materials were developed with peer input and followed the information-motivation-behavioral skills model; the intervention was moderated by peer educators. The participants filled out the online questionnaires before and after the 6-week intervention period. Outcome evaluations included safer sex attitudes, behavioral skills, and behaviors, while process evaluation focused on online experience, online-visiting frequency, and online engagement. The effect of online-visiting frequency and online engagement on outcome variables was investigated. Of 196 eligible participants-100 in the control group and 96 in the intervention group-who joined the study, 2 (1.0%) control participants joined the Facebook group and 24 of the remaining 194 participants (12.4%) were lost to follow-up. For the process evaluation, participants in the intervention group reported more satisfying online experiences (P<.001) and a higher level of online-visiting frequency (P<.001). They also had more positive comments when compared with the control group. For outcome evaluation, within-group analysis showed significant improvement in condom use attitude (P=.02) and behavioral skills (P<.001) in the intervention group, but not in the control group. No significant between-group difference was found. After adjusting for demographic data, increased online-visiting frequency was associated with better

“He lacks his fatherhood”: Safer conception technologies and the biological imperative for fatherhood among recently-diagnosed Xhosa-speaking men living with HIV in South Africa

PubMed Central

Taylor, Tonya N.; Mantell, Joanne E.; Nywagi, Ntobeko; Cishe, Nomazizi; Cooper, Diane

2013-01-01

This paper explores notions of fatherhood and their linkages to fertility desires and intentions among a treatment-naïve cohort of Xhosa-speaking male key informants living with HIV aged 20-53 in Cape Town, South Africa. Analysis is based on an initial 27 and 20 follow up interviews with men who were part of a study that assessed the acceptability of safer conception and alternative parenting strategies among men and women newly diagnosed with HIV to inform an intervention. Grounded theory analysis revealed themes related to the cultural imperative of biologically-connected fatherhood. Certain safer conception strategies aimed at minimising the risk of HIV transmission were perceived as threats to paternity. These findings suggest that understanding of social and cultural beliefs related to notions of paternity and fatherhood may inform the implementation of acceptable safer conception options for HIV-positive men and their infected and uninfected female partners in a high HIV prevalence, low-resource setting. PMID:23862770

Piroxicam-β-Cyclodextrin: A GI Safer Piroxicam

PubMed Central

Scarpignato, C

2013-01-01

Although NSAIDs are very effective drugs, their use is associated with a broad spectrum of adverse reactions in the liver, kidney, cardiovascular (CV) system, skin and gut. Gastrointestinal (GI) side effects are the most common and constitute a wide clinical spectrum ranging from dyspepsia, heartburn and abdominal discomfort to more serious events such as peptic ulcer with life-threatening complications of bleeding and perforation. The appreciation that CV risk is also increased further complicates the choices of physicians prescribing anti-inflammatory therapy. Despite prevention strategies should be implemented in patients at risk, gastroprotection is often underused and adherence to treatment is generally poor. A more appealing approach would be therefore to develop drugs that are devoid of or have reduced GI toxicity. Gastro-duodenal mucosa possesses many defensive mechanisms and NSAIDs have a deleterious effect on most of them. This results in a mucosa less able to cope with even a reduced acid load. NSAIDs cause gastro-duodenal damage, by two main mechanisms: a physiochemical disruption of the gastric mucosal barrier and systemic inhibition of gastric mucosal protection, through inhibition of cyclooxygenase (COX, PG endoperoxide G/H synthase) activity of the GI mucosa. However, against a background of COX inhibition by anti-inflammatory doses of NSAIDs, their physicochemical properties, in particular their acidity, underlie the topical effect leading to short-term damage. It has been shown that esterification of acidic NSAIDs suppresses their gastrotoxicity without adversely affecting anti-inflammatory activity. Another way to develop NSAIDs with better GI tolerability is to complex these molecules with cyclodextrins (CDs), giving rise to so-called “inclusion complexes” that can have physical, chemical and biological properties very different from either those of the drug or the cyclodextrin. Complexation of NSAIDs with β-cyclodextrin potentially leads

AlzhCPI: A knowledge base for predicting chemical-protein interactions towards Alzheimer's disease.

PubMed

Fang, Jiansong; Wang, Ling; Li, Yecheng; Lian, Wenwen; Pang, Xiaocong; Wang, Hong; Yuan, Dongsheng; Wang, Qi; Liu, Ai-Lin; Du, Guan-Hua

2017-01-01

Alzheimer's disease (AD) is a complicated progressive neurodegeneration disorder. To confront AD, scientists are searching for multi-target-directed ligands (MTDLs) to delay disease progression. The in silico prediction of chemical-protein interactions (CPI) can accelerate target identification and drug discovery. Previously, we developed 100 binary classifiers to predict the CPI for 25 key targets against AD using the multi-target quantitative structure-activity relationship (mt-QSAR) method. In this investigation, we aimed to apply the mt-QSAR method to enlarge the model library to predict CPI towards AD. Another 104 binary classifiers were further constructed to predict the CPI for 26 preclinical AD targets based on the naive Bayesian (NB) and recursive partitioning (RP) algorithms. The internal 5-fold cross-validation and external test set validation were applied to evaluate the performance of the training sets and test set, respectively. The area under the receiver operating characteristic curve (ROC) for the test sets ranged from 0.629 to 1.0, with an average of 0.903. In addition, we developed a web server named AlzhCPI to integrate the comprehensive information of approximately 204 binary classifiers, which has potential applications in network pharmacology and drug repositioning. AlzhCPI is available online at http://rcidm.org/AlzhCPI/index.html. To illustrate the applicability of AlzhCPI, the developed system was employed for the systems pharmacology-based investigation of shichangpu against AD to enhance the understanding of the mechanisms of action of shichangpu from a holistic perspective.

Biological Networks for Predicting Chemical Hepatocarcinogenicity Using Gene Expression Data from Treated Mice and Relevance across Human and Rat Species

PubMed Central

Thomas, Reuben; Thomas, Russell S.; Auerbach, Scott S.; Portier, Christopher J.

2013-01-01

Background Several groups have employed genomic data from subchronic chemical toxicity studies in rodents (90 days) to derive gene-centric predictors of chronic toxicity and carcinogenicity. Genes are annotated to belong to biological processes or molecular pathways that are mechanistically well understood and are described in public databases. Objectives To develop a molecular pathway-based prediction model of long term hepatocarcinogenicity using 90-day gene expression data and to evaluate the performance of this model with respect to both intra-species, dose-dependent and cross-species predictions. Methods Genome-wide hepatic mRNA expression was retrospectively measured in B6C3F1 mice following subchronic exposure to twenty-six (26) chemicals (10 were positive, 2 equivocal and 14 negative for liver tumors) previously studied by the US National Toxicology Program. Using these data, a pathway-based predictor model for long-term liver cancer risk was derived using random forests. The prediction model was independently validated on test sets associated with liver cancer risk obtained from mice, rats and humans. Results Using 5-fold cross validation, the developed prediction model had reasonable predictive performance with the area under receiver-operator curve (AUC) equal to 0.66. The developed prediction model was then used to extrapolate the results to data associated with rat and human liver cancer. The extrapolated model worked well for both extrapolated species (AUC value of 0.74 for rats and 0.91 for humans). The prediction models implied a balanced interplay between all pathway responses leading to carcinogenicity predictions. Conclusions Pathway-based prediction models estimated from sub-chronic data hold promise for predicting long-term carcinogenicity and also for its ability to extrapolate results across multiple species. PMID:23737943

How Can We Make PV Modules Safer?: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wohlgemuth, J. H.; Kurtz, S. R.

2012-06-01

Safety is a prime concern for the photovoltaics (PV) industry. As a technology deployed on residential and commercial buildings, it is critical that PV not cause damage to the buildings nor harm the occupants. Many of the PV systems on buildings are of sufficiently high voltage (300 to 600 Volts dc) that they may present potential hazards. These PV systems must be safe in terms of mechanical damage (nothing falls on someone), shock hazard (no risk of electrical shock when touching an exposed circuit element), and fire (the modules neither cause nor promote a fire). The present safety standards (IECmore » 61730 and UL 1703) do a good job of providing for design rules and test requirements for mechanical, shock, and spread of flame dangers. However, neither standard addresses the issue of electrical arcing within a module that can cause a fire. To make PV modules, they must be designed, built, and installed with an emphasis on minimizing the potential for open circuits and ground faults. This paper provides recommendations on redundant connection designs, robust mounting methods, and changes to the safety standards to yield safer PV modules.« less

Modelling the Tox21 10 K chemical profiles for in vivo toxicity prediction and mechanism characterization

PubMed Central

Huang, Ruili; Xia, Menghang; Sakamuru, Srilatha; Zhao, Jinghua; Shahane, Sampada A.; Attene-Ramos, Matias; Zhao, Tongan; Austin, Christopher P.; Simeonov, Anton

2016-01-01

Target-specific, mechanism-oriented in vitro assays post a promising alternative to traditional animal toxicology studies. Here we report the first comprehensive analysis of the Tox21 effort, a large-scale in vitro toxicity screening of chemicals. We test ∼10,000 chemicals in triplicates at 15 concentrations against a panel of nuclear receptor and stress response pathway assays, producing more than 50 million data points. Compound clustering by structure similarity and activity profile similarity across the assays reveals structure–activity relationships that are useful for the generation of mechanistic hypotheses. We apply structural information and activity data to build predictive models for 72 in vivo toxicity end points using a cluster-based approach. Models based on in vitro assay data perform better in predicting human toxicity end points than animal toxicity, while a combination of structural and activity data results in better models than using structure or activity data alone. Our results suggest that in vitro activity profiles can be applied as signatures of compound mechanism of toxicity and used in prioritization for more in-depth toxicological testing. PMID:26811972

In silico prediction of Tetrahymena pyriformis toxicity for diverse industrial chemicals with substructure pattern recognition and machine learning methods.

PubMed

Cheng, Feixiong; Shen, Jie; Yu, Yue; Li, Weihua; Liu, Guixia; Lee, Philip W; Tang, Yun

2011-03-01

There is an increasing need for the rapid safety assessment of chemicals by both industries and regulatory agencies throughout the world. In silico techniques are practical alternatives in the environmental hazard assessment. It is especially true to address the persistence, bioaccumulative and toxicity potentials of organic chemicals. Tetrahymena pyriformis toxicity is often used as a toxic endpoint. In this study, 1571 diverse unique chemicals were collected from the literature and composed of the largest diverse data set for T. pyriformis toxicity. Classification predictive models of T. pyriformis toxicity were developed by substructure pattern recognition and different machine learning methods, including support vector machine (SVM), C4.5 decision tree, k-nearest neighbors and random forest. The results of a 5-fold cross-validation showed that the SVM method performed better than other algorithms. The overall predictive accuracies of the SVM classification model with radial basis functions kernel was 92.2% for the 5-fold cross-validation and 92.6% for the external validation set, respectively. Furthermore, several representative substructure patterns for characterizing T. pyriformis toxicity were also identified via the information gain analysis methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

Fate of chemical warfare agents and toxic industrial chemicals in landfills.

PubMed

Bartelt-Hunt, Shannon L; Barlaz, Morton A; Knappe, Detlef R U; Kjeldsen, Peter

2006-07-01

One component of preparedness for a chemical attack is planning for the disposal of contaminated debris. To assess the feasibility of contaminated debris disposal in municipal solid waste (MSW) landfills, the fate of selected chemical warfare agents (CWAs) and toxic industrial chemicals (TICs) in MSW landfills was predicted with a mathematical model. Five blister agents [sulfur mustard (HD), nitrogen mustard (HN-2), lewisite (L), ethyldichloroarsine (ED), and phosgene oxime (CX)], eight nerve agents [tabun (GA), sarin (GB), soman (GD), GE, GF, VX, VG, and VM], one riot-control agent [CS], and two TICs [furan and carbon disulfide] were studied. The effects of both infiltration (climate) and contaminant biodegradability on fate predictions were assessed. Model results showed that hydrolysis and gas-phase advection were the principal fate pathways for CWAs and TICs, respectively. Apart from CX and the TICs, none of the investigated compounds was predicted to persist in a landfill for more than 5 years. Climate had little impact on CWA/TIC fate, and biodegradability was only important for compounds with long hydrolysis half-lives. Monte Carlo simulations were performed to assess the influence of uncertainty in model input parameters on CWA/TIC fate predictions. Correlation analyses showed that uncertainty in hydrolysis rate constants was the primary contributor to variance of CWA fate predictions, while uncertainty in the Henry's Law constant and landfill gas-production rate accounted for most of the variance of TIC fate predictions. CWA hydrolysates were more persistent than the parent CWAs, but limited information is available on abiotic or biotic transformation rates for these chemicals.

Safer Conception Methods and Counseling: Psychometric Evaluation of New Measures of Attitudes and Beliefs Among HIV Clients and Providers.

PubMed

Woldetsadik, Mahlet Atakilt; Goggin, Kathy; Staggs, Vincent S; Wanyenze, Rhoda K; Beyeza-Kashesya, Jolly; Mindry, Deborah; Finocchario-Kessler, Sarah; Khanakwa, Sarah; Wagner, Glenn J

2016-06-01

With data from 400 HIV clients with fertility intentions and 57 HIV providers in Uganda, we evaluated the psychometrics of new client and provider scales measuring constructs related to safer conception methods (SCM) and safer conception counselling (SCC). Several forms of validity (i.e., content, face, and construct validity) were examined using standard methods including exploratory and confirmatory factor analysis. Internal consistency was established using Cronbach's alpha correlation coefficient. The final scales consisted of measures of attitudes towards use of SCM and delivery of SCC, including measures of self-efficacy and motivation to use SCM, and perceived community stigma towards childbearing. Most client and all provider measures had moderate to high internal consistency (alphas 0.60-0.94), most had convergent validity (associations with other SCM or SCC-related measures), and client measures had divergent validity (poor associations with depression). These findings establish preliminary psychometric properties of these scales and should facilitate future studies of SCM and SCC.

Goneis.gr: Training Greek Parents on ICT and Safer Internet

NASA Astrophysics Data System (ADS)

Manouselis, Nikos; Riviou, Katerina; Palavitsinis, Nikos; Giannikopoulou, Vasiliki; Tsanakas, Panayotis

Children's use of the Internet has significantly risen in the last decade. Nevertheless, children spend a lot of time online which makes them susceptible to various threats (such as inappropriate material, offensive language, etc). Parents are the last frontier to this menace but they also need to be educated and trained in order to protect their children. Goneis.gr is an initiative launched by the Greek government that aims to educate parents on safer Internet and the use of parental control software. Parents are also entitled to distance learning courses covering basic computer skills. This paper presents the results of two separate surveys that took place in the last few months (December 2008-January 2009). The first survey targeted the parents that have completed the programme and the second one the educational providers that participate in the programme and offer the training to the beneficiaries.

Chemical Compatibility of Polymeric Materials.

ERIC Educational Resources Information Center

Solen, Kenneth A.; Kuchar, Marvin C.

1990-01-01

Presents some principles for specifying general classes of polymers for predicting relative chemical attack from acids, bases, oxidants, and certain common antagonists. Also discusses predicting relative solvent effects. Suggests uses of this information in two or three lectures in a chemical engineering materials course. (YP)

"We need somewhere to smoke crack": An ethnographic study of an unsanctioned safer smoking room in Vancouver, Canada.

PubMed

McNeil, Ryan; Kerr, Thomas; Lampkin, Hugh; Small, Will

2015-07-01

Many cities around the globe have experienced substantial increases in crack cocaine use. Public health programmes have begun to address crack smoking, primarily through the distribution of safer crack use equipment, but their impacts have been limited. More comprehensive safer environmental interventions, specifically safer smoking rooms (SSR), have been implemented only in select European cities. However, none have been subjected to rigorous evaluation. This ethnographic study was undertaken at an 'unsanctioned' SSR operated by a drug user-led organization in Vancouver, Canada, to explore how this intervention shaped crack smoking practices, public crack smoking, and related harms. Ethnographic fieldwork was undertaken at this SSR from September to December 2011, and included approximately 50 hours of ethnographic observation and 23 in-depth interviews with people who smoke crack. Data were analyzed by drawing on the 'Risk Environment' framework and concepts of 'symbolic', 'everyday', and 'structural' violence. Our findings illustrate how a high demand for SSRs was driven by the need to minimize exposure to policing (structural violence), drug scene violence (everyday violence), and stigma (symbolic violence) that characterized unregulated drug use settings (e.g., public spaces). Although resource scarcity and social norms operating within the local drug scene (e.g., gendered power relations) perpetuated crack pipe-sharing within unregulated drug use settings, the SSR fostered harm reduction practices by reshaping the social-structural context of crack smoking and reduced the potential for health harms. Given the significant potential of SSRs in reducing health and social harms, there is an urgent need to scale up these interventions. Integrating SSRs into public health systems, and supplementing these interventions with health and social supports, has potential to improve the health and safety of crack-smoking populations. Copyright © 2015 Elsevier B.V. All

A Novel Two-Step Hierarchial Quantitative Structure-Activity Relationship Modeling Workflow for Predicting Acute Toxicity of Chemicals in Rodents

EPA Science Inventory

Background: Accurate prediction of in vivo toxicity from in vitro testing is a challenging problem. Large public–private consortia have been formed with the goal of improving chemical safety assessment by the means of high-throughput screening. Methods and results: A database co...

Free variable selection QSPR study to predict 19F chemical shifts of some fluorinated organic compounds using Random Forest and RBF-PLS methods

NASA Astrophysics Data System (ADS)

Goudarzi, Nasser

2016-04-01

In this work, two new and powerful chemometrics methods are applied for the modeling and prediction of the 19F chemical shift values of some fluorinated organic compounds. The radial basis function-partial least square (RBF-PLS) and random forest (RF) are employed to construct the models to predict the 19F chemical shifts. In this study, we didn't used from any variable selection method and RF method can be used as variable selection and modeling technique. Effects of the important parameters affecting the ability of the RF prediction power such as the number of trees (nt) and the number of randomly selected variables to split each node (m) were investigated. The root-mean-square errors of prediction (RMSEP) for the training set and the prediction set for the RBF-PLS and RF models were 44.70, 23.86, 29.77, and 23.69, respectively. Also, the correlation coefficients of the prediction set for the RBF-PLS and RF models were 0.8684 and 0.9313, respectively. The results obtained reveal that the RF model can be used as a powerful chemometrics tool for the quantitative structure-property relationship (QSPR) studies.

Perspectives of healthcare providers and HIV-affected individuals and couples during the development of a Safer Conception Counseling Toolkit in Kenya: stigma, fears, and recommendations for the delivery of services.

PubMed

Mmeje, Okeoma; Njoroge, Betty; Akama, Eliud; Leddy, Anna; Breitnauer, Brooke; Darbes, Lynae; Brown, Joelle

2016-01-01

Reproduction is important to many HIV-affected individuals and couples and healthcare providers (HCPs) are responsible for providing resources to help them safely conceive while minimizing the risk of sexual and perinatal HIV transmission. In order to fulfill their reproductive goals, HIV-affected individuals and their partners need access to information regarding safer methods of conception. The objective of this qualitative study was to develop a Safer Conception Counseling Toolkit that can be used to train HCPs and counsel HIV-affected individuals and couples in HIV care and treatment clinics in Kenya. We conducted a two-phased qualitative study among HCPs and HIV-affected individuals and couples from eight HIV care and treatment sites in Kisumu, Kenya. We conducted in-depth interviews (IDIs) and focus group discussions (FGDs) to assess the perspectives of HCPs and HIV-affected individuals and couples in order to develop and refine the content of the Toolkit. Subsequently, IDIs were conducted among HCPs who were trained using the Toolkit and FGDs among HIV-affected individuals and couples who were counseled with the Toolkit. HIV-related stigma, fears, and recommendations for delivery of safer conception counseling were assessed during the discussions. One hundred and six individuals participated in FGDs and IDIs; 29 HCPs, 49 HIV-affected women and men, and 14 HIV-serodiscordant couples. Participants indicated that a safer conception counseling and training program for HCPs is needed and that routine provision of safer conception counseling may promote maternal and child health by enhancing reproductive autonomy among HIV-affected couples. They also reported that the Toolkit may help dispel the stigma and fears associated with reproduction in HIV-affected couples, while supporting them in achieving their reproductive goals. Additional research is needed to evaluate the Safer Conception Toolkit in order to support its implementation and use in HIV care and

Chemical differentiation, thermal evolution, and catastrophic overturn on Venus: Predictions and geologic observations

NASA Technical Reports Server (NTRS)

Head, James W.; Parmentier, E. M.; Hess, P. C.

1993-01-01

Observations from Magellan show that: (1) the surface of Venus is generally geologically young, (2) there is no evidence for widespread recent crustal spreading or subduction, (3) the crater population permits the hypothesis that the surface is in production, and (4) relatively few impact craters appear to be embayed by volcanic deposits suggesting that the volcanic flux has drastically decreased as a function of time. These observations have led to consideration of hypotheses suggesting that the geological history of Venus may have changed dramatically as a function of time due to general thermal evolution, and/or thermal and chemical evolution of a depleted mantle layer, perhaps punctuated by catastrophic overturn of upper layers or episodic plate tectonics. We have previously examined the geological implications of some of these models, and here we review the predictions associated with two periods of Venus history. Stationary thick lithosphere and depleted mantle layer, and development of regional to global development of regional to global instabilities, and compare these predictions to the geological characteristics of Venus revealed by Magellan.

Predicted Thermal Responses of Military Working Dog (MWD) to Chemical, Biological, Radiological, Nuclear (CBRN) Protective Kennel Enclosure

DTIC Science & Technology

2011-08-01

meteorological conditions. More specifically, climate chamber studies of the chemical protective kennel cover were conducted over a range of...responses to predict how long the dog could safely remain in the enclosure for various ambient environmental conditions. Climate chamber studies of...Engineering Center (NSRDEC) was tested in a climate - controlled chamber to quantify its insulation and vapor permeability properties. A schematic of

Creating a Highly Reliable Neonatal Intensive Care Unit Through Safer Systems of Care.

PubMed

Panagos, Patoula G; Pearlman, Stephen A

2017-09-01

Neonates requiring intensive care are at high risk for medical errors due to their unique characteristics and high acuity. Designing a safer work environment begins with safe processes. Creating a culture of safety demands the involvement of all organizational levels and an interdisciplinary approach. Adverse events can result from suboptimal communication and lack of a shared mental model. This chapter describes tools to promote better patient safety in the NICU through monitoring adverse events, improving communication and using information technology. Unplanned extubation is an example of a neonatal safety concern that can be reduced by employing quality improvement methodology. Copyright © 2017 Elsevier Inc. All rights reserved.

In vitro cytotoxicity testing of 30 reference chemicals to predict acute human and animal toxicity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barile, F.A.; Arjun, S.; Borges, L.

1991-03-11

This study was conducted in cooperation with the Scandinavian Society of Cell Toxicology, as part of the Multicenter Evaluation for In Vitro Cytotoxicity (MEIC), and was designed to develop an in vitro model for predicting acute human and animal toxicity. The technique relies on the ability of cultured transformed rat lung epithelial cells (L2) to incorporate radiolabled amino acids into newly synthesized proteins in the absence or presence of increasing doses of the test chemical, during a 24-hr incubation. IC50 values were extrapolated from the dose-response curves after linear regression analysis. Human toxic blood concentrations estimated from rodent LD50 valuesmore » suggest that our experimental IC50's are in close correlation with the former. Validation of the data by the MEIC committee shows that our IC50 values predicted human lethal dosage as efficient as rodent LD50's. It is anticipated that this and related procedures may supplement or replace currently used animal protocols for predicting human toxicity.« less

Application of Mouse Embryonic Stem Cell Test to Detect Gender-Specific Effect of Chemicals: A Supplementary Tool for Embryotoxicity Prediction.

PubMed

Cheng, Wei; Zhou, Ren; Liang, Fan; Wei, Hongying; Feng, Yan; Wang, Yan

2016-09-19

Gender effect is an inherent property of chemicals, characterized by variations caused by the chemical-biology interaction. It has widely existed, but the shortage of an appropriate model restricts the study on gender-specific effect. The embryonic stem cell test (EST) has been utilized as an alternative test for developmental toxicity. Despite its numerous improvements, mouse embryonic stem cells with an XX karyotype have not been used in the EST, which restricts the ability of the EST to identify gender-specific effects during high-throughput-screening (HTS) of chemicals to date. To address this, the embryonic stem cell (ESC) SP3 line with an XX karyotype was used to establish a "female" model as a complement to EST. Here, we proposed a "double-objects in unison" (DOU)-EST, which consisted of male ESC and female ESC; a seven-day EST protocol was utilized, and the gender-specific effect of chemicals was determined and discriminated; the replacement of myosin heavy chain (MHC) with myosin light chain (MLC) provided a suitable molecular biomarker in the DOU-EST. New linear discriminant functions were given in the purpose of distinguishing chemicals into three classes, namely, no gender-specific effect, male-susceptive, and female-susceptive. For 15 chemicals in the training set, the concordances of prediction result as no gender effect, male susceptive, and female susceptive were 86.67%, 86.67%, and 93.33%, respectively, the sensitivities were 66.67%, 83.33%, and 83.33%, respectively, and the specificities were 91.67%, 88.89%, and 100%, respectively; the total accuracy of DOU-EST was 86.67%. For three chemicals in the test set, one was incorrectively predicted. The possible reason for misclassification may due to the absence of hormone environment in vitro. Leave-one-out cross-validation (LOOCV) indicated a mean error rate of 18.34%. Taken together, these data suggested a good performance of the proposed DOU-EST. Emerging chemicals with undiscovered gender

Chemical Transformation Simulator

EPA Science Inventory

The Chemical Transformation Simulator (CTS) is a web-based, high-throughput screening tool that automates the calculation and collection of physicochemical properties for an organic chemical of interest and its predicted products resulting from transformations in environmental sy...

Development and Application of In Vitro Models for Screening Drugs and Environmental Chemicals that Predict Toxicity in Animals and Humans

EPA Pesticide Factsheets

Development and Application of In Vitro Models for Screening Drugs and Environmental Chemicals that Predict Toxicity in Animals and Humans (Presented by James McKim, Ph.D., DABT, Founder and Chief Science Officer, CeeTox) (5/25/2012)