Abnormal erythrocyte-related parameters in children with Pb, Cr, Cu and Zn exposure

The link between exposure to a particular heavy metal or metalloid and the development of anemia is well established. However, the association between combined exposure to multiple heavy metal(loid)s and anemia in children is still lacking in evidence. In this study, a total of 266 children aged 3 t...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Biometals 2024-12, Vol.37 (6), p.1537-1549
Hauptverfasser: Zhang, Zhuxia, Xie, Bo, Zhong, Qi, Dai, Chenxu, Xu, Xijin, Huo, Xia
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1549
container_issue 6
container_start_page 1537
container_title Biometals
container_volume 37
creator Zhang, Zhuxia
Xie, Bo
Zhong, Qi
Dai, Chenxu
Xu, Xijin
Huo, Xia
description The link between exposure to a particular heavy metal or metalloid and the development of anemia is well established. However, the association between combined exposure to multiple heavy metal(loid)s and anemia in children is still lacking in evidence. In this study, a total of 266 children aged 3 to 7 were recruited from Guiyu, China. Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure blood heavy metal(loid) concentrations. Blood cell count, hemoglobin (HGB), mean corpuscular hemoglobin (MCH), mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), hematocrit (HCT), and red blood cell distribution width (RDW) were measured by an automated hematology analyzer. Erythrocyte-related parameters were negatively correlated with the Cu and Cu/Zn ratios and positively correlated with Cr, Ni, Zn, and Se by Spearman correlation analysis. Only blood Cu level was negatively correlated with HGB [β = −2.74, (95% Cl: −4.49, −0.995)], MCH [β = −0.505, (95% Cl: −0.785, −0.226)], MCV [β = −1.024, (95% Cl: −1.767, −0.281)], and MCHC [β = −2.137, (95% Cl: −3.54, −0.734)] by multiple linear regression analysis. The Bayesian Kernel Machine Regression (BKMR) model analysis indicated a negative correlation between the combined exposure to Cu, Zn, Pb, and Cr and MCH and MCV. The single-factor analysis showed a considerable statistical difference only with Cu on MCV, MCH, and HGB. Furthermore, the interaction analysis highlighted the interdependent effects of Cu and Zn, Pb and Zn, and Cr and Zn on MCH and MCV levels. Additionally, the oxidation and/or antioxidation reactions may play a significant role in the development of metal(loid)-induced anemia risk. It is crucial to investigate the effects of co-exposure to multiple heavy metal(loid) elements on anemia, especially the interrelationships and mechanisms among them.
doi_str_mv 10.1007/s10534-024-00624-y
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_3094046186</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3094046186</sourcerecordid><originalsourceid>FETCH-LOGICAL-c256t-32c13b94cee87b45ba4833dbc909ee4128e16e119f2da78e7eedb981a93f56fe3</originalsourceid><addsrcrecordid>eNp9kE1v1DAQhi1ERbeFP8ABWeLCgZSZ2PHHcbUqFGmlVipcuFhOMmFT5WOxE9H8-xpSQOLQw8wc_Mw71sPYa4QLBNAfIkIhZAZ5KlCpL8_YBgudZ0Zr8ZxtwCqVgZHylJ3FeAcAVoN6wU6FxUIiqg273ZbDGHrfcQrLdAhjtUyUBer8RDU_-uB7mihE3g68OrRdHWjgP9vpwG_K93wXUs3cDzX_NnC6P45xDvSSnTS-i_TqcZ6zrx8vv-yusv31p8-77T6r8kJNmcgrFKWVFZHRpSxKL40QdVlZsEQSc0OoCNE2ee21IU1Ul9agt6IpVEPinL1bc49h_DFTnFzfxoq6zg80ztEJsBKkQqMS-vY_9G6cw5B-5wRK0IXJBSYqX6kqjDEGatwxtL0Pi0Nwv5S7VblLyt1v5W5JS28eo-eyp_rvyh_HCRArENPT8J3Cv9tPxD4ANPiL4g</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3140758231</pqid></control><display><type>article</type><title>Abnormal erythrocyte-related parameters in children with Pb, Cr, Cu and Zn exposure</title><source>MEDLINE</source><source>Springer Nature - Complete Springer Journals</source><creator>Zhang, Zhuxia ; Xie, Bo ; Zhong, Qi ; Dai, Chenxu ; Xu, Xijin ; Huo, Xia</creator><creatorcontrib>Zhang, Zhuxia ; Xie, Bo ; Zhong, Qi ; Dai, Chenxu ; Xu, Xijin ; Huo, Xia</creatorcontrib><description>The link between exposure to a particular heavy metal or metalloid and the development of anemia is well established. However, the association between combined exposure to multiple heavy metal(loid)s and anemia in children is still lacking in evidence. In this study, a total of 266 children aged 3 to 7 were recruited from Guiyu, China. Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure blood heavy metal(loid) concentrations. Blood cell count, hemoglobin (HGB), mean corpuscular hemoglobin (MCH), mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), hematocrit (HCT), and red blood cell distribution width (RDW) were measured by an automated hematology analyzer. Erythrocyte-related parameters were negatively correlated with the Cu and Cu/Zn ratios and positively correlated with Cr, Ni, Zn, and Se by Spearman correlation analysis. Only blood Cu level was negatively correlated with HGB [β = −2.74, (95% Cl: −4.49, −0.995)], MCH [β = −0.505, (95% Cl: −0.785, −0.226)], MCV [β = −1.024, (95% Cl: −1.767, −0.281)], and MCHC [β = −2.137, (95% Cl: −3.54, −0.734)] by multiple linear regression analysis. The Bayesian Kernel Machine Regression (BKMR) model analysis indicated a negative correlation between the combined exposure to Cu, Zn, Pb, and Cr and MCH and MCV. The single-factor analysis showed a considerable statistical difference only with Cu on MCV, MCH, and HGB. Furthermore, the interaction analysis highlighted the interdependent effects of Cu and Zn, Pb and Zn, and Cr and Zn on MCH and MCV levels. Additionally, the oxidation and/or antioxidation reactions may play a significant role in the development of metal(loid)-induced anemia risk. It is crucial to investigate the effects of co-exposure to multiple heavy metal(loid) elements on anemia, especially the interrelationships and mechanisms among them.</description><identifier>ISSN: 0966-0844</identifier><identifier>ISSN: 1572-8773</identifier><identifier>EISSN: 1572-8773</identifier><identifier>DOI: 10.1007/s10534-024-00624-y</identifier><identifier>PMID: 39154116</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Anemia ; Bayesian analysis ; Biochemistry ; Biomedical and Life Sciences ; Blood ; Blood levels ; Cell Biology ; Child ; Child, Preschool ; Children ; Chromium ; Chromium - blood ; Copper ; Copper - blood ; Correlation analysis ; Erythrocyte Indices ; Erythrocytes ; Erythrocytes, Abnormal - pathology ; Exposure ; Factor analysis ; Female ; Heavy metals ; Hematocrit ; Hematology ; Hemoglobin ; Humans ; Inductively coupled plasma mass spectrometry ; Lead ; Lead - blood ; Life Sciences ; Male ; Mass spectrometry ; Mass spectroscopy ; Medicine/Public Health ; Metal concentrations ; Metals, Heavy - blood ; Microbiology ; Oxidation ; Parameters ; Pharmacology/Toxicology ; Plant Physiology ; Regression analysis ; Regression models ; Statistical analysis ; Zinc ; Zinc - blood</subject><ispartof>Biometals, 2024-12, Vol.37 (6), p.1537-1549</ispartof><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2024 Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2024. The Author(s), under exclusive licence to Springer Nature B.V.</rights><rights>Copyright Springer Nature B.V. Dec 2024</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c256t-32c13b94cee87b45ba4833dbc909ee4128e16e119f2da78e7eedb981a93f56fe3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10534-024-00624-y$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10534-024-00624-y$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39154116$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhang, Zhuxia</creatorcontrib><creatorcontrib>Xie, Bo</creatorcontrib><creatorcontrib>Zhong, Qi</creatorcontrib><creatorcontrib>Dai, Chenxu</creatorcontrib><creatorcontrib>Xu, Xijin</creatorcontrib><creatorcontrib>Huo, Xia</creatorcontrib><title>Abnormal erythrocyte-related parameters in children with Pb, Cr, Cu and Zn exposure</title><title>Biometals</title><addtitle>Biometals</addtitle><addtitle>Biometals</addtitle><description>The link between exposure to a particular heavy metal or metalloid and the development of anemia is well established. However, the association between combined exposure to multiple heavy metal(loid)s and anemia in children is still lacking in evidence. In this study, a total of 266 children aged 3 to 7 were recruited from Guiyu, China. Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure blood heavy metal(loid) concentrations. Blood cell count, hemoglobin (HGB), mean corpuscular hemoglobin (MCH), mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), hematocrit (HCT), and red blood cell distribution width (RDW) were measured by an automated hematology analyzer. Erythrocyte-related parameters were negatively correlated with the Cu and Cu/Zn ratios and positively correlated with Cr, Ni, Zn, and Se by Spearman correlation analysis. Only blood Cu level was negatively correlated with HGB [β = −2.74, (95% Cl: −4.49, −0.995)], MCH [β = −0.505, (95% Cl: −0.785, −0.226)], MCV [β = −1.024, (95% Cl: −1.767, −0.281)], and MCHC [β = −2.137, (95% Cl: −3.54, −0.734)] by multiple linear regression analysis. The Bayesian Kernel Machine Regression (BKMR) model analysis indicated a negative correlation between the combined exposure to Cu, Zn, Pb, and Cr and MCH and MCV. The single-factor analysis showed a considerable statistical difference only with Cu on MCV, MCH, and HGB. Furthermore, the interaction analysis highlighted the interdependent effects of Cu and Zn, Pb and Zn, and Cr and Zn on MCH and MCV levels. Additionally, the oxidation and/or antioxidation reactions may play a significant role in the development of metal(loid)-induced anemia risk. It is crucial to investigate the effects of co-exposure to multiple heavy metal(loid) elements on anemia, especially the interrelationships and mechanisms among them.</description><subject>Anemia</subject><subject>Bayesian analysis</subject><subject>Biochemistry</subject><subject>Biomedical and Life Sciences</subject><subject>Blood</subject><subject>Blood levels</subject><subject>Cell Biology</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Children</subject><subject>Chromium</subject><subject>Chromium - blood</subject><subject>Copper</subject><subject>Copper - blood</subject><subject>Correlation analysis</subject><subject>Erythrocyte Indices</subject><subject>Erythrocytes</subject><subject>Erythrocytes, Abnormal - pathology</subject><subject>Exposure</subject><subject>Factor analysis</subject><subject>Female</subject><subject>Heavy metals</subject><subject>Hematocrit</subject><subject>Hematology</subject><subject>Hemoglobin</subject><subject>Humans</subject><subject>Inductively coupled plasma mass spectrometry</subject><subject>Lead</subject><subject>Lead - blood</subject><subject>Life Sciences</subject><subject>Male</subject><subject>Mass spectrometry</subject><subject>Mass spectroscopy</subject><subject>Medicine/Public Health</subject><subject>Metal concentrations</subject><subject>Metals, Heavy - blood</subject><subject>Microbiology</subject><subject>Oxidation</subject><subject>Parameters</subject><subject>Pharmacology/Toxicology</subject><subject>Plant Physiology</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Statistical analysis</subject><subject>Zinc</subject><subject>Zinc - blood</subject><issn>0966-0844</issn><issn>1572-8773</issn><issn>1572-8773</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kE1v1DAQhi1ERbeFP8ABWeLCgZSZ2PHHcbUqFGmlVipcuFhOMmFT5WOxE9H8-xpSQOLQw8wc_Mw71sPYa4QLBNAfIkIhZAZ5KlCpL8_YBgudZ0Zr8ZxtwCqVgZHylJ3FeAcAVoN6wU6FxUIiqg273ZbDGHrfcQrLdAhjtUyUBer8RDU_-uB7mihE3g68OrRdHWjgP9vpwG_K93wXUs3cDzX_NnC6P45xDvSSnTS-i_TqcZ6zrx8vv-yusv31p8-77T6r8kJNmcgrFKWVFZHRpSxKL40QdVlZsEQSc0OoCNE2ee21IU1Ul9agt6IpVEPinL1bc49h_DFTnFzfxoq6zg80ztEJsBKkQqMS-vY_9G6cw5B-5wRK0IXJBSYqX6kqjDEGatwxtL0Pi0Nwv5S7VblLyt1v5W5JS28eo-eyp_rvyh_HCRArENPT8J3Cv9tPxD4ANPiL4g</recordid><startdate>20241201</startdate><enddate>20241201</enddate><creator>Zhang, Zhuxia</creator><creator>Xie, Bo</creator><creator>Zhong, Qi</creator><creator>Dai, Chenxu</creator><creator>Xu, Xijin</creator><creator>Huo, Xia</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QL</scope><scope>7QO</scope><scope>7T7</scope><scope>7U5</scope><scope>7U7</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>JG9</scope><scope>K9.</scope><scope>L7M</scope><scope>M7N</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>20241201</creationdate><title>Abnormal erythrocyte-related parameters in children with Pb, Cr, Cu and Zn exposure</title><author>Zhang, Zhuxia ; Xie, Bo ; Zhong, Qi ; Dai, Chenxu ; Xu, Xijin ; Huo, Xia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c256t-32c13b94cee87b45ba4833dbc909ee4128e16e119f2da78e7eedb981a93f56fe3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Anemia</topic><topic>Bayesian analysis</topic><topic>Biochemistry</topic><topic>Biomedical and Life Sciences</topic><topic>Blood</topic><topic>Blood levels</topic><topic>Cell Biology</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>Children</topic><topic>Chromium</topic><topic>Chromium - blood</topic><topic>Copper</topic><topic>Copper - blood</topic><topic>Correlation analysis</topic><topic>Erythrocyte Indices</topic><topic>Erythrocytes</topic><topic>Erythrocytes, Abnormal - pathology</topic><topic>Exposure</topic><topic>Factor analysis</topic><topic>Female</topic><topic>Heavy metals</topic><topic>Hematocrit</topic><topic>Hematology</topic><topic>Hemoglobin</topic><topic>Humans</topic><topic>Inductively coupled plasma mass spectrometry</topic><topic>Lead</topic><topic>Lead - blood</topic><topic>Life Sciences</topic><topic>Male</topic><topic>Mass spectrometry</topic><topic>Mass spectroscopy</topic><topic>Medicine/Public Health</topic><topic>Metal concentrations</topic><topic>Metals, Heavy - blood</topic><topic>Microbiology</topic><topic>Oxidation</topic><topic>Parameters</topic><topic>Pharmacology/Toxicology</topic><topic>Plant Physiology</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Statistical analysis</topic><topic>Zinc</topic><topic>Zinc - blood</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Zhuxia</creatorcontrib><creatorcontrib>Xie, Bo</creatorcontrib><creatorcontrib>Zhong, Qi</creatorcontrib><creatorcontrib>Dai, Chenxu</creatorcontrib><creatorcontrib>Xu, Xijin</creatorcontrib><creatorcontrib>Huo, Xia</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Toxicology Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Biometals</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Zhuxia</au><au>Xie, Bo</au><au>Zhong, Qi</au><au>Dai, Chenxu</au><au>Xu, Xijin</au><au>Huo, Xia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Abnormal erythrocyte-related parameters in children with Pb, Cr, Cu and Zn exposure</atitle><jtitle>Biometals</jtitle><stitle>Biometals</stitle><addtitle>Biometals</addtitle><date>2024-12-01</date><risdate>2024</risdate><volume>37</volume><issue>6</issue><spage>1537</spage><epage>1549</epage><pages>1537-1549</pages><issn>0966-0844</issn><issn>1572-8773</issn><eissn>1572-8773</eissn><abstract>The link between exposure to a particular heavy metal or metalloid and the development of anemia is well established. However, the association between combined exposure to multiple heavy metal(loid)s and anemia in children is still lacking in evidence. In this study, a total of 266 children aged 3 to 7 were recruited from Guiyu, China. Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure blood heavy metal(loid) concentrations. Blood cell count, hemoglobin (HGB), mean corpuscular hemoglobin (MCH), mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), hematocrit (HCT), and red blood cell distribution width (RDW) were measured by an automated hematology analyzer. Erythrocyte-related parameters were negatively correlated with the Cu and Cu/Zn ratios and positively correlated with Cr, Ni, Zn, and Se by Spearman correlation analysis. Only blood Cu level was negatively correlated with HGB [β = −2.74, (95% Cl: −4.49, −0.995)], MCH [β = −0.505, (95% Cl: −0.785, −0.226)], MCV [β = −1.024, (95% Cl: −1.767, −0.281)], and MCHC [β = −2.137, (95% Cl: −3.54, −0.734)] by multiple linear regression analysis. The Bayesian Kernel Machine Regression (BKMR) model analysis indicated a negative correlation between the combined exposure to Cu, Zn, Pb, and Cr and MCH and MCV. The single-factor analysis showed a considerable statistical difference only with Cu on MCV, MCH, and HGB. Furthermore, the interaction analysis highlighted the interdependent effects of Cu and Zn, Pb and Zn, and Cr and Zn on MCH and MCV levels. Additionally, the oxidation and/or antioxidation reactions may play a significant role in the development of metal(loid)-induced anemia risk. It is crucial to investigate the effects of co-exposure to multiple heavy metal(loid) elements on anemia, especially the interrelationships and mechanisms among them.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><pmid>39154116</pmid><doi>10.1007/s10534-024-00624-y</doi><tpages>13</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0966-0844
ispartof Biometals, 2024-12, Vol.37 (6), p.1537-1549
issn 0966-0844
1572-8773
1572-8773
language eng
recordid cdi_proquest_miscellaneous_3094046186
source MEDLINE; Springer Nature - Complete Springer Journals
subjects Anemia
Bayesian analysis
Biochemistry
Biomedical and Life Sciences
Blood
Blood levels
Cell Biology
Child
Child, Preschool
Children
Chromium
Chromium - blood
Copper
Copper - blood
Correlation analysis
Erythrocyte Indices
Erythrocytes
Erythrocytes, Abnormal - pathology
Exposure
Factor analysis
Female
Heavy metals
Hematocrit
Hematology
Hemoglobin
Humans
Inductively coupled plasma mass spectrometry
Lead
Lead - blood
Life Sciences
Male
Mass spectrometry
Mass spectroscopy
Medicine/Public Health
Metal concentrations
Metals, Heavy - blood
Microbiology
Oxidation
Parameters
Pharmacology/Toxicology
Plant Physiology
Regression analysis
Regression models
Statistical analysis
Zinc
Zinc - blood
title Abnormal erythrocyte-related parameters in children with Pb, Cr, Cu and Zn exposure
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-31T20%3A05%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Abnormal%20erythrocyte-related%20parameters%20in%20children%20with%20Pb,%20Cr,%20Cu%20and%20Zn%20exposure&rft.jtitle=Biometals&rft.au=Zhang,%20Zhuxia&rft.date=2024-12-01&rft.volume=37&rft.issue=6&rft.spage=1537&rft.epage=1549&rft.pages=1537-1549&rft.issn=0966-0844&rft.eissn=1572-8773&rft_id=info:doi/10.1007/s10534-024-00624-y&rft_dat=%3Cproquest_cross%3E3094046186%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3140758231&rft_id=info:pmid/39154116&rfr_iscdi=true