المؤلفون: Gómez-Pascual, Alicia, Naccache, Talel, Xu, Jin, Hooshmand, Kourosh, Wretlind, Asger, Gabrielli, Martina, Lombardo, Marta Tiffany, Shi, Liu, Buckley, Noel J, Tijms, Betty M, Vos, Stephanie J B, Ten Kate, Mara, Engelborghs, Sebastiaan, Sleegers, Kristel, Frisoni, Giovanni B, Wallin, Anders, Lleó, Alberto, Popp, Julius, Martinez-Lage, Pablo, Streffer, Johannes, Barkhof, Frederik, Zetterberg, Henrik, Visser, Pieter Jelle, Lovestone, Simon, Bertram, Lars, Nevado-Holgado, Alejo J, Gualerzi, Alice, Picciolini, Silvia, Proitsi, Petroula, Verderio, Claudia, Botía, Juan A, Legido-Quigley, Cristina

المساهمون: Gómez-Pascual, A, Naccache, T, Xu, J, Hooshmand, K, Wretlind, A, Gabrielli, M, Lombardo, M, Shi, L, Buckley, N, Tijms, B, Vos, S, Ten Kate, M, Engelborghs, S, Sleegers, K, Frisoni, G, Wallin, A, Lleó, A, Popp, J, Martinez-Lage, P, Streffer, J, Barkhof, F, Zetterberg, H, Visser, P, Lovestone, S, Bertram, L, Nevado-Holgado, A, Gualerzi, A, Picciolini, S, Proitsi, P, Verderio, C, Botía, J, Legido-Quigley, C

مصطلحات موضوعية: Alzheimer's disease, Integrative omic, Machine learning, Metabolomic, Mild cognitive impairment, Proteomic

الوصف: Background: Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed. Method: Here, we propose a machine learning-based approach to detect the key metabolites and proteins involved in MCI progression to AD using data from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Study. Proteins and metabolites were evaluated separately in multiclass models (controls, MCI and AD) and together in MCI conversion models (MCI stable vs converter). Only features selected as relevant by 3/4 algorithms proposed were kept for downstream analysis. Results: Multiclass models of metabolites highlighted nine features further validated in an independent cohort (0.726 mean balanced accuracy). Among these features, one metabolite, oleamide, was selected by all the algorithms. Further in-vitro experiments in rodents showed that disease-associated microglia excreted oleamide in vesicles. Multiclass models of proteins stood out with nine features, validated in an independent cohort (0.720 mean balanced accuracy). However, none of the proteins was selected by all the algorithms. Besides, to distinguish between MCI stable and converters, 14 key features were selected (0.872 AUC), including tTau, alpha-synuclein (SNCA), junctophilin-3 (JPH3), properdin (CFP) and peptidase inhibitor 15 (PI15) among others. Conclusions: This omics integration approach highlighted a set of molecules associated with MCI conversion important in neuronal and glia inflammation pathways.

وصف الملف: STAMPA

العلاقة: info:eu-repo/semantics/altIdentifier/pmid/38761503; volume:176; issue:June 2024; journal:COMPUTERS IN BIOLOGY AND MEDICINE; https://hdl.handle.net/10281/478359Test; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85193235306

الإتاحة: https://doi.org/10.1016Test/j.compbiomed.2024.108588
https://hdl.handle.net/10281/478359Test

المؤلفون: Biyong, John Pougue, Wang, Bo, Lyons, Terry, Nevado-Holgado, Alejo J

مصطلحات موضوعية: Computer Science - Computation and Language, 60L10, I.2.7

الوصف: Relying on large pretrained language models such as Bidirectional Encoder Representations from Transformers (BERT) for encoding and adding a simple prediction layer has led to impressive performance in many clinical natural language processing (NLP) tasks. In this work, we present a novel extension to the Transformer architecture, by incorporating signature transform with the self-attention model. This architecture is added between embedding and prediction layers. Experiments on a new Swedish prescription data show the proposed architecture to be superior in two of the three information extraction tasks, comparing to baseline models. Finally, we evaluate two different embedding approaches between applying Multilingual BERT and translating the Swedish text to English then encode with a BERT model pretrained on clinical notes.

الوصول الحر: http://arxiv.org/abs/2010.04897Test

المؤلفون: Wang, Bo, Wu, Yue, Taylor, Niall, Lyons, Terry, Liakata, Maria, Nevado-Holgado, Alejo J, Saunders, Kate E A

مصطلحات موضوعية: Computer Science - Machine Learning, Computer Science - Computation and Language, Electrical Engineering and Systems Science - Audio and Speech Processing, Statistics - Machine Learning, 60L10

الوصف: Bipolar disorder (BD) and borderline personality disorder (BPD) are both chronic psychiatric disorders. However, their overlapping symptoms and common comorbidity make it challenging for the clinicians to distinguish the two conditions on the basis of a clinical interview. In this work, we first present a new multi-modal dataset containing interviews involving individuals with BD or BPD being interviewed about a non-clinical topic . We investigate the automatic detection of the two conditions, and demonstrate a good linear classifier that can be learnt using a down-selected set of features from the different aspects of the interviews and a novel approach of summarising these features. Finally, we find that different sets of features characterise BD and BPD, thus providing insights into the difference between the automatic screening of the two conditions.

الوصول الحر: http://arxiv.org/abs/2008.03408Test

المؤلفون: Westwood, Sarah, Baird, Alison L., Anand, Sneha N., Nevado-Holgado, Alejo J., Kormilitzin, Andrey, Shi, Liu, Hye, Abdul, Ashton, Nicholas J., Morgan, Angharad R., Bos, Isabelle, Vos, Stephanie J. B., Baker, Susan, Buckley, Noel J., Ten Kate, Mara, Scheltens, Philip, Teunissen, Charlotte E., Vandenberghe, Rik, Gabel, Silvy, Meersmans, Karen, Engelborghs, Sebastiaan, De Roeck, Ellen E., Sleegers, Kristel, Frisoni, Giovanni B., Blin, Olivier, Richardson, Jill C., Bordet, Régis, Molinuevo, José L., Rami, Lorena, Wallin, Anders, Kettunen, Petronella, Tsolaki, Magda, Verhey, Frans, Lléo, Alberto, Sala, Isabel, Popp, Julius, Peyratout, Gwendoline, Martinez-Lage, Pablo, Tainta, Mikel, Johannsen, Peter, Freund-Levi, Yvonne, 1956, Frölich, Lutz, Dobricic, Valerija, Legido-Quigley, Cristina, Bertram, Lars, Barkhof, Frederik, Zetterberg, Henrik, Morgan, B. Paul, Streffer, Johannes, Visser, Pieter Jelle, Lovestone, Simon

المصدر: Journal of Alzheimer's Disease. 74(1):213-225

مصطلحات موضوعية: Alzheimer’s disease, amyloid-β, biomarkers, plasma, proteomics

الوصف: We have previously investigated, discovered, and replicated plasma protein biomarkers for use to triage potential trials participants for PET or cerebrospinal fluid measures of Alzheimer's disease (AD) pathology. This study sought to undertake validation of these candidate plasma biomarkers in a large, multi-center sample collection. Targeted plasma analyses of 34 proteins with prior evidence for prediction of in vivo pathology were conducted in up to 1,000 samples from cognitively healthy elderly individuals, people with mild cognitive impairment, and in patients with AD-type dementia, selected from the EMIF-AD catalogue. Proteins were measured using Luminex xMAP, ELISA, and Meso Scale Discovery assays. Seven proteins replicated in their ability to predict in vivo amyloid pathology. These proteins form a biomarker panel that, along with age, could significantly discriminate between individuals with high and low amyloid pathology with an area under the curve of 0.74. The performance of this biomarker panel remained consistent when tested in apolipoprotein E ɛ4 non-carrier individuals only. This blood-based panel is biologically relevant, measurable using practical immunocapture arrays, and could significantly reduce the cost incurred to clinical trials through screen failure.

وصف الملف: print

الوصول الحر: https://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-79728Test
https://doi.org/10.3233/JAD-190434Test

المؤلفون: Shi, Liu, Xu, Jin, Green, Rebecca, Wretlind, Asger, Homann, Jan, Buckley, Noel J., Tijms, Betty M., Vos, Stephanie J. B., Lill, Christina M., Kate, Mara ten, Engelborghs, Sebastiaan, Sleegers, Kristel, Frisoni, Giovanni B., Wallin, Anders, Lleó, Alberto, Popp, Julius, Martinez-Lage, Pablo, Streffer, Johannes, Barkhof, Frederik, Zetterberg, Henrik, Visser, Pieter Jelle, Lovestone, Simon, Bertram, Lars, Nevado-Holgado, Alejo J., Proitsi, Petroula, Legido-Quigley, Cristina

المصدر: Shi , L , Xu , J , Green , R , Wretlind , A , Homann , J , Buckley , N J , Tijms , B M , Vos , S J B , Lill , C M , Kate , M T , Engelborghs , S , Sleegers , K , Frisoni , G B , Wallin , A , Lleó , A , Popp , J , Martinez-Lage , P , Streffer , J , Barkhof , F , Zetterberg , H , Visser , P J , Lovestone , S , Bertram , L ....

الوصف: Introduction: This study employed an integrative system and causal inference approach to explore molecular signatures in blood and CSF, the amyloid/tau/neurodegeneration [AT(N)] framework, mild cognitive impairment (MCI) conversion to Alzheimer's disease (AD), and genetic risk for AD. Methods: Using the European Medical Information Framework (EMIF)-AD cohort, we measured 696 proteins in cerebrospinal fluid (n = 371), 4001 proteins in plasma (n = 972), 611 metabolites in plasma (n = 696), and genotyped whole-blood (7,778,465 autosomal single nucleotide epolymorphisms, n = 936). We investigated associations: molecular modules to AT(N), module hubs with AD Polygenic Risk scores and APOE4 genotypes, molecular hubs to MCI conversion and probed for causality with AD using Mendelian randomization (MR). Results: AT(N) framework associated with protein and lipid hubs. In plasma, Proprotein Convertase Subtilisin/Kexin Type 7 showed evidence for causal associations with AD. AD was causally associated with Reticulocalbin 2 and sphingomyelins, an association driven by the APOE isoform. Discussion: This study reveals multi-omics networks associated with AT(N) and causal AD molecular candidates.

العلاقة: https://research.vumc.nl/en/publications/611c1de7-f35a-47d5-b856-071f55702665Test

الإتاحة: https://doi.org/10.1002/alz.12961Test
https://research.vumc.nl/en/publications/611c1de7-f35a-47d5-b856-071f55702665Test
http://www.scopus.com/inward/record.url?scp=85148343008&partnerID=8YFLogxKTest

المؤلفون: Shi, Liu, Freund-Levi, Yvonne, 1956, Nevado-Holgado, Alejo J.

المصدر: Alzheimer's & Dementia. 15(11):1478-1488

مصطلحات موضوعية: Amyloid beta, SOMAscan assay, Plasma proteomics, Replication, Causal relationship, Tau

الوصف: Introduction: Plasma proteins have been widely studied as candidate biomarkers to predict brain amyloid deposition to increase recruitment efficiency in secondary prevention clinical trials for Alzheimer's disease. Most such biomarker studies are targeted to specific proteins or are biased toward high abundant proteins.Methods: 4001 plasma proteins were measured in two groups of participants (discovery group = 516, replication group = 365) selected from the European Medical Information Framework for Alzheimer's disease Multimodal Biomarker Discovery study, all of whom had measures of amyloid.Results: A panel of proteins (n = 44), along with age and apolipoprotein E (APOE) e4, predicted brain amyloid deposition with good performance in both the discovery group (area under the curve = 0.78) and the replication group (area under the curve = 0.68). Furthermore, a causal relationship between amyloid and tau was confirmed by Mendelian randomization.Discussion: The results suggest that high-dimensional plasma protein testing could be a useful and reproducible approach for measuring brain amyloid deposition.

وصف الملف: print

الوصول الحر: https://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-78371Test
https://doi.org/10.1016Test/j.jalz.2019.06.4951

المؤلفون: Argentieri, M. Austin, Amin, Najaf, Nevado-Holgado, Alejo, J, Sproviero, William, Collister, Jennifer, A, Keestra, Sarai, M, Doherty, Aiden, Hunter, David, J, Alvergne, Alexandra, van Duijn, Cornelia, M

المساهمون: School of Anthropology and Museum Ethnography, University of Oxford, Massachusetts General Hospital, Boston, Massachusetts, parent, Unknown, Institut des Sciences de l'Evolution de Montpellier (UMR ISEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École Pratique des Hautes Études (EPHE), Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut de recherche pour le développement IRD : UR226-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)

المصدر: https://hal.science/hal-04301069Test ; 2023.

مصطلحات موضوعية: [SDV]Life Sciences [q-bio]

الوصف: It has long been suggested that environmental exposures (i.e., the exposome) play a dominant role in shaping trajectories of human aging and premature mortality. Here we aimed to quantify the contribution of the exposome and genome to aging and mortality. We conducted an exposome-wide analysis in the UK Biobank (n=492,567) to systematically identify exposures associated with mortality while accounting for exposure correlation and mismeasurement. We found that the exposome is a major mortality determinant irrespective of genetic disease risk via shaping distinct biological and multimorbidity patterns. We identified 41 independent exposures associated with mortality, and demonstrate that most identified exposures are associated with a common signature of age-related multimorbidity, aging biomarkers, and major cardiometabolic risk factors. Compared with age and sex, polygenic risk for 22 major diseases and aging phenotypes explained an additional 2% of mortality variation, whereas the exposome explained an additional 19%. While genetics explained the majority of variation in dementias and breast, prostate, and colorectal cancers, the exposome explained the majority of variation for diseases of the lung, heart, and liver. Our findings provide a comprehensive map of the contributions of environment and genetics to mortality and common age-related diseases.

العلاقة: hal-04301069; https://hal.science/hal-04301069Test; https://hal.science/hal-04301069/documentTest; https://hal.science/hal-04301069/file/2023.03.10.23286340.full.pdfTest; MEDRXIV: 2023.03.10.23286340

الإتاحة: https://doi.org/10.1101/2023.03.10.23286340Test
https://hal.science/hal-04301069Test
https://hal.science/hal-04301069/documentTest
https://hal.science/hal-04301069/file/2023.03.10.23286340.full.pdfTest

المؤلفون: Newby, Danielle, Linden, Andrew Brent, Fernandes, Marco, Molero, Yasmina, Winchester, Laura, Sproviero, William, Ghose, Upamanyu, Li, Qingqin S., Launer, Lenore J., Duijn, Cornelia M.Van, Nevado-Holgado, Alejo J.

المساهمون: University of St Andrews. School of Medicine, University of St Andrews. Population and Behavioural Science Division

مصطلحات موضوعية: Alzheimer Disease, Dementia, Diabetes Mellitus, Type 2, Neurology, Endocrinology, Diabetes and Metabolism, 3rd-DAS, SDG 3 - Good Health and Well-being

الوصف: This work was supported by Janssen Pharmaceuticals. LJL is supported by the National Institute on Aging Intramural Research Program, USA. Additional funds were provided by Rosetrees Trust (M937) and John Black Charitable Fund (ID A2926). AJN-H has received funding from Janssen Pharmaceuticals, GlaxoSmithKline and Ono Pharma. QSL is an employee of Janssen Research & Development, Johnson & Johnson, and may hold equity in Johnson & Johnson. ; Introduction Type 2 diabetes is a risk factor for dementia and Parkinson's disease (PD). Drug treatments for diabetes, such as metformin, could be used as novel treatments for these neurological conditions. Using electronic health records from the USA (OPTUM EHR) we aimed to assess the association of metformin with all-cause dementia, dementia subtypes and PD compared with sulfonylureas. Research design and methods A new user comparator study design was conducted in patients ≥50 years old with diabetes who were new users of metformin or sulfonylureas between 2006 and 2018. Primary outcomes were all-cause dementia and PD. Secondary outcomes were Alzheimer's disease (AD), vascular dementia (VD) and mild cognitive impairment (MCI). Cox proportional hazards models with inverse probability of treatment weighting (IPTW) were used to estimate the HRs. Subanalyses included stratification by age, race, renal function, and glycemic control. Results We identified 96 140 and 16 451 new users of metformin and sulfonylureas, respectively. Mean age was 66.4±8.2 years (48% male, 83% Caucasian). Over the 5-year follow-up, 3207 patients developed all-cause dementia (2256 (2.3%) metformin, 951 (5.8%) sulfonylurea users) and 760 patients developed PD (625 (0.7%) metformin, 135 (0.8%) sulfonylurea users). After IPTW, HRs for all-cause dementia and PD were 0.80 (95% CI 0.73 to 0.88) and 1.00 (95% CI 0.79 to 1.28). HRs for AD, VD and MCI were 0.81 (0.70-0.94), 0.79 (0.63-1.00) and 0.91 (0.79-1.04). Stronger associations were observed in patients who were younger (<75 years old), ...

وصف الملف: application/pdf

العلاقة: BMJ Open Diabetes Research and Care; 301366522; 7f975425-ee81-4244-8150-3c89ee148b10; 85137943287; Newby , D , Linden , A B , Fernandes , M , Molero , Y , Winchester , L , Sproviero , W , Ghose , U , Li , Q S , Launer , L J , Duijn , C M V & Nevado-Holgado , A J 2022 , ' Comparative effect of metformin versus sulfonylureas with dementia and Parkinson's disease risk in US patients over 50 with type 2 diabetes mellitus ' , BMJ Open Diabetes Research and Care , vol. 10 , no. 5 , e003036 . https://doi.org/10.1136/bmjdrc-2022-003036Test; ORCID: /0000-0002-4768-0934/work/158592729; https://hdl.handle.net/10023/29736Test; http://www.scopus.com/inward/record.url?scp=85137943287&partnerID=8YFLogxKTest

الإتاحة: https://doi.org/10.1136/bmjdrc-2022-003036Test
https://hdl.handle.net/10023/29736Test
http://www.scopus.com/inward/record.url?scp=85137943287&partnerID=8YFLogxKTest

المؤلفون: Li, Zhenpeng, Kormilitzin, Andrey, Fernandes, Marco, Vaci, Nemanja, Liu, Qiang, Newby, Danielle, Goodday, Sarah, Smith, Tanya, Nevado-Holgado, Alejo J., Winchester, Laura

المساهمون: University of St Andrews. School of Medicine, University of St Andrews. Population and Behavioural Science Division

مصطلحات موضوعية: Data resource, Linkage studies, Mental health, Neuro-epidemiology, UK Biobank, Validation study, Health Informatics, 3rd-DAS, SDG 3 - Good Health and Well-being

الوصف: The study was funded by the MRC Pathfinder Grant (MC_PC_17215); the National Institute for Health Research’s (NIHR) Oxford Health Biomedical Research Centre (BRC-1215-20005) and the Virtual Brain Cloud from European Commission (grant no. H2020SC1-DTH-2018-1). This work was supported by the UK Clinical Record Interactive Search (UK-CRIS) system funded by the National Institute for Health Research (NIHR) and the Medical Research Council, with the University of Oxford, using data and systems of the NIHR Oxford Health Biomedical Research Centre (BRC-1215-20005). ; UK Biobank (UKB) is widely employed to investigate mental health disorders and related exposures; however, its applicability and relevance in a clinical setting and the assumptions required have not been sufficiently and systematically investigated. Here, we present the first validation study using secondary care mental health data with linkage to UKB from Oxford - Clinical Record Interactive Search (CRIS) focusing on comparison of demographic information, diagnostic outcome, medication record and cognitive test results, with missing data and the implied bias from both resources depicted. We applied a natural language processing model to extract information embedded in unstructured text from clinical notes and attachments. Using a contingency table we compared the demographic information recorded in UKB and CRIS. We calculated the positive predictive value (PPV, proportion of true positives cases detected) for mental health diagnosis and relevant medication. Amongst the cohort of 854 subjects, PPVs for any mental health diagnosis for dementia, depression, bipolar disorder and schizophrenia were 41.6%, and were 59.5%, 12.5%, 50.0% and 52.6%, respectively. Self-reported medication records in UKB had general PPV of 47.0%, with the prevalence of frequently prescribed medicines to each typical mental health disorder considerably different from the information provided by CRIS. UKB is highly multimodal, but with limited follow-up records, whereas CRIS offers a ...

وصف الملف: application/pdf

العلاقة: International Journal of Medical Informatics; 301366735; d32dd2f7-62d6-42d5-9ab6-d12b81c7703d; 85124408917; Li , Z , Kormilitzin , A , Fernandes , M , Vaci , N , Liu , Q , Newby , D , Goodday , S , Smith , T , Nevado-Holgado , A J & Winchester , L 2022 , ' Validation of UK Biobank data for mental health outcomes : a pilot study using secondary care electronic health records ' , International Journal of Medical Informatics , vol. 160 , 104704 . https://doi.org/10.1016Test/j.ijmedinf.2022.104704; ORCID: /0000-0002-4768-0934/work/158592727; https://hdl.handle.net/10023/29733Test

الإتاحة: https://doi.org/10.1016Test/j.ijmedinf.2022.104704
https://hdl.handle.net/10023/29733Test

المؤلفون: Sproviero, William, Winchester, Laura, Newby, Danielle, Fernandes, Marco, Shi, Liu, Goodday, Sarah M., Prats-Uribe, Albert, Alhambra, Daniel P., Buckley, Noel J., Nevado-Holgado, Alejo J.

المساهمون: University of St Andrews. School of Medicine, University of St Andrews. Population and Behavioural Science Division

مصطلحات موضوعية: Alzheimer's disease, Blood pressure, Family history of Alzheimer's disease, Genetic variants, Mendelian randomization, Biological Psychiatry, 3rd-NDAS

الوصف: This work was supported by Janssen Research and Development , LLC (of Johnson & Johnson). ; Background: Findings from randomized controlled trials have yielded conflicting results on the association between blood pressure (BP) and dementia traits. We tested the hypothesis that a causal relationship exists between systolic BP (SBP) and/or diastolic BP (DBP) and risk of Alzheimer's disease (AD). Methods: We performed a generalized summary Mendelian randomization (GSMR) analysis using summary statistics of a genome-wide association study meta-analysis of 299,024 individuals of SBP or DBP as exposure variables against three different outcomes: 1) AD diagnosis (International Genomics of Alzheimer's Project), 2) maternal family history of AD (UK Biobank), and 3) paternal family history of AD (UK Biobank). Finally, a combined meta-analysis of 368,440 individuals that included these three summary statistics was used as final outcome. Results: GSMR applied to the International Genomics of Alzheimer's Project dataset revealed a significant effect of high SBP lowering the risk of AD (βGSMR = −0.19, p =.04). GSMR applied to the maternal family history of AD UK Biobank dataset (SBP [βGSMR = −0.12, p =.02], DBP [βGSMR = −0.10, p =.05]) and to the paternal family history of AD UK Biobank dataset (SBP [βGSMR = −0.16, p =.02], DBP [βGSMR = −0.24, p = 7.4 × 10−4]) showed the same effect. A subsequent combined meta-analysis confirmed the overall significant effect for the other SBP analyses (βGSMR = −0.14, p =.03). The DBP analysis in the combined meta-analysis also confirmed a DBP effect on AD (βGSMR = −0.14, p =.03). Conclusions: A causal effect exists between high BP and a reduced late-life risk of AD. The results were obtained through careful consideration of confounding factors and the application of complementary MR methods on independent cohorts. ; Peer reviewed

وصف الملف: application/pdf

العلاقة: Biological Psychiatry; 301366939; 90b7b640-320c-4f41-b8b2-dc032c420c30; 85102583040; Sproviero , W , Winchester , L , Newby , D , Fernandes , M , Shi , L , Goodday , S M , Prats-Uribe , A , Alhambra , D P , Buckley , N J & Nevado-Holgado , A J 2021 , ' High blood pressure and risk of dementia : a two-sample Mendelian randomization study in the UK biobank ' , Biological Psychiatry , vol. 89 , no. 8 , pp. 817-824 . https://doi.org/10.1016Test/j.biopsych.2020.12.015; ORCID: /0000-0002-4768-0934/work/158592723; https://hdl.handle.net/10023/29734Test

الإتاحة: https://doi.org/10.1016Test/j.biopsych.2020.12.015
https://hdl.handle.net/10023/29734Test