PeerJ
type: channel
link: https://peerj.com/articles/
description: Articles published in PeerJ
publisher: PeerJ Inc.
publication name: PeerJ
issn: 2167-8359
items: Optimizing chlorine dioxide treatment for enhanced post-harvest storage quality of Toona Sinensis
items: Long-term alfalfa planting mediates the coupling of soil water and organic carbon storage in a semi-arid area of the Loess Plateau, China
items: Citizen science enhances understanding of sea turtle distribution in the Gulf of California
items: Effect of habitual physical activity on motor performance and prefrontal cortex activity during implicit motor learning
items: Genomic complexity and clinical significance of the RCCX locus
items: Dietary reference intake for military operations: a scoping review
items: Common laboratory results-based artificial intelligence analysis achieves accurate classification of plasma cell dyscrasias
items: Application of composite reference intervals in the diagnosis of subclinical hypothyroidism in the elderly: a retrospective study
items: Quality improvement bundles to decrease hypothermia in very low/extremely low birth weight infants at birth: a systematic review and meta-analysis
items: Applying stacking ensemble method to predict chronic kidney disease progression in Chinese population based on laboratory information system: a retrospective study

Optimizing chlorine dioxide treatment for enhanced post-harvest storage quality of Toona Sinensis
type: item
type: AcademicArticle
description: This study investigated the impact of chlorine dioxide (ClO2) treatment on the storage quality of Toona sinensis after harvesting. Toona sinensis samples treated with different concentrations (0.2, 0.4, 0.8, 1.6 mg/L) of chlorine dioxide and stored at (4 ± 1) °C, with sampling test every 2nd day. The changes in sensory, nutritional, and chlorine dioxide residues of T. sinensis were checked regularly. Results revealed that moderate (0.4~0.8 mg/L) chlorine dioxide concentrations maintained sensory quality, inhibited T. sinensis weight loss, slowed flavonoid and vitamin C content depletion, reduced nitrite content, and enhanced superoxide dismutase activity. The chlorine dioxide resides in T. sinensis were below the national standards (<2.0 mg/kg; GB 5009.244-2016). Overall, 0.4~0.8 mg/L chlorine dioxide treatment showed optimal effects on T. sinensis, providing a scientific basis for extended storage and preservation of T. sinensis.
format: application/pdf
format: text/html
creator: Rui Zeng
creator: Yunhong Gao
creator: Mingmin Zheng
creator: Min Lai
creator: Yishi JiGu
creator: Jiayu Chen
creator: Yun Pei
creator: Muhammad Umer Farooq
creator: Khalid Mashay Al-Anazi
creator: Mohammad Abul Farah
subject: Agricultural Science
subject: Food Science and Technology
subject: Plant Science
description: doi:10.7717/peerj.18346
publisher: PeerJ Inc.
rights: © 2024 Zeng et al.
abstract: This study investigated the impact of chlorine dioxide (ClO2) treatment on the storage quality of Toona sinensis after harvesting. Toona sinensis samples treated with different concentrations (0.2, 0.4, 0.8, 1.6 mg/L) of chlorine dioxide and stored at (4 ± 1) °C, with sampling test every 2nd day. The changes in sensory, nutritional, and chlorine dioxide residues of T. sinensis were checked regularly. Results revealed that moderate (0.4~0.8 mg/L) chlorine dioxide concentrations maintained sensory quality, inhibited T. sinensis weight loss, slowed flavonoid and vitamin C content depletion, reduced nitrite content, and enhanced superoxide dismutase activity. The chlorine dioxide resides in T. sinensis were below the national standards (<2.0 mg/kg; GB 5009.244-2016). Overall, 0.4~0.8 mg/L chlorine dioxide treatment showed optimal effects on T. sinensis, providing a scientific basis for extended storage and preservation of T. sinensis.
bibliographic citation: Zeng et al. (2024) Optimizing chlorine dioxide treatment for enhanced post-harvest storage quality of Toona Sinensis. PeerJ 12:e18346 https://doi.org/10.7717/peerj.18346
date submitted: 2024-06-21
date accepted: 2024-09-27
issued: 2024-11-05
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Zeng
  given name: Rui
author list: Agent
  family name: Gao
  given name: Yunhong
author list: Agent
  family name: Zheng
  given name: Mingmin
author list: Agent
  family name: Lai
  given name: Min
author list: Agent
  family name: JiGu
  given name: Yishi
author list: Agent
  family name: Chen
  given name: Jiayu
author list: Agent
  family name: Pei
  given name: Yun
author list: Agent
  family name: Farooq
  given name: Muhammad Umer
author list: Agent
  family name: Al-Anazi
  given name: Khalid Mashay
author list: Agent
  family name: Farah
  given name: Mohammad Abul
doi: 10.7717/peerj.18346
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-11-05
copyright: © 2024 Zeng et al.
attribution name: Zeng et al.

Long-term alfalfa planting mediates the coupling of soil water and organic carbon storage in a semi-arid area of the Loess Plateau, China
type: item
type: AcademicArticle
description: The key to restoring arid and semi-arid ecosystems is maintaining soil water and organic carbon contents. Alfalfa (Medicago sativa L.) is a high-yield perennial forage crop and performs ecological functions as a drought-resistance leguminous herb. It has been widely planted for reconstruction of degraded soils in the Loess Plateau in northwestern China, but long-term planting may affect soil carbon–water coupling and lead to crop yield reduction. To maximize the benefits of reconstructed grassland, this study explored the couplings of soil water, organic carbon, and alfalfa productivity along a reconstruction chronosequence in a semi-arid area of the Loess Plateau. Space-for-time substitution approach was used to select different-aged stands of reconstructed grassland (1, 5, 7, 10, 15, 20, 30 years old). Alfalfa above-ground biomass (AGB), soil water storage (SWS), organic carbon storage (SOCS), and carbon–water coupling coordination degree (D) were measured in the 0–100 cm soil profile. Alfalfa AGB reached a peak in the 7th year, and the degradation began in the 10th year. Both SWS and SOCS varied nonlinearly with stand age. The greatest loss of SWS occurred in the 15th year (80–100 cm depth), whereas the largest increase of SOCS occurred in the 30th year (0–20 cm depth). There was a negative feedback relationship between AGB and SWS over the 30-year study period (Pearson r = −0.835, P = 0.098). AGB and SOCS initially showed a trade-off within the first 10 years (Pearson r = −0.7431, P = 0.2569), in contrast to their positive feedback in the 20–30th years (Pearson r = 0.9978, P = 0.0421). A decoupling between SWS and SOCS (D < 0.6) was observed after 12 years of alfalfa planting. For agricultural production, a greater supply of water and organic fertilizer is required from the 7th year of alfalfa planting, and reseeding may be needed around the 10th year to prolong the life of alfalfa community. Alfalfa should be planted for no more than 12 consecutive years in the…
format: application/pdf
format: text/html
creator: Yuanyuan Ma
creator: Xiaoping Zhou
creator: Yan Shen
creator: Hongbin Ma
creator: Bingzhe Fu
creator: Jian Lan
subject: Agricultural Science
subject: Ecology
subject: Plant Science
subject: Soil Science
description: doi:10.7717/peerj.18373
publisher: PeerJ Inc.
rights: © 2024 Ma et al.
abstract: The key to restoring arid and semi-arid ecosystems is maintaining soil water and organic carbon contents. Alfalfa (Medicago sativa L.) is a high-yield perennial forage crop and performs ecological functions as a drought-resistance leguminous herb. It has been widely planted for reconstruction of degraded soils in the Loess Plateau in northwestern China, but long-term planting may affect soil carbon–water coupling and lead to crop yield reduction. To maximize the benefits of reconstructed grassland, this study explored the couplings of soil water, organic carbon, and alfalfa productivity along a reconstruction chronosequence in a semi-arid area of the Loess Plateau. Space-for-time substitution approach was used to select different-aged stands of reconstructed grassland (1, 5, 7, 10, 15, 20, 30 years old). Alfalfa above-ground biomass (AGB), soil water storage (SWS), organic carbon storage (SOCS), and carbon–water coupling coordination degree (D) were measured in the 0–100 cm soil profile. Alfalfa AGB reached a peak in the 7th year, and the degradation began in the 10th year. Both SWS and SOCS varied nonlinearly with stand age. The greatest loss of SWS occurred in the 15th year (80–100 cm depth), whereas the largest increase of SOCS occurred in the 30th year (0–20 cm depth). There was a negative feedback relationship between AGB and SWS over the 30-year study period (Pearson r = −0.835, P = 0.098). AGB and SOCS initially showed a trade-off within the first 10 years (Pearson r = −0.7431, P = 0.2569), in contrast to their positive feedback in the 20–30th years (Pearson r = 0.9978, P = 0.0421). A decoupling between SWS and SOCS (D < 0.6) was observed after 12 years of alfalfa planting. For agricultural production, a greater supply of water and organic fertilizer is required from the 7th year of alfalfa planting, and reseeding may be needed around the 10th year to prolong the life of alfalfa community. Alfalfa should be planted for no more than 12 consecutive years in the…
bibliographic citation: Ma et al. (2024) Long-term alfalfa planting mediates the coupling of soil water and organic carbon storage in a semi-arid area of the Loess Plateau, China. PeerJ 12:e18373 https://doi.org/10.7717/peerj.18373
date submitted: 2024-08-20
date accepted: 2024-09-30
issued: 2024-11-05
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Ma
  given name: Yuanyuan
author list: Agent
  family name: Zhou
  given name: Xiaoping
author list: Agent
  family name: Shen
  given name: Yan
author list: Agent
  family name: Ma
  given name: Hongbin
author list: Agent
  family name: Fu
  given name: Bingzhe
author list: Agent
  family name: Lan
  given name: Jian
doi: 10.7717/peerj.18373
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-11-05
copyright: ©2024 Ma et al.
attribution name: Ma et al.

Citizen science enhances understanding of sea turtle distribution in the Gulf of California
type: item
type: AcademicArticle
description: Citizen science is a valuable tool for addressing spatial distribution gaps in endangered species, especially in data-limited regions. Given the logistical and financial challenges of studying migratory species, this cost-effective approach contributes to strategic conservation planning. The Bay of La Paz, located in Baja California Sur, México, is considered an ecologically important region within the larger Gulf of California. Due to its rich biodiversity and abundant natural resources, the region serves as a hub for ecotourism and fishing, affording diverse opportunities for community-based scientific initiatives. This paper examines the value of citizen science contributions from three diverse community groups (i.e., coastal residents, SCUBA divers, and artisanal fishers) to help scientists obtain information on sea turtle distribution in the Bay of La Paz. Our findings represent the first records of loggerhead turtles (Caretta caretta) in the bay based on ten citizen science reports that include live and dead turtles (either observed swimming, as bycatch, or stranded), providing new information on an endangered pelagic species identified in a coastal bay. Although the sample size is small, our diversity of sources and sighting types highlight the value of collaborative citizen science initiatives in complementing traditional research methods.
format: application/pdf
format: text/html
creator: Stephanie J. Rousso
creator: María Dinorah Herrero Perezrul
creator: Agnese Mancini
creator: Alan A. Zavala-Norzagaray
creator: Jesse F. Senko
subject: Biodiversity
subject: Conservation Biology
subject: Marine Biology
subject: Natural Resource Management
subject: Environmental Impacts
description: doi:10.7717/peerj.18203
publisher: PeerJ Inc.
rights: © 2024 Rousso et al.
abstract: Citizen science is a valuable tool for addressing spatial distribution gaps in endangered species, especially in data-limited regions. Given the logistical and financial challenges of studying migratory species, this cost-effective approach contributes to strategic conservation planning. The Bay of La Paz, located in Baja California Sur, México, is considered an ecologically important region within the larger Gulf of California. Due to its rich biodiversity and abundant natural resources, the region serves as a hub for ecotourism and fishing, affording diverse opportunities for community-based scientific initiatives. This paper examines the value of citizen science contributions from three diverse community groups (i.e., coastal residents, SCUBA divers, and artisanal fishers) to help scientists obtain information on sea turtle distribution in the Bay of La Paz. Our findings represent the first records of loggerhead turtles (Caretta caretta) in the bay based on ten citizen science reports that include live and dead turtles (either observed swimming, as bycatch, or stranded), providing new information on an endangered pelagic species identified in a coastal bay. Although the sample size is small, our diversity of sources and sighting types highlight the value of collaborative citizen science initiatives in complementing traditional research methods.
bibliographic citation: Rousso et al. (2024) Citizen science enhances understanding of sea turtle distribution in the Gulf of California. PeerJ 12:e18203 https://doi.org/10.7717/peerj.18203
date submitted: 2024-06-13
date accepted: 2024-09-09
issued: 2024-11-04
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Rousso
  given name: Stephanie J.
author list: Agent
  family name: Herrero Perezrul
  given name: María Dinorah
author list: Agent
  family name: Mancini
  given name: Agnese
author list: Agent
  family name: Zavala-Norzagaray
  given name: Alan A.
author list: Agent
  family name: Senko
  given name: Jesse F.
doi: 10.7717/peerj.18203
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-11-04
copyright: ©2024 Rousso et al.
attribution name: Rousso et al.

Effect of habitual physical activity on motor performance and prefrontal cortex activity during implicit motor learning
type: item
type: AcademicArticle
description: Background Acute bouts of exercise have been shown to improve motor learning. However, whether these benefits can be observed from habitual physical activity (PA) levels remains unclear and has important implications around PA guidelines to promote motor learning across the lifespan. This study investigated the effect of habitual PA levels on brain activity within the dorsolateral prefrontal cortex (DLPFC) during procedural motor skill acquisition. Methods Twenty-six right-handed healthy young adults had physical activity levels quantified by calculating the metabolic equivalent of task (METs) in minutes per week, derived from the International Physical Activity Questionnaire (IPAQ). Functional near-infrared spectroscopy (fNIRS) over the DLPFC was recorded to measure neural activation during a serial reaction time task (SRTT). Behavioural indicators of procedural motor skill acquisition were quantified as reaction time and accuracy of correct trials during the SRTT. DLPFC activation was characterised as task-related changes in oxyhaemoglobin (∆[HbO2]). Results Findings showed that higher PA levels were associated with improvements in reaction time during procedural motor skill acquisition (p = 0.03). However, no significant effects of PA levels on accuracy or ∆[HbO2] during procedural motor skill acquisition were observed. These findings show that while habitual PA may promote motor performance in young adults, this is not reflected by changes in the DLPFC area of the brain.
format: application/pdf
format: text/html
creator: Fu-Miao Tan
creator: Wei-Peng Teo
creator: Jessie Siew-Pin Leuk
creator: Alicia M. Goodwill
subject: Neuroscience
subject: Kinesiology
subject: Psychiatry and Psychology
description: doi:10.7717/peerj.18217
publisher: PeerJ Inc.
rights: © 2024 Tan et al.
abstract: Background Acute bouts of exercise have been shown to improve motor learning. However, whether these benefits can be observed from habitual physical activity (PA) levels remains unclear and has important implications around PA guidelines to promote motor learning across the lifespan. This study investigated the effect of habitual PA levels on brain activity within the dorsolateral prefrontal cortex (DLPFC) during procedural motor skill acquisition. Methods Twenty-six right-handed healthy young adults had physical activity levels quantified by calculating the metabolic equivalent of task (METs) in minutes per week, derived from the International Physical Activity Questionnaire (IPAQ). Functional near-infrared spectroscopy (fNIRS) over the DLPFC was recorded to measure neural activation during a serial reaction time task (SRTT). Behavioural indicators of procedural motor skill acquisition were quantified as reaction time and accuracy of correct trials during the SRTT. DLPFC activation was characterised as task-related changes in oxyhaemoglobin (∆[HbO2]). Results Findings showed that higher PA levels were associated with improvements in reaction time during procedural motor skill acquisition (p = 0.03). However, no significant effects of PA levels on accuracy or ∆[HbO2] during procedural motor skill acquisition were observed. These findings show that while habitual PA may promote motor performance in young adults, this is not reflected by changes in the DLPFC area of the brain.
bibliographic citation: Tan et al. (2024) Effect of habitual physical activity on motor performance and prefrontal cortex activity during implicit motor learning. PeerJ 12:e18217 https://doi.org/10.7717/peerj.18217
date submitted: 2024-05-23
date accepted: 2024-09-11
issued: 2024-11-04
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Tan
  given name: Fu-Miao
author list: Agent
  family name: Teo
  given name: Wei-Peng
author list: Agent
  family name: Leuk
  given name: Jessie Siew-Pin
author list: Agent
  family name: Goodwill
  given name: Alicia M.
doi: 10.7717/peerj.18217
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-11-04
copyright: © 2024 Tan et al.
attribution name: Tan et al.

Genomic complexity and clinical significance of the RCCX locus
type: item
type: AcademicArticle
description: Nearly identical, repetitive elements in the genome contribute to the variability in genetic inheritance patterns, particularly in regions like the RCCX locus, where such repeats can lead to structural variations. In addition, during the formation of gametes as a result of meiosis, variants of loci with repetitive elements that do not code for the required proteins may occur. As a result, an individual with certain genetic rearrangements in this region may have an increased risk of developing a congenital disorder, particularly in cases where the non-functional allele is inherited dominantly. At the same time, there is still no routine or generally recognized diagnostic method to determine the sequence of the repetitive fragments. The functionally important RCCX locus consists of such repetitive fragments. The available knowledge about the genomic variants of the RCCX locus is fragmented, as there is no standardized method to determine its structure. It should be noted that in some structural variants of the RCCX locus, the sequence of protein-coding genes is disrupted, leading to the development of diseases such as congenital adrenal hyperplasia (CAH). Although genetic testing is generally accepted as a gold standard for CAH diagnosis, there are a myriad of strategies on which exact methods to use and in which order. The reason for this inconsistency lies in the complexity of the RCCX locus and the fact that each patient or carrier may have a highly individualized mutation or combination thereof. In this review, we have discussed all known methods that can be used to study the structure of the RCCX locus. As a result, optimal approaches are proposed for the diagnosis of the most common disease caused by lesions in the RCCX–CAH due to CYP21A2 deficiency.
format: application/pdf
format: text/html
creator: Vladimir V. Shiryagin
creator: Andrey A. Devyatkin
creator: Oleg D. Fateev
creator: Ekaterina S. Petriaikina
creator: Viktor P. Bogdanov
creator: Zoia G. Antysheva
creator: Pavel Yu Volchkov
creator: Sergey M. Yudin
creator: Mary Woroncow
creator: Veronika I. Skvortsova
subject: Genetics
subject: Genomics
subject: Medical Genetics
description: doi:10.7717/peerj.18243
publisher: PeerJ Inc.
rights: © 2024 Shiryagin et al.
abstract: Nearly identical, repetitive elements in the genome contribute to the variability in genetic inheritance patterns, particularly in regions like the RCCX locus, where such repeats can lead to structural variations. In addition, during the formation of gametes as a result of meiosis, variants of loci with repetitive elements that do not code for the required proteins may occur. As a result, an individual with certain genetic rearrangements in this region may have an increased risk of developing a congenital disorder, particularly in cases where the non-functional allele is inherited dominantly. At the same time, there is still no routine or generally recognized diagnostic method to determine the sequence of the repetitive fragments. The functionally important RCCX locus consists of such repetitive fragments. The available knowledge about the genomic variants of the RCCX locus is fragmented, as there is no standardized method to determine its structure. It should be noted that in some structural variants of the RCCX locus, the sequence of protein-coding genes is disrupted, leading to the development of diseases such as congenital adrenal hyperplasia (CAH). Although genetic testing is generally accepted as a gold standard for CAH diagnosis, there are a myriad of strategies on which exact methods to use and in which order. The reason for this inconsistency lies in the complexity of the RCCX locus and the fact that each patient or carrier may have a highly individualized mutation or combination thereof. In this review, we have discussed all known methods that can be used to study the structure of the RCCX locus. As a result, optimal approaches are proposed for the diagnosis of the most common disease caused by lesions in the RCCX–CAH due to CYP21A2 deficiency.
bibliographic citation: Shiryagin et al. (2024) Genomic complexity and clinical significance of the RCCX locus. PeerJ 12:e18243 https://doi.org/10.7717/peerj.18243
date submitted: 2024-05-28
date accepted: 2024-09-15
issued: 2024-11-04
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Shiryagin
  given name: Vladimir V.
author list: Agent
  family name: Devyatkin
  given name: Andrey A.
author list: Agent
  family name: Fateev
  given name: Oleg D.
author list: Agent
  family name: Petriaikina
  given name: Ekaterina S.
author list: Agent
  family name: Bogdanov
  given name: Viktor P.
author list: Agent
  family name: Antysheva
  given name: Zoia G.
author list: Agent
  family name: Volchkov
  given name: Pavel Yu
author list: Agent
  family name: Yudin
  given name: Sergey M.
author list: Agent
  family name: Woroncow
  given name: Mary
author list: Agent
  family name: Skvortsova
  given name: Veronika I.
doi: 10.7717/peerj.18243
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-11-04
copyright: ©2024 Shiryagin et al.
attribution name: Shiryagin et al.

Dietary reference intake for military operations: a scoping review
type: item
type: AcademicArticle
description: Background Reports that collect and organize dietary reference intake (DRI) data for military operations in different countries and regions worldwide are limited.This scoping review aimed to collect and organize information on the status of formulating a DRI for military operations in each country. Methodology For the information search, we queried PubMed and Google for literature and reports on the DRI for military operations and summarized the content of the adopted literature and reports. Results The content and rationale for DRI for military operations in Australia, the United Kingdom (UK), the United States of America (USA), and the North Atlantic Treaty Organization (NATO) can be summarized as follows: (1) Energy requirements: Four reports formulated physical activity levels (PALs) and corresponding energy requirements that differed from those for the civilian public. The PAL range for the military was set as high as 1.50–3.20, as opposed to the standard civilian upper PAL set at 1.20–2.20. (2) Protein: Three military reports outside of the UK had different standards than those for the civilian public with an increased intake in accordance with the high PAL while simultaneously preventing excessive intake.In the military, values were formulated 1.2–4.8 times higher than the standards for civilians (45–65 g/day to 55–307 g/day). (3) Macronutrient energy distribution: Four military reports established macronutrient energy distributions that differed from those for the civilian public. The DRI for the Australian and UK militaries was formulated such that as PAL increased, protein decreased, fat decreased or remained unchanged, and carbohydrate increased. (4) Sodium: Considering that military personnel sweat more due to high physical activity and their environment, two Australian and NATO reports were established with sodium levels that were twice as high as that of the civilian public (460–2,300 mg/day to 920–3,200 mg/day). Increasing sodium intake to <4,800 mg/d…
format: application/pdf
format: text/html
creator: Ryoko Mizushima
creator: Motohiko Miyachi
creator: Eiichi Yoshimura
creator: Yoichi Hatamoto
creator: Mai Matsumoto
creator: Yuka Hamada
creator: Mana Hatanaka
creator: Aya Maeno
creator: Chifumi Shimomura
creator: Hidemi Takimoto
subject: Nutrition
subject: Public Health
description: doi:10.7717/peerj.18353
publisher: PeerJ Inc.
rights: © 2024 Mizushima et al.
abstract: Background Reports that collect and organize dietary reference intake (DRI) data for military operations in different countries and regions worldwide are limited.This scoping review aimed to collect and organize information on the status of formulating a DRI for military operations in each country. Methodology For the information search, we queried PubMed and Google for literature and reports on the DRI for military operations and summarized the content of the adopted literature and reports. Results The content and rationale for DRI for military operations in Australia, the United Kingdom (UK), the United States of America (USA), and the North Atlantic Treaty Organization (NATO) can be summarized as follows: (1) Energy requirements: Four reports formulated physical activity levels (PALs) and corresponding energy requirements that differed from those for the civilian public. The PAL range for the military was set as high as 1.50–3.20, as opposed to the standard civilian upper PAL set at 1.20–2.20. (2) Protein: Three military reports outside of the UK had different standards than those for the civilian public with an increased intake in accordance with the high PAL while simultaneously preventing excessive intake.In the military, values were formulated 1.2–4.8 times higher than the standards for civilians (45–65 g/day to 55–307 g/day). (3) Macronutrient energy distribution: Four military reports established macronutrient energy distributions that differed from those for the civilian public. The DRI for the Australian and UK militaries was formulated such that as PAL increased, protein decreased, fat decreased or remained unchanged, and carbohydrate increased. (4) Sodium: Considering that military personnel sweat more due to high physical activity and their environment, two Australian and NATO reports were established with sodium levels that were twice as high as that of the civilian public (460–2,300 mg/day to 920–3,200 mg/day). Increasing sodium intake to <4,800 mg/d…
bibliographic citation: Mizushima et al. (2024) Dietary reference intake for military operations: a scoping review. PeerJ 12:e18353 https://doi.org/10.7717/peerj.18353
date submitted: 2024-03-08
date accepted: 2024-09-27
issued: 2024-11-04
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Mizushima
  given name: Ryoko
author list: Agent
  family name: Miyachi
  given name: Motohiko
author list: Agent
  family name: Yoshimura
  given name: Eiichi
author list: Agent
  family name: Hatamoto
  given name: Yoichi
author list: Agent
  family name: Matsumoto
  given name: Mai
author list: Agent
  family name: Hamada
  given name: Yuka
author list: Agent
  family name: Hatanaka
  given name: Mana
author list: Agent
  family name: Maeno
  given name: Aya
author list: Agent
  family name: Shimomura
  given name: Chifumi
author list: Agent
  family name: Takimoto
  given name: Hidemi
doi: 10.7717/peerj.18353
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-11-04
copyright: ©2024 Mizushima et al.
attribution name: Mizushima et al.

Common laboratory results-based artificial intelligence analysis achieves accurate classification of plasma cell dyscrasias
type: item
type: AcademicArticle
description: Background Plasma cell dyscrasias encompass a diverse set of disorders, where early and precise diagnosis is essential for optimizing patient outcomes. Despite advancements, current diagnostic methodologies remain underutilized in applying artificial intelligence (AI) to routine laboratory data. This study seeks to construct an AI-driven model leveraging standard laboratory parameters to enhance diagnostic accuracy and classification efficiency in plasma cell dyscrasias. Methods Data from 1,188 participants (609 with plasma cell dyscrasias and 579 controls) collected between 2018 and 2023 were analyzed. Initial variable selection employed Kruskal-Wallis and Wilcoxon tests, followed by dimensionality reduction and variable prioritization using the Shapley Additive Explanations (SHAP) approach. Nine pivotal variables were identified, including hemoglobin (HGB), serum creatinine, and β2-microglobulin. Utilizing these, four machine learning models (gradient boosting decision tree (GBDT), support vector machine (SVM), deep neural network (DNN), and decision tree (DT) were developed and evaluated, with performance metrics such as accuracy, recall, and area under the curve (AUC) assessed through 5-fold cross-validation. A subtype classification model was also developed, analyzing data from 380 cases to classify disorders such as multiple myeloma (MM) and monoclonal gammopathy of undetermined significance (MGUS). Results 1. Variable selection: The SHAP method pinpointed nine critical variables, including hemoglobin (HGB), serum creatinine, erythrocyte sedimentation rate (ESR), and β2-microglobulin. 2. Diagnostic model performance: The GBDT model exhibited superior diagnostic performance for plasma cell dyscrasias, achieving 93.5% accuracy, 98.1% recall, and an AUC of 0.987. External validation reinforced its robustness, with 100% accuracy and an F1 score of 98.5%. 3. Subtype Classification: The DNN model excelled in classifying multiple myeloma, MGUS, and light-chain myelom…
format: application/pdf
format: text/html
creator: Bihua Yao
creator: Yicheng Liu
creator: Yuwei Wu
creator: Siyu Mao
creator: Hangbiao Zhang
creator: Lei Jiang
creator: Cheng Fei
creator: Shuang Wang
creator: Jijun Tong
creator: Jianguo Wu
subject: Computational Biology
subject: Hematology
subject: Oncology
subject: Computational Science
subject: Data Mining and Machine Learning
description: doi:10.7717/peerj.18391
publisher: PeerJ Inc.
rights: © 2024 Yao et al.
abstract: Background Plasma cell dyscrasias encompass a diverse set of disorders, where early and precise diagnosis is essential for optimizing patient outcomes. Despite advancements, current diagnostic methodologies remain underutilized in applying artificial intelligence (AI) to routine laboratory data. This study seeks to construct an AI-driven model leveraging standard laboratory parameters to enhance diagnostic accuracy and classification efficiency in plasma cell dyscrasias. Methods Data from 1,188 participants (609 with plasma cell dyscrasias and 579 controls) collected between 2018 and 2023 were analyzed. Initial variable selection employed Kruskal-Wallis and Wilcoxon tests, followed by dimensionality reduction and variable prioritization using the Shapley Additive Explanations (SHAP) approach. Nine pivotal variables were identified, including hemoglobin (HGB), serum creatinine, and β2-microglobulin. Utilizing these, four machine learning models (gradient boosting decision tree (GBDT), support vector machine (SVM), deep neural network (DNN), and decision tree (DT) were developed and evaluated, with performance metrics such as accuracy, recall, and area under the curve (AUC) assessed through 5-fold cross-validation. A subtype classification model was also developed, analyzing data from 380 cases to classify disorders such as multiple myeloma (MM) and monoclonal gammopathy of undetermined significance (MGUS). Results 1. Variable selection: The SHAP method pinpointed nine critical variables, including hemoglobin (HGB), serum creatinine, erythrocyte sedimentation rate (ESR), and β2-microglobulin. 2. Diagnostic model performance: The GBDT model exhibited superior diagnostic performance for plasma cell dyscrasias, achieving 93.5% accuracy, 98.1% recall, and an AUC of 0.987. External validation reinforced its robustness, with 100% accuracy and an F1 score of 98.5%. 3. Subtype Classification: The DNN model excelled in classifying multiple myeloma, MGUS, and light-chain myelom…
bibliographic citation: Yao et al. (2024) Common laboratory results-based artificial intelligence analysis achieves accurate classification of plasma cell dyscrasias. PeerJ 12:e18391 https://doi.org/10.7717/peerj.18391
date submitted: 2024-05-07
date accepted: 2024-10-02
issued: 2024-11-04
is part of: PeerJ
license: https://creativecommons.org/licenses/by-nc/4.0
author list: Agent
  family name: Yao
  given name: Bihua
author list: Agent
  family name: Liu
  given name: Yicheng
author list: Agent
  family name: Wu
  given name: Yuwei
author list: Agent
  family name: Mao
  given name: Siyu
author list: Agent
  family name: Zhang
  given name: Hangbiao
author list: Agent
  family name: Jiang
  given name: Lei
author list: Agent
  family name: Fei
  given name: Cheng
author list: Agent
  family name: Wang
  given name: Shuang
author list: Agent
  family name: Tong
  given name: Jijun
author list: Agent
  family name: Wu
  given name: Jianguo
doi: 10.7717/peerj.18391
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-11-04
copyright: © 2024 Yao et al.
attribution name: Yao et al.

Application of composite reference intervals in the diagnosis of subclinical hypothyroidism in the elderly: a retrospective study
type: item
type: AcademicArticle
description: Background Thyroid stimulating hormone releasing hormone (TSH) is a key indicator for diagnosing subclinical hypothyroidism (SCH). We evaluated factors affecting TSH levels in elderly SCH, establishing a composite reference interval, and comparing it with traditional one in diagnosis. Methods We collected data on patients aged ≥60 undergoing physical examinations in Chengdu, screening the influencing factors associated with TSH. Then, a two-dimensional composite reference interval was established for TSH and FT4, and the differences between the new and traditional diagnosing methods were compared. Results The incidence of subclinical thyroid dysfunction was about 14%, with SCH accounting for 97%. Regression analysis found that TSH levels increase as FT4 and uric acid levels decrease. Compared with the two-dimensional composite reference interval, the traditional one has a higher incidence rate of SCH. Conclusion Compared with the two-dimensional composite reference interval, the traditional one is more likely to overestimate the incidence rate of SCH, leading to excessive diagnosis and treatment.
format: application/pdf
format: text/html
creator: Peijuan Li
creator: Wenming Yang
creator: Guohua Tang
creator: Zhipeng Li
subject: Diabetes and Endocrinology
subject: Internal Medicine
description: doi:10.7717/peerj.18417
publisher: PeerJ Inc.
rights: © 2024 Li et al.
abstract: Background Thyroid stimulating hormone releasing hormone (TSH) is a key indicator for diagnosing subclinical hypothyroidism (SCH). We evaluated factors affecting TSH levels in elderly SCH, establishing a composite reference interval, and comparing it with traditional one in diagnosis. Methods We collected data on patients aged ≥60 undergoing physical examinations in Chengdu, screening the influencing factors associated with TSH. Then, a two-dimensional composite reference interval was established for TSH and FT4, and the differences between the new and traditional diagnosing methods were compared. Results The incidence of subclinical thyroid dysfunction was about 14%, with SCH accounting for 97%. Regression analysis found that TSH levels increase as FT4 and uric acid levels decrease. Compared with the two-dimensional composite reference interval, the traditional one has a higher incidence rate of SCH. Conclusion Compared with the two-dimensional composite reference interval, the traditional one is more likely to overestimate the incidence rate of SCH, leading to excessive diagnosis and treatment.
bibliographic citation: Li et al. (2024) Application of composite reference intervals in the diagnosis of subclinical hypothyroidism in the elderly: a retrospective study. PeerJ 12:e18417 https://doi.org/10.7717/peerj.18417
date submitted: 2024-05-19
date accepted: 2024-10-07
issued: 2024-11-01
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Li
  given name: Peijuan
author list: Agent
  family name: Yang
  given name: Wenming
author list: Agent
  family name: Tang
  given name: Guohua
author list: Agent
  family name: Li
  given name: Zhipeng
doi: 10.7717/peerj.18417
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-11-01
copyright: ©2024 Li et al.
attribution name: Li et al.

Quality improvement bundles to decrease hypothermia in very low/extremely low birth weight infants at birth: a systematic review and meta-analysis
type: item
type: AcademicArticle
description: Background Numerous studies have demonstrated that hypothermia in preterm infants correlates with increased morbidity and mortality, especially among those with very low or extremely low birth weights (VLBW/ELBW). An increasing number of healthcare facilities are implementing quality improvement (QI) bundles to lower the incidence of hypothermia at birth in this vulnerable population. However, the effectiveness and safety of these interventions have yet to be fully assessed. A meta-analysis is necessary to evaluate the efficacy and safety of QI bundles in reducing hypothermia at birth among VLBW/ELBW infants. Methods We searched PubMed, Embase, the Cochrane Library and Web of Science through April 22nd, 2024. Study selection, data extraction, quality evaluation and risk bias assessment were performed independently by two investigators. Meta-analysis was performed using Review Manager 5.4.1. Results A total of 18 studies were included for qualitative analysis and 12 for meta-analysis. For VLBW infants, meta-analysis revealed a reduction in hypothermia and an increase in hyperthermia following the introduction of QI bundles (mild hypothermia, OR 0.22, 95% CI [0.13–0.37]; moderate hypothermia, OR 0.18, 95% CI [0.15–0.22]; hyperthermia, OR 2.79, 95% CI [1.53–5.09]). For ELBW infants, meta-analysis showed a decrease in hypothermia but no increase in hyperthermia after implementing QI bundles (mild hypothermia, OR 0.46, 95% CI [0.26–0.81]; moderate hypothermia, OR 0.21, 95% CI [0.08–0.58]; hyperthermia, OR 1.10, 95% CI [0.22–5.43]). Conclusion QI bundles effectively reduce hypothermia in VLBW/ELBW infants, but they may also increase hyperthermia, especially in VLBW infants.
format: application/pdf
format: text/html
creator: Guichao Zhong
creator: Jie Qi
creator: Lijuan Sheng
creator: Jing Zhuang
creator: Zhangbin Yu
creator: Benqing Wu
subject: Nursing
subject: Pediatrics
description: doi:10.7717/peerj.18425
publisher: PeerJ Inc.
rights: © 2024 Zhong et al.
abstract: Background Numerous studies have demonstrated that hypothermia in preterm infants correlates with increased morbidity and mortality, especially among those with very low or extremely low birth weights (VLBW/ELBW). An increasing number of healthcare facilities are implementing quality improvement (QI) bundles to lower the incidence of hypothermia at birth in this vulnerable population. However, the effectiveness and safety of these interventions have yet to be fully assessed. A meta-analysis is necessary to evaluate the efficacy and safety of QI bundles in reducing hypothermia at birth among VLBW/ELBW infants. Methods We searched PubMed, Embase, the Cochrane Library and Web of Science through April 22nd, 2024. Study selection, data extraction, quality evaluation and risk bias assessment were performed independently by two investigators. Meta-analysis was performed using Review Manager 5.4.1. Results A total of 18 studies were included for qualitative analysis and 12 for meta-analysis. For VLBW infants, meta-analysis revealed a reduction in hypothermia and an increase in hyperthermia following the introduction of QI bundles (mild hypothermia, OR 0.22, 95% CI [0.13–0.37]; moderate hypothermia, OR 0.18, 95% CI [0.15–0.22]; hyperthermia, OR 2.79, 95% CI [1.53–5.09]). For ELBW infants, meta-analysis showed a decrease in hypothermia but no increase in hyperthermia after implementing QI bundles (mild hypothermia, OR 0.46, 95% CI [0.26–0.81]; moderate hypothermia, OR 0.21, 95% CI [0.08–0.58]; hyperthermia, OR 1.10, 95% CI [0.22–5.43]). Conclusion QI bundles effectively reduce hypothermia in VLBW/ELBW infants, but they may also increase hyperthermia, especially in VLBW infants.
bibliographic citation: Zhong et al. (2024) Quality improvement bundles to decrease hypothermia in very low/extremely low birth weight infants at birth: a systematic review and meta-analysis. PeerJ 12:e18425 https://doi.org/10.7717/peerj.18425
date submitted: 2024-06-17
date accepted: 2024-10-08
issued: 2024-11-01
is part of: PeerJ
license: https://creativecommons.org/licenses/by/4.0/
author list: Agent
  family name: Zhong
  given name: Guichao
author list: Agent
  family name: Qi
  given name: Jie
author list: Agent
  family name: Sheng
  given name: Lijuan
author list: Agent
  family name: Zhuang
  given name: Jing
author list: Agent
  family name: Yu
  given name: Zhangbin
author list: Agent
  family name: Wu
  given name: Benqing
doi: 10.7717/peerj.18425
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-11-01
copyright: © 2024 Zhong et al.
attribution name: Zhong et al.

Applying stacking ensemble method to predict chronic kidney disease progression in Chinese population based on laboratory information system: a retrospective study
type: item
type: AcademicArticle
description: Background and Objective Chronic kidney disease (CKD) is a major public health issue, and accurate prediction of the progression of kidney failure is critical for clinical decision-making and helps improve patient outcomes. As such, we aimed to develop and externally validate a machine-learned model to predict the progression of CKD using common laboratory variables, demographic characteristics, and an electronic health records database. Methods We developed a predictive model using longitudinal clinical data from a single center for Chinese CKD patients. The cohort included 987 patients who were followed up for more than 24 months. Fifty-three laboratory features were considered for inclusion in the model. The primary outcome in our study was an estimated glomerular filtration rate ≤15 mL/min/1.73 m2 or kidney failure. Machine learning algorithms were applied to the modeling dataset (n = 296), and an external dataset (n = 71) was used for model validation. We assessed model discrimination via area under the curve (AUC) values, accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score. Results Over a median follow-up period of 3.75 years, 148 patients experienced kidney failure. The optimal model was based on stacking different classifier algorithms with six laboratory features, including 24-h urine protein, potassium, glucose, urea, prealbumin and total protein. The model had considerable predictive power, with AUC values of 0.896 and 0.771 in the validation and external datasets, respectively. This model also accurately predicted the progression of renal function in patients over different follow-up periods after their initial assessment. Conclusions A prediction model that leverages routinely collected laboratory features in the Chinese population can accurately identify patients with CKD at high risk of progressing to kidney failure. An online version of the model can be easily and quickly applied in clinical manageme…
format: application/pdf
format: text/html
creator: Jialin Du
creator: Jie Gao
creator: Jie Guan
creator: Bo Jin
creator: Nan Duan
creator: Lu Pang
creator: Haiming Huang
creator: Qian Ma
creator: Chenwei Huang
creator: Haixia Li
subject: Evidence Based Medicine
subject: Nephrology
subject: Data Mining and Machine Learning
subject: Data Science
description: doi:10.7717/peerj.18436
publisher: PeerJ Inc.
rights: © 2024 Du et al.
abstract: Background and Objective Chronic kidney disease (CKD) is a major public health issue, and accurate prediction of the progression of kidney failure is critical for clinical decision-making and helps improve patient outcomes. As such, we aimed to develop and externally validate a machine-learned model to predict the progression of CKD using common laboratory variables, demographic characteristics, and an electronic health records database. Methods We developed a predictive model using longitudinal clinical data from a single center for Chinese CKD patients. The cohort included 987 patients who were followed up for more than 24 months. Fifty-three laboratory features were considered for inclusion in the model. The primary outcome in our study was an estimated glomerular filtration rate ≤15 mL/min/1.73 m2 or kidney failure. Machine learning algorithms were applied to the modeling dataset (n = 296), and an external dataset (n = 71) was used for model validation. We assessed model discrimination via area under the curve (AUC) values, accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score. Results Over a median follow-up period of 3.75 years, 148 patients experienced kidney failure. The optimal model was based on stacking different classifier algorithms with six laboratory features, including 24-h urine protein, potassium, glucose, urea, prealbumin and total protein. The model had considerable predictive power, with AUC values of 0.896 and 0.771 in the validation and external datasets, respectively. This model also accurately predicted the progression of renal function in patients over different follow-up periods after their initial assessment. Conclusions A prediction model that leverages routinely collected laboratory features in the Chinese population can accurately identify patients with CKD at high risk of progressing to kidney failure. An online version of the model can be easily and quickly applied in clinical manageme…
bibliographic citation: Du et al. (2024) Applying stacking ensemble method to predict chronic kidney disease progression in Chinese population based on laboratory information system: a retrospective study. PeerJ 12:e18436 https://doi.org/10.7717/peerj.18436
date submitted: 2024-07-26
date accepted: 2024-10-10
issued: 2024-11-01
is part of: PeerJ
license: https://creativecommons.org/licenses/by-nc/4.0
author list: Agent
  family name: Du
  given name: Jialin
author list: Agent
  family name: Gao
  given name: Jie
author list: Agent
  family name: Guan
  given name: Jie
author list: Agent
  family name: Jin
  given name: Bo
author list: Agent
  family name: Duan
  given name: Nan
author list: Agent
  family name: Pang
  given name: Lu
author list: Agent
  family name: Huang
  given name: Haiming
author list: Agent
  family name: Ma
  given name: Qian
author list: Agent
  family name: Huang
  given name: Chenwei
author list: Agent
  family name: Li
  given name: Haixia
doi: 10.7717/peerj.18436
volume: 12
issn: 2167-8359
publication name: PeerJ
publication date: 2024-11-01
copyright: © 2024 Du et al.
attribution name: Du et al.

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