PeerJ
type: channel
link: https://peerj.com/articles/
description: Articles published in PeerJ
publisher: PeerJ Inc.
publication name: PeerJ
issn: 2167-8359
items: Using repeatability of performance within and across contexts to validate measures of behavioral flexibility
items: Review of knockout technology approaches in bacterial drug resistance research
items: Curcumin Chalcone Derivatives Database (CCDD): a Python framework for natural compound derivatives database
items: MMP12 serves as an immune cell–related marker of disease status and prognosis in lung squamous cell carcinoma
items: Hub gene associated with prognosis in bladder cancer is a novel therapeutic target
items: Antifungal effects of eugenol on Candida albicans adherence to denture polymers
items: Life-expectancy changes during the COVID-19 pandemic from 2019–2021: estimates from Japan, a country with low pandemic impact
items: Detection of single nucleotide polymorphisms in virus genomes assembled from high-throughput sequencing data: large-scale performance testing of sequence analysis strategies
items: LIDER: cell embedding based deep neural network classifier for supervised cell type identification
items: Effects of post-activation protocols based on slow tempo bodyweight squat and isometric activity on vertical jump height enhancement in trained males: a randomized controlled trial

Using repeatability of performance within and across contexts to validate measures of behavioral flexibility
type: item
type: AcademicArticle
description: Research into animal cognitive abilities is increasing quickly and often uses methods where behavioral performance on a task is assumed to represent variation in the underlying cognitive trait. However, because these methods rely on behavioral responses as a proxy for cognitive ability, it is important to validate that the task structure does, in fact, target the cognitive trait of interest rather than non-target cognitive, personality, or motivational traits (construct validity). Although it can be difficult, or impossible, to definitively assign performance to one cognitive trait, one way to validate that task structure is more likely to elicit performance based on the target cognitive trait is to assess the temporal and contextual repeatability of performance. In other words, individual performance is likely to represent an inherent trait when it is consistent across time and across similar or different tasks that theoretically test the same trait. Here, we assessed the temporal and contextual repeatability of performance on tasks intended to test the cognitive trait behavioral flexibility in great-tailed grackles (Quiscalus mexicanus). For temporal repeatability, we quantified the number of trials to form a color preference after each of multiple color reversals on a serial reversal learning task. For contextual repeatability, we then compared performance on the serial color reversal task to the latency to switch among solutions on each of two different multi-access boxes. We found that the number of trials to form a preference in reversal learning was repeatable across serial color reversals and the latency to switch a preference was repeatable across color reversal learning and the multi-access box contexts. This supports the idea that the reversal learning task structure elicits performance reflective of an inherent trait, and that reversal learning and solution switching on multi-access boxes similarly reflect the inherent trait of behavioral flexibility.
format: application/pdf
format: text/html
creator: Kelsey McCune
creator: Aaron Blaisdell
creator: Zoe Johnson-Ulrich
creator: August Sevchik
creator: Dieter Lukas
creator: Maggie MacPherson
creator: Benjamin Seitz
creator: Corina J. Logan
subject: Animal Behavior
subject: Ecology
subject: Zoology
description: doi:10.7717/peerj.15773
publisher: PeerJ Inc.
rights: © 2023 McCune et al.
abstract: Research into animal cognitive abilities is increasing quickly and often uses methods where behavioral performance on a task is assumed to represent variation in the underlying cognitive trait. However, because these methods rely on behavioral responses as a proxy for cognitive ability, it is important to validate that the task structure does, in fact, target the cognitive trait of interest rather than non-target cognitive, personality, or motivational traits (construct validity). Although it can be difficult, or impossible, to definitively assign performance to one cognitive trait, one way to validate that task structure is more likely to elicit performance based on the target cognitive trait is to assess the temporal and contextual repeatability of performance. In other words, individual performance is likely to represent an inherent trait when it is consistent across time and across similar or different tasks that theoretically test the same trait. Here, we assessed the temporal and contextual repeatability of performance on tasks intended to test the cognitive trait behavioral flexibility in great-tailed grackles (Quiscalus mexicanus). For temporal repeatability, we quantified the number of trials to form a color preference after each of multiple color reversals on a serial reversal learning task. For contextual repeatability, we then compared performance on the serial color reversal task to the latency to switch among solutions on each of two different multi-access boxes. We found that the number of trials to form a preference in reversal learning was repeatable across serial color reversals and the latency to switch a preference was repeatable across color reversal learning and the multi-access box contexts. This supports the idea that the reversal learning task structure elicits performance reflective of an inherent trait, and that reversal learning and solution switching on multi-access boxes similarly reflect the inherent trait of behavioral flexibility.
bibliographic citation: McCune et al. (2023) Using repeatability of performance within and across contexts to validate measures of behavioral flexibility. PeerJ 11:e15773 https://doi.org/10.7717/peerj.15773
date submitted: 2023-06-28
date accepted: 2023-06-29
issued: 2023-08-17
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: McCune
  given name: Kelsey
author list: Agent
  family name: Blaisdell
  given name: Aaron
author list: Agent
  family name: Johnson-Ulrich
  given name: Zoe
author list: Agent
  family name: Sevchik
  given name: August
author list: Agent
  family name: Lukas
  given name: Dieter
author list: Agent
  family name: MacPherson
  given name: Maggie
author list: Agent
  family name: Seitz
  given name: Benjamin
author list: Agent
  family name: Logan
  given name: Corina J.
doi: 10.7717/peerj.15773
volume: 11
issn: 2167-8359
publication name: PeerJ
publication date: 2023-08-17
copyright: © 2023 McCune et al.
attribution name: McCune et al.

Review of knockout technology approaches in bacterial drug resistance research
type: item
type: AcademicArticle
description: Gene knockout is a widely used method in biology for investigating gene function. Several technologies are available for gene knockout, including zinc-finger nuclease technology (ZFN), suicide plasmid vector systems, transcription activator-like effector protein nuclease technology (TALEN), Red homologous recombination technology, CRISPR/Cas, and others. Of these, Red homologous recombination technology, CRISPR/Cas9 technology, and suicide plasmid vector systems have been the most extensively used for knocking out bacterial drug resistance genes. These three technologies have been shown to yield significant results in researching bacterial gene functions in numerous studies. This study provides an overview of current gene knockout methods that are effective for genetic drug resistance testing in bacteria. The study aims to serve as a reference for selecting appropriate techniques.
format: application/pdf
format: text/html
creator: Chunyu Tong
creator: Yimin Liang
creator: Zhelin Zhang
creator: Sen Wang
creator: Xiaohui Zheng
creator: Qi Liu
creator: Bocui Song
subject: Biotechnology
subject: Genetics
subject: Microbiology
subject: Molecular Biology
description: doi:10.7717/peerj.15790
publisher: PeerJ Inc.
rights: © 2023 Tong et al.
abstract: Gene knockout is a widely used method in biology for investigating gene function. Several technologies are available for gene knockout, including zinc-finger nuclease technology (ZFN), suicide plasmid vector systems, transcription activator-like effector protein nuclease technology (TALEN), Red homologous recombination technology, CRISPR/Cas, and others. Of these, Red homologous recombination technology, CRISPR/Cas9 technology, and suicide plasmid vector systems have been the most extensively used for knocking out bacterial drug resistance genes. These three technologies have been shown to yield significant results in researching bacterial gene functions in numerous studies. This study provides an overview of current gene knockout methods that are effective for genetic drug resistance testing in bacteria. The study aims to serve as a reference for selecting appropriate techniques.
bibliographic citation: Tong et al. (2023) Review of knockout technology approaches in bacterial drug resistance research. PeerJ 11:e15790 https://doi.org/10.7717/peerj.15790
date submitted: 2023-05-17
date accepted: 2023-07-04
issued: 2023-08-17
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Tong
  given name: Chunyu
author list: Agent
  family name: Liang
  given name: Yimin
author list: Agent
  family name: Zhang
  given name: Zhelin
author list: Agent
  family name: Wang
  given name: Sen
author list: Agent
  family name: Zheng
  given name: Xiaohui
author list: Agent
  family name: Liu
  given name: Qi
author list: Agent
  family name: Song
  given name: Bocui
doi: 10.7717/peerj.15790
volume: 11
issn: 2167-8359
publication name: PeerJ
publication date: 2023-08-17
copyright: © 2023 Tong et al.
attribution name: Tong et al.

Curcumin Chalcone Derivatives Database (CCDD): a Python framework for natural compound derivatives database
type: item
type: AcademicArticle
description: We built the Curcumin Chalcone Derivatives Database (CCDD) to enable the effective virtual screening of highly potent curcumin and its analogs. The two-dimensional (2D) structures were drawn using the ChemBioOffice package and converted to 3D structures using Discovery Studio Visualizer V 2021 (DS). The database was built using different Python modules. For the 3D structures, different Python packages were used to obtain the data frame of compounds. This framework is also used to visualize the compounds. The webserver enables the users to screen the compounds according to Lipinski’s rule of five. The structures can be downloaded in .sdf and .mol format. The data frame (df) can be downloaded in .csv format. Our webserver can help computational drug discovery researchers find new therapeutics and build new webservers. The CCDD is freely available at: https://srampogu-ccdd-ccdd-8uldk8.streamlit.app/.
format: application/pdf
format: text/html
creator: Shailima Rampogu
creator: Thananjeyan Balasubramaniyam
creator: Joon-Hwa Lee
subject: Bioinformatics
subject: Data Science
description: doi:10.7717/peerj.15885
publisher: PeerJ Inc.
rights: © 2023 Rampogu et al.
abstract: We built the Curcumin Chalcone Derivatives Database (CCDD) to enable the effective virtual screening of highly potent curcumin and its analogs. The two-dimensional (2D) structures were drawn using the ChemBioOffice package and converted to 3D structures using Discovery Studio Visualizer V 2021 (DS). The database was built using different Python modules. For the 3D structures, different Python packages were used to obtain the data frame of compounds. This framework is also used to visualize the compounds. The webserver enables the users to screen the compounds according to Lipinski’s rule of five. The structures can be downloaded in .sdf and .mol format. The data frame (df) can be downloaded in .csv format. Our webserver can help computational drug discovery researchers find new therapeutics and build new webservers. The CCDD is freely available at: https://srampogu-ccdd-ccdd-8uldk8.streamlit.app/.
bibliographic citation: Rampogu et al. (2023) Curcumin Chalcone Derivatives Database (CCDD): a Python framework for natural compound derivatives database. PeerJ 11:e15885 https://doi.org/10.7717/peerj.15885
date submitted: 2023-03-20
date accepted: 2023-07-20
issued: 2023-08-17
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Rampogu
  given name: Shailima
author list: Agent
  family name: Balasubramaniyam
  given name: Thananjeyan
author list: Agent
  family name: Lee
  given name: Joon-Hwa
doi: 10.7717/peerj.15885
volume: 11
issn: 2167-8359
publication name: PeerJ
publication date: 2023-08-17
copyright: © 2023 Rampogu et al.
attribution name: Rampogu et al.

MMP12 serves as an immune cell–related marker of disease status and prognosis in lung squamous cell carcinoma
type: item
type: AcademicArticle
description: Background Worldwide, lung squamous cell carcinoma (LUSC) has wreaked havoc on humanity. Matrix metallopeptidase 12 (MMP12) plays an essential role in a variety of cancers. This study aimed to reveal the expression, clinical significance, and potential molecular mechanisms of MMP12 in LUSC. Methods There were 2,738 messenger RNA (mRNA) samples from several multicenter databases used to detect MMP12 expression in LUSC, and 125 tissue samples were validated by immunohistochemistry (IHC) experiments. Receiver operator characteristic (ROC) curves, Kaplan–Meier curves, and univariate and multivariate Cox regression analyses were used to assess the clinical value of MMP12 in LUSC. The potential molecular mechanisms of MMP12 were explored by gene enrichment analysis and immune correlation analysis. Furthermore, single-cell sequencing was used to determine the distribution of MMP12 in multiple tumor microenvironment cells. Results MMP12 was significantly overexpressed at the mRNA level (p < 0.05, SMD = 3.13, 95% CI [2.51–3.75]), which was verified at the protein level (p < 0.001) by internal IHC experiments. MMP12 expression could be used to differentiate LUSC samples from normal samples, and overexpression of MMP12 itself implied a worse clinical prognosis and higher levels of immune cell infiltration in LUSC patients. MMP12 was involved in cancer development and progression through two immune-related signaling pathways. The high expression of MMP12 in LUSC might act as an antigen-presenting cell–associated tumor neoantigen and activate the body’s immune response. Conclusions MMP12 expression is upregulated in LUSC and high expression of MMP12 serves as a risk factor for LUSC patients. MMP12 may be involved in cancer development by participating in immune-related signaling pathways and elevating the level of immune cell infiltration.
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format: text/html
creator: Wei Zhang
creator: Guo-Sheng Li
creator: Xiang-Yu Gan
creator: Zhi-Guang Huang
creator: Rong-Quan He
creator: Hong Huang
creator: Dong-Ming Li
creator: Yu-Lu Tang
creator: Deng Tang
creator: Wen Zou
creator: Jun Liu
creator: Yi-Wu Dang
creator: Gang Chen
creator: Hua-Fu Zhou
creator: Jin-Liang Kong
creator: Hui-ping Lu
subject: Bioinformatics
subject: Molecular Biology
subject: Oncology
subject: Pathology
subject: Respiratory Medicine
description: doi:10.7717/peerj.15598
publisher: PeerJ Inc.
rights: © 2023 Zhang et al.
abstract: Background Worldwide, lung squamous cell carcinoma (LUSC) has wreaked havoc on humanity. Matrix metallopeptidase 12 (MMP12) plays an essential role in a variety of cancers. This study aimed to reveal the expression, clinical significance, and potential molecular mechanisms of MMP12 in LUSC. Methods There were 2,738 messenger RNA (mRNA) samples from several multicenter databases used to detect MMP12 expression in LUSC, and 125 tissue samples were validated by immunohistochemistry (IHC) experiments. Receiver operator characteristic (ROC) curves, Kaplan–Meier curves, and univariate and multivariate Cox regression analyses were used to assess the clinical value of MMP12 in LUSC. The potential molecular mechanisms of MMP12 were explored by gene enrichment analysis and immune correlation analysis. Furthermore, single-cell sequencing was used to determine the distribution of MMP12 in multiple tumor microenvironment cells. Results MMP12 was significantly overexpressed at the mRNA level (p < 0.05, SMD = 3.13, 95% CI [2.51–3.75]), which was verified at the protein level (p < 0.001) by internal IHC experiments. MMP12 expression could be used to differentiate LUSC samples from normal samples, and overexpression of MMP12 itself implied a worse clinical prognosis and higher levels of immune cell infiltration in LUSC patients. MMP12 was involved in cancer development and progression through two immune-related signaling pathways. The high expression of MMP12 in LUSC might act as an antigen-presenting cell–associated tumor neoantigen and activate the body’s immune response. Conclusions MMP12 expression is upregulated in LUSC and high expression of MMP12 serves as a risk factor for LUSC patients. MMP12 may be involved in cancer development by participating in immune-related signaling pathways and elevating the level of immune cell infiltration.
bibliographic citation: Zhang et al. (2023) MMP12 serves as an immune cell–related marker of disease status and prognosis in lung squamous cell carcinoma. PeerJ 11:e15598 https://doi.org/10.7717/peerj.15598
date submitted: 2023-02-09
date accepted: 2023-05-30
issued: 2023-08-16
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Zhang
  given name: Wei
author list: Agent
  family name: Li
  given name: Guo-Sheng
author list: Agent
  family name: Gan
  given name: Xiang-Yu
author list: Agent
  family name: Huang
  given name: Zhi-Guang
author list: Agent
  family name: He
  given name: Rong-Quan
author list: Agent
  family name: Huang
  given name: Hong
author list: Agent
  family name: Li
  given name: Dong-Ming
author list: Agent
  family name: Tang
  given name: Yu-Lu
author list: Agent
  family name: Tang
  given name: Deng
author list: Agent
  family name: Zou
  given name: Wen
author list: Agent
  family name: Liu
  given name: Jun
author list: Agent
  family name: Dang
  given name: Yi-Wu
author list: Agent
  family name: Chen
  given name: Gang
author list: Agent
  family name: Zhou
  given name: Hua-Fu
author list: Agent
  family name: Kong
  given name: Jin-Liang
author list: Agent
  family name: Lu
  given name: Hui-ping
doi: 10.7717/peerj.15598
volume: 11
issn: 2167-8359
publication name: PeerJ
publication date: 2023-08-16
copyright: ©2023 Zhang et al.
attribution name: Zhang et al.

Hub gene associated with prognosis in bladder cancer is a novel therapeutic target
type: item
type: AcademicArticle
description: Objective Bladder cancer is a clinical and social conundrum due to its high incidence and recurrence rate. It is urgent to find new targets for the diagnosis and treatment of bladder cancer and improve the prognosis and survival rate of bladder cancer patients. We sought a prognosis-related gene, built related models of evaluated bladder cancer and identified the function of the hub gene in bladder cancer. Methods We downloaded the data of bladder cancer patients from the TCGA database, and used differentially expressed genes (DEGs), copy number variation (CNV) and survival analysis to scan the hub genes associated with prognosis in bladder cancer. Then, multi-factor cox regression was used to obtain the bladder cancer prognosis correlation model. Then, we analyzed the relationship between the expression of hub gene and immune microenvironment of bladder cancer. The relationship between the expression of hub gene and prognosis in bladder cancer patients was verified by immunohistochemistry. Cell proliferation assay and drug sensitivity test in vivo were used to verify the inhibition of bladder cancer by targeted inhibitors. Results In bladder cancer, we screened seven hub genes (ACLY, CNP, NKIRAS2, P3H4, PDIA6, VPS25 and XPO1) associated with survival. Moreover, the multifactor regression model constructed with hub gene can well distinguish the prognosis of bladder cancer. Hub gene is mostly associated with immune microenvironment. Immunohistochemical results basically confirmed the importance of XPO1 in bladder cancer. Selinexor (an inhibitor of XPO1) could effectively inhibit the proliferation of bladder cancer in the cell proliferation experiments by CCK-8 assays and it could suppress the growth of bladder cancer in mouse bladder cancer model. Conclusions In this study, a prognostic model with seven hub genes has provided great help for the prognosis prediction of bladder cancer patients. And XPO1 is an important target affecting the prognosis of bladder cancer, …
format: application/pdf
format: text/html
creator: Dengpan Fang
creator: Yuanqiao He
creator: Yun Yi
creator: Jiaqi Mei
creator: Cundong Liu
subject: Bioinformatics
subject: Molecular Biology
subject: Oncology
subject: Urology
description: doi:10.7717/peerj.15670
publisher: PeerJ Inc.
rights: © 2023 Fang et al.
abstract: Objective Bladder cancer is a clinical and social conundrum due to its high incidence and recurrence rate. It is urgent to find new targets for the diagnosis and treatment of bladder cancer and improve the prognosis and survival rate of bladder cancer patients. We sought a prognosis-related gene, built related models of evaluated bladder cancer and identified the function of the hub gene in bladder cancer. Methods We downloaded the data of bladder cancer patients from the TCGA database, and used differentially expressed genes (DEGs), copy number variation (CNV) and survival analysis to scan the hub genes associated with prognosis in bladder cancer. Then, multi-factor cox regression was used to obtain the bladder cancer prognosis correlation model. Then, we analyzed the relationship between the expression of hub gene and immune microenvironment of bladder cancer. The relationship between the expression of hub gene and prognosis in bladder cancer patients was verified by immunohistochemistry. Cell proliferation assay and drug sensitivity test in vivo were used to verify the inhibition of bladder cancer by targeted inhibitors. Results In bladder cancer, we screened seven hub genes (ACLY, CNP, NKIRAS2, P3H4, PDIA6, VPS25 and XPO1) associated with survival. Moreover, the multifactor regression model constructed with hub gene can well distinguish the prognosis of bladder cancer. Hub gene is mostly associated with immune microenvironment. Immunohistochemical results basically confirmed the importance of XPO1 in bladder cancer. Selinexor (an inhibitor of XPO1) could effectively inhibit the proliferation of bladder cancer in the cell proliferation experiments by CCK-8 assays and it could suppress the growth of bladder cancer in mouse bladder cancer model. Conclusions In this study, a prognostic model with seven hub genes has provided great help for the prognosis prediction of bladder cancer patients. And XPO1 is an important target affecting the prognosis of bladder cancer, …
bibliographic citation: Fang et al. (2023) Hub gene associated with prognosis in bladder cancer is a novel therapeutic target. PeerJ 11:e15670 https://doi.org/10.7717/peerj.15670
date submitted: 2023-03-27
date accepted: 2023-06-09
issued: 2023-08-16
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Fang
  given name: Dengpan
author list: Agent
  family name: He
  given name: Yuanqiao
author list: Agent
  family name: Yi
  given name: Yun
author list: Agent
  family name: Mei
  given name: Jiaqi
author list: Agent
  family name: Liu
  given name: Cundong
doi: 10.7717/peerj.15670
volume: 11
issn: 2167-8359
publication name: PeerJ
publication date: 2023-08-16
copyright: ©2023 Fang et al.
attribution name: Fang et al.

Antifungal effects of eugenol on Candida albicans adherence to denture polymers
type: item
type: AcademicArticle
description: Background The study’s objective is to assess the adherence of C. albicans in different types of denture polymers and the effectiveness of eugenol and commercialized denture cleansers in the removal of C. albicans. Three types of denture base polymers (Lucitone® 199 (High-Impact PMMA), Impact® (conventional PMMA) and Eclipse® (UDMA)) and two hard denture reline materials (Kooliner® and Tokuyama® Rebase II Fast) were used in this study. Methods Three hundred samples were prepared (6 × 2 mm disc shape) and divided into five groups of denture polymers (n = 60) and further subjected into five treatment groups (Polident®, Steradent, distilled water, eugenol 5-minutes, and eugenol 10-min). Three samples were extracted from each treatment group for baseline data (n = 12). Baseline data were used to calculate the initial number of C. albicans adherence. A 0.5 ml immersion solution from each specimen was cultured on YPD agar and incubated for 48 h at 37 °C. Visible colonies were counted using a colony counter machine (ROCKER Galaxy 230). Results The result showed that the denture base polymer significantly affected the initial adherence (p = 0.007). The removal of C. albicans was also considerably affected by the denture base polymers and denture cleansers (p < 0.05). Lucitone®, Tokuyama®, and Kooliner® denture base polymers immersed for 3 min in eugenol showed the best results of removal. Discussion This study’s overall results showed that all denture polymers used as denture bases had an effect on C. albicans initial adherence and removal from the denture base, and eugenol is comparable to commercialised denture cleansers in reducing the number of attached C. albicans on denture base polymers.
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format: text/html
creator: Zubaidah Zanul Abidin
creator: Nosizana Mohd Salleh
creator: Wan Harun Himratul-Aznita
creator: Siti Fauzza Ahmad
creator: Ghee Seong Lim
creator: Noorhayati Raja Mohd
creator: Nabihah Dziaruddin
subject: Biochemistry
subject: Microbiology
subject: Mycology
subject: Dentistry
description: doi:10.7717/peerj.15750
publisher: PeerJ Inc.
rights: © 2023 Zanul Abidin et al.
abstract: Background The study’s objective is to assess the adherence of C. albicans in different types of denture polymers and the effectiveness of eugenol and commercialized denture cleansers in the removal of C. albicans. Three types of denture base polymers (Lucitone® 199 (High-Impact PMMA), Impact® (conventional PMMA) and Eclipse® (UDMA)) and two hard denture reline materials (Kooliner® and Tokuyama® Rebase II Fast) were used in this study. Methods Three hundred samples were prepared (6 × 2 mm disc shape) and divided into five groups of denture polymers (n = 60) and further subjected into five treatment groups (Polident®, Steradent, distilled water, eugenol 5-minutes, and eugenol 10-min). Three samples were extracted from each treatment group for baseline data (n = 12). Baseline data were used to calculate the initial number of C. albicans adherence. A 0.5 ml immersion solution from each specimen was cultured on YPD agar and incubated for 48 h at 37 °C. Visible colonies were counted using a colony counter machine (ROCKER Galaxy 230). Results The result showed that the denture base polymer significantly affected the initial adherence (p = 0.007). The removal of C. albicans was also considerably affected by the denture base polymers and denture cleansers (p < 0.05). Lucitone®, Tokuyama®, and Kooliner® denture base polymers immersed for 3 min in eugenol showed the best results of removal. Discussion This study’s overall results showed that all denture polymers used as denture bases had an effect on C. albicans initial adherence and removal from the denture base, and eugenol is comparable to commercialised denture cleansers in reducing the number of attached C. albicans on denture base polymers.
bibliographic citation: Zanul Abidin et al. (2023) Antifungal effects of eugenol on Candida albicans adherence to denture polymers. PeerJ 11:e15750 https://doi.org/10.7717/peerj.15750
date submitted: 2022-12-01
date accepted: 2023-06-22
issued: 2023-08-16
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Zanul Abidin
  given name: Zubaidah
author list: Agent
  family name: Mohd Salleh
  given name: Nosizana
author list: Agent
  family name: Himratul-Aznita
  given name: Wan Harun
author list: Agent
  family name: Ahmad
  given name: Siti Fauzza
author list: Agent
  family name: Lim
  given name: Ghee Seong
author list: Agent
  family name: Raja Mohd
  given name: Noorhayati
author list: Agent
  family name: Dziaruddin
  given name: Nabihah
doi: 10.7717/peerj.15750
volume: 11
issn: 2167-8359
publication name: PeerJ
publication date: 2023-08-16
copyright: ©2023 Zanul Abidin et al.
attribution name: Zanul Abidin et al.

Life-expectancy changes during the COVID-19 pandemic from 2019–2021: estimates from Japan, a country with low pandemic impact
type: item
type: AcademicArticle
description: Background The COVID-19 pandemic had a low impact on Japan in 2020, but the size of the epidemic increased considerably there in 2021. This study made a statistical analysis of life expectancy changes up to the end of 2021 in Japan. Objective We aimed to estimate changes in life expectancy from 2019 to 2021 associated with the COVID-19 pandemic. To do so, we decomposed the life expectancy changes from 2020–2021 into age-specific and cause of death-specific contributions. Methods We used the absolute number of deaths by age and prefecture in Japan to calculate life expectancy from 2019–21 at both national and prefectural levels, and also examined the correlation between life expectancy gap and annual number of COVID-19 cases, total person-days spent in intensive care, and documented deaths due to COVID-19. We used the Arriaga decomposition method to decompose national life expectancy changes from 2020 to 2021 into age and cause of death components. Results From 2019–2020, Japan’s national level life expectancy across the entire population was extended by 0.24 years. From 2020–2021, it shortened by 0.15 years. The life expectancy shortened more among women (0.15 years) than men (0.12 years). There was significant heterogeneity in life expectancy changes from 2020–2021 by prefecture. It ranged from the maximum shortening of 0.57 years in Tottori prefecture to the maximum extension of 0.23 years in Fukui. The regression analysis revealed the negative correlation between the life expectancy change and burden of COVID-19 at prefectural level. The decomposition of life expectancy changes at birth from 2020–2021 showed that losses in life expectancy were largely attributable to the mortality of the population over 70 years old. Changes in life expectancy among infants and working-age adults mostly contributed to lengthening overall life expectancy. Among leading major causes of death, deaths due to neoplastic tumor and cardiovascular diseases contributed to shortening life …
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creator: Mst Sirajum Munira
creator: Yuta Okada
creator: Hiroshi Nishiura
subject: Epidemiology
subject: Infectious Diseases
subject: Public Health
subject: COVID-19
description: doi:10.7717/peerj.15784
publisher: PeerJ Inc.
rights: © 2023 Mst Sirajum Munira et al.
abstract: Background The COVID-19 pandemic had a low impact on Japan in 2020, but the size of the epidemic increased considerably there in 2021. This study made a statistical analysis of life expectancy changes up to the end of 2021 in Japan. Objective We aimed to estimate changes in life expectancy from 2019 to 2021 associated with the COVID-19 pandemic. To do so, we decomposed the life expectancy changes from 2020–2021 into age-specific and cause of death-specific contributions. Methods We used the absolute number of deaths by age and prefecture in Japan to calculate life expectancy from 2019–21 at both national and prefectural levels, and also examined the correlation between life expectancy gap and annual number of COVID-19 cases, total person-days spent in intensive care, and documented deaths due to COVID-19. We used the Arriaga decomposition method to decompose national life expectancy changes from 2020 to 2021 into age and cause of death components. Results From 2019–2020, Japan’s national level life expectancy across the entire population was extended by 0.24 years. From 2020–2021, it shortened by 0.15 years. The life expectancy shortened more among women (0.15 years) than men (0.12 years). There was significant heterogeneity in life expectancy changes from 2020–2021 by prefecture. It ranged from the maximum shortening of 0.57 years in Tottori prefecture to the maximum extension of 0.23 years in Fukui. The regression analysis revealed the negative correlation between the life expectancy change and burden of COVID-19 at prefectural level. The decomposition of life expectancy changes at birth from 2020–2021 showed that losses in life expectancy were largely attributable to the mortality of the population over 70 years old. Changes in life expectancy among infants and working-age adults mostly contributed to lengthening overall life expectancy. Among leading major causes of death, deaths due to neoplastic tumor and cardiovascular diseases contributed to shortening life …
bibliographic citation: Munira et al. (2023) Life-expectancy changes during the COVID-19 pandemic from 2019–2021: estimates from Japan, a country with low pandemic impact. PeerJ 11:e15784 https://doi.org/10.7717/peerj.15784
date submitted: 2023-03-23
date accepted: 2023-07-03
issued: 2023-08-16
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Munira
  given name: Mst Sirajum
author list: Agent
  family name: Okada
  given name: Yuta
author list: Agent
  family name: Nishiura
  given name: Hiroshi
doi: 10.7717/peerj.15784
volume: 11
issn: 2167-8359
publication name: PeerJ
publication date: 2023-08-16
copyright: © 2023 Mst Sirajum Munira et al.
attribution name: Mst Sirajum Munira et al.

Detection of single nucleotide polymorphisms in virus genomes assembled from high-throughput sequencing data: large-scale performance testing of sequence analysis strategies
type: item
type: AcademicArticle
description: Recent developments in high-throughput sequencing (HTS) technologies and bioinformatics have drastically changed research in virology, especially for virus discovery. Indeed, proper monitoring of the viral population requires information on the different isolates circulating in the studied area. For this purpose, HTS has greatly facilitated the sequencing of new genomes of detected viruses and their comparison. However, bioinformatics analyses allowing reconstruction of genome sequences and detection of single nucleotide polymorphisms (SNPs) can potentially create bias and has not been widely addressed so far. Therefore, more knowledge is required on the limitations of predicting SNPs based on HTS-generated sequence samples. To address this issue, we compared the ability of 14 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 21 variants of pepino mosaic virus (PepMV) in three samples through large-scale performance testing (PT) using three artificially designed datasets. To evaluate the impact of bioinformatics analyses, they were divided into three key steps: reads pre-processing, virus-isolate identification, and variant calling. Each step was evaluated independently through an original, PT design including discussion and validation between participants at each step. Overall, this work underlines key parameters influencing SNPs detection and proposes recommendations for reliable variant calling for plant viruses. The identification of the closest reference, mapping parameters and manual validation of the detection were recognized as the most impactful analysis steps for the success of the SNPs detections. Strategies to improve the prediction of SNPs are also discussed.
format: application/pdf
format: text/html
creator: Johan Rollin
creator: Rachelle Bester
creator: Yves Brostaux
creator: Kadriye Caglayan
creator: Kris De Jonghe
creator: Ales Eichmeier
creator: Yoika Foucart
creator: Annelies Haegeman
creator: Igor Koloniuk
creator: Petr Kominek
creator: Hans Maree
creator: Serkan Onder
creator: Susana Posada Céspedes
creator: Vahid Roumi
creator: Dana Šafářová
creator: Olivier Schumpp
creator: Cigdem Ulubas Serce
creator: Merike Sõmera
creator: Lucie Tamisier
creator: Eeva Vainio
creator: Rene AA van der Vlugt
creator: Sebastien Massart
subject: Bioinformatics
subject: Genomics
subject: Plant Science
subject: Virology
description: doi:10.7717/peerj.15816
publisher: PeerJ Inc.
rights: © 2023 Rollin et al.
abstract: Recent developments in high-throughput sequencing (HTS) technologies and bioinformatics have drastically changed research in virology, especially for virus discovery. Indeed, proper monitoring of the viral population requires information on the different isolates circulating in the studied area. For this purpose, HTS has greatly facilitated the sequencing of new genomes of detected viruses and their comparison. However, bioinformatics analyses allowing reconstruction of genome sequences and detection of single nucleotide polymorphisms (SNPs) can potentially create bias and has not been widely addressed so far. Therefore, more knowledge is required on the limitations of predicting SNPs based on HTS-generated sequence samples. To address this issue, we compared the ability of 14 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 21 variants of pepino mosaic virus (PepMV) in three samples through large-scale performance testing (PT) using three artificially designed datasets. To evaluate the impact of bioinformatics analyses, they were divided into three key steps: reads pre-processing, virus-isolate identification, and variant calling. Each step was evaluated independently through an original, PT design including discussion and validation between participants at each step. Overall, this work underlines key parameters influencing SNPs detection and proposes recommendations for reliable variant calling for plant viruses. The identification of the closest reference, mapping parameters and manual validation of the detection were recognized as the most impactful analysis steps for the success of the SNPs detections. Strategies to improve the prediction of SNPs are also discussed.
bibliographic citation: Rollin et al. (2023) Detection of single nucleotide polymorphisms in virus genomes assembled from high-throughput sequencing data: large-scale performance testing of sequence analysis strategies. PeerJ 11:e15816 https://doi.org/10.7717/peerj.15816
date submitted: 2023-02-20
date accepted: 2023-07-10
issued: 2023-08-16
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Rollin
  given name: Johan
author list: Agent
  family name: Bester
  given name: Rachelle
author list: Agent
  family name: Brostaux
  given name: Yves
author list: Agent
  family name: Caglayan
  given name: Kadriye
author list: Agent
  family name: De Jonghe
  given name: Kris
author list: Agent
  family name: Eichmeier
  given name: Ales
author list: Agent
  family name: Foucart
  given name: Yoika
author list: Agent
  family name: Haegeman
  given name: Annelies
author list: Agent
  family name: Koloniuk
  given name: Igor
author list: Agent
  family name: Kominek
  given name: Petr
author list: Agent
  family name: Maree
  given name: Hans
author list: Agent
  family name: Onder
  given name: Serkan
author list: Agent
  family name: Posada Céspedes
  given name: Susana
author list: Agent
  family name: Roumi
  given name: Vahid
author list: Agent
  family name: Šafářová
  given name: Dana
author list: Agent
  family name: Schumpp
  given name: Olivier
author list: Agent
  family name: Ulubas Serce
  given name: Cigdem
author list: Agent
  family name: Sõmera
  given name: Merike
author list: Agent
  family name: Tamisier
  given name: Lucie
author list: Agent
  family name: Vainio
  given name: Eeva
author list: Agent
  family name: van der Vlugt
  given name: Rene AA
author list: Agent
  family name: Massart
  given name: Sebastien
doi: 10.7717/peerj.15816
volume: 11
issn: 2167-8359
publication name: PeerJ
publication date: 2023-08-16
copyright: © 2023 Rollin et al.
attribution name: Rollin et al.

LIDER: cell embedding based deep neural network classifier for supervised cell type identification
type: item
type: AcademicArticle
description: Background Automatic cell type identification has been an urgent task for the rapid development of single-cell RNA-seq techniques. Generally, the current approach for cell type identification is to generate cell clusters by unsupervised clustering and later assign labels to each cell cluster with manual annotation. Methods Here, we introduce LIDER (celL embeddIng based Deep nEural netwoRk classifier), a deep supervised learning method that combines cell embedding and deep neural network classifier for automatic cell type identification. Based on a stacked denoising autoencoder with a tailored and reconstructed loss function, LIDER identifies cell embedding and predicts cell types with a deep neural network classifier. LIDER was developed upon a stacked denoising autoencoder to learn encoder-decoder structures for identifying cell embedding. Results LIDER accurately identifies cell types by using stacked denoising autoencoder. Benchmarking against state-of-the-art methods across eight types of single-cell data, LIDER achieves comparable or even superior enhancement performance. Moreover, LIDER suggests comparable robust to batch effects. Our results show a potential in deep supervised learning for automatic cell type identification of single-cell RNA-seq data. The LIDER codes are available at https://github.com/ShiMGLab/LIDER.
format: application/pdf
format: text/html
creator: Yachen Tang
creator: Xuefeng Li
creator: Mingguang Shi
subject: Bioinformatics
subject: Cell Biology
subject: Computational Biology
description: doi:10.7717/peerj.15862
publisher: PeerJ Inc.
rights: © 2023 Tang et al.
abstract: Background Automatic cell type identification has been an urgent task for the rapid development of single-cell RNA-seq techniques. Generally, the current approach for cell type identification is to generate cell clusters by unsupervised clustering and later assign labels to each cell cluster with manual annotation. Methods Here, we introduce LIDER (celL embeddIng based Deep nEural netwoRk classifier), a deep supervised learning method that combines cell embedding and deep neural network classifier for automatic cell type identification. Based on a stacked denoising autoencoder with a tailored and reconstructed loss function, LIDER identifies cell embedding and predicts cell types with a deep neural network classifier. LIDER was developed upon a stacked denoising autoencoder to learn encoder-decoder structures for identifying cell embedding. Results LIDER accurately identifies cell types by using stacked denoising autoencoder. Benchmarking against state-of-the-art methods across eight types of single-cell data, LIDER achieves comparable or even superior enhancement performance. Moreover, LIDER suggests comparable robust to batch effects. Our results show a potential in deep supervised learning for automatic cell type identification of single-cell RNA-seq data. The LIDER codes are available at https://github.com/ShiMGLab/LIDER.
bibliographic citation: Tang et al. (2023) LIDER: cell embedding based deep neural network classifier for supervised cell type identification. PeerJ 11:e15862 https://doi.org/10.7717/peerj.15862
date submitted: 2023-04-14
date accepted: 2023-07-17
issued: 2023-08-16
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Tang
  given name: Yachen
author list: Agent
  family name: Li
  given name: Xuefeng
author list: Agent
  family name: Shi
  given name: Mingguang
doi: 10.7717/peerj.15862
volume: 11
issn: 2167-8359
publication name: PeerJ
publication date: 2023-08-16
copyright: ©2023 Tang et al.
attribution name: Tang et al.

Effects of post-activation protocols based on slow tempo bodyweight squat and isometric activity on vertical jump height enhancement in trained males: a randomized controlled trial
type: item
type: AcademicArticle
description: This study aimed to establish the effectiveness of slow tempo bodyweight squat combined with an isometric squat (ST-ISO), and an isometric squat alone (ISO), as a post-activation performance enhancement protocol (PAPE) for jump height improvement. The study sample consisted of 41 trained men aged 18–24. The ST-ISO group (n = 17) performed three five-second sets of the maximal voluntary back squat while pushing on an immovable bar and two sets of five repetitions of a slow-tempo (5-0-5-0) body squat immediately after isometry with a 2-m rest interval. The ISO (n = 14) group only performed isometric squats, and the control group (CG; n = 10) performed a 5-min treadmill run at 6 km/h. The countermovement jump (CMJ) height results were analyzed from the baseline and then at 3, 5, 7, and 9 min after the PAPE protocols. The statistical significance was set at p < 0.05. RM-ANOVA revealed differences in the group-minute interaction (F = 2.70; p = 0.0083; η2 = 0.1243), and post-hoc tests demonstrated a significant decrease in CMJ after 5 min in the ISO group (p < 0.0446). The performance of the ST-ISO group markedly decreased in the 3rd and 7th min after PAPE (p = 0.0137; p = 0.0424, respectively), though it improved significantly in the final minute (p < 0.0030). Chi-squared analysis revealed that the ST-ISO group peaked more frequently in the 9th min (X2 = 17.97; p = 0.0214). However, CMJ height improvement did not differ between the PAPE protocols, thus it was close to statistical significance (t = −1.82; p = 0.07; ES = 0.7). The ST-ISO protocol provided jump enhancement, though the deterioration observed in the first minutes after the protocols suggest the rest period after activity requires attention, and the methods need to be individualized.
format: application/pdf
format: text/html
creator: Dawid Koźlenia
creator: Jarosław Domaradzki
subject: Kinesiology
subject: Sports Medicine
description: doi:10.7717/peerj.15753
publisher: PeerJ Inc.
rights: © 2023 Koźlenia and Domaradzki
abstract: This study aimed to establish the effectiveness of slow tempo bodyweight squat combined with an isometric squat (ST-ISO), and an isometric squat alone (ISO), as a post-activation performance enhancement protocol (PAPE) for jump height improvement. The study sample consisted of 41 trained men aged 18–24. The ST-ISO group (n = 17) performed three five-second sets of the maximal voluntary back squat while pushing on an immovable bar and two sets of five repetitions of a slow-tempo (5-0-5-0) body squat immediately after isometry with a 2-m rest interval. The ISO (n = 14) group only performed isometric squats, and the control group (CG; n = 10) performed a 5-min treadmill run at 6 km/h. The countermovement jump (CMJ) height results were analyzed from the baseline and then at 3, 5, 7, and 9 min after the PAPE protocols. The statistical significance was set at p < 0.05. RM-ANOVA revealed differences in the group-minute interaction (F = 2.70; p = 0.0083; η2 = 0.1243), and post-hoc tests demonstrated a significant decrease in CMJ after 5 min in the ISO group (p < 0.0446). The performance of the ST-ISO group markedly decreased in the 3rd and 7th min after PAPE (p = 0.0137; p = 0.0424, respectively), though it improved significantly in the final minute (p < 0.0030). Chi-squared analysis revealed that the ST-ISO group peaked more frequently in the 9th min (X2 = 17.97; p = 0.0214). However, CMJ height improvement did not differ between the PAPE protocols, thus it was close to statistical significance (t = −1.82; p = 0.07; ES = 0.7). The ST-ISO protocol provided jump enhancement, though the deterioration observed in the first minutes after the protocols suggest the rest period after activity requires attention, and the methods need to be individualized.
bibliographic citation: Koźlenia et al. (2023) Effects of post-activation protocols based on slow tempo bodyweight squat and isometric activity on vertical jump height enhancement in trained males: a randomized controlled trial. PeerJ 11:e15753 https://doi.org/10.7717/peerj.15753
date submitted: 2023-03-20
date accepted: 2023-06-23
issued: 2023-08-15
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Koźlenia
  given name: Dawid
author list: Agent
  family name: Domaradzki
  given name: Jarosław
doi: 10.7717/peerj.15753
volume: 11
issn: 2167-8359
publication name: PeerJ
publication date: 2023-08-15
copyright: © 2023 Koźlenia and Domaradzki
attribution name: Koźlenia and Domaradzki

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