PeerJ
type: channel
link: https://peerj.com/articles/
description: Articles published in PeerJ
publisher: PeerJ Inc.
publication name: PeerJ
issn: 2167-8359
items: In rats fed high-energy diets, taste, rather than fat content, is the key factor increasing food intake: a comparison of a cafeteria and a lipid-supplemented standard diet
items: Awareness about antibiotic resistance in a self-medication user group from Eastern Romania: a pilot study
items: Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach
items: Greater reproductive investment, but shorter lifespan, in agrosystem than in natural-habitat toads
items: Factors influencing healthcare provider respondent fatigue answering a globally administered in-app survey
items: Identification and analysis of CYP450 genes from transcriptome of Lonicera japonica and expression analysis of chlorogenic acid biosynthesis related CYP450s
items: Comparison of polybrominated diphenyl ethers (PBDEs) and polychlorinated biphenyls (PCBs) in the serum of hypothyroxinemic and euthyroid dogs
items: The landscape of fear conceptual framework: definition and review of current applications and misuses
items: Habitat suitability—density relationship in an endangered woodland species: the case of the Blue Chaffinch (Fringilla polatzeki)
items: Challenging a bioinformatic tool’s ability to detect microbial contaminants using in silico whole genome sequencing data

In rats fed high-energy diets, taste, rather than fat content, is the key factor increasing food intake: a comparison of a cafeteria and a lipid-supplemented standard diet
type: item
type: AcademicArticle
description: Background Food selection and ingestion both in humans and rodents, often is a critical factor in determining excess energy intake and its related disorders. Methods Two different concepts of high-fat diets were tested for their obesogenic effects in rats; in both cases, lipids constituted about 40% of their energy intake. The main difference with controls fed standard lab chow, was, precisely, the lipid content. Cafeteria diets (K) were self-selected diets devised to be desirable to the rats, mainly because of its diverse mix of tastes, particularly salty and sweet. This diet was compared with another, more classical high-fat (HF) diet, devised not to be as tasty as K, and prepared by supplementing standard chow pellets with fat. We also analysed the influence of sex on the effects of the diets. Results K rats grew faster because of a high lipid, sugar and protein intake, especially the males, while females showed lower weight but higher proportion of body lipid. In contrast, the weight of HF groups were not different from controls. Individual nutrient’s intake were analysed, and we found that K rats ingested large amounts of both disaccharides and salt, with scant differences of other nutrients’ proportion between the three groups. The results suggest that the key differential factor of the diet eliciting excess energy intake was the massive presence of sweet and salty tasting food. Conclusions The significant presence of sugar and salt appears as a powerful inducer of excess food intake, more effective than a simple (albeit large) increase in the diet’s lipid content. These effects appeared already after a relatively short treatment. The differential effects of sex agree with their different hedonic and obesogenic response to diet.
format: application/pdf
format: text/html
creator: Laia Oliva
creator: Tània Aranda
creator: Giada Caviola
creator: Anna Fernández-Bernal
creator: Marià Alemany
creator: José Antonio Fernández-López
creator: Xavier Remesar
subject: Biochemistry
subject: Nutrition
subject: Metabolic Sciences
description: doi:10.7717/peerj.3697
publisher: PeerJ Inc.
rights: © 2017 Oliva et al.
abstract: Background Food selection and ingestion both in humans and rodents, often is a critical factor in determining excess energy intake and its related disorders. Methods Two different concepts of high-fat diets were tested for their obesogenic effects in rats; in both cases, lipids constituted about 40% of their energy intake. The main difference with controls fed standard lab chow, was, precisely, the lipid content. Cafeteria diets (K) were self-selected diets devised to be desirable to the rats, mainly because of its diverse mix of tastes, particularly salty and sweet. This diet was compared with another, more classical high-fat (HF) diet, devised not to be as tasty as K, and prepared by supplementing standard chow pellets with fat. We also analysed the influence of sex on the effects of the diets. Results K rats grew faster because of a high lipid, sugar and protein intake, especially the males, while females showed lower weight but higher proportion of body lipid. In contrast, the weight of HF groups were not different from controls. Individual nutrient’s intake were analysed, and we found that K rats ingested large amounts of both disaccharides and salt, with scant differences of other nutrients’ proportion between the three groups. The results suggest that the key differential factor of the diet eliciting excess energy intake was the massive presence of sweet and salty tasting food. Conclusions The significant presence of sugar and salt appears as a powerful inducer of excess food intake, more effective than a simple (albeit large) increase in the diet’s lipid content. These effects appeared already after a relatively short treatment. The differential effects of sex agree with their different hedonic and obesogenic response to diet.
bibliographic citation: Oliva et al. (2017) In rats fed high-energy diets, taste, rather than fat content, is the key factor increasing food intake: a comparison of a cafeteria and a lipid-supplemented standard diet. PeerJ 5:e3697 https://doi.org/10.7717/peerj.3697
date submitted: 2017-05-22
date accepted: 2017-07-26
issued: 2017-09-13
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Oliva
  given name: Laia
author list: Agent
  family name: Aranda
  given name: Tània
author list: Agent
  family name: Caviola
  given name: Giada
author list: Agent
  family name: Fernández-Bernal
  given name: Anna
author list: Agent
  family name: Alemany
  given name: Marià
author list: Agent
  family name: Fernández-López
  given name: José Antonio
author list: Agent
  family name: Remesar
  given name: Xavier
doi: 10.7717/peerj.3697
volume: 5
issn: 2167-8359
publication name: PeerJ
publication date: 2017-09-13
copyright: ©2017 Oliva et al.
attribution name: Oliva et al.

Awareness about antibiotic resistance in a self-medication user group from Eastern Romania: a pilot study
type: item
type: AcademicArticle
description: Background Awareness about antibiotic resistance depends on the attitudes and information about antibiotic resistance of both patients and physicians. Persons who practice self-medication are at high risk of also self-medicating with antibiotics. The purpose of the present study was to evaluate the awareness about antibiotic resistance by investigating the practice in a group of self-medication users in a sample of adults in Romania and the variables associated with such practice. Material and Methods A cross-sectional self-filled questionnaire based study was conducted from December 2016 through January 2017 amongst 218 self-medication users (SMUG). The attitudes, the level of knowledge, the perceptions, about antibiotic use (ABU) and about antibiotic resistance (ABR) were compared to a reference group represented by medical residents group in their specialty training (MRG) considered to have a higher level of knowledge and awareness about ABU and ABR. Results The response rate was 87.2% in the SMUG group and 100% in the MRG group. The SMUG group reported self-medication practices for antibiotics with a high frequency at any time in life (72%), but with a very low frequency from the month previous to the date of the study (12%), comparative with the MRG group (75% and 7%, respectively). The multivariate logistic regression analysis showed that self-medication with antibiotics at any time in life in the SMUG group could be predicted by the answers to two questions regarding the practices and knowledge about ABU (Q13 and Q20). On the other hand, in the MRG group, a question about ABR perception (Q23), could be predictor for self-medication with antibiotics. Self-medication with antibiotics in the month previous to the date of the study in the SMUG group could be predicted with three questions: one about ABU practice (Q14), one about ABR perception (Q26) and one referring to ABR knowledge (Q28). On the other hand, in the MRG group, a question about ABR knowledge (Q32)…
format: application/pdf
format: text/html
creator: Gabi Topor
creator: Ionela-Alina Grosu
creator: Cristina Mihaela Ghiciuc
creator: Aurel Lulu Strat
creator: Cătălina Elena Lupuşoru
subject: Health Policy
subject: Pharmacology
description: doi:10.7717/peerj.3803
publisher: PeerJ Inc.
rights: © 2017 Topor et al.
abstract: Background Awareness about antibiotic resistance depends on the attitudes and information about antibiotic resistance of both patients and physicians. Persons who practice self-medication are at high risk of also self-medicating with antibiotics. The purpose of the present study was to evaluate the awareness about antibiotic resistance by investigating the practice in a group of self-medication users in a sample of adults in Romania and the variables associated with such practice. Material and Methods A cross-sectional self-filled questionnaire based study was conducted from December 2016 through January 2017 amongst 218 self-medication users (SMUG). The attitudes, the level of knowledge, the perceptions, about antibiotic use (ABU) and about antibiotic resistance (ABR) were compared to a reference group represented by medical residents group in their specialty training (MRG) considered to have a higher level of knowledge and awareness about ABU and ABR. Results The response rate was 87.2% in the SMUG group and 100% in the MRG group. The SMUG group reported self-medication practices for antibiotics with a high frequency at any time in life (72%), but with a very low frequency from the month previous to the date of the study (12%), comparative with the MRG group (75% and 7%, respectively). The multivariate logistic regression analysis showed that self-medication with antibiotics at any time in life in the SMUG group could be predicted by the answers to two questions regarding the practices and knowledge about ABU (Q13 and Q20). On the other hand, in the MRG group, a question about ABR perception (Q23), could be predictor for self-medication with antibiotics. Self-medication with antibiotics in the month previous to the date of the study in the SMUG group could be predicted with three questions: one about ABU practice (Q14), one about ABR perception (Q26) and one referring to ABR knowledge (Q28). On the other hand, in the MRG group, a question about ABR knowledge (Q32)…
bibliographic citation: Topor et al. (2017) Awareness about antibiotic resistance in a self-medication user group from Eastern Romania: a pilot study. PeerJ 5:e3803 https://doi.org/10.7717/peerj.3803
date submitted: 2017-06-24
date accepted: 2017-08-23
issued: 2017-09-12
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Topor
  given name: Gabi
author list: Agent
  family name: Grosu
  given name: Ionela-Alina
author list: Agent
  family name: Ghiciuc
  given name: Cristina Mihaela
author list: Agent
  family name: Strat
  given name: Aurel Lulu
author list: Agent
  family name: Lupuşoru
  given name: Cătălina Elena
doi: 10.7717/peerj.3803
volume: 5
issn: 2167-8359
publication name: PeerJ
publication date: 2017-09-12
copyright: ©2017 Topor et al.
attribution name: Topor et al.

Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach
type: item
type: AcademicArticle
description: Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM), Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD), Histogram of Oriented Gradients (HOG), Hu invariant moments (Hu) and Zernike moments (ZM). Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN), random forest (RF), support vector machine (SVM), k-nearest neighbour (k-NN), linear discriminant analysis (LDA) and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM). In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS) and Pearson’s coefficient correlation (PCC). The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia dataset and 99.…
format: application/pdf
format: text/html
creator: Miraemiliana Murat
creator: Siow-Wee Chang
creator: Arpah Abu
creator: Hwa Jen Yap
creator: Kien-Thai Yong
subject: Bioinformatics
subject: Computational Biology
subject: Plant Science
description: doi:10.7717/peerj.3792
publisher: PeerJ Inc.
rights: © 2017 Murat et al.
abstract: Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM), Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD), Histogram of Oriented Gradients (HOG), Hu invariant moments (Hu) and Zernike moments (ZM). Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN), random forest (RF), support vector machine (SVM), k-nearest neighbour (k-NN), linear discriminant analysis (LDA) and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM). In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS) and Pearson’s coefficient correlation (PCC). The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia dataset and 99.…
bibliographic citation: Murat et al. (2017) Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach. PeerJ 5:e3792 https://doi.org/10.7717/peerj.3792
date submitted: 2017-05-23
date accepted: 2017-08-20
issued: 2017-09-12
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Murat
  given name: Miraemiliana
author list: Agent
  family name: Chang
  given name: Siow-Wee
author list: Agent
  family name: Abu
  given name: Arpah
author list: Agent
  family name: Yap
  given name: Hwa Jen
author list: Agent
  family name: Yong
  given name: Kien-Thai
doi: 10.7717/peerj.3792
volume: 5
issn: 2167-8359
publication name: PeerJ
publication date: 2017-09-12
copyright: ©2017 Murat et al.
attribution name: Murat et al.

Greater reproductive investment, but shorter lifespan, in agrosystem than in natural-habitat toads
type: item
type: AcademicArticle
description: Global amphibian decline is due to several factors: habitat loss, anthropization, pollution, emerging diseases, and global warming. Amphibians, with complex life cycles, are particularly susceptible to habitat alterations, and their survival may be impaired in anthropized habitats. Increased mortality is a well-known consequence of anthropization. Life-history theory predicts higher reproductive investment when mortality is increased. In this work, we compared age, body size, and different indicators of reproductive investment, as well as prey availability, in natterjack toads (Epidalea calamita) from agrosystems and adjacent natural pine groves in Southwestern Spain. Mean age was lower in agrosystems than in pine groves, possibly as a consequence of increased mortality due to agrosystem environmental stressors. Remarkably, agrosystem toads were larger despite being younger, suggesting accelerated growth rate. Although we detected no differences in prey availability between habitats, artificial irrigation could shorten aestivation in agrosystems, thus increasing energy trade. Moreover, agrosystem toads exhibited increased indicators of reproductive investment. In the light of life-history theory, agrosystem toads might compensate for lesser reproductive events—due to shorter lives—with a higher reproductive investment in each attempt. Our results show that agrosystems may alter demography, which may have complex consequences on both individual fitness and population stability.
format: application/pdf
format: text/html
creator: Francisco Javier Zamora-Camacho
creator: Mar Comas
subject: Biosphere Interactions
subject: Conservation Biology
subject: Environmental Impacts
subject: Evolutionary Studies
subject: Zoology
description: doi:10.7717/peerj.3791
publisher: PeerJ Inc.
rights: © 2017 Zamora-Camacho and Comas
abstract: Global amphibian decline is due to several factors: habitat loss, anthropization, pollution, emerging diseases, and global warming. Amphibians, with complex life cycles, are particularly susceptible to habitat alterations, and their survival may be impaired in anthropized habitats. Increased mortality is a well-known consequence of anthropization. Life-history theory predicts higher reproductive investment when mortality is increased. In this work, we compared age, body size, and different indicators of reproductive investment, as well as prey availability, in natterjack toads (Epidalea calamita) from agrosystems and adjacent natural pine groves in Southwestern Spain. Mean age was lower in agrosystems than in pine groves, possibly as a consequence of increased mortality due to agrosystem environmental stressors. Remarkably, agrosystem toads were larger despite being younger, suggesting accelerated growth rate. Although we detected no differences in prey availability between habitats, artificial irrigation could shorten aestivation in agrosystems, thus increasing energy trade. Moreover, agrosystem toads exhibited increased indicators of reproductive investment. In the light of life-history theory, agrosystem toads might compensate for lesser reproductive events—due to shorter lives—with a higher reproductive investment in each attempt. Our results show that agrosystems may alter demography, which may have complex consequences on both individual fitness and population stability.
bibliographic citation: Zamora-Camacho et al. (2017) Greater reproductive investment, but shorter lifespan, in agrosystem than in natural-habitat toads. PeerJ 5:e3791 https://doi.org/10.7717/peerj.3791
date submitted: 2017-04-29
date accepted: 2017-08-19
issued: 2017-09-12
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Zamora-Camacho
  given name: Francisco Javier
author list: Agent
  family name: Comas
  given name: Mar
doi: 10.7717/peerj.3791
volume: 5
issn: 2167-8359
publication name: PeerJ
publication date: 2017-09-12
copyright: ©2017 Zamora-Camacho and Comas
attribution name: Zamora-Camacho and Comas

Factors influencing healthcare provider respondent fatigue answering a globally administered in-app survey
type: item
type: AcademicArticle
description: Background Respondent fatigue, also known as survey fatigue, is a common problem in the collection of survey data. Factors that are known to influence respondent fatigue include survey length, survey topic, question complexity, and open-ended question type. There is a great deal of interest in understanding the drivers of physician survey responsiveness due to the value of information received from these practitioners. With the recent explosion of mobile smartphone technology, it has been possible to obtain survey data from users of mobile applications (apps) on a question-by-question basis. The author obtained basic demographic survey data as well as survey data related to an anesthesiology-specific drug called sugammadex and leveraged nonresponse rates to examine factors that influenced respondent fatigue. Methods Primary data were collected between December 2015 and February 2017. Surveys and in-app analytics were collected from global users of a mobile anesthesia calculator app. Key independent variables were user country, healthcare provider role, rating of importance of the app to personal practice, length of time in practice, and frequency of app use. Key dependent variable was the metric of respondent fatigue. Results Provider role and World Bank country income level were predictive of the rate of respondent fatigue for this in-app survey. Importance of the app to the provider and length of time in practice were moderately associated with fatigue. Frequency of app use was not associated. This study focused on a survey with a topic closely related to the subject area of the app. Respondent fatigue rates will likely change dramatically if the topic does not align closely. Discussion Although apps may serve as powerful platforms for data collection, responses rates to in-app surveys may differ on the basis of important respondent characteristics. Studies should be carefully designed to mitigate fatigue as well as powered with the understanding of the respondent…
format: application/pdf
format: text/html
creator: Vikas N. O’Reilly-Shah
subject: Anesthesiology and Pain Management
subject: Global Health
subject: Human-Computer Interaction
subject: Statistics
description: doi:10.7717/peerj.3785
publisher: PeerJ Inc.
rights: © 2017 O’Reilly-Shah
abstract: Background Respondent fatigue, also known as survey fatigue, is a common problem in the collection of survey data. Factors that are known to influence respondent fatigue include survey length, survey topic, question complexity, and open-ended question type. There is a great deal of interest in understanding the drivers of physician survey responsiveness due to the value of information received from these practitioners. With the recent explosion of mobile smartphone technology, it has been possible to obtain survey data from users of mobile applications (apps) on a question-by-question basis. The author obtained basic demographic survey data as well as survey data related to an anesthesiology-specific drug called sugammadex and leveraged nonresponse rates to examine factors that influenced respondent fatigue. Methods Primary data were collected between December 2015 and February 2017. Surveys and in-app analytics were collected from global users of a mobile anesthesia calculator app. Key independent variables were user country, healthcare provider role, rating of importance of the app to personal practice, length of time in practice, and frequency of app use. Key dependent variable was the metric of respondent fatigue. Results Provider role and World Bank country income level were predictive of the rate of respondent fatigue for this in-app survey. Importance of the app to the provider and length of time in practice were moderately associated with fatigue. Frequency of app use was not associated. This study focused on a survey with a topic closely related to the subject area of the app. Respondent fatigue rates will likely change dramatically if the topic does not align closely. Discussion Although apps may serve as powerful platforms for data collection, responses rates to in-app surveys may differ on the basis of important respondent characteristics. Studies should be carefully designed to mitigate fatigue as well as powered with the understanding of the respondent…
bibliographic citation: O’Reilly-Shah (2017) Factors influencing healthcare provider respondent fatigue answering a globally administered in-app survey. PeerJ 5:e3785 https://doi.org/10.7717/peerj.3785
date submitted: 2017-04-19
date accepted: 2017-08-18
issued: 2017-09-12
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: O’Reilly-Shah
  given name: Vikas N.
doi: 10.7717/peerj.3785
volume: 5
issn: 2167-8359
publication name: PeerJ
publication date: 2017-09-12
copyright: ©2017 O’Reilly-Shah
attribution name: O’Reilly-Shah

Identification and analysis of CYP450 genes from transcriptome of Lonicera japonica and expression analysis of chlorogenic acid biosynthesis related CYP450s
type: item
type: AcademicArticle
description: Background Lonicera japonica is an important medicinal plant that has been widely used in traditional Chinese medicine for thousands of years. The pharmacological activities of L. japonica are mainly due to its rich natural active ingredients, most of which are secondary metabolites. CYP450s are a large, complex, and widespread superfamily of proteins that participate in many endogenous and exogenous metabolic reactions, especially secondary metabolism. Here, we identified CYP450s in L. japonica transcriptome and analyzed CYP450s that may be involved in chlorogenic acid (CGA) biosynthesis. Methods The recent availability of L. japonica transcriptome provided opportunity to identify CYP450s in this herb. BLAST based method and HMM based method were used to identify CYP450s in L. japonica transcriptome. Then, phylogenetic analysis, conserved motifs analysis, GO annotation, and KEGG annotation analyses were conducted to characterize the identified CYP450s. qRT-PCR was used to explore expression patterns of five CGA biosynthesis related CYP450s. Results In this study, 151 putative CYP450s with complete cytochrome P450 domain, which belonged to 10 clans, 45 families and 76 subfamilies, were identified in L. japonica transcriptome. Phylogenetic analysis classified these CYP450s into two major branches, A-type (47%) and non-A type (53%). Both types of CYP450s had conserved motifs in L. japonica. The differences of typical motif sequences between A-type and non-A type CYP450s in L. japonica were similar with other plants. GO classification indicated that non-A type CYP450s participated in more molecular functions and biological processes than A-type. KEGG pathway annotation totally assigned 47 CYP450s to 25 KEGG pathways. From these data, we cloned two LjC3Hs (CYP98A subfamily) and three LjC4Hs (CYP73A subfamily) that may be involved in biosynthesis of CGA, the major ingredient for pharmacological activities of L. japonica. qRT-PCR results indicated that two LjC3Hs exhibite…
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creator: Xiwu Qi
creator: Xu Yu
creator: Daohua Xu
creator: Hailing Fang
creator: Ke Dong
creator: Weilin Li
creator: Chengyuan Liang
subject: Molecular Biology
subject: Plant Science
description: doi:10.7717/peerj.3781
publisher: PeerJ Inc.
rights: © 2017 Qi et al.
abstract: Background Lonicera japonica is an important medicinal plant that has been widely used in traditional Chinese medicine for thousands of years. The pharmacological activities of L. japonica are mainly due to its rich natural active ingredients, most of which are secondary metabolites. CYP450s are a large, complex, and widespread superfamily of proteins that participate in many endogenous and exogenous metabolic reactions, especially secondary metabolism. Here, we identified CYP450s in L. japonica transcriptome and analyzed CYP450s that may be involved in chlorogenic acid (CGA) biosynthesis. Methods The recent availability of L. japonica transcriptome provided opportunity to identify CYP450s in this herb. BLAST based method and HMM based method were used to identify CYP450s in L. japonica transcriptome. Then, phylogenetic analysis, conserved motifs analysis, GO annotation, and KEGG annotation analyses were conducted to characterize the identified CYP450s. qRT-PCR was used to explore expression patterns of five CGA biosynthesis related CYP450s. Results In this study, 151 putative CYP450s with complete cytochrome P450 domain, which belonged to 10 clans, 45 families and 76 subfamilies, were identified in L. japonica transcriptome. Phylogenetic analysis classified these CYP450s into two major branches, A-type (47%) and non-A type (53%). Both types of CYP450s had conserved motifs in L. japonica. The differences of typical motif sequences between A-type and non-A type CYP450s in L. japonica were similar with other plants. GO classification indicated that non-A type CYP450s participated in more molecular functions and biological processes than A-type. KEGG pathway annotation totally assigned 47 CYP450s to 25 KEGG pathways. From these data, we cloned two LjC3Hs (CYP98A subfamily) and three LjC4Hs (CYP73A subfamily) that may be involved in biosynthesis of CGA, the major ingredient for pharmacological activities of L. japonica. qRT-PCR results indicated that two LjC3Hs exhibite…
bibliographic citation: Qi et al. (2017) Identification and analysis of CYP450 genes from transcriptome of Lonicera japonica and expression analysis of chlorogenic acid biosynthesis related CYP450s. PeerJ 5:e3781 https://doi.org/10.7717/peerj.3781
date submitted: 2017-04-21
date accepted: 2017-08-17
issued: 2017-09-12
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Qi
  given name: Xiwu
author list: Agent
  family name: Yu
  given name: Xu
author list: Agent
  family name: Xu
  given name: Daohua
author list: Agent
  family name: Fang
  given name: Hailing
author list: Agent
  family name: Dong
  given name: Ke
author list: Agent
  family name: Li
  given name: Weilin
author list: Agent
  family name: Liang
  given name: Chengyuan
doi: 10.7717/peerj.3781
volume: 5
issn: 2167-8359
publication name: PeerJ
publication date: 2017-09-12
copyright: ©2017 Qi et al.
attribution name: Qi et al.

Comparison of polybrominated diphenyl ethers (PBDEs) and polychlorinated biphenyls (PCBs) in the serum of hypothyroxinemic and euthyroid dogs
type: item
type: AcademicArticle
description: Objective To determine the profile of 14 polybrominated diphenyl ethers (PBDEs) and 23 polychlorinated biphenyls (PCBs) in serum of domestic canines and whether this was predictive of thyroid hormone status. Samples Serum samples were collected from 51 client-owned dogs visiting the University of California Davis William R. Pritchard Veterinary Medical Teaching Hospital during 2012 to 2016 for routine appointments. Fifteen dogs were diagnosed with hypothyroxinemia while 36 were euthyroid. Procedures Concentrations of PBDEs and PCBs in canine serum samples were measured by gas chromatography mass spectrometry. Logistic regression analysis was used to determine the association between the presence/absence of canine hypothyroxinemia and the serum concentration of individual PBDE or PCB congeners. Results The median concentrations of total PBDE and PCB congeners in the hypothyroxinemic group were 660 and 1,371 ng/g lipid, respectively, which were higher than concentrations detected in the control group. However, logistic regression analysis determined that current concentrations of PBDEs and PCBs in canines were not significantly associated with hypothyroxinemia. BDE 183 was the only congener showing near significance (p = 0.068). Conclusions PBDE and PCB congeners were detected in all canine samples confirming ongoing exposure to these pollutants. Because household dogs share the human environment, they may serve as biosentinels of human exposure to these contaminants.
format: application/pdf
format: text/html
creator: Grace Lau
creator: Kyla Walter
creator: Philip Kass
creator: Birgit Puschner
subject: Ecotoxicology
subject: Environmental Contamination and Remediation
subject: Environmental Sciences
subject: Toxicology
subject: Veterinary Medicine
description: doi:10.7717/peerj.3780
publisher: PeerJ Inc.
rights: © 2017 Lau et al.
abstract: Objective To determine the profile of 14 polybrominated diphenyl ethers (PBDEs) and 23 polychlorinated biphenyls (PCBs) in serum of domestic canines and whether this was predictive of thyroid hormone status. Samples Serum samples were collected from 51 client-owned dogs visiting the University of California Davis William R. Pritchard Veterinary Medical Teaching Hospital during 2012 to 2016 for routine appointments. Fifteen dogs were diagnosed with hypothyroxinemia while 36 were euthyroid. Procedures Concentrations of PBDEs and PCBs in canine serum samples were measured by gas chromatography mass spectrometry. Logistic regression analysis was used to determine the association between the presence/absence of canine hypothyroxinemia and the serum concentration of individual PBDE or PCB congeners. Results The median concentrations of total PBDE and PCB congeners in the hypothyroxinemic group were 660 and 1,371 ng/g lipid, respectively, which were higher than concentrations detected in the control group. However, logistic regression analysis determined that current concentrations of PBDEs and PCBs in canines were not significantly associated with hypothyroxinemia. BDE 183 was the only congener showing near significance (p = 0.068). Conclusions PBDE and PCB congeners were detected in all canine samples confirming ongoing exposure to these pollutants. Because household dogs share the human environment, they may serve as biosentinels of human exposure to these contaminants.
bibliographic citation: Lau et al. (2017) Comparison of polybrominated diphenyl ethers (PBDEs) and polychlorinated biphenyls (PCBs) in the serum of hypothyroxinemic and euthyroid dogs. PeerJ 5:e3780 https://doi.org/10.7717/peerj.3780
date submitted: 2017-02-23
date accepted: 2017-08-17
issued: 2017-09-12
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Lau
  given name: Grace
author list: Agent
  family name: Walter
  given name: Kyla
author list: Agent
  family name: Kass
  given name: Philip
author list: Agent
  family name: Puschner
  given name: Birgit
doi: 10.7717/peerj.3780
volume: 5
issn: 2167-8359
publication name: PeerJ
publication date: 2017-09-12
copyright: ©2017 Lau et al.
attribution name: Lau et al.

The landscape of fear conceptual framework: definition and review of current applications and misuses
type: item
type: AcademicArticle
description: Landscapes of Fear (LOF), the spatially explicit distribution of perceived predation risk as seen by a population, is increasingly cited in ecological literature and has become a frequently used “buzz-word”. With the increase in popularity, it became necessary to clarify the definition for the term, suggest boundaries and propose a common framework for its use. The LOF, as a progeny of the “ecology of fear” conceptual framework, defines fear as the strategic manifestation of the cost-benefit analysis of food and safety tradeoffs. In addition to direct predation risk, the LOF is affected by individuals’ energetic-state, inter- and intra-specific competition and is constrained by the evolutionary history of each species. Herein, based on current applications of the LOF conceptual framework, I suggest the future research in this framework will be directed towards: (1) finding applied management uses as a trait defining a population’s habitat-use and habitat-suitability; (2) studying multi-dimensional distribution of risk-assessment through time and space; (3) studying variability between individuals within a population; (4) measuring eco-neurological implications of risk as a feature of environmental heterogeneity and (5) expanding temporal and spatial scales of empirical studies.
format: application/pdf
format: text/html
creator: Sonny S. Bleicher
subject: Animal Behavior
subject: Biodiversity
subject: Conservation Biology
subject: Ecology
subject: Zoology
description: doi:10.7717/peerj.3772
publisher: PeerJ Inc.
rights: © 2017 Bleicher
abstract: Landscapes of Fear (LOF), the spatially explicit distribution of perceived predation risk as seen by a population, is increasingly cited in ecological literature and has become a frequently used “buzz-word”. With the increase in popularity, it became necessary to clarify the definition for the term, suggest boundaries and propose a common framework for its use. The LOF, as a progeny of the “ecology of fear” conceptual framework, defines fear as the strategic manifestation of the cost-benefit analysis of food and safety tradeoffs. In addition to direct predation risk, the LOF is affected by individuals’ energetic-state, inter- and intra-specific competition and is constrained by the evolutionary history of each species. Herein, based on current applications of the LOF conceptual framework, I suggest the future research in this framework will be directed towards: (1) finding applied management uses as a trait defining a population’s habitat-use and habitat-suitability; (2) studying multi-dimensional distribution of risk-assessment through time and space; (3) studying variability between individuals within a population; (4) measuring eco-neurological implications of risk as a feature of environmental heterogeneity and (5) expanding temporal and spatial scales of empirical studies.
bibliographic citation: Bleicher (2017) The landscape of fear conceptual framework: definition and review of current applications and misuses. PeerJ 5:e3772 https://doi.org/10.7717/peerj.3772
date submitted: 2017-02-27
date accepted: 2017-08-16
issued: 2017-09-12
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Bleicher
  given name: Sonny S.
doi: 10.7717/peerj.3772
volume: 5
issn: 2167-8359
publication name: PeerJ
publication date: 2017-09-12
copyright: ©2017 Bleicher
attribution name: Bleicher

Habitat suitability—density relationship in an endangered woodland species: the case of the Blue Chaffinch (Fringilla polatzeki)
type: item
type: AcademicArticle
description: Background Understanding constraints to the distribution of threatened species may help to ascertain whether there are other suitable sectors for reducing the risks associated with species that are recorded in only one protected locality, and to inform about the suitability of other areas for reintroduction or translocation programs. Methods We studied the Gran Canaria blue chaffinch (Fringilla polatzeki), a habitat specialist endemic of the Canary Islands restricted to the pine forest of Inagua, the only area where the species has been naturally present as a regular breeder in the last 25 years. A suitability distribution model using occurrences with demographic relevance (i.e., nest locations of successful breeding attempts analysed using boosted classification trees) was built considering orographic, climatic and habitat structure predictors. By means of a standardized survey program we monitored the yearly abundance of the species in 100 sectors since the declaration of Inagua as a Strict Nature Reserve in 1994. Results The variables with the highest relative importance in blue chaffinch habitat preferences were pine height, tree cover, altitude, and rainfall during the driest trimester (July–September). The observed local abundance of the blue chaffinch in Inagua (survey data) was significantly correlated with habitat suitability derived from modelling the location of successful nesting attempts (using linear and quantile regressions). The outcomes of the habitat suitability model were used to quantify the suitability of other natural, historic, pine forests of Gran Canaria. Tamadaba is the forest with most suitable woodland patches for the species. We estimated a population size of 195–430 blue chaffinches in Inagua since 2011 (95% CI), the smallest population size of a woodland passerine in the Western Palearctic. Discussion Habitat suitability obtained from modelling the location of successful breeding attempts is a good surrogate of the observed local abund…
format: application/pdf
format: text/html
creator: Luis M. Carrascal
creator: Ángel C. Moreno
creator: Alejandro Delgado
creator: Víctor Suárez
creator: Domingo Trujillo
subject: Biogeography
subject: Conservation Biology
subject: Ecology
subject: Zoology
description: doi:10.7717/peerj.3771
publisher: PeerJ Inc.
rights: © 2017 Carrascal et al.
abstract: Background Understanding constraints to the distribution of threatened species may help to ascertain whether there are other suitable sectors for reducing the risks associated with species that are recorded in only one protected locality, and to inform about the suitability of other areas for reintroduction or translocation programs. Methods We studied the Gran Canaria blue chaffinch (Fringilla polatzeki), a habitat specialist endemic of the Canary Islands restricted to the pine forest of Inagua, the only area where the species has been naturally present as a regular breeder in the last 25 years. A suitability distribution model using occurrences with demographic relevance (i.e., nest locations of successful breeding attempts analysed using boosted classification trees) was built considering orographic, climatic and habitat structure predictors. By means of a standardized survey program we monitored the yearly abundance of the species in 100 sectors since the declaration of Inagua as a Strict Nature Reserve in 1994. Results The variables with the highest relative importance in blue chaffinch habitat preferences were pine height, tree cover, altitude, and rainfall during the driest trimester (July–September). The observed local abundance of the blue chaffinch in Inagua (survey data) was significantly correlated with habitat suitability derived from modelling the location of successful nesting attempts (using linear and quantile regressions). The outcomes of the habitat suitability model were used to quantify the suitability of other natural, historic, pine forests of Gran Canaria. Tamadaba is the forest with most suitable woodland patches for the species. We estimated a population size of 195–430 blue chaffinches in Inagua since 2011 (95% CI), the smallest population size of a woodland passerine in the Western Palearctic. Discussion Habitat suitability obtained from modelling the location of successful breeding attempts is a good surrogate of the observed local abund…
bibliographic citation: Carrascal et al. (2017) Habitat suitability—density relationship in an endangered woodland species: the case of the Blue Chaffinch (Fringilla polatzeki). PeerJ 5:e3771 https://doi.org/10.7717/peerj.3771
date submitted: 2017-04-21
date accepted: 2017-08-16
issued: 2017-09-12
is part of: PeerJ
license: http://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Carrascal
  given name: Luis M.
author list: Agent
  family name: Moreno
  given name: Ángel C.
author list: Agent
  family name: Delgado
  given name: Alejandro
author list: Agent
  family name: Suárez
  given name: Víctor
author list: Agent
  family name: Trujillo
  given name: Domingo
doi: 10.7717/peerj.3771
volume: 5
issn: 2167-8359
publication name: PeerJ
publication date: 2017-09-12
copyright: ©2017 Carrascal et al.
attribution name: Carrascal et al.

Challenging a bioinformatic tool’s ability to detect microbial contaminants using in silico whole genome sequencing data
type: item
type: AcademicArticle
description: High sensitivity methods such as next generation sequencing and polymerase chain reaction (PCR) are adversely impacted by organismal and DNA contaminants. Current methods for detecting contaminants in microbial materials (genomic DNA and cultures) are not sensitive enough and require either a known or culturable contaminant. Whole genome sequencing (WGS) is a promising approach for detecting contaminants due to its sensitivity and lack of need for a priori assumptions about the contaminant. Prior to applying WGS, we must first understand its limitations for detecting contaminants and potential for false positives. Herein we demonstrate and characterize a WGS-based approach to detect organismal contaminants using an existing metagenomic taxonomic classification algorithm. Simulated WGS datasets from ten genera as individuals and binary mixtures of eight organisms at varying ratios were analyzed to evaluate the role of contaminant concentration and taxonomy on detection. For the individual genomes the false positive contaminants reported depended on the genus, with Staphylococcus, Escherichia, and Shigella having the highest proportion of false positives. For nearly all binary mixtures the contaminant was detected in the in-silico datasets at the equivalent of 1 in 1,000 cells, though F. tularensis was not detected in any of the simulated contaminant mixtures and Y. pestis was only detected at the equivalent of one in 10 cells. Once a WGS method for detecting contaminants is characterized, it can be applied to evaluate microbial material purity, in efforts to ensure that contaminants are characterized in microbial materials used to validate pathogen detection assays, generate genome assemblies for database submission, and benchmark sequencing methods.
format: application/pdf
format: text/html
creator: Nathan D. Olson
creator: Justin M. Zook
creator: Jayne B. Morrow
creator: Nancy J. Lin
subject: Bioinformatics
subject: Genomics
subject: Microbiology
description: doi:10.7717/peerj.3729
publisher: PeerJ Inc.
rights: © 2017
abstract: High sensitivity methods such as next generation sequencing and polymerase chain reaction (PCR) are adversely impacted by organismal and DNA contaminants. Current methods for detecting contaminants in microbial materials (genomic DNA and cultures) are not sensitive enough and require either a known or culturable contaminant. Whole genome sequencing (WGS) is a promising approach for detecting contaminants due to its sensitivity and lack of need for a priori assumptions about the contaminant. Prior to applying WGS, we must first understand its limitations for detecting contaminants and potential for false positives. Herein we demonstrate and characterize a WGS-based approach to detect organismal contaminants using an existing metagenomic taxonomic classification algorithm. Simulated WGS datasets from ten genera as individuals and binary mixtures of eight organisms at varying ratios were analyzed to evaluate the role of contaminant concentration and taxonomy on detection. For the individual genomes the false positive contaminants reported depended on the genus, with Staphylococcus, Escherichia, and Shigella having the highest proportion of false positives. For nearly all binary mixtures the contaminant was detected in the in-silico datasets at the equivalent of 1 in 1,000 cells, though F. tularensis was not detected in any of the simulated contaminant mixtures and Y. pestis was only detected at the equivalent of one in 10 cells. Once a WGS method for detecting contaminants is characterized, it can be applied to evaluate microbial material purity, in efforts to ensure that contaminants are characterized in microbial materials used to validate pathogen detection assays, generate genome assemblies for database submission, and benchmark sequencing methods.
bibliographic citation: Olson et al. (2017) Challenging a bioinformatic tool’s ability to detect microbial contaminants using in silico whole genome sequencing data. PeerJ 5:e3729 https://doi.org/10.7717/peerj.3729
date submitted: 2017-04-03
date accepted: 2017-08-02
issued: 2017-09-12
is part of: PeerJ
license: http://creativecommons.org/publicdomain/zero/1.0/
author list: Agent
  family name: Olson
  given name: Nathan D.
author list: Agent
  family name: Zook
  given name: Justin M.
author list: Agent
  family name: Morrow
  given name: Jayne B.
author list: Agent
  family name: Lin
  given name: Nancy J.
doi: 10.7717/peerj.3729
volume: 5
issn: 2167-8359
publication name: PeerJ
publication date: 2017-09-12

PeerJ
type: Periodical
uri: PeerJ
issn: 2167-8359