PeerJ
type: channel
link: https://peerj.com/articles/
description: Articles published in PeerJ
publisher: PeerJ Inc.
publication name: PeerJ
issn: 2167-8359
items: Natural grazing by horses and cattle promotes bird diversity in a restored European alluvial grassland
items: Revolutionizing CAD/CAM-based restorative dental processes and materials with artificial intelligence: a concise narrative review
items: Acute clomipramine exposure elicits dose-dependent surfacing behavior in adult zebrafish (Danio rerio)
items: Bioprospecting of soil-borne microorganisms and chemical dereplication of their anti-microbial constituents with the aid of UPLC-QTOF-MS and molecular networking approach
items: Automated identification and segmentation of urine spots based on deep-learning
items: Intraspecific variation in the pterosaur Rhamphorhynchus muensteri—implications for flight and socio-sexual signaling
items: The prognostic role of lymphocyte-to-monocyte ratio in patients with resectable pancreatic cancer: a systematic review and meta-analysis
items: A multi-ethnic proteomic profiling analysis in Alzheimer’s disease identifies the disparities in dysregulation of proteins and pathogenesis
items: Classification of major species in the sericite–Artemisia desert grassland using hyperspectral images and spectral feature identification
items: Associations between SNPs and vegetation indices: unraveling molecular insights for enhanced cultivation of tea plant (Camellia sinensis (L.) O. Kuntze)

Natural grazing by horses and cattle promotes bird diversity in a restored European alluvial grassland
type: item
type: AcademicArticle
description: Context A challenge in grassland conservation is to maintain both the openness and the heterogeneity of the habitat to support the diversity of their animal communities, including birds—a taxon that is known to be sensitive to disturbance. An increasingly used management tool in European grassland conservation, especially in rewilding projects, is grazing by large herbivores such as horses and cattle. These grazers are believed to create and maintain patchy landscapes that promote diversity and richness of other species, but their influence on birds is often debated by conservationists, who raise concerns about the impact of disturbance by the grazers. Objectives Our aim was to examine the relationship between the abundance and species richness of birds across four foraging guilds and the area utilization patterns of Highland cattle and Konik horses in an alluvial grassland in France. We also aimed to examine the influence of land cover and season on the spatial distribution, including abundance and species richness, of different bird guilds present in the grazed area. Methods We used GPS-collars on all grazers and recorded their positions on an hourly basis over a study period of 1.5 years, assessing patterns of area usage. We counted birds weekly along three transects to describe their distribution within the grazed area and carried out land-cover surveys to describe the habitat. To assess how species richness and abundance of birds of different guilds were related to grazer density, season, and habitat characteristics, we used GAMM models in a spatially explicit framework. We also compared bird numbers at our main study site with a nearby non-grazed control area. Results The number of birds in the grazed area was about twice the number in the non-grazed control area. Within the grazed area, the abundance of open-area foraging birds increased with increasing grazer density. The number of woodland-foraging birds was also positively correlated with grazer density bu…
format: application/pdf
format: text/html
creator: Lilla Lovász
creator: Fränzi Korner-Nievergelt
creator: Valentin Amrhein
subject: Biodiversity
subject: Conservation Biology
subject: Ecology
subject: Ecosystem Science
description: doi:10.7717/peerj.17777
publisher: PeerJ Inc.
rights: © 2024 Lovász et al.
abstract: Context A challenge in grassland conservation is to maintain both the openness and the heterogeneity of the habitat to support the diversity of their animal communities, including birds—a taxon that is known to be sensitive to disturbance. An increasingly used management tool in European grassland conservation, especially in rewilding projects, is grazing by large herbivores such as horses and cattle. These grazers are believed to create and maintain patchy landscapes that promote diversity and richness of other species, but their influence on birds is often debated by conservationists, who raise concerns about the impact of disturbance by the grazers. Objectives Our aim was to examine the relationship between the abundance and species richness of birds across four foraging guilds and the area utilization patterns of Highland cattle and Konik horses in an alluvial grassland in France. We also aimed to examine the influence of land cover and season on the spatial distribution, including abundance and species richness, of different bird guilds present in the grazed area. Methods We used GPS-collars on all grazers and recorded their positions on an hourly basis over a study period of 1.5 years, assessing patterns of area usage. We counted birds weekly along three transects to describe their distribution within the grazed area and carried out land-cover surveys to describe the habitat. To assess how species richness and abundance of birds of different guilds were related to grazer density, season, and habitat characteristics, we used GAMM models in a spatially explicit framework. We also compared bird numbers at our main study site with a nearby non-grazed control area. Results The number of birds in the grazed area was about twice the number in the non-grazed control area. Within the grazed area, the abundance of open-area foraging birds increased with increasing grazer density. The number of woodland-foraging birds was also positively correlated with grazer density bu…
bibliographic citation: Lovász et al. (2024) Natural grazing by horses and cattle promotes bird diversity in a restored European alluvial grassland. PeerJ 12:e17777 https://doi.org/10.7717/peerj.17777
date submitted: 2023-12-29
date accepted: 2024-06-28
issued: 2024-07-19
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Lovász
  given name: Lilla
author list: Agent
  family name: Korner-Nievergelt
  given name: Fränzi
author list: Agent
  family name: Amrhein
  given name: Valentin
doi: 10.7717/peerj.17777
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-07-19
copyright: ©2024 Lovász et al.
attribution name: Lovász et al.

Revolutionizing CAD/CAM-based restorative dental processes and materials with artificial intelligence: a concise narrative review
type: item
type: AcademicArticle
description: Artificial intelligence (AI) is increasingly prevalent in biomedical and industrial development, capturing the interest of dental professionals and patients. Its potential to improve the accuracy and speed of dental procedures is set to revolutionize dental care. The use of AI in computer-aided design/computer-aided manufacturing (CAD/CAM) within the restorative dental and material science fields offers numerous benefits, providing a new dimension to these practices. This study aims to provide a concise overview of the implementation of AI-powered technologies in CAD/CAM restorative dental procedures and materials. A comprehensive literature search was conducted using keywords from 2000 to 2023 to obtain pertinent information. This method was implemented to guarantee a thorough investigation of the subject matter. Keywords included; “Artificial Intelligence”, “Machine Learning”, “Neural Networks”, “Virtual Reality”, “Digital Dentistry”, “CAD/CAM”, and “Restorative Dentistry”. Artificial intelligence in digital restorative dentistry has proven to be highly beneficial in various dental CAD/CAM applications. It helps in automating and incorporating esthetic factors, occlusal schemes, and previous practitioners’ CAD choices in fabricating dental restorations. AI can also predict the debonding risk of CAD/CAM restorations and the compositional effects on the mechanical properties of its materials. Continuous enhancements are being made to overcome its limitations and open new possibilities for future developments in this field.
format: application/pdf
format: text/html
creator: Hanin E. Yeslam
creator: Nadine Freifrau von Maltzahn
creator: Hani M. Nassar
subject: Biotechnology
subject: Dentistry
subject: Human-Computer Interaction
subject: Data Mining and Machine Learning
subject: Data Science
description: doi:10.7717/peerj.17793
publisher: PeerJ Inc.
rights: © 2024 Yeslam et al.
abstract: Artificial intelligence (AI) is increasingly prevalent in biomedical and industrial development, capturing the interest of dental professionals and patients. Its potential to improve the accuracy and speed of dental procedures is set to revolutionize dental care. The use of AI in computer-aided design/computer-aided manufacturing (CAD/CAM) within the restorative dental and material science fields offers numerous benefits, providing a new dimension to these practices. This study aims to provide a concise overview of the implementation of AI-powered technologies in CAD/CAM restorative dental procedures and materials. A comprehensive literature search was conducted using keywords from 2000 to 2023 to obtain pertinent information. This method was implemented to guarantee a thorough investigation of the subject matter. Keywords included; “Artificial Intelligence”, “Machine Learning”, “Neural Networks”, “Virtual Reality”, “Digital Dentistry”, “CAD/CAM”, and “Restorative Dentistry”. Artificial intelligence in digital restorative dentistry has proven to be highly beneficial in various dental CAD/CAM applications. It helps in automating and incorporating esthetic factors, occlusal schemes, and previous practitioners’ CAD choices in fabricating dental restorations. AI can also predict the debonding risk of CAD/CAM restorations and the compositional effects on the mechanical properties of its materials. Continuous enhancements are being made to overcome its limitations and open new possibilities for future developments in this field.
bibliographic citation: Yeslam et al. (2024) Revolutionizing CAD/CAM-based restorative dental processes and materials with artificial intelligence: a concise narrative review. PeerJ 12:e17793 https://doi.org/10.7717/peerj.17793
date submitted: 2023-09-08
date accepted: 2024-07-01
issued: 2024-07-19
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Yeslam
  given name: Hanin E.
author list: Agent
  family name: Freifrau von Maltzahn
  given name: Nadine
author list: Agent
  family name: Nassar
  given name: Hani M.
doi: 10.7717/peerj.17793
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-07-19
copyright: © 2024 Yeslam et al.
attribution name: Yeslam et al.

Acute clomipramine exposure elicits dose-dependent surfacing behavior in adult zebrafish (Danio rerio)
type: item
type: AcademicArticle
description: Chronic treatment with clomipramine, a tricyclic antidepressant drug, reduces symptoms of obsessive-compulsive disorder (OCD) and can influence the activity of the hypothalamic-pituitary-adrenal axis. However, little is known regarding the effects of acute clomipramine on the immediate expression of stress responses. Serotonergic drugs can elicit surfacing, a behavioral profile potentially related to toxicity in fish, although surfacing has not yet been observed after clomipramine exposure. The present study investigated the impact of acute exposure to clomipramine on basal and stress-induced behaviors in the novel tank test and cortisol levels in mixed-sex, wild-type, adult zebrafish (Danio rerio). The findings show clomipramine-exposed groups (regardless of stress exposure) spent much more time in the top of the novel tank and had significantly less overall motor activity in the behavioral task compared to the fish not exposed to the drug. Then, the dose-dependent effects of acute clomipramine on activity in the surface of the novel tank (top third of the top half) were investigated further. Clomipramine dose-dependently increased surface-dwelling and elicited a dose-dependent hypoactivity in overall motor behavior. There were no statistically significant differences in whole-body cortisol levels in either experiment. Like other serotonin-acting drugs, clomipramine strongly elicited surface-dwelling and depressed motor behavior in adult zebrafish. Additional testing is needed to elucidate whether surfacing represents a toxic state and how serotonin regulates surfacing.
format: application/pdf
format: text/html
creator: Adeel Shafiq
creator: Mercedes Andrade
creator: Richanne Matthews
creator: Alexandria Umbarger
creator: Maureen L. Petrunich-Rutherford
subject: Animal Behavior
subject: Aquaculture, Fisheries and Fish Science
subject: Biochemistry
subject: Neuroscience
subject: Freshwater Biology
description: doi:10.7717/peerj.17803
publisher: PeerJ Inc.
rights: © 2024 Shafiq et al.
abstract: Chronic treatment with clomipramine, a tricyclic antidepressant drug, reduces symptoms of obsessive-compulsive disorder (OCD) and can influence the activity of the hypothalamic-pituitary-adrenal axis. However, little is known regarding the effects of acute clomipramine on the immediate expression of stress responses. Serotonergic drugs can elicit surfacing, a behavioral profile potentially related to toxicity in fish, although surfacing has not yet been observed after clomipramine exposure. The present study investigated the impact of acute exposure to clomipramine on basal and stress-induced behaviors in the novel tank test and cortisol levels in mixed-sex, wild-type, adult zebrafish (Danio rerio). The findings show clomipramine-exposed groups (regardless of stress exposure) spent much more time in the top of the novel tank and had significantly less overall motor activity in the behavioral task compared to the fish not exposed to the drug. Then, the dose-dependent effects of acute clomipramine on activity in the surface of the novel tank (top third of the top half) were investigated further. Clomipramine dose-dependently increased surface-dwelling and elicited a dose-dependent hypoactivity in overall motor behavior. There were no statistically significant differences in whole-body cortisol levels in either experiment. Like other serotonin-acting drugs, clomipramine strongly elicited surface-dwelling and depressed motor behavior in adult zebrafish. Additional testing is needed to elucidate whether surfacing represents a toxic state and how serotonin regulates surfacing.
bibliographic citation: Shafiq et al. (2024) Acute clomipramine exposure elicits dose-dependent surfacing behavior in adult zebrafish (Danio rerio). PeerJ 12:e17803 https://doi.org/10.7717/peerj.17803
date submitted: 2023-07-07
date accepted: 2024-07-03
issued: 2024-07-19
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Shafiq
  given name: Adeel
author list: Agent
  family name: Andrade
  given name: Mercedes
author list: Agent
  family name: Matthews
  given name: Richanne
author list: Agent
  family name: Umbarger
  given name: Alexandria
author list: Agent
  family name: Petrunich-Rutherford
  given name: Maureen L.
doi: 10.7717/peerj.17803
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-07-19
copyright: ©2024 Shafiq et al.
attribution name: Shafiq et al.

Bioprospecting of soil-borne microorganisms and chemical dereplication of their anti-microbial constituents with the aid of UPLC-QTOF-MS and molecular networking approach
type: item
type: AcademicArticle
description: Due to the emergence of drug-resistant microorganisms, the search for broad-spectrum antimicrobial compounds has become extremely crucial. Natural sources like plants and soils have been explored for diverse metabolites with antimicrobial properties. This study aimed to identify microorganisms from agricultural soils exhibiting antimicrobial effects against known human pathogens, and to highlight the chemical space of the responsible compounds through the computational metabolomics-based bioprospecting approach. Herein, bacteria were extracted from soil samples and their antimicrobial potential was measured via the agar well diffusion method. Methanolic extracts from the active bacteria were analyzed using the liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) technique, and the subsequent data was further analyzed through molecular networking approach which aided in identification of potential anti-microbial compounds. Furthermore, 16S rRNA gene sequencing enabled identification of the active bacterial isolates, where isolate 1 and 2 were identified as strains of Bacillus pumilus, whilst isolate 3 was found to be Bacillus subtilis. Interestingly, isolate 3 (Bacillus subtilis) displayed wide-ranging antimicrobial activity against the tested human pathogens. Molecular networking revealed the presence of Diketopiperazine compounds such as cyclo (D-Pro-D-Leu), cyclo (L-Tyr-L-Pro), cyclo (L-Pro-D-Phe), and cyclo (L-Pro-L-Val), alongside Surfactin C, Surfactin B, Pumilacidin E, and Isarrin D in the Bacillus strains as the main anti-microbial compounds. The application of the molecular networking approach represents an innovation in the field of bio-guided bioprospection of microorganisms and has proved to be an effective and feasible towards unearthing potent antimicrobial compounds. Additionally, the (computational metabolomics-based) approach accelerates the discovery of bioactive compounds and isolation of strains which offer a promising av…
format: application/pdf
format: text/html
creator: Adivhaho Khwathisi
creator: Ntakadzeni Edwin Madala
creator: Afsatou Ndama Traore
creator: Amidou Samie
subject: Biochemistry
subject: Microbiology
subject: Data Science
description: doi:10.7717/peerj.17364
publisher: PeerJ Inc.
rights: © 2024 Khwathisi et al.
abstract: Due to the emergence of drug-resistant microorganisms, the search for broad-spectrum antimicrobial compounds has become extremely crucial. Natural sources like plants and soils have been explored for diverse metabolites with antimicrobial properties. This study aimed to identify microorganisms from agricultural soils exhibiting antimicrobial effects against known human pathogens, and to highlight the chemical space of the responsible compounds through the computational metabolomics-based bioprospecting approach. Herein, bacteria were extracted from soil samples and their antimicrobial potential was measured via the agar well diffusion method. Methanolic extracts from the active bacteria were analyzed using the liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) technique, and the subsequent data was further analyzed through molecular networking approach which aided in identification of potential anti-microbial compounds. Furthermore, 16S rRNA gene sequencing enabled identification of the active bacterial isolates, where isolate 1 and 2 were identified as strains of Bacillus pumilus, whilst isolate 3 was found to be Bacillus subtilis. Interestingly, isolate 3 (Bacillus subtilis) displayed wide-ranging antimicrobial activity against the tested human pathogens. Molecular networking revealed the presence of Diketopiperazine compounds such as cyclo (D-Pro-D-Leu), cyclo (L-Tyr-L-Pro), cyclo (L-Pro-D-Phe), and cyclo (L-Pro-L-Val), alongside Surfactin C, Surfactin B, Pumilacidin E, and Isarrin D in the Bacillus strains as the main anti-microbial compounds. The application of the molecular networking approach represents an innovation in the field of bio-guided bioprospection of microorganisms and has proved to be an effective and feasible towards unearthing potent antimicrobial compounds. Additionally, the (computational metabolomics-based) approach accelerates the discovery of bioactive compounds and isolation of strains which offer a promising av…
bibliographic citation: Khwathisi et al. (2024) Bioprospecting of soil-borne microorganisms and chemical dereplication of their anti-microbial constituents with the aid of UPLC-QTOF-MS and molecular networking approach. PeerJ 12:e17364 https://doi.org/10.7717/peerj.17364
date submitted: 2024-01-24
date accepted: 2024-04-18
issued: 2024-07-18
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Khwathisi
  given name: Adivhaho
author list: Agent
  family name: Madala
  given name: Ntakadzeni Edwin
author list: Agent
  family name: Traore
  given name: Afsatou Ndama
author list: Agent
  family name: Samie
  given name: Amidou
doi: 10.7717/peerj.17364
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-07-18
copyright: ©2024 Khwathisi et al.
attribution name: Khwathisi et al.

Automated identification and segmentation of urine spots based on deep-learning
type: item
type: AcademicArticle
description: Micturition serves an essential physiological function that allows the body to eliminate metabolic wastes and maintain water-electrolyte balance. The urine spot assay (VSA), as a simple and economical assay, has been widely used in the study of micturition behavior in rodents. However, the traditional VSA method relies on manual judgment, introduces subjective errors, faces difficulty in obtaining appearance time of each urine spot, and struggles with quantitative analysis of overlapping spots. To address these challenges, we developed a deep learning-based approach for the automatic identification and segmentation of urine spots. Our system employs a target detection network to efficiently detect each urine spot and utilizes an instance segmentation network to achieve precise segmentation of overlapping urine spots. Compared with the traditional VSA method, our system achieves automated detection of urine spot area of micturition in rodents, greatly reducing subjective errors. It accurately determines the urination time of each spot and effectively quantifies the overlapping spots. This study enables high-throughput and precise urine spot detection, providing important technical support for the analysis of urination behavior and the study of the neural mechanism underlying urination.
format: application/pdf
format: text/html
creator: Xin Fan
creator: Jun Li
creator: Junan Yan
subject: Biochemistry
subject: Computational Biology
subject: Urology
description: doi:10.7717/peerj.17398
publisher: PeerJ Inc.
rights: © 2024 Fan et al.
abstract: Micturition serves an essential physiological function that allows the body to eliminate metabolic wastes and maintain water-electrolyte balance. The urine spot assay (VSA), as a simple and economical assay, has been widely used in the study of micturition behavior in rodents. However, the traditional VSA method relies on manual judgment, introduces subjective errors, faces difficulty in obtaining appearance time of each urine spot, and struggles with quantitative analysis of overlapping spots. To address these challenges, we developed a deep learning-based approach for the automatic identification and segmentation of urine spots. Our system employs a target detection network to efficiently detect each urine spot and utilizes an instance segmentation network to achieve precise segmentation of overlapping urine spots. Compared with the traditional VSA method, our system achieves automated detection of urine spot area of micturition in rodents, greatly reducing subjective errors. It accurately determines the urination time of each spot and effectively quantifies the overlapping spots. This study enables high-throughput and precise urine spot detection, providing important technical support for the analysis of urination behavior and the study of the neural mechanism underlying urination.
bibliographic citation: Fan et al. (2024) Automated identification and segmentation of urine spots based on deep-learning. PeerJ 12:e17398 https://doi.org/10.7717/peerj.17398
date submitted: 2024-02-09
date accepted: 2024-04-25
issued: 2024-07-18
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Fan
  given name: Xin
author list: Agent
  family name: Li
  given name: Jun
author list: Agent
  family name: Yan
  given name: Junan
doi: 10.7717/peerj.17398
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-07-18
copyright: ©2024 Fan et al.
attribution name: Fan et al.

Intraspecific variation in the pterosaur Rhamphorhynchus muensteri—implications for flight and socio-sexual signaling
type: item
type: AcademicArticle
description: Pterosaurs were the first powered flying vertebrates, with a fossil record that stretches back to about 230 million years before present. Most species are only known from one to three specimens, which are most often fragmentary. However, Rhamphorhynchus muensteri is known from numerous excellent specimens, including multiple specimens with soft tissue preservation. As such, Rhamphorhynchus muensteri is one of the only pterosaurs amenable to analysis for intraspecific variation. It has been previously predicted that elements directly involved in the flight apparatus, such as those of the forelimb, will be more highly constrained in their proportions than other parts of the skeleton. We investigated the degree of variation seen in elements and body parts of Rhamphorhynchus, which represents the best model system among pterosaurs for testing these expectations of intraspecific variation. We recover evidence for high levels of constraint throughout the appendicular and axial elements (head, neck, torso, tail, forelimbs, hindlimbs), suggesting that all were important for flight. We further find that tail variation increases among the largest specimens, suggesting reduced constraint and/or stronger sexual selection on the tail in more mature individuals.
format: application/pdf
format: text/html
creator: Michael B. Habib
creator: David WE. Hone
subject: Animal Behavior
subject: Ecology
subject: Evolutionary Studies
subject: Paleontology
description: doi:10.7717/peerj.17524
publisher: PeerJ Inc.
rights: © 2024 Habib and Hone
abstract: Pterosaurs were the first powered flying vertebrates, with a fossil record that stretches back to about 230 million years before present. Most species are only known from one to three specimens, which are most often fragmentary. However, Rhamphorhynchus muensteri is known from numerous excellent specimens, including multiple specimens with soft tissue preservation. As such, Rhamphorhynchus muensteri is one of the only pterosaurs amenable to analysis for intraspecific variation. It has been previously predicted that elements directly involved in the flight apparatus, such as those of the forelimb, will be more highly constrained in their proportions than other parts of the skeleton. We investigated the degree of variation seen in elements and body parts of Rhamphorhynchus, which represents the best model system among pterosaurs for testing these expectations of intraspecific variation. We recover evidence for high levels of constraint throughout the appendicular and axial elements (head, neck, torso, tail, forelimbs, hindlimbs), suggesting that all were important for flight. We further find that tail variation increases among the largest specimens, suggesting reduced constraint and/or stronger sexual selection on the tail in more mature individuals.
bibliographic citation: Habib et al. (2024) Intraspecific variation in the pterosaur Rhamphorhynchus muensteri—implications for flight and socio-sexual signaling. PeerJ 12:e17524 https://doi.org/10.7717/peerj.17524
date submitted: 2023-12-10
date accepted: 2024-05-16
issued: 2024-07-18
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Habib
  given name: Michael B.
author list: Agent
  family name: Hone
  given name: David WE.
doi: 10.7717/peerj.17524
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-07-18
copyright: © 2024 Habib and Hone
attribution name: Habib and Hone

The prognostic role of lymphocyte-to-monocyte ratio in patients with resectable pancreatic cancer: a systematic review and meta-analysis
type: item
type: AcademicArticle
description: Objectives This systematic review and meta-analysis examined whether the lymphocyte-to-monocyte ratio (LMR) can serve as an indicator for predicting the prognosis of patients with resectable pancreatic cancer. Patients and Methods This meta-analysis was registered with PROSPERO: CRD42023461260. A systematic literature search was conducted in the PubMed, Embase, Cochrane, and Web of Science databases up to September 2023 to assess whether LMR can predict the prognosis of patients with resectable pancreatic cancer. The outcomes measured included subgroup analyses of overall survival (OS) with hazard ratios (HR) and confidence intervals of geographical region, patient population, and LMR threshold. A sensitivity analysis was also performed for OS and HR and confidence intervals were calculated for recurrence-free survival (RFS). Results A total of 14 eligible articles, comprising 4,019 patients, were included in the comprehensive analysis. The results of this comprehensive analysis indicate that LMR is a robust predictor of OS, demonstrating strong prognostic significance (HR = 0.55, 95% CI [0.44–0.69], I2 = 79%, P < 0.00001). This predictive significance extended to various types of pancreatic cancer, such as pancreatic ductal adenocarcinoma (HR = 0.73, 95% CI [0.57–0.93], I2 = 46%, P = 0.01), pancreatic neuroendocrine neoplasms (HR = 0.81, 95% CI [0.66–0.99], P = 0.04) and other subtypes (HR = 0.40, 95% CI [0.22–0.72], I2 = 89%, P < 0.00001), but not to pancreatic head cancer (HR = 0.46, 95% CI [0.16–1.13], I2 = 59%, P = 0.12). LMR retained its predictive value across different regions, including Asia (HR = 0.62, 95% CI [0.47–0.76], I2 = 68%, P < 0.0001), Europe (HR = 0.78, 95% CI [0.67–0.91], I2 = 0%, P = 0.002), and the Americas (HR = 0.14, 95% CI [0.08–0.24], I2 = 0%, P < 0.00001). Notably, both LMR cut-off values greater than or equal to three (HR = 0.62, 95% CI [0.47–0.82], I2 = 67%, P = 0.0009) and less than three (HR = 0.47, 95% CI [0.32–0.69], I2 = 85%, P = 0…
format: application/pdf
format: text/html
creator: Haipeng Li
creator: Shang Peng
creator: Ran An
creator: Nana Du
creator: Huan Wu
creator: Xiangcheng Zhen
creator: Yuanzhi Gao
creator: Zhenghong Li
creator: Jingting Min
subject: Gastroenterology and Hepatology
subject: Immunology
subject: Oncology
description: doi:10.7717/peerj.17585
publisher: PeerJ Inc.
rights: © 2024 Li et al.
abstract: Objectives This systematic review and meta-analysis examined whether the lymphocyte-to-monocyte ratio (LMR) can serve as an indicator for predicting the prognosis of patients with resectable pancreatic cancer. Patients and Methods This meta-analysis was registered with PROSPERO: CRD42023461260. A systematic literature search was conducted in the PubMed, Embase, Cochrane, and Web of Science databases up to September 2023 to assess whether LMR can predict the prognosis of patients with resectable pancreatic cancer. The outcomes measured included subgroup analyses of overall survival (OS) with hazard ratios (HR) and confidence intervals of geographical region, patient population, and LMR threshold. A sensitivity analysis was also performed for OS and HR and confidence intervals were calculated for recurrence-free survival (RFS). Results A total of 14 eligible articles, comprising 4,019 patients, were included in the comprehensive analysis. The results of this comprehensive analysis indicate that LMR is a robust predictor of OS, demonstrating strong prognostic significance (HR = 0.55, 95% CI [0.44–0.69], I2 = 79%, P < 0.00001). This predictive significance extended to various types of pancreatic cancer, such as pancreatic ductal adenocarcinoma (HR = 0.73, 95% CI [0.57–0.93], I2 = 46%, P = 0.01), pancreatic neuroendocrine neoplasms (HR = 0.81, 95% CI [0.66–0.99], P = 0.04) and other subtypes (HR = 0.40, 95% CI [0.22–0.72], I2 = 89%, P < 0.00001), but not to pancreatic head cancer (HR = 0.46, 95% CI [0.16–1.13], I2 = 59%, P = 0.12). LMR retained its predictive value across different regions, including Asia (HR = 0.62, 95% CI [0.47–0.76], I2 = 68%, P < 0.0001), Europe (HR = 0.78, 95% CI [0.67–0.91], I2 = 0%, P = 0.002), and the Americas (HR = 0.14, 95% CI [0.08–0.24], I2 = 0%, P < 0.00001). Notably, both LMR cut-off values greater than or equal to three (HR = 0.62, 95% CI [0.47–0.82], I2 = 67%, P = 0.0009) and less than three (HR = 0.47, 95% CI [0.32–0.69], I2 = 85%, P = 0…
bibliographic citation: Li et al. (2024) The prognostic role of lymphocyte-to-monocyte ratio in patients with resectable pancreatic cancer: a systematic review and meta-analysis. PeerJ 12:e17585 https://doi.org/10.7717/peerj.17585
date submitted: 2023-12-19
date accepted: 2024-05-27
issued: 2024-07-18
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Li
  given name: Haipeng
author list: Agent
  family name: Peng
  given name: Shang
author list: Agent
  family name: An
  given name: Ran
author list: Agent
  family name: Du
  given name: Nana
author list: Agent
  family name: Wu
  given name: Huan
author list: Agent
  family name: Zhen
  given name: Xiangcheng
author list: Agent
  family name: Gao
  given name: Yuanzhi
author list: Agent
  family name: Li
  given name: Zhenghong
author list: Agent
  family name: Min
  given name: Jingting
doi: 10.7717/peerj.17585
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-07-18
copyright: © 2024 Li et al.
attribution name: Li et al.

A multi-ethnic proteomic profiling analysis in Alzheimer’s disease identifies the disparities in dysregulation of proteins and pathogenesis
type: item
type: AcademicArticle
description: Background Alzheimer’s disease (AD) is the most common type of dementia that affects the elderly population. Lately, blood-based proteomics have been intensively sought in the discovery of AD biomarkers studies due to the capability to link external environmental factors with the development of AD. Demographic differences have been shown to affect the expression of the proteins in different populations which play a vital role in the degeneration of cognitive function. Method In this study, a proteomic study focused on Malaysian Chinese and Malay prospects was conducted. Differentially expressed proteins (DEPs) in AD patients and normal controls for Chinese and Malays were identified. Functional enrichment analysis was conducted to further interpret the biological functions and pathways of the DEPs. In addition, a survey investigating behavioural practices among Chinese and Malay participants was conducted to support the results from the proteomic analysis. Result The variation of dysregulated proteins identified in Chinese and Malay samples suggested the disparities of pathways involved in this pathological condition for each respective ethnicity. Functional enrichment analysis supported this assumption in understanding the protein-protein interactions of the identified protein signatures and indicate that differentially expressed proteins identified from the Chinese group were significantly enriched with the functional terms related to Aβ/tau protein-related processes, oxidative stress and inflammation whereas neuroinflammation was associated with the Malay group. Besides that, a significant difference in sweet drinks/food intake habits between these two groups implies a relationship between sugar levels and the dysregulation of protein APOA4 in the Malay group. Additional meta-analysis further supported the dysregulation of proteins TF, AHSG, A1BG, APOA4 and C4A among AD groups. Conclusion These findings serve as a preliminary understanding in the molecular and de…
format: application/pdf
format: text/html
creator: Mei Sze Tan
creator: Phaik-Leng Cheah
creator: Ai-Vyrn Chin
creator: Lai-Meng Looi
creator: Siow-Wee Chang
subject: Bioinformatics
subject: Genetics
subject: Genomics
subject: Epidemiology
subject: Neurology
description: doi:10.7717/peerj.17643
publisher: PeerJ Inc.
rights: © 2024 Tan et al.
abstract: Background Alzheimer’s disease (AD) is the most common type of dementia that affects the elderly population. Lately, blood-based proteomics have been intensively sought in the discovery of AD biomarkers studies due to the capability to link external environmental factors with the development of AD. Demographic differences have been shown to affect the expression of the proteins in different populations which play a vital role in the degeneration of cognitive function. Method In this study, a proteomic study focused on Malaysian Chinese and Malay prospects was conducted. Differentially expressed proteins (DEPs) in AD patients and normal controls for Chinese and Malays were identified. Functional enrichment analysis was conducted to further interpret the biological functions and pathways of the DEPs. In addition, a survey investigating behavioural practices among Chinese and Malay participants was conducted to support the results from the proteomic analysis. Result The variation of dysregulated proteins identified in Chinese and Malay samples suggested the disparities of pathways involved in this pathological condition for each respective ethnicity. Functional enrichment analysis supported this assumption in understanding the protein-protein interactions of the identified protein signatures and indicate that differentially expressed proteins identified from the Chinese group were significantly enriched with the functional terms related to Aβ/tau protein-related processes, oxidative stress and inflammation whereas neuroinflammation was associated with the Malay group. Besides that, a significant difference in sweet drinks/food intake habits between these two groups implies a relationship between sugar levels and the dysregulation of protein APOA4 in the Malay group. Additional meta-analysis further supported the dysregulation of proteins TF, AHSG, A1BG, APOA4 and C4A among AD groups. Conclusion These findings serve as a preliminary understanding in the molecular and de…
bibliographic citation: Tan et al. (2024) A multi-ethnic proteomic profiling analysis in Alzheimer’s disease identifies the disparities in dysregulation of proteins and pathogenesis. PeerJ 12:e17643 https://doi.org/10.7717/peerj.17643
date submitted: 2023-12-04
date accepted: 2024-06-06
issued: 2024-07-18
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Tan
  given name: Mei Sze
author list: Agent
  family name: Cheah
  given name: Phaik-Leng
author list: Agent
  family name: Chin
  given name: Ai-Vyrn
author list: Agent
  family name: Looi
  given name: Lai-Meng
author list: Agent
  family name: Chang
  given name: Siow-Wee
doi: 10.7717/peerj.17643
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-07-18
copyright: © 2024 Tan et al.
attribution name: Tan et al.

Classification of major species in the sericite–Artemisia desert grassland using hyperspectral images and spectral feature identification
type: item
type: AcademicArticle
description: Background The species composition of and changes in grassland communities are important indices for inferring the number, quality and community succession of grasslands, and accurate monitoring is the foundation for evaluating, protecting, and utilizing grassland resources. Remote sensing technology provides a reliable and powerful approach for measuring regional terrain information, and the identification of grassland species by remote sensing will improve the quality and effectiveness of grassland monitoring. Methods Ground hyperspectral images of a sericite–Artemisia desert grassland in different seasons were obtained with a Soc710 VP imaging spectrometer. First-order differential processing was used to calculate the characteristic parameters. Analysis of variance was used to extract the main species, namely, Seriphidium transiliense (Poljak), Ceratocarpus arenarius L., Petrosimonia sibirica (Pall), bare land and the spectral characteristic parameters and vegetation indices in different seasons. On this basis, Fisher discriminant analysis was used to divide the samples into a training set and a test set at a ratio of 7:3. The spectral characteristic parameters and vegetation indices were used to identify the three main plants and bare land. Results The selection of parameters with significant differences (P < 0.05) between the recognition objects effectively distinguished different land features, and the identification parameters also differed due to differences in growth period and species. The overall accuracy of the recognition model established by the vegetation index decreased in the following order: June (98.87%) > September (91.53%) > April (90.37%). The overall accuracy of the recognition model established by the feature parameters decreased in the following order: September (89.77%) > June (88.48%) > April (85.98%). Conclusions The recognition models based on vegetation indices in different months are superior to those based on feature parameters, with …
format: application/pdf
format: text/html
creator: Wenhao Liu
creator: Wanqiang Han
creator: Guili Jin
creator: Ke Gong
creator: Jian Ma
subject: Agricultural Science
subject: Plant Science
subject: Natural Resource Management
description: doi:10.7717/peerj.17663
publisher: PeerJ Inc.
rights: © 2024 Liu et al.
abstract: Background The species composition of and changes in grassland communities are important indices for inferring the number, quality and community succession of grasslands, and accurate monitoring is the foundation for evaluating, protecting, and utilizing grassland resources. Remote sensing technology provides a reliable and powerful approach for measuring regional terrain information, and the identification of grassland species by remote sensing will improve the quality and effectiveness of grassland monitoring. Methods Ground hyperspectral images of a sericite–Artemisia desert grassland in different seasons were obtained with a Soc710 VP imaging spectrometer. First-order differential processing was used to calculate the characteristic parameters. Analysis of variance was used to extract the main species, namely, Seriphidium transiliense (Poljak), Ceratocarpus arenarius L., Petrosimonia sibirica (Pall), bare land and the spectral characteristic parameters and vegetation indices in different seasons. On this basis, Fisher discriminant analysis was used to divide the samples into a training set and a test set at a ratio of 7:3. The spectral characteristic parameters and vegetation indices were used to identify the three main plants and bare land. Results The selection of parameters with significant differences (P < 0.05) between the recognition objects effectively distinguished different land features, and the identification parameters also differed due to differences in growth period and species. The overall accuracy of the recognition model established by the vegetation index decreased in the following order: June (98.87%) > September (91.53%) > April (90.37%). The overall accuracy of the recognition model established by the feature parameters decreased in the following order: September (89.77%) > June (88.48%) > April (85.98%). Conclusions The recognition models based on vegetation indices in different months are superior to those based on feature parameters, with …
bibliographic citation: Liu et al. (2024) Classification of major species in the sericite–Artemisia desert grassland using hyperspectral images and spectral feature identification. PeerJ 12:e17663 https://doi.org/10.7717/peerj.17663
date submitted: 2023-10-23
date accepted: 2024-06-10
issued: 2024-07-18
is part of: PeerJ
license: https://creativecommons.org/licenses/by-nc/4.0
author list: Agent
  family name: Liu
  given name: Wenhao
author list: Agent
  family name: Han
  given name: Wanqiang
author list: Agent
  family name: Jin
  given name: Guili
author list: Agent
  family name: Gong
  given name: Ke
author list: Agent
  family name: Ma
  given name: Jian
doi: 10.7717/peerj.17663
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-07-18
copyright: ©2024 Liu et al.
attribution name: Liu et al.

Associations between SNPs and vegetation indices: unraveling molecular insights for enhanced cultivation of tea plant (Camellia sinensis (L.) O. Kuntze)
type: item
type: AcademicArticle
description: Background Breeding programs for nutrient-efficient tea plant varieties could be advanced by the combination of genotyping and phenotyping technologies. This study was aimed to search functional SNPs in key genes related to the nitrogen-assimilation in the collection of tea plant Camellia sinensis (L.) Kuntze. In addition, the objective of this study was to reveal efficient vegetation indices for phenotyping of nitrogen deficiency response in tea collection. Methods The study was conducted on the tea plant collection of Camellia sinensis (L.) Kuntze of Western Caucasus grown without nitrogen fertilizers. Phenotypic data was collected by measuring the spectral reflectance of leaves in the 350–1100 nm range calculated as vegetation indices by the portable hyperspectral spectrometer Ci710s. Single nucleotide polymorphisms were identified in 30 key genes related to nitrogen assimilation and tea quality. For this, pooled amplicon sequencing, SNPs annotation and effect prediction with SnpEFF tool were used. Further, a linear regression model was applied to reveal associations between the functional SNPs and the efficient vegetation indices. Results PCA and regression analysis revealed significant vegetation indices with high R2 values (more than 0.5) and the most reliable indices to select ND-tolerant genotypes were established: ZMI, CNDVI, RENDVI, VREI1, GM2, GM1, PRI, and Ctr2, VREI3, VREI2. The largest SNPs frequency was observed in several genes, namely F3’5’Hb, UFGTa, UFGTb, 4Cl, and AMT1.2. SNPs in NRT2.4, PIP, AlaDC, DFRa, and GS1.2 were inherent in ND-susceptible genotypes. Additionally, SNPs in AlaAT1, MYB4, and WRKY57, were led to alterations in protein structure and were observed in ND-susceptible tea genotypes. Associations were revealed between flavanol reflectance index (FRI) and SNPs in ASNb and PIP, that change the amino acids. In addition, two SNPs in 4Cl were associated with water band index (WBI). Conclusions The results will be useful to identify toler…
format: application/pdf
format: text/html
creator: Daria Kuzmina
creator: Lyudmila S. Malyukova
creator: Karina Manakhova
creator: Tatyana Kovalenko
creator: Jaroslava Fedorina
creator: Aleksandra O. Matskiv
creator: Alexey V. Ryndin
creator: Maya V. Gvasaliya
creator: Yuriy L. Orlov
creator: Lidiia S. Samarina
subject: Agricultural Science
subject: Biochemistry
subject: Bioinformatics
subject: Genetics
subject: Plant Science
description: doi:10.7717/peerj.17689
publisher: PeerJ Inc.
rights: © 2024 Kuzmina et al.
abstract: Background Breeding programs for nutrient-efficient tea plant varieties could be advanced by the combination of genotyping and phenotyping technologies. This study was aimed to search functional SNPs in key genes related to the nitrogen-assimilation in the collection of tea plant Camellia sinensis (L.) Kuntze. In addition, the objective of this study was to reveal efficient vegetation indices for phenotyping of nitrogen deficiency response in tea collection. Methods The study was conducted on the tea plant collection of Camellia sinensis (L.) Kuntze of Western Caucasus grown without nitrogen fertilizers. Phenotypic data was collected by measuring the spectral reflectance of leaves in the 350–1100 nm range calculated as vegetation indices by the portable hyperspectral spectrometer Ci710s. Single nucleotide polymorphisms were identified in 30 key genes related to nitrogen assimilation and tea quality. For this, pooled amplicon sequencing, SNPs annotation and effect prediction with SnpEFF tool were used. Further, a linear regression model was applied to reveal associations between the functional SNPs and the efficient vegetation indices. Results PCA and regression analysis revealed significant vegetation indices with high R2 values (more than 0.5) and the most reliable indices to select ND-tolerant genotypes were established: ZMI, CNDVI, RENDVI, VREI1, GM2, GM1, PRI, and Ctr2, VREI3, VREI2. The largest SNPs frequency was observed in several genes, namely F3’5’Hb, UFGTa, UFGTb, 4Cl, and AMT1.2. SNPs in NRT2.4, PIP, AlaDC, DFRa, and GS1.2 were inherent in ND-susceptible genotypes. Additionally, SNPs in AlaAT1, MYB4, and WRKY57, were led to alterations in protein structure and were observed in ND-susceptible tea genotypes. Associations were revealed between flavanol reflectance index (FRI) and SNPs in ASNb and PIP, that change the amino acids. In addition, two SNPs in 4Cl were associated with water band index (WBI). Conclusions The results will be useful to identify toler…
bibliographic citation: Kuzmina et al. (2024) Associations between SNPs and vegetation indices: unraveling molecular insights for enhanced cultivation of tea plant (Camellia sinensis (L.) O. Kuntze). PeerJ 12:e17689 https://doi.org/10.7717/peerj.17689
date submitted: 2024-03-15
date accepted: 2024-06-14
issued: 2024-07-18
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Kuzmina
  given name: Daria
author list: Agent
  family name: Malyukova
  given name: Lyudmila S.
author list: Agent
  family name: Manakhova
  given name: Karina
author list: Agent
  family name: Kovalenko
  given name: Tatyana
author list: Agent
  family name: Fedorina
  given name: Jaroslava
author list: Agent
  family name: Matskiv
  given name: Aleksandra O.
author list: Agent
  family name: Ryndin
  given name: Alexey V.
author list: Agent
  family name: Gvasaliya
  given name: Maya V.
author list: Agent
  family name: Orlov
  given name: Yuriy L.
author list: Agent
  family name: Samarina
  given name: Lidiia S.
doi: 10.7717/peerj.17689
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-07-18
copyright: ©2024 Kuzmina et al.
attribution name: Kuzmina et al.

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