PeerJ
type: channel
link: https://peerj.com/articles/
description: Articles published in PeerJ
publisher: PeerJ Inc.
publication name: PeerJ
issn: 2167-8359
items: Nomogram for predicting cancer specific survival in inflammatory breast carcinoma: a SEER population-based study
items: Land use management based on multi-scenario allocation and trade-offs of ecosystem services in Wafangdian County, Liaoning Province, China
items: Why the long face? Comparative shape analysis of miniature, pony, and other horse skulls reveals changes in ontogenetic growth
items: Effects of Lecanicillium lecanii strain JMC-01 on the physiology, biochemistry, and mortality of Bemisia tabaci Q-biotype nymphs
items: The mineralization characteristics of organic carbon and particle composition analysis in reconstructed soil with different proportions of soft rock and sand
items: AURKB: a promising biomarker in clear cell renal cell carcinoma
items: Prediction model for patients with acute respiratory distress syndrome: use of a genetic algorithm to develop a neural network model
items: CeRNA network analysis and functional enrichment of salt sensitivity of blood pressure by weighted-gene co-expression analysis
items: Genome skimming is a low-cost and robust strategy to assemble complete mitochondrial genomes from ethanol preserved specimens in biodiversity studies
items: Biochar application significantly affects the N pool and microbial community structure in purple and paddy soils

Nomogram for predicting cancer specific survival in inflammatory breast carcinoma: a SEER population-based study
type: item
type: AcademicArticle
description: The clinicopathological features of inflammatory breast carcinoma (IBC), the effect of therapeutic options on survival outcome and the identification of prognostic factors were investigated in this study. Information on IBC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. Cox proportional hazard regression was used to determine potential significant prognostic factors of IBC. A nomogram was then constructed to evaluate patient survival based on certain variables. Univariate and multivariate analyses revealed that race (p < 0.001), M stage (p < 0.001), surgery (p = 0.010), chemotherapy (CT) (p < 0.001), tumor size (p = 0.010), estrogen receptor (p < 0.001), progesterone receptor (p = 0.04), and human epidermal growth factor receptor 2 (p < 0.001) were all independent risk factors. The concordance index (C-index) of the nomogram was 0.735, which showed good predictive efficiency. Survival analysis indicated that IBC patients without CT had poorer survival than those with CT (p < 0.001). Stratified analyses showed that modified radical mastectomy (MRM) had significant survival advantages over non-MRM in patients with stage IV IBC (p = 0.031). Patients treated with or without CT stratified by stage III and stage IV showed better survival than those without stage III and IV (p < 0.001). Trimodality therapy resulted in better survival than surgery combined with CT or CT alone (p < 0.001). Competing risk analysis also showed the same results. The nomogram was effectively applied to predict the 1, 3 and 5-year survival of IBC. Our nomogram showed relatively good accuracy with a C-index of 0.735 and is a visualized individually predictive tool for prognosis. Treatment strategy greatly affected the survival of patients. Trimodality therapy was the preferable therapeutic strategy for IBC. Further prospective studies are needed to validate these findings.
format: application/pdf
format: text/html
creator: Haige Zhang
creator: Guifen Ma
creator: Shisuo Du
creator: Jing Sun
creator: Qian Zhang
creator: Baoying Yuan
creator: Xiaoyong Luo
subject: Bioinformatics
subject: Epidemiology
subject: Oncology
subject: Women’s Health
description: doi:10.7717/peerj.7659
publisher: PeerJ Inc.
rights: © 2019 Zhang et al.
abstract: The clinicopathological features of inflammatory breast carcinoma (IBC), the effect of therapeutic options on survival outcome and the identification of prognostic factors were investigated in this study. Information on IBC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. Cox proportional hazard regression was used to determine potential significant prognostic factors of IBC. A nomogram was then constructed to evaluate patient survival based on certain variables. Univariate and multivariate analyses revealed that race (p < 0.001), M stage (p < 0.001), surgery (p = 0.010), chemotherapy (CT) (p < 0.001), tumor size (p = 0.010), estrogen receptor (p < 0.001), progesterone receptor (p = 0.04), and human epidermal growth factor receptor 2 (p < 0.001) were all independent risk factors. The concordance index (C-index) of the nomogram was 0.735, which showed good predictive efficiency. Survival analysis indicated that IBC patients without CT had poorer survival than those with CT (p < 0.001). Stratified analyses showed that modified radical mastectomy (MRM) had significant survival advantages over non-MRM in patients with stage IV IBC (p = 0.031). Patients treated with or without CT stratified by stage III and stage IV showed better survival than those without stage III and IV (p < 0.001). Trimodality therapy resulted in better survival than surgery combined with CT or CT alone (p < 0.001). Competing risk analysis also showed the same results. The nomogram was effectively applied to predict the 1, 3 and 5-year survival of IBC. Our nomogram showed relatively good accuracy with a C-index of 0.735 and is a visualized individually predictive tool for prognosis. Treatment strategy greatly affected the survival of patients. Trimodality therapy was the preferable therapeutic strategy for IBC. Further prospective studies are needed to validate these findings.
bibliographic citation: Zhang et al. (2019) Nomogram for predicting cancer specific survival in inflammatory breast carcinoma: a SEER population-based study. PeerJ 7:e7659 https://doi.org/10.7717/peerj.7659
date submitted: 2019-05-08
date accepted: 2019-08-12
issued: 2019-09-16
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Zhang
  given name: Haige
author list: Agent
  family name: Ma
  given name: Guifen
author list: Agent
  family name: Du
  given name: Shisuo
author list: Agent
  family name: Sun
  given name: Jing
author list: Agent
  family name: Zhang
  given name: Qian
author list: Agent
  family name: Yuan
  given name: Baoying
author list: Agent
  family name: Luo
  given name: Xiaoyong
doi: 10.7717/peerj.7659
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-09-16
copyright: ©2019 Zhang et al.
attribution name: Zhang et al.

Land use management based on multi-scenario allocation and trade-offs of ecosystem services in Wafangdian County, Liaoning Province, China
type: item
type: AcademicArticle
description: Developing effective methods to coordinate the trade-offs among ecosystem services (ES) is important for achieving inclusive growth and sustainable development, and has been the focus of scholars and ecosystem managers globally. Using remote sensing and geographic information system (GIS) data, our study examined Wafangdian County of Liaoning Province as a case study to reveal the spatiotemporal evolution of four ES (food supply [FS], net primary productivity [NPP], water yield [WY], and soil conservation [SC]) and changes among their interactions. Then, an ordered weighted averaging model was introduced to simulate the optimal scenario of ES allocation. Results showed that: (1) the spatial and temporal changes in ES were significant over 14 years. All ES presented an inverted U-shaped growth curve from 2000–2014. (2) Synergies were observed within provisioning services, and there were trade-offs between provisioning services and regulating services, as well as provisioning services and supporting services. (3) The optimal scenario for Wafangdian was scenario 5 (trade-off coefficient, 0.68). The allocation of FS, NPP, WY, and SC in scenario 5 were 0.187, 0.427, 0.131, and 0.063, respectively. Implementing each ES weight of optimal scenario in land use management contributed to achieving intercoordination of ES. We propose to coordinate land and sea management to restore natural habitats that were expanded into in the high ES area. It is our anticipation that this study could provide a scientific basis for optimizing the allocation of ES and improving land use structure of coastal zones in the future.
format: application/pdf
format: text/html
creator: Wenzhen Zhao
creator: Zenglin Han
creator: Xiaolu Yan
creator: Jingqiu Zhong
subject: Ecosystem Science
subject: Natural Resource Management
subject: Spatial and Geographic Information Science
description: doi:10.7717/peerj.7673
publisher: PeerJ Inc.
rights: © 2019 Zhao et al.
abstract: Developing effective methods to coordinate the trade-offs among ecosystem services (ES) is important for achieving inclusive growth and sustainable development, and has been the focus of scholars and ecosystem managers globally. Using remote sensing and geographic information system (GIS) data, our study examined Wafangdian County of Liaoning Province as a case study to reveal the spatiotemporal evolution of four ES (food supply [FS], net primary productivity [NPP], water yield [WY], and soil conservation [SC]) and changes among their interactions. Then, an ordered weighted averaging model was introduced to simulate the optimal scenario of ES allocation. Results showed that: (1) the spatial and temporal changes in ES were significant over 14 years. All ES presented an inverted U-shaped growth curve from 2000–2014. (2) Synergies were observed within provisioning services, and there were trade-offs between provisioning services and regulating services, as well as provisioning services and supporting services. (3) The optimal scenario for Wafangdian was scenario 5 (trade-off coefficient, 0.68). The allocation of FS, NPP, WY, and SC in scenario 5 were 0.187, 0.427, 0.131, and 0.063, respectively. Implementing each ES weight of optimal scenario in land use management contributed to achieving intercoordination of ES. We propose to coordinate land and sea management to restore natural habitats that were expanded into in the high ES area. It is our anticipation that this study could provide a scientific basis for optimizing the allocation of ES and improving land use structure of coastal zones in the future.
bibliographic citation: Zhao et al. (2019) Land use management based on multi-scenario allocation and trade-offs of ecosystem services in Wafangdian County, Liaoning Province, China. PeerJ 7:e7673 https://doi.org/10.7717/peerj.7673
date submitted: 2019-05-03
date accepted: 2019-08-14
issued: 2019-09-16
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Zhao
  given name: Wenzhen
author list: Agent
  family name: Han
  given name: Zenglin
author list: Agent
  family name: Yan
  given name: Xiaolu
author list: Agent
  family name: Zhong
  given name: Jingqiu
doi: 10.7717/peerj.7673
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-09-16
copyright: ©2019 Zhao et al.
attribution name: Zhao et al.

Why the long face? Comparative shape analysis of miniature, pony, and other horse skulls reveals changes in ontogenetic growth
type: item
type: AcademicArticle
description: Background Much of the shape variation found in animals is based on allometry and heterochrony. Horses represent an excellent model to investigate patterns of size-shape variation among breeds that were intentionally bred for extreme small and large sizes. Methods We tested whether ponies (wither height < 148 cm) have a diverging size-shape relationship in skull shape as compared to regular-sized horse breeds (wither height > 148 cm, here-after called horses) during ontogenetic growth. We used a dataset of 194 specimens from 25 horse and 13 pony breeds, two of which are miniature breeds (wither height < 96.5 cm)—Falabella, Shetland. We applied three-dimensional geometric morphometrics, linear measurements, and multivariate analyses (Procrustes ANOVAs) to quantitatively examine and compare the ontogenetic trajectories between pony and horse breeds with an emphasis on the miniature breeds as an extreme case of artificial selection on size. Additionally, we tested for juvenile characteristics in adult horse and miniature breeds that could resemble “paedomorphosis”—retention of juvenile characteristics in adult stage; e.g. large eyes, large braincase-to-face-relationship, and large head-to-body relationship. Results Allometric regression of size on shape revealed that 42% of shape variation could be explained by variation in size in all breeds. The ontogenetic trajectories of ponies and horses vary in slope and therefore in rate of change per unit size, and length. The differences in trajectory lengths and slopes result in ponies having a similar skull shape in an older age stage than horses of the same size in a younger age stage. This pattern could cause the generally perceived “paedomorphic” appearance of ponies. Miniature breeds have larger heads in relation to wither height compared to horses, a non-paedomorphic feature in horses specifically. Also, rostra (faces) are longer in adult individuals than in juveniles across all kinds of breeds. This pattern can be expl…
format: application/pdf
format: text/html
creator: Laura Heck
creator: Marcelo R. Sanchez-Villagra
creator: Madlen Stange
subject: Evolutionary Studies
subject: Zoology
description: doi:10.7717/peerj.7678
publisher: PeerJ Inc.
rights: © 2019 Heck et al.
abstract: Background Much of the shape variation found in animals is based on allometry and heterochrony. Horses represent an excellent model to investigate patterns of size-shape variation among breeds that were intentionally bred for extreme small and large sizes. Methods We tested whether ponies (wither height < 148 cm) have a diverging size-shape relationship in skull shape as compared to regular-sized horse breeds (wither height > 148 cm, here-after called horses) during ontogenetic growth. We used a dataset of 194 specimens from 25 horse and 13 pony breeds, two of which are miniature breeds (wither height < 96.5 cm)—Falabella, Shetland. We applied three-dimensional geometric morphometrics, linear measurements, and multivariate analyses (Procrustes ANOVAs) to quantitatively examine and compare the ontogenetic trajectories between pony and horse breeds with an emphasis on the miniature breeds as an extreme case of artificial selection on size. Additionally, we tested for juvenile characteristics in adult horse and miniature breeds that could resemble “paedomorphosis”—retention of juvenile characteristics in adult stage; e.g. large eyes, large braincase-to-face-relationship, and large head-to-body relationship. Results Allometric regression of size on shape revealed that 42% of shape variation could be explained by variation in size in all breeds. The ontogenetic trajectories of ponies and horses vary in slope and therefore in rate of change per unit size, and length. The differences in trajectory lengths and slopes result in ponies having a similar skull shape in an older age stage than horses of the same size in a younger age stage. This pattern could cause the generally perceived “paedomorphic” appearance of ponies. Miniature breeds have larger heads in relation to wither height compared to horses, a non-paedomorphic feature in horses specifically. Also, rostra (faces) are longer in adult individuals than in juveniles across all kinds of breeds. This pattern can be expl…
bibliographic citation: Heck et al. (2019) Why the long face? Comparative shape analysis of miniature, pony, and other horse skulls reveals changes in ontogenetic growth. PeerJ 7:e7678 https://doi.org/10.7717/peerj.7678
date submitted: 2019-04-12
date accepted: 2019-08-15
issued: 2019-09-16
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Heck
  given name: Laura
author list: Agent
  family name: Sanchez-Villagra
  given name: Marcelo R.
author list: Agent
  family name: Stange
  given name: Madlen
doi: 10.7717/peerj.7678
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-09-16
copyright: ©2019 Heck et al.
attribution name: Heck et al.

Effects of Lecanicillium lecanii strain JMC-01 on the physiology, biochemistry, and mortality of Bemisia tabaci Q-biotype nymphs
type: item
type: AcademicArticle
description: Background Lecanicillium lecanii is an entomopathogenic fungi, which was isolated from insects suffering from disease. Now, it is an effective bio-control resource that can control agricultural pests such as whitefly and aphids. There are many studies on the control of various agricultural pests by L. lecanii, but no report on its control of Bemisia tabaci biotype-Q exists. In this work, we studied the susceptibility of B. tabaci Q-biotype (from Ningxia, China) to L. lecanii JMC-01 in terms of nymph mortality and the changes in detoxifying protective enzymes activities. Methods B. tabaci nymphs were exposed to L. lecanii JMC-01 conidia by immersion with the host culture. Mortality was assessed daily for all nymph stages. The detoxifying and protective enzyme activity changes, weight changes, and fat, and water contents of the nymphs were determined spectrophotometrically. Results All instars of B. tabaci died after being infested with 1 × 108 conidia/mL. The 2nd-instar nymphs were the most susceptible, followed by the 3rd-instar nymphs. The corrected cumulative mortality of the 2nd- and 3rd-instar nymphs was 82.22% and 75.55%, respectively. The levels of detoxifying and protective enzymes initially increased and then decreased. The highest activities of carboxylesterase, acetylcholinesterase, peroxidase, and catalase occurred on the 3rd day, reaching 10.5, 0.32, 20, and 6.3 U/mg prot, respectively. These levels were 2.2-, 4.3-, 2.4-, and 1.4-fold the control levels, respectively. The highest activities of glutathione-S transferase and superoxide dismutase on the 2nd day were, respectively, 64 and 43.5 U/mg prot. These levels were, respectively, 2.7 and 1.1-fold that of the control level. The water and fat content in the infected B. tabaci nymphs decreased and differed significantly from the control levels. The weight increased continuously in the first 24 h, decreasing thereafter. At 72 h, the infestation level was about 0.78-fold that of the control level. Conclusi…
format: application/pdf
format: text/html
creator: Ting Xie
creator: Ling Jiang
creator: Jianshe Li
creator: Bo Hong
creator: Xinpu Wang
creator: Yanxia Jia
subject: Agricultural Science
subject: Entomology
subject: Mycology
description: doi:10.7717/peerj.7690
publisher: PeerJ Inc.
rights: © 2019 Xie et al.
abstract: Background Lecanicillium lecanii is an entomopathogenic fungi, which was isolated from insects suffering from disease. Now, it is an effective bio-control resource that can control agricultural pests such as whitefly and aphids. There are many studies on the control of various agricultural pests by L. lecanii, but no report on its control of Bemisia tabaci biotype-Q exists. In this work, we studied the susceptibility of B. tabaci Q-biotype (from Ningxia, China) to L. lecanii JMC-01 in terms of nymph mortality and the changes in detoxifying protective enzymes activities. Methods B. tabaci nymphs were exposed to L. lecanii JMC-01 conidia by immersion with the host culture. Mortality was assessed daily for all nymph stages. The detoxifying and protective enzyme activity changes, weight changes, and fat, and water contents of the nymphs were determined spectrophotometrically. Results All instars of B. tabaci died after being infested with 1 × 108 conidia/mL. The 2nd-instar nymphs were the most susceptible, followed by the 3rd-instar nymphs. The corrected cumulative mortality of the 2nd- and 3rd-instar nymphs was 82.22% and 75.55%, respectively. The levels of detoxifying and protective enzymes initially increased and then decreased. The highest activities of carboxylesterase, acetylcholinesterase, peroxidase, and catalase occurred on the 3rd day, reaching 10.5, 0.32, 20, and 6.3 U/mg prot, respectively. These levels were 2.2-, 4.3-, 2.4-, and 1.4-fold the control levels, respectively. The highest activities of glutathione-S transferase and superoxide dismutase on the 2nd day were, respectively, 64 and 43.5 U/mg prot. These levels were, respectively, 2.7 and 1.1-fold that of the control level. The water and fat content in the infected B. tabaci nymphs decreased and differed significantly from the control levels. The weight increased continuously in the first 24 h, decreasing thereafter. At 72 h, the infestation level was about 0.78-fold that of the control level. Conclusi…
bibliographic citation: Xie et al. (2019) Effects of Lecanicillium lecanii strain JMC-01 on the physiology, biochemistry, and mortality of Bemisia tabaci Q-biotype nymphs. PeerJ 7:e7690 https://doi.org/10.7717/peerj.7690
date submitted: 2019-02-09
date accepted: 2019-08-19
issued: 2019-09-16
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Xie
  given name: Ting
author list: Agent
  family name: Jiang
  given name: Ling
author list: Agent
  family name: Li
  given name: Jianshe
author list: Agent
  family name: Hong
  given name: Bo
author list: Agent
  family name: Wang
  given name: Xinpu
author list: Agent
  family name: Jia
  given name: Yanxia
doi: 10.7717/peerj.7690
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-09-16
copyright: © 2019 Xie et al.
attribution name: Xie et al.

The mineralization characteristics of organic carbon and particle composition analysis in reconstructed soil with different proportions of soft rock and sand
type: item
type: AcademicArticle
description: The organic carbon mineralization process reflects the release intensity of soil CO2. Therefore, the study of organic carbon mineralization and particle composition analysis of soft rock and sand compound soil can provide technical support and a theoretical basis for soil organic reconstruction (soil structure, materials and biological nutrition). Based on previous research, four treatments were selected: CK (soft rock:sand=0:1), C1 (soft rock:sand=1:5), C2 (soft rock:sand=1:2) and C3 (soft rock:sand=1:1), respectively. Specifically, we analyzed the organic carbon mineralization process and soil particle composition by lye absorption, laser granulometer, and scanning electron microscope. The results showed that there was no significant difference in organic carbon content between C1, C2 , and C3 treatments, but they were significantly higher than in the CK treatment (P < 0.05). The organic carbon mineralization rate in each treatment accords with a logarithmic function throughout the incubation period (P < 0.01), which can be divided into a rapid decline phase in days 1 to 11 followed by a steady decline phase in days 11 to 30. The cumulative mineralization on the 11th day reached 54.96%–74.44% of the total mineralization amount. At the end of the incubation, the cumulative mineralization and potential mineralizable organic carbon content of the C1, C2 and C3 treatments were significantly higher than those of the CK treatment. The cumulative mineralization rate was also the lowest in the C1 and C2 treatment. The turnover rate constant of soil organic carbon in each treatment was significantly lower than that of the CK treatment, and the residence time increased. With the increase of volume fraction of soft rock, the content of silt and clay particles increased gradually, the texture of soil changed from sandy soil to sandy loam, loam , and silty loam, respectively. With the increase of small particles, the structure of soil appear ed to collapse when the volume rati…
format: application/pdf
format: text/html
creator: Zhen Guo
creator: Jichang Han
creator: Yan Xu
creator: Yangjie Lu
creator: Chendi Shi
creator: Lei Ge
creator: Tingting Cao
creator: Juan Li
subject: Agricultural Science
subject: Ecology
subject: Soil Science
description: doi:10.7717/peerj.7707
publisher: PeerJ Inc.
rights: © 2019 Guo et al.
abstract: The organic carbon mineralization process reflects the release intensity of soil CO2. Therefore, the study of organic carbon mineralization and particle composition analysis of soft rock and sand compound soil can provide technical support and a theoretical basis for soil organic reconstruction (soil structure, materials and biological nutrition). Based on previous research, four treatments were selected: CK (soft rock:sand=0:1), C1 (soft rock:sand=1:5), C2 (soft rock:sand=1:2) and C3 (soft rock:sand=1:1), respectively. Specifically, we analyzed the organic carbon mineralization process and soil particle composition by lye absorption, laser granulometer, and scanning electron microscope. The results showed that there was no significant difference in organic carbon content between C1, C2 , and C3 treatments, but they were significantly higher than in the CK treatment (P < 0.05). The organic carbon mineralization rate in each treatment accords with a logarithmic function throughout the incubation period (P < 0.01), which can be divided into a rapid decline phase in days 1 to 11 followed by a steady decline phase in days 11 to 30. The cumulative mineralization on the 11th day reached 54.96%–74.44% of the total mineralization amount. At the end of the incubation, the cumulative mineralization and potential mineralizable organic carbon content of the C1, C2 and C3 treatments were significantly higher than those of the CK treatment. The cumulative mineralization rate was also the lowest in the C1 and C2 treatment. The turnover rate constant of soil organic carbon in each treatment was significantly lower than that of the CK treatment, and the residence time increased. With the increase of volume fraction of soft rock, the content of silt and clay particles increased gradually, the texture of soil changed from sandy soil to sandy loam, loam , and silty loam, respectively. With the increase of small particles, the structure of soil appear ed to collapse when the volume rati…
bibliographic citation: Guo et al. (2019) The mineralization characteristics of organic carbon and particle composition analysis in reconstructed soil with different proportions of soft rock and sand. PeerJ 7:e7707 https://doi.org/10.7717/peerj.7707
date submitted: 2019-05-29
date accepted: 2019-08-20
issued: 2019-09-16
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Guo
  given name: Zhen
author list: Agent
  family name: Han
  given name: Jichang
author list: Agent
  family name: Xu
  given name: Yan
author list: Agent
  family name: Lu
  given name: Yangjie
author list: Agent
  family name: Shi
  given name: Chendi
author list: Agent
  family name: Ge
  given name: Lei
author list: Agent
  family name: Cao
  given name: Tingting
author list: Agent
  family name: Li
  given name: Juan
doi: 10.7717/peerj.7707
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-09-16
copyright: ©2019 Guo et al.
attribution name: Guo et al.

AURKB: a promising biomarker in clear cell renal cell carcinoma
type: item
type: AcademicArticle
description: Background Aurora kinase B (AURKB) is an important carcinogenic factor in various tumors, while its role in clear cell renal cell carcinoma (ccRCC) still remains unclear. This study aimed to investigate its prognostic value and mechanism of action in ccRCC. Methods Gene expression profiles and clinical data of ccRCC patients were downloaded from The Cancer Genome Atlas database. R software was utilized to analyze the expression and prognostic role of AURKB in ccRCC. Gene set enrichment analysis (GSEA) was used to analyze AURKB related signaling pathways in ccRCC. Results AURKB was expressed at higher levels in ccRCC tissues than normal kidney tissues. Increased AURKB expression in ccRCC correlated with high histological grade, pathological stage, T stage, N stage and distant metastasis (M stage). Kaplan-Meier survival analysis suggested that high AURKB expression patients had a worse prognosis than patients with low AURKB expression levels. Multivariate Cox analysis showed that AURKB expression is a prognostic factor of ccRCC. GSEA indicated that genes involved in autoimmune thyroid disease, intestinal immune network for IgA production, antigen processing and presentation, cytokine-cytokine receptor interaction, asthma, etc., were differentially enriched in the AURKB high expression phenotype. Conclusions AURKB is a promising biomarker for predicting prognosis of ccRCC patients and a potential therapeutic target. In addition, AURKB might regulate progression of ccRCC through modulating intestinal immune network for IgA production and cytokine-cytokine receptor interaction, etc. signaling pathways. However, more research is necessary to validate the findings.
format: application/pdf
format: text/html
creator: Bangbei Wan
creator: Yuan Huang
creator: Bo Liu
creator: Likui Lu
creator: Cai Lv
subject: Bioinformatics
subject: Oncology
description: doi:10.7717/peerj.7718
publisher: PeerJ Inc.
rights: © 2019 Wan et al.
abstract: Background Aurora kinase B (AURKB) is an important carcinogenic factor in various tumors, while its role in clear cell renal cell carcinoma (ccRCC) still remains unclear. This study aimed to investigate its prognostic value and mechanism of action in ccRCC. Methods Gene expression profiles and clinical data of ccRCC patients were downloaded from The Cancer Genome Atlas database. R software was utilized to analyze the expression and prognostic role of AURKB in ccRCC. Gene set enrichment analysis (GSEA) was used to analyze AURKB related signaling pathways in ccRCC. Results AURKB was expressed at higher levels in ccRCC tissues than normal kidney tissues. Increased AURKB expression in ccRCC correlated with high histological grade, pathological stage, T stage, N stage and distant metastasis (M stage). Kaplan-Meier survival analysis suggested that high AURKB expression patients had a worse prognosis than patients with low AURKB expression levels. Multivariate Cox analysis showed that AURKB expression is a prognostic factor of ccRCC. GSEA indicated that genes involved in autoimmune thyroid disease, intestinal immune network for IgA production, antigen processing and presentation, cytokine-cytokine receptor interaction, asthma, etc., were differentially enriched in the AURKB high expression phenotype. Conclusions AURKB is a promising biomarker for predicting prognosis of ccRCC patients and a potential therapeutic target. In addition, AURKB might regulate progression of ccRCC through modulating intestinal immune network for IgA production and cytokine-cytokine receptor interaction, etc. signaling pathways. However, more research is necessary to validate the findings.
bibliographic citation: Wan et al. (2019) AURKB: a promising biomarker in clear cell renal cell carcinoma. PeerJ 7:e7718 https://doi.org/10.7717/peerj.7718
date submitted: 2019-06-05
date accepted: 2019-08-21
issued: 2019-09-16
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Wan
  given name: Bangbei
author list: Agent
  family name: Huang
  given name: Yuan
author list: Agent
  family name: Liu
  given name: Bo
author list: Agent
  family name: Lu
  given name: Likui
author list: Agent
  family name: Lv
  given name: Cai
doi: 10.7717/peerj.7718
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-09-16
copyright: ©2019 Wan et al.
attribution name: Wan et al.

Prediction model for patients with acute respiratory distress syndrome: use of a genetic algorithm to develop a neural network model
type: item
type: AcademicArticle
description: Background Acute respiratory distress syndrome (ARDS) is associated with significantly increased risk of death, and early risk stratification may help to choose the appropriate treatment. The study aimed to develop a neural network model by using a genetic algorithm (GA) for the prediction of mortality in patients with ARDS. Methods This was a secondary analysis of two multicenter randomized controlled trials conducted in forty-four hospitals that are members of the National Heart, Lung, and Blood Institute, founded to create an acute respiratory distress syndrome Clinical Trials Network. Model training and validation were performed using the SAILS and OMEGA studies, respectively. A GA was employed to screen variables in order to predict 90-day mortality, and a neural network model was trained for the prediction. This machine learning model was compared to the logistic regression model and APACHE III score in the validation cohort. Results A total number of 1,071 ARDS patients were included for analysis. The GA search identified seven important variables, which were age, AIDS, leukemia, metastatic tumor, hepatic failure, lowest albumin, and FiO2. A representative neural network model was constructed using the forward selection procedure. The area under the curve (AUC) of the neural network model evaluated with the validation cohort was 0.821 (95% CI [0.753–0.888]), which was greater than the APACHE III score (0.665; 95% CI [0.590–0.739]; p = 0.002 by Delong’s test) and logistic regression model, albeit not statistically significant (0.743; 95% CI [0.669–0.817], p = 0.130 by Delong’s test). Conclusions The study developed a neural network model using a GA, which outperformed conventional scoring systems for the prediction of mortality in ARDS patients.
format: application/pdf
format: text/html
creator: Zhongheng Zhang
subject: Emergency and Critical Care
description: doi:10.7717/peerj.7719
publisher: PeerJ Inc.
rights: © 2019 Zhang
abstract: Background Acute respiratory distress syndrome (ARDS) is associated with significantly increased risk of death, and early risk stratification may help to choose the appropriate treatment. The study aimed to develop a neural network model by using a genetic algorithm (GA) for the prediction of mortality in patients with ARDS. Methods This was a secondary analysis of two multicenter randomized controlled trials conducted in forty-four hospitals that are members of the National Heart, Lung, and Blood Institute, founded to create an acute respiratory distress syndrome Clinical Trials Network. Model training and validation were performed using the SAILS and OMEGA studies, respectively. A GA was employed to screen variables in order to predict 90-day mortality, and a neural network model was trained for the prediction. This machine learning model was compared to the logistic regression model and APACHE III score in the validation cohort. Results A total number of 1,071 ARDS patients were included for analysis. The GA search identified seven important variables, which were age, AIDS, leukemia, metastatic tumor, hepatic failure, lowest albumin, and FiO2. A representative neural network model was constructed using the forward selection procedure. The area under the curve (AUC) of the neural network model evaluated with the validation cohort was 0.821 (95% CI [0.753–0.888]), which was greater than the APACHE III score (0.665; 95% CI [0.590–0.739]; p = 0.002 by Delong’s test) and logistic regression model, albeit not statistically significant (0.743; 95% CI [0.669–0.817], p = 0.130 by Delong’s test). Conclusions The study developed a neural network model using a GA, which outperformed conventional scoring systems for the prediction of mortality in ARDS patients.
bibliographic citation: Zhang (2019) Prediction model for patients with acute respiratory distress syndrome: use of a genetic algorithm to develop a neural network model. PeerJ 7:e7719 https://doi.org/10.7717/peerj.7719
date submitted: 2019-02-15
date accepted: 2019-08-21
issued: 2019-09-16
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Zhang
  given name: Zhongheng
doi: 10.7717/peerj.7719
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-09-16
copyright: ©2019 Zhang
attribution name: Zhang

CeRNA network analysis and functional enrichment of salt sensitivity of blood pressure by weighted-gene co-expression analysis
type: item
type: AcademicArticle
description: Background Salt sensitivity of blood pressure (SSBP) is an independent risk factor for cardiovascular disease. The pathogenic mechanisms of SSBP are still uncertain. This study aimed to construct the co-regulatory network of SSBP and data mining strategy based on the competitive endogenous RNA (ceRNA) theory. Methods LncRNA and mRNA microarray was performed to screen for candidate RNAs. Four criteria were used to select the potential differently expressed RNAs. The weighted correlation network analysis (WGCNA) package of R software and target miRNA and mRNA prediction online databases were used to construct the ceRNA co-regulatory network and discover the pathways related to SSBP. Gene ontology enrichment, gene set enrichment analysis (GSEA) and KEGG pathway analysis were performed to explore the functions of hub genes in networks. Results There were 274 lncRNAs and 36 mRNAs that differently expressed between salt-sensitive and salt-resistant groups (P < 0.05). Using WGCNA analysis, two modules were identified (blue and turquoise). The blue module had a positive relationship with salt-sensitivity (R = 0.7, P < 0.01), high-density lipoprotein (HDL) (R = 0.53, P = 0.02), and total cholesterol (TC) (R = 0.55, P = 0.01). The turquoise module was positively related with triglyceride (TG) (R = 0.8, P < 0.01) and low-density lipoprotein (LDL) (R = 0.54, P = 0.01). Furthermore, 84 ceRNA loops were identified and one loop may be of great importance for involving in pathogenesis of SSBP. KEGG analysis showed that differently expressed mRNAs were mostly enriched in the SSBP-related pathways. However, the enrichment results of GSEA were mainly focused on basic physical metabolic processes. Conclusion The microarray data mining process based on WGCNA co-expression analysis had identified 84 ceRNA loops that closely related with known SSBP pathogenesis. The results of our study provide implications for further understanding of the pathogenesis of SSBP and facilitate the precise d…
format: application/pdf
format: text/html
creator: Han Cao
creator: Han Qi
creator: Zheng Liu
creator: Wen-Juan Peng
creator: Chun-Yue Guo
creator: Yan-Yan Sun
creator: Christine Pao
creator: Yu-Tao Xiang
creator: Ling Zhang
subject: Bioinformatics
subject: Cardiology
subject: Epidemiology
subject: Medical Genetics
description: doi:10.7717/peerj.7534
publisher: PeerJ Inc.
rights: © 2019 Cao et al.
abstract: Background Salt sensitivity of blood pressure (SSBP) is an independent risk factor for cardiovascular disease. The pathogenic mechanisms of SSBP are still uncertain. This study aimed to construct the co-regulatory network of SSBP and data mining strategy based on the competitive endogenous RNA (ceRNA) theory. Methods LncRNA and mRNA microarray was performed to screen for candidate RNAs. Four criteria were used to select the potential differently expressed RNAs. The weighted correlation network analysis (WGCNA) package of R software and target miRNA and mRNA prediction online databases were used to construct the ceRNA co-regulatory network and discover the pathways related to SSBP. Gene ontology enrichment, gene set enrichment analysis (GSEA) and KEGG pathway analysis were performed to explore the functions of hub genes in networks. Results There were 274 lncRNAs and 36 mRNAs that differently expressed between salt-sensitive and salt-resistant groups (P < 0.05). Using WGCNA analysis, two modules were identified (blue and turquoise). The blue module had a positive relationship with salt-sensitivity (R = 0.7, P < 0.01), high-density lipoprotein (HDL) (R = 0.53, P = 0.02), and total cholesterol (TC) (R = 0.55, P = 0.01). The turquoise module was positively related with triglyceride (TG) (R = 0.8, P < 0.01) and low-density lipoprotein (LDL) (R = 0.54, P = 0.01). Furthermore, 84 ceRNA loops were identified and one loop may be of great importance for involving in pathogenesis of SSBP. KEGG analysis showed that differently expressed mRNAs were mostly enriched in the SSBP-related pathways. However, the enrichment results of GSEA were mainly focused on basic physical metabolic processes. Conclusion The microarray data mining process based on WGCNA co-expression analysis had identified 84 ceRNA loops that closely related with known SSBP pathogenesis. The results of our study provide implications for further understanding of the pathogenesis of SSBP and facilitate the precise d…
bibliographic citation: Cao et al. (2019) CeRNA network analysis and functional enrichment of salt sensitivity of blood pressure by weighted-gene co-expression analysis. PeerJ 7:e7534 https://doi.org/10.7717/peerj.7534
date submitted: 2019-05-10
date accepted: 2019-07-22
issued: 2019-09-13
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Cao
  given name: Han
author list: Agent
  family name: Qi
  given name: Han
author list: Agent
  family name: Liu
  given name: Zheng
author list: Agent
  family name: Peng
  given name: Wen-Juan
author list: Agent
  family name: Guo
  given name: Chun-Yue
author list: Agent
  family name: Sun
  given name: Yan-Yan
author list: Agent
  family name: Pao
  given name: Christine
author list: Agent
  family name: Xiang
  given name: Yu-Tao
author list: Agent
  family name: Zhang
  given name: Ling
doi: 10.7717/peerj.7534
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-09-13
copyright: ©2019 Cao et al.
attribution name: Cao et al.

Genome skimming is a low-cost and robust strategy to assemble complete mitochondrial genomes from ethanol preserved specimens in biodiversity studies
type: item
type: AcademicArticle
description: Global loss of biodiversity is an ongoing process that concerns both local and global authorities. Studies of biodiversity mainly involve traditional methods using morphological characters and molecular protocols. However, conventional methods are a time consuming and resource demanding task. The development of high-throughput sequencing (HTS) techniques has reshaped the way we explore biodiversity and opened a path to new questions and novel empirical approaches. With the emergence of HTS, sequencing the complete mitochondrial genome became more accessible, and the number of genome sequences published has increased exponentially during the last decades. Despite the current state of knowledge about the potential of mitogenomics in phylogenetics, this is still a relatively under-explored area for a multitude of taxonomic groups, especially for those without commercial relevance, non-models organisms and with preserved DNA. Here we take the first step to assemble and annotate the genomes from HTS data using a new protocol of genome skimming which will offer an opportunity to extend the field of mitogenomics to under-studied organisms. We extracted genomic DNA from specimens preserved in ethanol. We used Nextera XT DNA to prepare indexed paired-end libraries since it is a powerful tool for working with diverse samples, requiring a low amount of input DNA. We sequenced the samples in two different Illumina platform (MiSeq or NextSeq 550). We trimmed raw reads, filtered and had their quality tested accordingly. We performed the assembly using a baiting and iterative mapping strategy, and the annotated the putative mitochondrion through a semi-automatic procedure. We applied the contiguity index to access the completeness of each new mitogenome. Our results reveal the efficiency of the proposed method to recover the whole mitogenomes of preserved DNA from non-model organisms even if there are gene rearrangement in the specimens. Our findings suggest the potential of combi…
format: application/pdf
format: text/html
creator: Bruna Trevisan
creator: Daniel M.C. Alcantara
creator: Denis Jacob Machado
creator: Fernando P.L. Marques
creator: Daniel J.G. Lahr
subject: Biodiversity
subject: Evolutionary Studies
subject: Parasitology
subject: Zoology
subject: Histology
description: doi:10.7717/peerj.7543
publisher: PeerJ Inc.
rights: © 2019 Trevisan et al.
abstract: Global loss of biodiversity is an ongoing process that concerns both local and global authorities. Studies of biodiversity mainly involve traditional methods using morphological characters and molecular protocols. However, conventional methods are a time consuming and resource demanding task. The development of high-throughput sequencing (HTS) techniques has reshaped the way we explore biodiversity and opened a path to new questions and novel empirical approaches. With the emergence of HTS, sequencing the complete mitochondrial genome became more accessible, and the number of genome sequences published has increased exponentially during the last decades. Despite the current state of knowledge about the potential of mitogenomics in phylogenetics, this is still a relatively under-explored area for a multitude of taxonomic groups, especially for those without commercial relevance, non-models organisms and with preserved DNA. Here we take the first step to assemble and annotate the genomes from HTS data using a new protocol of genome skimming which will offer an opportunity to extend the field of mitogenomics to under-studied organisms. We extracted genomic DNA from specimens preserved in ethanol. We used Nextera XT DNA to prepare indexed paired-end libraries since it is a powerful tool for working with diverse samples, requiring a low amount of input DNA. We sequenced the samples in two different Illumina platform (MiSeq or NextSeq 550). We trimmed raw reads, filtered and had their quality tested accordingly. We performed the assembly using a baiting and iterative mapping strategy, and the annotated the putative mitochondrion through a semi-automatic procedure. We applied the contiguity index to access the completeness of each new mitogenome. Our results reveal the efficiency of the proposed method to recover the whole mitogenomes of preserved DNA from non-model organisms even if there are gene rearrangement in the specimens. Our findings suggest the potential of combi…
bibliographic citation: Trevisan et al. (2019) Genome skimming is a low-cost and robust strategy to assemble complete mitochondrial genomes from ethanol preserved specimens in biodiversity studies. PeerJ 7:e7543 https://doi.org/10.7717/peerj.7543
date submitted: 2019-01-14
date accepted: 2019-07-24
issued: 2019-09-13
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Trevisan
  given name: Bruna
author list: Agent
  family name: Alcantara
  given name: Daniel M.C.
author list: Agent
  family name: Machado
  given name: Denis Jacob
author list: Agent
  family name: Marques
  given name: Fernando P.L.
author list: Agent
  family name: Lahr
  given name: Daniel J.G.
doi: 10.7717/peerj.7543
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-09-13
copyright: ©2019 Trevisan et al.
attribution name: Trevisan et al.

Biochar application significantly affects the N pool and microbial community structure in purple and paddy soils
type: item
type: AcademicArticle
description: Background The increasing demand for food production has resulted in the use of large quantities of chemical fertilizers. This has created major environmental problems, such as increased ammonia volatilization, N2O emission, and nitrogen (N) leaching from agricultural soil. In particular, the utilization rate of N fertilizer is low in subtropical southern parts of China due to high rainfall. This causes not only large financial losses in agriculture, but also serious environmental pollution. Methods In this study, 16S rDNA-based analysis and static-chamber gas chromatography were used to elucidate the effects of continuous straw biochar application on the N pool and bacteria environment in two typical soil types, purple and paddy soils, in southern China. Results Straw biochar application (1) improved the soil N pool in both rhizosphere and non-rhizosphere soils; (2) significantly reduced the emission of N2O, with no difference in emission between 1 and 2 years of application; (3) increased the abundance of N-processing bacteria in the soil and altered the bacterial community structure; and (4) improved the tobacco yield and N use efficiency in paddy soil. These findings suggest that, in southern China, the application of straw biochar can promote N transformation in purple and paddy soils and reduce the emission of the greenhouse gas N2O.
format: application/pdf
format: text/html
creator: Shen Yan
creator: Zhengyang Niu
creator: Haitao Yan
creator: Fei Yun
creator: Guixin Peng
creator: Yongfeng Yang
creator: Guoshun Liu
subject: Agricultural Science
subject: Microbiology
subject: Plant Science
subject: Soil Science
description: doi:10.7717/peerj.7576
publisher: PeerJ Inc.
rights: © 2019 Yan et al.
abstract: Background The increasing demand for food production has resulted in the use of large quantities of chemical fertilizers. This has created major environmental problems, such as increased ammonia volatilization, N2O emission, and nitrogen (N) leaching from agricultural soil. In particular, the utilization rate of N fertilizer is low in subtropical southern parts of China due to high rainfall. This causes not only large financial losses in agriculture, but also serious environmental pollution. Methods In this study, 16S rDNA-based analysis and static-chamber gas chromatography were used to elucidate the effects of continuous straw biochar application on the N pool and bacteria environment in two typical soil types, purple and paddy soils, in southern China. Results Straw biochar application (1) improved the soil N pool in both rhizosphere and non-rhizosphere soils; (2) significantly reduced the emission of N2O, with no difference in emission between 1 and 2 years of application; (3) increased the abundance of N-processing bacteria in the soil and altered the bacterial community structure; and (4) improved the tobacco yield and N use efficiency in paddy soil. These findings suggest that, in southern China, the application of straw biochar can promote N transformation in purple and paddy soils and reduce the emission of the greenhouse gas N2O.
bibliographic citation: Yan et al. (2019) Biochar application significantly affects the N pool and microbial community structure in purple and paddy soils. PeerJ 7:e7576 https://doi.org/10.7717/peerj.7576
date submitted: 2019-04-08
date accepted: 2019-07-29
issued: 2019-09-13
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Yan
  given name: Shen
author list: Agent
  family name: Niu
  given name: Zhengyang
author list: Agent
  family name: Yan
  given name: Haitao
author list: Agent
  family name: Yun
  given name: Fei
author list: Agent
  family name: Peng
  given name: Guixin
author list: Agent
  family name: Yang
  given name: Yongfeng
author list: Agent
  family name: Liu
  given name: Guoshun
doi: 10.7717/peerj.7576
volume: 7
issn: 2167-8359
publication name: PeerJ
publication date: 2019-09-13
copyright: ©2019 Yan et al.
attribution name: Yan et al.

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