PeerJ
type: channel
link: https://peerj.com/articles/
description: Articles published in PeerJ
publisher: PeerJ Inc.
publication name: PeerJ
issn: 2167-8359
items: Expression of collagen type 1 alpha 1 indicates lymph node metastasis and poor outcomes in squamous cell carcinomas of the lung
items: The role of m6A-related genes in the prognosis and immune microenvironment of pancreatic adenocarcinoma
items: No one-size-fits-all solution to clean GBIF
items: Identification of an 8-miRNA signature as a potential prognostic biomarker for glioma
items: Isolation and characterization of a motility-defective mutant of Euglena gracilis
items: Differing physiological and behavioral responses to anthropogenic factors between resident and non-resident African elephants at Mpala Ranch, Laikipia County, Kenya
items: Pyruvate is required for catecholamine-stimulated growth of different strains of Campylobacter jejuni
items: The utility of MEWS for predicting the mortality in the elderly adults with COVID-19: a retrospective cohort study with comparison to other predictive clinical scores
items: Predicting CoVID-19 community mortality risk using machine learning and development of an online prognostic tool
items: Suitability of native milkweed (Asclepias) species versus cultivars for supporting monarch butterflies and bees in urban gardens

Expression of collagen type 1 alpha 1 indicates lymph node metastasis and poor outcomes in squamous cell carcinomas of the lung
type: item
type: AcademicArticle
description: Background Squamous cell carcinomas of the lung are an extremely common and deadly form of non-small cell lung cancers. Clinical management of the disease is dependent on staging and metastatic status. Metastasis to the lymph node is especially crucial to diagnose as it occurs at an earlier stage. However, lymphadenectomies are invasive and tumor cells may be overlooked during evaluation.There are limited approved biomarkers for predicting lymph node metastasis with squamous cell carcinomas of the lung (LSCC). Methods Genome data of 60 tumor-adjacent samples were downloaded from Genome Expression Omnibus. We identified over-expressed HUB genes using Cytoscape as key prognostic markers. The selected markers were further evaluated based on gene ontology and overall expression levels compared to normal tissue using The Cancer Genome Atlas. We further validated these results using clinical biopsy tissue taken from squamous cell carcinoma patients. Results Analysis of the genome expression data resulted in 13 relevant hub genes that were differentially expressed in cancerous samples. All of these genes are associated with collagen biosynthesis within the tumor microenvironment. We chose Collagen Type 1 Alpha 1 (COL1A1) as the most relevant prognostic marker due to its high number of pathway connections and over expression in the tumor microenvironment compared to the other 12 genes. Additionally, based on analysis of The Cancer Genome Atlas, tumors with higher levels of COL1A1 expression are associated with poorer overall survival. Finally, evaluation of clinical biopsy samples suggests that overexpression of COL1A1 in the LSCC microenvironment highly correlates with lymph node metastasis. These results suggest COL1A1 is a clinically relevant marker that should be used to justify lymphadenectomies.
format: application/pdf
format: text/html
creator: Siyuan Dong
creator: Peiyao Zhu
creator: Shuguang Zhang
subject: Bioinformatics
subject: Oncology
subject: Respiratory Medicine
subject: Surgery and Surgical Specialties
subject: Medical Genetics
description: doi:10.7717/peerj.10089
publisher: PeerJ Inc.
rights: © 2020 Dong et al.
abstract: Background Squamous cell carcinomas of the lung are an extremely common and deadly form of non-small cell lung cancers. Clinical management of the disease is dependent on staging and metastatic status. Metastasis to the lymph node is especially crucial to diagnose as it occurs at an earlier stage. However, lymphadenectomies are invasive and tumor cells may be overlooked during evaluation.There are limited approved biomarkers for predicting lymph node metastasis with squamous cell carcinomas of the lung (LSCC). Methods Genome data of 60 tumor-adjacent samples were downloaded from Genome Expression Omnibus. We identified over-expressed HUB genes using Cytoscape as key prognostic markers. The selected markers were further evaluated based on gene ontology and overall expression levels compared to normal tissue using The Cancer Genome Atlas. We further validated these results using clinical biopsy tissue taken from squamous cell carcinoma patients. Results Analysis of the genome expression data resulted in 13 relevant hub genes that were differentially expressed in cancerous samples. All of these genes are associated with collagen biosynthesis within the tumor microenvironment. We chose Collagen Type 1 Alpha 1 (COL1A1) as the most relevant prognostic marker due to its high number of pathway connections and over expression in the tumor microenvironment compared to the other 12 genes. Additionally, based on analysis of The Cancer Genome Atlas, tumors with higher levels of COL1A1 expression are associated with poorer overall survival. Finally, evaluation of clinical biopsy samples suggests that overexpression of COL1A1 in the LSCC microenvironment highly correlates with lymph node metastasis. These results suggest COL1A1 is a clinically relevant marker that should be used to justify lymphadenectomies.
bibliographic citation: Dong et al. (2020) Expression of collagen type 1 alpha 1 indicates lymph node metastasis and poor outcomes in squamous cell carcinomas of the lung. PeerJ 8:e10089 https://doi.org/10.7717/peerj.10089
date submitted: 2020-04-20
date accepted: 2020-09-13
issued: 2020-09-29
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Dong
  given name: Siyuan
author list: Agent
  family name: Zhu
  given name: Peiyao
author list: Agent
  family name: Zhang
  given name: Shuguang
doi: 10.7717/peerj.10089
volume: 8
issn: 2167-8359
publication name: PeerJ
publication date: 2020-09-29
copyright: ©2020 Dong et al.
attribution name: Dong et al.

The role of m6A-related genes in the prognosis and immune microenvironment of pancreatic adenocarcinoma
type: item
type: AcademicArticle
description: Background Pancreatic adenocarcinoma (PAAD) is among the most lethal diseases and has a dismal prognosis; however, efficient treatment is currently limited. Several studies have observed epigenetic variation during tumorigenesis, suggesting the potential role of RNA methylation, especially N6-methyladenosine (m6A) modification, as a novel epigenetic modification mediating PAAD prognosis. Methods The expression levels of m6A-related genes were downloaded from The Cancer Genome Atlas-Pancreatic Adenocarcinoma (TCGA) and Genotype-Tissue Expression (GTEx) projects, and the findings were validated in four Expression Omnibus (GEO) datasets. A predictive model was constructed using a lasso regression and evaluated by a survival analysis and receiver operating characteristic curve. Consensus clustering identified two distinct subgroups with different immune activity signatures based on the expression pattern of m6A-related genes. The relationship between the mutation state of m6A-related genes and infiltration of immune cells was established and visualized using Tumor Immune Estimation Resource (https://cistrome.shinyapps.io/timer/). Results Fourteen of twenty-one m6A-related genes were differentially expressed between PAAD and normal tissues in TCGA-GTEx cohort. Among these genes, HNRNPC, IGF2BP2 and YTHDF1 were further validated in four GEO datasets. Moreover, an m6A-based model exhibited moderate accuracy in predicting overall survival in PAAD samples. Additionally, potential m6A modification targets were screened by selecting genes from a set of 23,391 genes that not only harbored the most m6A-modified sites but also showed a robust correlation with PAAD survival. Moreover, we correlated the expression level of m6A-related genes with the immune microenvironment of pancreatic cancer for the first time. Specifically, both arm-level gain and deletion of ALKBH5 decreased the infiltration of CD8+T cells (P < 0.05 and P < 0.01, respectively). Conclusion Collectively, our find…
format: application/pdf
format: text/html
creator: Rong Tang
creator: Yiyin Zhang
creator: Chen Liang
creator: Jin Xu
creator: Qingcai Meng
creator: Jie Hua
creator: Jiang Liu
creator: Bo Zhang
creator: Xianjun Yu
creator: Si Shi
subject: Bioinformatics
subject: Gastroenterology and Hepatology
subject: Oncology
subject: Medical Genetics
description: doi:10.7717/peerj.9602
publisher: PeerJ Inc.
rights: © 2020 Tang et al.
abstract: Background Pancreatic adenocarcinoma (PAAD) is among the most lethal diseases and has a dismal prognosis; however, efficient treatment is currently limited. Several studies have observed epigenetic variation during tumorigenesis, suggesting the potential role of RNA methylation, especially N6-methyladenosine (m6A) modification, as a novel epigenetic modification mediating PAAD prognosis. Methods The expression levels of m6A-related genes were downloaded from The Cancer Genome Atlas-Pancreatic Adenocarcinoma (TCGA) and Genotype-Tissue Expression (GTEx) projects, and the findings were validated in four Expression Omnibus (GEO) datasets. A predictive model was constructed using a lasso regression and evaluated by a survival analysis and receiver operating characteristic curve. Consensus clustering identified two distinct subgroups with different immune activity signatures based on the expression pattern of m6A-related genes. The relationship between the mutation state of m6A-related genes and infiltration of immune cells was established and visualized using Tumor Immune Estimation Resource (https://cistrome.shinyapps.io/timer/). Results Fourteen of twenty-one m6A-related genes were differentially expressed between PAAD and normal tissues in TCGA-GTEx cohort. Among these genes, HNRNPC, IGF2BP2 and YTHDF1 were further validated in four GEO datasets. Moreover, an m6A-based model exhibited moderate accuracy in predicting overall survival in PAAD samples. Additionally, potential m6A modification targets were screened by selecting genes from a set of 23,391 genes that not only harbored the most m6A-modified sites but also showed a robust correlation with PAAD survival. Moreover, we correlated the expression level of m6A-related genes with the immune microenvironment of pancreatic cancer for the first time. Specifically, both arm-level gain and deletion of ALKBH5 decreased the infiltration of CD8+T cells (P < 0.05 and P < 0.01, respectively). Conclusion Collectively, our find…
bibliographic citation: Tang et al. (2020) The role of m6A-related genes in the prognosis and immune microenvironment of pancreatic adenocarcinoma. PeerJ 8:e9602 https://doi.org/10.7717/peerj.9602
date submitted: 2020-03-30
date accepted: 2020-07-03
issued: 2020-09-28
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Tang
  given name: Rong
author list: Agent
  family name: Zhang
  given name: Yiyin
author list: Agent
  family name: Liang
  given name: Chen
author list: Agent
  family name: Xu
  given name: Jin
author list: Agent
  family name: Meng
  given name: Qingcai
author list: Agent
  family name: Hua
  given name: Jie
author list: Agent
  family name: Liu
  given name: Jiang
author list: Agent
  family name: Zhang
  given name: Bo
author list: Agent
  family name: Yu
  given name: Xianjun
author list: Agent
  family name: Shi
  given name: Si
doi: 10.7717/peerj.9602
volume: 8
issn: 2167-8359
publication name: PeerJ
publication date: 2020-09-28
copyright: ©2020 Tang et al.
attribution name: Tang et al.

No one-size-fits-all solution to clean GBIF
type: item
type: AcademicArticle
description: Species occurrence records provide the basis for many biodiversity studies. They derive from georeferenced specimens deposited in natural history collections and visual observations, such as those obtained through various mobile applications. Given the rapid increase in availability of such data, the control of quality and accuracy constitutes a particular concern. Automatic filtering is a scalable and reproducible means to identify potentially problematic records and tailor datasets from public databases such as the Global Biodiversity Information Facility (GBIF; http://www.gbif.org), for biodiversity analyses. However, it is unclear how much data may be lost by filtering, whether the same filters should be applied across all taxonomic groups, and what the effect of filtering is on common downstream analyses. Here, we evaluate the effect of 13 recently proposed filters on the inference of species richness patterns and automated conservation assessments for 18 Neotropical taxa, including terrestrial and marine animals, fungi, and plants downloaded from GBIF. We find that a total of 44.3% of the records are potentially problematic, with large variation across taxonomic groups (25–90%). A small fraction of records was identified as erroneous in the strict sense (4.2%), and a much larger proportion as unfit for most downstream analyses (41.7%). Filters of duplicated information, collection year, and basis of record, as well as coordinates in urban areas, or for terrestrial taxa in the sea or marine taxa on land, have the greatest effect. Automated filtering can help in identifying problematic records, but requires customization of which tests and thresholds should be applied to the taxonomic group and geographic area under focus. Our results stress the importance of thorough recording and exploration of the meta-data associated with species records for biodiversity research.
format: application/pdf
format: text/html
creator: Alexander Zizka
creator: Fernanda Antunes Carvalho
creator: Alice Calvente
creator: Mabel Rocio Baez-Lizarazo
creator: Andressa Cabral
creator: Jéssica Fernanda Ramos Coelho
creator: Matheus Colli-Silva
creator: Mariana Ramos Fantinati
creator: Moabe F. Fernandes
creator: Thais Ferreira-Araújo
creator: Fernanda Gondim Lambert Moreira
creator: Nathália Michellyda Cunha Santos
creator: Tiago Andrade Borges Santos
creator: Renata Clicia dos Santos-Costa
creator: Filipe C. Serrano
creator: Ana Paula Alves da Silva
creator: Arthur de Souza Soares
creator: Paolla Gabryelle Cavalcante de Souza
creator: Eduardo Calisto Tomaz
creator: Valéria Fonseca Vale
creator: Tiago Luiz Vieira
creator: Alexandre Antonelli
subject: Biodiversity
subject: Biogeography
subject: Conservation Biology
subject: Ecology
description: doi:10.7717/peerj.9916
publisher: PeerJ Inc.
rights: © 2020 Zizka et al.
abstract: Species occurrence records provide the basis for many biodiversity studies. They derive from georeferenced specimens deposited in natural history collections and visual observations, such as those obtained through various mobile applications. Given the rapid increase in availability of such data, the control of quality and accuracy constitutes a particular concern. Automatic filtering is a scalable and reproducible means to identify potentially problematic records and tailor datasets from public databases such as the Global Biodiversity Information Facility (GBIF; http://www.gbif.org), for biodiversity analyses. However, it is unclear how much data may be lost by filtering, whether the same filters should be applied across all taxonomic groups, and what the effect of filtering is on common downstream analyses. Here, we evaluate the effect of 13 recently proposed filters on the inference of species richness patterns and automated conservation assessments for 18 Neotropical taxa, including terrestrial and marine animals, fungi, and plants downloaded from GBIF. We find that a total of 44.3% of the records are potentially problematic, with large variation across taxonomic groups (25–90%). A small fraction of records was identified as erroneous in the strict sense (4.2%), and a much larger proportion as unfit for most downstream analyses (41.7%). Filters of duplicated information, collection year, and basis of record, as well as coordinates in urban areas, or for terrestrial taxa in the sea or marine taxa on land, have the greatest effect. Automated filtering can help in identifying problematic records, but requires customization of which tests and thresholds should be applied to the taxonomic group and geographic area under focus. Our results stress the importance of thorough recording and exploration of the meta-data associated with species records for biodiversity research.
bibliographic citation: Zizka et al. (2020) No one-size-fits-all solution to clean GBIF. PeerJ 8:e9916 https://doi.org/10.7717/peerj.9916
date submitted: 2020-03-17
date accepted: 2020-08-20
issued: 2020-09-28
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Zizka
  given name: Alexander
author list: Agent
  family name: Antunes Carvalho
  given name: Fernanda
author list: Agent
  family name: Calvente
  given name: Alice
author list: Agent
  family name: Rocio Baez-Lizarazo
  given name: Mabel
author list: Agent
  family name: Cabral
  given name: Andressa
author list: Agent
  family name: Coelho
  given name: Jéssica Fernanda Ramos
author list: Agent
  family name: Colli-Silva
  given name: Matheus
author list: Agent
  family name: Fantinati
  given name: Mariana Ramos
author list: Agent
  family name: Fernandes
  given name: Moabe F.
author list: Agent
  family name: Ferreira-Araújo
  given name: Thais
author list: Agent
  family name: Gondim Lambert Moreira
  given name: Fernanda
author list: Agent
  family name: Santos
  given name: Nathália Michellyda Cunha
author list: Agent
  family name: Santos
  given name: Tiago Andrade Borges
author list: Agent
  family name: dos Santos-Costa
  given name: Renata Clicia
author list: Agent
  family name: Serrano
  given name: Filipe C.
author list: Agent
  family name: Alves da Silva
  given name: Ana Paula
author list: Agent
  family name: de Souza Soares
  given name: Arthur
author list: Agent
  family name: Cavalcante de Souza
  given name: Paolla Gabryelle
author list: Agent
  family name: Calisto Tomaz
  given name: Eduardo
author list: Agent
  family name: Vale
  given name: Valéria Fonseca
author list: Agent
  family name: Vieira
  given name: Tiago Luiz
author list: Agent
  family name: Antonelli
  given name: Alexandre
doi: 10.7717/peerj.9916
volume: 8
issn: 2167-8359
publication name: PeerJ
publication date: 2020-09-28
copyright: ©2020 Zizka et al.
attribution name: Zizka et al.

Identification of an 8-miRNA signature as a potential prognostic biomarker for glioma
type: item
type: AcademicArticle
description: Background Glioma is the most common form of primary malignant intracranial tumor. Methods In the current study, miRNA matrix were obtained from the Chinese Glioma Genome Atlas (CGGA), and then univariate Cox regression analysis and Lasso regression analysis were utilized to select candidate miRNAs and multivariate Cox regression analysis was applied to establish a miRNA signature for predicting overall survival (OS) of glioma. The signature was assessed with the area under the curve (AUC) of the receiver operating characteristic curve (ROC) and validated by data from Gene Expression Omnibus (GEO). Results Eight miRNAs (miR-1246, miR-148a, miR-150, miR-196a, miR-338-3p, miR-342-5p, miR-548h and miR-645) were included in the miRNA signature. The AUC of ROC analysis for 1- and 3-year OS in the CGGA dataset was 0.747 and 0.905, respectively. In the GEO dataset, The AUC for 1- and 3-year was 0.736 and 0.809, respectively. The AUC in both the CGGA and GEO datasets was similar to that based on WHO 2007 classification (0.736 and 0.799) and WHO 2016 classification (0.663 and 0.807). Additionally, Kaplan–Meier plot revealed that high-risk score patients had a poorer clinical outcome. Multivariate Cox regression analysis suggested that the miRNA signature was an independent prognosis-related factor [HR: 6.579, 95% CI [1.227−35.268], p = 0.028]. Conclusion On the whole, in the present study, based on eight miRNAs, a novel prognostic signature was developed for predicting the 1- and 3- year survival rate in glioma. The results may be conducive to predict the precise prognosis of glioma and to elucidate the underlying molecular mechanisms. However, further experimental researches of miRNAs are needed to validate the findings of this study.
format: application/pdf
format: text/html
creator: Baowei Ji
creator: Lihua Chen
creator: Qiang Cai
creator: Qiao Guo
creator: Zhibiao Chen
creator: Du He
subject: Bioinformatics
subject: Computational Biology
subject: Molecular Biology
subject: Oncology
description: doi:10.7717/peerj.9943
publisher: PeerJ Inc.
rights: © 2020 Ji et al.
abstract: Background Glioma is the most common form of primary malignant intracranial tumor. Methods In the current study, miRNA matrix were obtained from the Chinese Glioma Genome Atlas (CGGA), and then univariate Cox regression analysis and Lasso regression analysis were utilized to select candidate miRNAs and multivariate Cox regression analysis was applied to establish a miRNA signature for predicting overall survival (OS) of glioma. The signature was assessed with the area under the curve (AUC) of the receiver operating characteristic curve (ROC) and validated by data from Gene Expression Omnibus (GEO). Results Eight miRNAs (miR-1246, miR-148a, miR-150, miR-196a, miR-338-3p, miR-342-5p, miR-548h and miR-645) were included in the miRNA signature. The AUC of ROC analysis for 1- and 3-year OS in the CGGA dataset was 0.747 and 0.905, respectively. In the GEO dataset, The AUC for 1- and 3-year was 0.736 and 0.809, respectively. The AUC in both the CGGA and GEO datasets was similar to that based on WHO 2007 classification (0.736 and 0.799) and WHO 2016 classification (0.663 and 0.807). Additionally, Kaplan–Meier plot revealed that high-risk score patients had a poorer clinical outcome. Multivariate Cox regression analysis suggested that the miRNA signature was an independent prognosis-related factor [HR: 6.579, 95% CI [1.227−35.268], p = 0.028]. Conclusion On the whole, in the present study, based on eight miRNAs, a novel prognostic signature was developed for predicting the 1- and 3- year survival rate in glioma. The results may be conducive to predict the precise prognosis of glioma and to elucidate the underlying molecular mechanisms. However, further experimental researches of miRNAs are needed to validate the findings of this study.
bibliographic citation: Ji et al. (2020) Identification of an 8-miRNA signature as a potential prognostic biomarker for glioma. PeerJ 8:e9943 https://doi.org/10.7717/peerj.9943
date submitted: 2020-04-03
date accepted: 2020-08-24
issued: 2020-09-28
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Ji
  given name: Baowei
author list: Agent
  family name: Chen
  given name: Lihua
author list: Agent
  family name: Cai
  given name: Qiang
author list: Agent
  family name: Guo
  given name: Qiao
author list: Agent
  family name: Chen
  given name: Zhibiao
author list: Agent
  family name: He
  given name: Du
doi: 10.7717/peerj.9943
volume: 8
issn: 2167-8359
publication name: PeerJ
publication date: 2020-09-28
copyright: ©2020 Ji et al.
attribution name: Ji et al.

Isolation and characterization of a motility-defective mutant of Euglena gracilis
type: item
type: AcademicArticle
description: Euglena gracilis is a green photosynthetic microalga that swims using its flagellum. This species has been used as a model organism for over half a century to study its metabolism and the mechanisms of its behavior. The development of mass-cultivation technology has led to E. gracilis application as a feedstock in various products such as foods. Therefore, breeding of E. gracilis has been attempted to improve the productivity of this feedstock for potential industrial applications. For this purpose, a characteristic that preserves the microalgal energy e.g., reduces motility, should be added to the cultivars. The objective of this study was to verify our hypothesis that E. gracilis locomotion-defective mutants are suitable for industrial applications because they save the energy required for locomotion. To test this hypothesis, we screened for E. gracilis mutants from Fe-ion-irradiated cell suspensions and established a mutant strain, ${\mathrm{M}}_{3}^{-}$ M 3 − ZFeL, which shows defects in flagellum formation and locomotion. The mutant strain exhibits a growth rate comparable to that of the wild type when cultured under autotrophic conditions, but had a slightly slower growth under heterotrophic conditions. It also stores 1.6 times the amount of paramylon, a crystal of β-1,3-glucan, under autotrophic culture conditions, and shows a faster sedimentation compared with that of the wild type, because of the deficiency in mobility and probably the high amount of paramylon accumulation. Such characteristics make E. gracilis mutant cells suitable for cost-effective mass cultivation and harvesting.
format: application/pdf
format: text/html
creator: Shuki Muramatsu
creator: Kohei Atsuji
creator: Koji Yamada
creator: Kazunari Ozasa
creator: Hideyuki Suzuki
creator: Takuto Takeuchi
creator: Yuka Hashimoto-Marukawa
creator: Yusuke Kazama
creator: Tomoko Abe
creator: Kengo Suzuki
creator: Osamu Iwata
subject: Agricultural Science
subject: Biotechnology
subject: Genetics
subject: Microbiology
description: doi:10.7717/peerj.10002
publisher: PeerJ Inc.
rights: © 2020 Muramatsu et al.
abstract: Euglena gracilis is a green photosynthetic microalga that swims using its flagellum. This species has been used as a model organism for over half a century to study its metabolism and the mechanisms of its behavior. The development of mass-cultivation technology has led to E. gracilis application as a feedstock in various products such as foods. Therefore, breeding of E. gracilis has been attempted to improve the productivity of this feedstock for potential industrial applications. For this purpose, a characteristic that preserves the microalgal energy e.g., reduces motility, should be added to the cultivars. The objective of this study was to verify our hypothesis that E. gracilis locomotion-defective mutants are suitable for industrial applications because they save the energy required for locomotion. To test this hypothesis, we screened for E. gracilis mutants from Fe-ion-irradiated cell suspensions and established a mutant strain, ${\mathrm{M}}_{3}^{-}$ M 3 − ZFeL, which shows defects in flagellum formation and locomotion. The mutant strain exhibits a growth rate comparable to that of the wild type when cultured under autotrophic conditions, but had a slightly slower growth under heterotrophic conditions. It also stores 1.6 times the amount of paramylon, a crystal of β-1,3-glucan, under autotrophic culture conditions, and shows a faster sedimentation compared with that of the wild type, because of the deficiency in mobility and probably the high amount of paramylon accumulation. Such characteristics make E. gracilis mutant cells suitable for cost-effective mass cultivation and harvesting.
bibliographic citation: Muramatsu et al. (2020) Isolation and characterization of a motility-defective mutant of Euglena gracilis. PeerJ 8:e10002 https://doi.org/10.7717/peerj.10002
date submitted: 2020-05-19
date accepted: 2020-08-30
issued: 2020-09-28
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Muramatsu
  given name: Shuki
author list: Agent
  family name: Atsuji
  given name: Kohei
author list: Agent
  family name: Yamada
  given name: Koji
author list: Agent
  family name: Ozasa
  given name: Kazunari
author list: Agent
  family name: Suzuki
  given name: Hideyuki
author list: Agent
  family name: Takeuchi
  given name: Takuto
author list: Agent
  family name: Hashimoto-Marukawa
  given name: Yuka
author list: Agent
  family name: Kazama
  given name: Yusuke
author list: Agent
  family name: Abe
  given name: Tomoko
author list: Agent
  family name: Suzuki
  given name: Kengo
author list: Agent
  family name: Iwata
  given name: Osamu
doi: 10.7717/peerj.10002
volume: 8
issn: 2167-8359
publication name: PeerJ
publication date: 2020-09-28
copyright: ©2020 Muramatsu et al.
attribution name: Muramatsu et al.

Differing physiological and behavioral responses to anthropogenic factors between resident and non-resident African elephants at Mpala Ranch, Laikipia County, Kenya
type: item
type: AcademicArticle
description: Background Heterogeneous landscapes like those of Laikipia County, Kenya consist of a mosaic of land-use types, which may exert differential physiological effects on elephants that occupy and traverse them. Understanding behavioral and physiological states of wild African elephants in response to the challenges of living in human-dominated landscapes is therefore important for conservation managers to evaluate risks imposed by elephants to humans and vice versa. Several conservation physiology tools have been developed to assess how animals respond to both natural and anthropogenic changes, and determine biological impacts. This study investigated how migratory and avoidance behavioral to vehicle presence, and vegetation quality affected fecal glucocorticoid (GC) metabolite (FGM) concentrations in African elephants at Mpala Ranch, Laikipia County, Kenya. Methods The study compared adrenal glucocorticoid activity of resident elephants that live within Mpala (n = 57) and non-resident elephants whose space use patterns overlap several ranches (n = 99) in Laikipia County, Kenya. Fecal samples were collected for a 4-month period between April and August for analysis of FGM concentrations. Behavioral reactions to research vehicles and body condition also were assessed. Satellite images from Terra Moderate Resolution Imaging (MODIS MOD13Q1) were downloaded and processed using Google Earth Engine to calculate a Normalized Difference Vegetation Index (NDVI) as a measure of vegetation quality. Results As expected, there was a positive correlation between avoidance behavior to vehicle presence and FGM concentrations in both resident and non-resident elephants, whereas there was an inverse relationship between FGM concentrations and NDVI values. Our study also found a positive influence of age on the FGM concentrations, but there were no relationships between FGM and sex, social group type, herd size, and body condition. However, contrary to our expectations, resident elephants…
format: application/pdf
format: text/html
creator: Sandy Oduor
creator: Janine Brown
creator: Geoffrey M. Macharia
creator: Nicole Boisseau
creator: Suzan Murray
creator: Paul Obade
subject: Animal Behavior
subject: Conservation Biology
subject: Ecology
subject: Zoology
description: doi:10.7717/peerj.10010
publisher: PeerJ Inc.
rights: © 2020 Oduor et al.
abstract: Background Heterogeneous landscapes like those of Laikipia County, Kenya consist of a mosaic of land-use types, which may exert differential physiological effects on elephants that occupy and traverse them. Understanding behavioral and physiological states of wild African elephants in response to the challenges of living in human-dominated landscapes is therefore important for conservation managers to evaluate risks imposed by elephants to humans and vice versa. Several conservation physiology tools have been developed to assess how animals respond to both natural and anthropogenic changes, and determine biological impacts. This study investigated how migratory and avoidance behavioral to vehicle presence, and vegetation quality affected fecal glucocorticoid (GC) metabolite (FGM) concentrations in African elephants at Mpala Ranch, Laikipia County, Kenya. Methods The study compared adrenal glucocorticoid activity of resident elephants that live within Mpala (n = 57) and non-resident elephants whose space use patterns overlap several ranches (n = 99) in Laikipia County, Kenya. Fecal samples were collected for a 4-month period between April and August for analysis of FGM concentrations. Behavioral reactions to research vehicles and body condition also were assessed. Satellite images from Terra Moderate Resolution Imaging (MODIS MOD13Q1) were downloaded and processed using Google Earth Engine to calculate a Normalized Difference Vegetation Index (NDVI) as a measure of vegetation quality. Results As expected, there was a positive correlation between avoidance behavior to vehicle presence and FGM concentrations in both resident and non-resident elephants, whereas there was an inverse relationship between FGM concentrations and NDVI values. Our study also found a positive influence of age on the FGM concentrations, but there were no relationships between FGM and sex, social group type, herd size, and body condition. However, contrary to our expectations, resident elephants…
bibliographic citation: Oduor et al. (2020) Differing physiological and behavioral responses to anthropogenic factors between resident and non-resident African elephants at Mpala Ranch, Laikipia County, Kenya. PeerJ 8:e10010 https://doi.org/10.7717/peerj.10010
date submitted: 2020-06-26
date accepted: 2020-08-31
issued: 2020-09-28
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Oduor
  given name: Sandy
author list: Agent
  family name: Brown
  given name: Janine
author list: Agent
  family name: Macharia
  given name: Geoffrey M.
author list: Agent
  family name: Boisseau
  given name: Nicole
author list: Agent
  family name: Murray
  given name: Suzan
author list: Agent
  family name: Obade
  given name: Paul
doi: 10.7717/peerj.10010
volume: 8
issn: 2167-8359
publication name: PeerJ
publication date: 2020-09-28
copyright: © 2020 Oduor et al.
attribution name: Oduor et al.

Pyruvate is required for catecholamine-stimulated growth of different strains of Campylobacter jejuni
type: item
type: AcademicArticle
description: Humans and food-producing animals are constantly exposed to and affected by stress. As a consequence of stress, the release of stress-related catecholamines, such as norepinephrine (NE) and dopamine (DA), from nerve terminals in the gastrointestinal tract potentiates both the growth and the virulence of pathogenic bacteria. This may lead to the enhancement of gastrointestinal infections in humans or food-producing animals. Compared with foodborne bacterial pathogens such as Escherichia coli and Salmonella spp., less is known about the effect of stress catecholamines on Campylobacter jejuni subsp. jejuni. The present study focuses on the effect(s) of stress catecholamines DA and NE in iron-restricted media and how they affect the growth of different C. jejuni strains NCTC 11168, 81–176, and ML2126. Results demonstrated that DA- and NE-enhanced growth of C. jejuni in iron-restricted media may involve different mechanisms that cannot be explained by current understanding which relies on catecholamine-mediated iron delivery. Specifically, we found that DA-enhanced growth requires pyruvate, whereas NE-enhanced growth does not. We further report significant strain-specific dependence of C. jejuni growth on various catecholamines in the presence or absence of pyruvate. These data provide novel insights into the effect(s) of stress catecholamines on the in vitro growth of C. jejuni in iron-restricted environments, such as the intestinal tract. They suggest a mechanism by which stress-related catecholamines affect the growth of C. jejuni in the intestinal tract of food-producing animals, which in turn may influence colonization and transmission to humans.
format: application/pdf
format: text/html
creator: Meicen Liu
creator: Mark Lyte
subject: Microbiology
subject: Neuroscience
subject: Veterinary Medicine
subject: Gastroenterology and Hepatology
description: doi:10.7717/peerj.10011
publisher: PeerJ Inc.
rights: © 2020 Liu and Lyte
abstract: Humans and food-producing animals are constantly exposed to and affected by stress. As a consequence of stress, the release of stress-related catecholamines, such as norepinephrine (NE) and dopamine (DA), from nerve terminals in the gastrointestinal tract potentiates both the growth and the virulence of pathogenic bacteria. This may lead to the enhancement of gastrointestinal infections in humans or food-producing animals. Compared with foodborne bacterial pathogens such as Escherichia coli and Salmonella spp., less is known about the effect of stress catecholamines on Campylobacter jejuni subsp. jejuni. The present study focuses on the effect(s) of stress catecholamines DA and NE in iron-restricted media and how they affect the growth of different C. jejuni strains NCTC 11168, 81–176, and ML2126. Results demonstrated that DA- and NE-enhanced growth of C. jejuni in iron-restricted media may involve different mechanisms that cannot be explained by current understanding which relies on catecholamine-mediated iron delivery. Specifically, we found that DA-enhanced growth requires pyruvate, whereas NE-enhanced growth does not. We further report significant strain-specific dependence of C. jejuni growth on various catecholamines in the presence or absence of pyruvate. These data provide novel insights into the effect(s) of stress catecholamines on the in vitro growth of C. jejuni in iron-restricted environments, such as the intestinal tract. They suggest a mechanism by which stress-related catecholamines affect the growth of C. jejuni in the intestinal tract of food-producing animals, which in turn may influence colonization and transmission to humans.
bibliographic citation: Liu et al. (2020) Pyruvate is required for catecholamine-stimulated growth of different strains of Campylobacter jejuni. PeerJ 8:e10011 https://doi.org/10.7717/peerj.10011
date submitted: 2019-12-18
date accepted: 2020-08-31
issued: 2020-09-28
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Liu
  given name: Meicen
author list: Agent
  family name: Lyte
  given name: Mark
doi: 10.7717/peerj.10011
volume: 8
issn: 2167-8359
publication name: PeerJ
publication date: 2020-09-28
copyright: ©2020 Liu and Lyte
attribution name: Liu and Lyte

The utility of MEWS for predicting the mortality in the elderly adults with COVID-19: a retrospective cohort study with comparison to other predictive clinical scores
type: item
type: AcademicArticle
description: Background Older adults have been reported to be a population with high-risk of death in the COVID-19 outbreak. Rapid detection of high-risk patients is crucial to reduce mortality in this population. The aim of this study was to evaluate the prognositc accuracy of the Modified Early Warning Score (MEWS) for in-hospital mortality in older adults with COVID-19. Methods A retrospective cohort study was conducted in Wuhan Hankou Hospital in China from 1 January 2020 to 29 February 2020. Receiver operating characteristic (ROC) analysis was used to evaluate the predictive value of MEWS, Acute Physiology and Chronic Health Evaluation II (APACHE II), Sequential Organ Function Assessment (SOFA), quick Sequential Organ Function Assessment (qSOFA), Pneumonia Severity Index (PSI), Combination of Confusion, Urea, Respiratory Rate, Blood Pressure, and Age ≥65 (CURB-65), and the Systemic Inflammatory Response Syndrome Criteria (SIRS) for in-hospital mortality. Logistic regression models were performed to detect the high-risk older adults with COVID-19. Results Among the 235 patients included in this study, 37 (15.74%) died and 131 (55.74%) were male, with an average age of 70.61 years (SD 8.02). ROC analysis suggested that the capacity of MEWS in predicting in-hospital mortality was as good as the APACHE II, SOFA, PSI and qSOFA (Difference in AUROC: MEWS vs. APACHE II, −0.025 (95% CI [−0.075 to 0.026]); MEWS vs. SOFA, −0.013 (95% CI [−0.049 to 0.024]); MEWS vs. PSI, −0.015 (95% CI [−0.065 to 0.035]); MEWS vs. qSOFA, 0.024 (95% CI [−0.029 to 0.076]), all P > 0.05), but was significantly higher than SIRS and CURB-65 (Difference in AUROC: MEWS vs. SIRS, 0.218 (95% CI [0.156–0.279]); MEWS vs. CURB-65, 0.064 (95% CI [0.002–0.125]), all P < 0.05). Logistic regression models implied that the male patients (≥75 years) had higher risk of death than the other older adults (estimated coefficients: 1.16, P = 0.044). Our analysis further suggests that the cut-off points of the MEWS score for …
format: application/pdf
format: text/html
creator: Lichun Wang
creator: Qingquan Lv
creator: Xiaofei Zhang
creator: Binyan Jiang
creator: Enhe Liu
creator: Chaoxing Xiao
creator: Xinyang Yu
creator: Chunhua Yang
creator: Lei Chen
subject: Virology
subject: Emergency and Critical Care
subject: Geriatrics
subject: Infectious Diseases
subject: Respiratory Medicine
description: doi:10.7717/peerj.10018
publisher: PeerJ Inc.
rights: © 2020 Wang et al.
abstract: Background Older adults have been reported to be a population with high-risk of death in the COVID-19 outbreak. Rapid detection of high-risk patients is crucial to reduce mortality in this population. The aim of this study was to evaluate the prognositc accuracy of the Modified Early Warning Score (MEWS) for in-hospital mortality in older adults with COVID-19. Methods A retrospective cohort study was conducted in Wuhan Hankou Hospital in China from 1 January 2020 to 29 February 2020. Receiver operating characteristic (ROC) analysis was used to evaluate the predictive value of MEWS, Acute Physiology and Chronic Health Evaluation II (APACHE II), Sequential Organ Function Assessment (SOFA), quick Sequential Organ Function Assessment (qSOFA), Pneumonia Severity Index (PSI), Combination of Confusion, Urea, Respiratory Rate, Blood Pressure, and Age ≥65 (CURB-65), and the Systemic Inflammatory Response Syndrome Criteria (SIRS) for in-hospital mortality. Logistic regression models were performed to detect the high-risk older adults with COVID-19. Results Among the 235 patients included in this study, 37 (15.74%) died and 131 (55.74%) were male, with an average age of 70.61 years (SD 8.02). ROC analysis suggested that the capacity of MEWS in predicting in-hospital mortality was as good as the APACHE II, SOFA, PSI and qSOFA (Difference in AUROC: MEWS vs. APACHE II, −0.025 (95% CI [−0.075 to 0.026]); MEWS vs. SOFA, −0.013 (95% CI [−0.049 to 0.024]); MEWS vs. PSI, −0.015 (95% CI [−0.065 to 0.035]); MEWS vs. qSOFA, 0.024 (95% CI [−0.029 to 0.076]), all P > 0.05), but was significantly higher than SIRS and CURB-65 (Difference in AUROC: MEWS vs. SIRS, 0.218 (95% CI [0.156–0.279]); MEWS vs. CURB-65, 0.064 (95% CI [0.002–0.125]), all P < 0.05). Logistic regression models implied that the male patients (≥75 years) had higher risk of death than the other older adults (estimated coefficients: 1.16, P = 0.044). Our analysis further suggests that the cut-off points of the MEWS score for …
bibliographic citation: Wang et al. (2020) The utility of MEWS for predicting the mortality in the elderly adults with COVID-19: a retrospective cohort study with comparison to other predictive clinical scores. PeerJ 8:e10018 https://doi.org/10.7717/peerj.10018
date submitted: 2020-06-02
date accepted: 2020-09-01
issued: 2020-09-28
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Wang
  given name: Lichun
author list: Agent
  family name: Lv
  given name: Qingquan
author list: Agent
  family name: Zhang
  given name: Xiaofei
author list: Agent
  family name: Jiang
  given name: Binyan
author list: Agent
  family name: Liu
  given name: Enhe
author list: Agent
  family name: Xiao
  given name: Chaoxing
author list: Agent
  family name: Yu
  given name: Xinyang
author list: Agent
  family name: Yang
  given name: Chunhua
author list: Agent
  family name: Chen
  given name: Lei
doi: 10.7717/peerj.10018
volume: 8
issn: 2167-8359
publication name: PeerJ
publication date: 2020-09-28
copyright: © 2020 Wang et al.
attribution name: Wang et al.

Predicting CoVID-19 community mortality risk using machine learning and development of an online prognostic tool
type: item
type: AcademicArticle
description: Background The recent pandemic of CoVID-19 has emerged as a threat to global health security. There are very few prognostic models on CoVID-19 using machine learning. Objectives To predict mortality among confirmed CoVID-19 patients in South Korea using machine learning and deploy the best performing algorithm as an open-source online prediction tool for decision-making. Materials and Methods Mortality for confirmed CoVID-19 patients (n = 3,524) between January 20, 2020 and May 30, 2020 was predicted using five machine learning algorithms (logistic regression, support vector machine, K nearest neighbor, random forest and gradient boosting). The performance of the algorithms was compared, and the best performing algorithm was deployed as an online prediction tool. Results The logistic regression algorithm was the best performer in terms of discrimination (area under ROC curve = 0.830), calibration (Matthews Correlation Coefficient = 0.433; Brier Score = 0.036) and. The best performing algorithm (logistic regression) was deployed as the online CoVID-19 Community Mortality Risk Prediction tool named CoCoMoRP (https://ashis-das.shinyapps.io/CoCoMoRP/). Conclusions We describe the development and deployment of an open-source machine learning tool to predict mortality risk among CoVID-19 confirmed patients using publicly available surveillance data. This tool can be utilized by potential stakeholders such as health providers and policymakers to triage patients at the community level in addition to other approaches.
format: application/pdf
format: text/html
creator: Ashis Kumar Das
creator: Shiba Mishra
creator: Saji Saraswathy Gopalan
subject: Epidemiology
subject: Evidence Based Medicine
subject: Global Health
subject: Infectious Diseases
subject: Public Health
description: doi:10.7717/peerj.10083
publisher: PeerJ Inc.
rights: © 2020 Das et al.
abstract: Background The recent pandemic of CoVID-19 has emerged as a threat to global health security. There are very few prognostic models on CoVID-19 using machine learning. Objectives To predict mortality among confirmed CoVID-19 patients in South Korea using machine learning and deploy the best performing algorithm as an open-source online prediction tool for decision-making. Materials and Methods Mortality for confirmed CoVID-19 patients (n = 3,524) between January 20, 2020 and May 30, 2020 was predicted using five machine learning algorithms (logistic regression, support vector machine, K nearest neighbor, random forest and gradient boosting). The performance of the algorithms was compared, and the best performing algorithm was deployed as an online prediction tool. Results The logistic regression algorithm was the best performer in terms of discrimination (area under ROC curve = 0.830), calibration (Matthews Correlation Coefficient = 0.433; Brier Score = 0.036) and. The best performing algorithm (logistic regression) was deployed as the online CoVID-19 Community Mortality Risk Prediction tool named CoCoMoRP (https://ashis-das.shinyapps.io/CoCoMoRP/). Conclusions We describe the development and deployment of an open-source machine learning tool to predict mortality risk among CoVID-19 confirmed patients using publicly available surveillance data. This tool can be utilized by potential stakeholders such as health providers and policymakers to triage patients at the community level in addition to other approaches.
bibliographic citation: Das et al. (2020) Predicting CoVID-19 community mortality risk using machine learning and development of an online prognostic tool. PeerJ 8:e10083 https://doi.org/10.7717/peerj.10083
date submitted: 2020-05-17
date accepted: 2020-09-11
issued: 2020-09-28
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Das
  given name: Ashis Kumar
author list: Agent
  family name: Mishra
  given name: Shiba
author list: Agent
  family name: Saraswathy Gopalan
  given name: Saji
doi: 10.7717/peerj.10083
volume: 8
issn: 2167-8359
publication name: PeerJ
publication date: 2020-09-28
copyright: © 2020 Das et al.
attribution name: Das et al.

Suitability of native milkweed (Asclepias) species versus cultivars for supporting monarch butterflies and bees in urban gardens
type: item
type: AcademicArticle
description: Public interest in ecological landscaping and gardening is fueling a robust market for native plants. Most plants available to consumers through the horticulture trade are cultivated forms that have been selected for modified flowers or foliage, compactness, or other ornamental characteristics. Depending on their traits, some native plant cultivars seem to support pollinators, specialist insect folivores, and insect-based vertebrate food webs as effectively as native plant species, whereas others do not. There is particular need for information on whether native cultivars can be as effective as true or “wild-type” native species for supporting specialist native insects of conservation concern. Herein we compared the suitability of native milkweed species and their cultivars for attracting and supporting one such insect, the iconic monarch butterfly (Danaus plexippus L.), as well as native bees in urban pollinator gardens. Wild-type Asclepias incarnata L. (swamp milkweed) and Asclepias tuberosa L. (butterfly milkweed) and three additional cultivars of each that vary in stature, floral display, and foliage color were grown in a replicated common garden experiment at a public arboretum. We monitored the plants for colonization by wild monarchs, assessed their suitability for supporting monarch larvae in greenhouse trials, measured their defensive characteristics (leaf trichome density, latex, and cardenolide levels), and compared the proportionate abundance and diversity of bee families and genera visiting their blooms. Significantly more monarch eggs and larvae were found on A. incarnata than A. tuberosa in both years, but within each milkweed group, cultivars were colonized to the same extent as wild types. Despite some differences in defense allocation, all cultivars were as suitable as wild-type milkweeds in supporting monarch larval growth. Five bee families and 17 genera were represented amongst the 2,436 total bees sampled from blooms of wild-type milkweeds and …
format: application/pdf
format: text/html
creator: Adam M. Baker
creator: Carl T. Redmond
creator: Stephen B. Malcolm
creator: Daniel A. Potter
subject: Conservation Biology
subject: Ecology
subject: Entomology
subject: Plant Science
subject: Zoology
description: doi:10.7717/peerj.9823
publisher: PeerJ Inc.
rights: © 2020 Baker et al.
abstract: Public interest in ecological landscaping and gardening is fueling a robust market for native plants. Most plants available to consumers through the horticulture trade are cultivated forms that have been selected for modified flowers or foliage, compactness, or other ornamental characteristics. Depending on their traits, some native plant cultivars seem to support pollinators, specialist insect folivores, and insect-based vertebrate food webs as effectively as native plant species, whereas others do not. There is particular need for information on whether native cultivars can be as effective as true or “wild-type” native species for supporting specialist native insects of conservation concern. Herein we compared the suitability of native milkweed species and their cultivars for attracting and supporting one such insect, the iconic monarch butterfly (Danaus plexippus L.), as well as native bees in urban pollinator gardens. Wild-type Asclepias incarnata L. (swamp milkweed) and Asclepias tuberosa L. (butterfly milkweed) and three additional cultivars of each that vary in stature, floral display, and foliage color were grown in a replicated common garden experiment at a public arboretum. We monitored the plants for colonization by wild monarchs, assessed their suitability for supporting monarch larvae in greenhouse trials, measured their defensive characteristics (leaf trichome density, latex, and cardenolide levels), and compared the proportionate abundance and diversity of bee families and genera visiting their blooms. Significantly more monarch eggs and larvae were found on A. incarnata than A. tuberosa in both years, but within each milkweed group, cultivars were colonized to the same extent as wild types. Despite some differences in defense allocation, all cultivars were as suitable as wild-type milkweeds in supporting monarch larval growth. Five bee families and 17 genera were represented amongst the 2,436 total bees sampled from blooms of wild-type milkweeds and …
bibliographic citation: Baker et al. (2020) Suitability of native milkweed (Asclepias) species versus cultivars for supporting monarch butterflies and bees in urban gardens. PeerJ 8:e9823 https://doi.org/10.7717/peerj.9823
date submitted: 2020-06-10
date accepted: 2020-08-05
issued: 2020-09-25
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Baker
  given name: Adam M.
author list: Agent
  family name: Redmond
  given name: Carl T.
author list: Agent
  family name: Malcolm
  given name: Stephen B.
author list: Agent
  family name: Potter
  given name: Daniel A.
doi: 10.7717/peerj.9823
volume: 8
issn: 2167-8359
publication name: PeerJ
publication date: 2020-09-25
copyright: ©2020 Baker et al.
attribution name: Baker et al.

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