{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,28]],"date-time":"2025-11-28T17:29:08Z","timestamp":1764350948312,"version":"build-2065373602"},"reference-count":60,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,4,28]],"date-time":"2024-04-28T00:00:00Z","timestamp":1714262400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Regional Development Fund (FEDER)","award":["NORTE-45-2020-75"],"award-info":[{"award-number":["NORTE-45-2020-75"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Understanding and classifying brain states as a function of sleep quality and age has important implications for developing lifestyle-based interventions involving sleep hygiene. Current studies use an algorithm that captures non-linear features of brain complexity to differentiate awake electroencephalography (EEG) states, as a function of age and sleep quality. Fifty-eight participants were assessed using the Pittsburgh Sleep Quality Inventory (PSQI) and awake resting state EEG. Groups were formed based on age and sleep quality (younger adults n = 24, mean age = 24.7 years, SD = 3.43, good sleepers n = 11; older adults n = 34, mean age = 72.87; SD = 4.18, good sleepers n = 9). Ten non-linear features were extracted from multiband EEG analysis to feed several classifiers followed by a leave-one-out cross-validation. Brain state complexity accurately predicted (i) age in good sleepers, with 75% mean accuracy (across all channels) for lower frequencies (alpha, theta, and delta) and 95% accuracy at specific channels (temporal, parietal); and (ii) sleep quality in older groups with moderate accuracy (70 and 72%) across sub-bands with some regions showing greater differences. It also differentiated younger good sleepers from older poor sleepers with 85% mean accuracy across all sub-bands, and 92% at specific channels. Lower accuracy levels (&lt;50%) were achieved in predicting sleep quality in younger adults. The algorithm discriminated older vs. younger groups excellently and could be used to explore intragroup differences in older adults to predict sleep intervention efficiency depending on their brain complexity.<\/jats:p>","DOI":"10.3390\/s24092811","type":"journal-article","created":{"date-parts":[[2024,4,29]],"date-time":"2024-04-29T08:49:24Z","timestamp":1714380564000},"page":"2811","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Classification of Sleep Quality and Aging as a Function of Brain Complexity: A Multiband Non-Linear EEG Analysis"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1937-5537","authenticated-orcid":false,"given":"Luc\u00eda","family":"Penalba-S\u00e1nchez","sequence":"first","affiliation":[{"name":"Facultat de Psicolog\u00eda, Ci\u00e8ncies de l\u2019Educaci\u00f3 i de l\u2019Esport (FPCEE), Blanquerna, Universitat Ramon Llull, 08022 Barcelona, Spain"},{"name":"Human Neurobehavioral Laboratory (HNL), Research Centre for Human Development (CEDH), Faculty of Education and Psychology, Universidade Cat\u00f3lica Portuguesa, 4169-005 Porto, Portugal"},{"name":"Department of Psychology, Nottingham Trent University (NTU), Nottingham NG1 4FQ, UK"},{"name":"Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke-University Magdeburg (OVGU), 39120 Magdeburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gabriel","family":"Silva","sequence":"additional","affiliation":[{"name":"Centro de Biotecnologia e Qu\u00edmica Fina (CBQF)\u2014Laborat\u00f3rio Associado, Escola Superior de Biotecnologia, Universidade Cat\u00f3lica Portuguesa, 4169-005 Porto, Portugal"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark","family":"Crook-Rumsey","sequence":"additional","affiliation":[{"name":"UK Dementia Research Institute (UK DRI), Centre for Care Research and Technology, Imperial College London, London W1T 7NF, UK"},{"name":"UK Dementia Research Institute (UK DRI), Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London SE5 9RX, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4333-8442","authenticated-orcid":false,"given":"Alexander","family":"Sumich","sequence":"additional","affiliation":[{"name":"Department of Psychology, Nottingham Trent University (NTU), Nottingham NG1 4FQ, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5381-6615","authenticated-orcid":false,"given":"Pedro Miguel","family":"Rodrigues","sequence":"additional","affiliation":[{"name":"Centro de Biotecnologia e Qu\u00edmica Fina (CBQF)\u2014Laborat\u00f3rio Associado, Escola Superior de Biotecnologia, Universidade Cat\u00f3lica Portuguesa, 4169-005 Porto, Portugal"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6550-3790","authenticated-orcid":false,"given":"Patr\u00edcia","family":"Oliveira-Silva","sequence":"additional","affiliation":[{"name":"Human Neurobehavioral Laboratory (HNL), Research Centre for Human Development (CEDH), Faculty of Education and Psychology, Universidade Cat\u00f3lica Portuguesa, 4169-005 Porto, Portugal"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0644-6022","authenticated-orcid":false,"given":"Ignacio","family":"Cifre","sequence":"additional","affiliation":[{"name":"Facultat de Psicolog\u00eda, Ci\u00e8ncies de l\u2019Educaci\u00f3 i de l\u2019Esport (FPCEE), Blanquerna, Universitat Ramon Llull, 08022 Barcelona, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1177\/1745691614556680","article-title":"Sleep, Cognition, and Normal Aging: Integrating a Half-Century of Multidisciplinary Research","volume":"10","author":"Scullin","year":"2015","journal-title":"Perspect. Psychol. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1093\/sleep\/20.3.192","article-title":"Aging and Sleep. 1 Longitudinal Changes in Diary-and Laboratory-Based Sleep Measures in Healthy \u201cOld Old\u201d and \u201cYoung Old\u201d Subjects: A Three-Year Follow-Up","volume":"20","author":"Hoch","year":"1997","journal-title":"Sleep"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"204","DOI":"10.1007\/s40675-017-0086-z","article-title":"Do Older Adults Need Sleep? A Review of Neuroimaging, Sleep, and Aging Studies","volume":"3","author":"Scullin","year":"2017","journal-title":"Curr. Sleep. Med. Rep."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"58","DOI":"10.3389\/fnagi.2019.00058","article-title":"Young and Older Adults Benefit From Sleep, but Not From Active Wakefulness for Memory Consolidation of What-Where-When Naturalistic Events","volume":"11","author":"Abichou","year":"2019","journal-title":"Front. Aging Neurosci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1016\/j.tins.2005.06.004","article-title":"Memory consolidation and reconsolidation: What is the role of sleep?","volume":"28","author":"Stickgold","year":"2005","journal-title":"Trends Neurosci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/0959-4388(95)80028-X","article-title":"Stress and cognitive function","volume":"5","author":"Mcewen","year":"1995","journal-title":"Curr. Opin. Neurobiol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2119","DOI":"10.1210\/jc.2003-031562","article-title":"Adverse Effects of Modest Sleep Restriction on Sleepiness, Performance, and Inflammatory Cytokines","volume":"89","author":"Vgontzas","year":"2004","journal-title":"J. Clin. Endocrinol. Metab."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"S20","DOI":"10.1016\/j.metabol.2006.07.008","article-title":"Sleep deprivation as a neurobiologic and physiologic stressor: Allostasis and allostatic load","volume":"55","author":"McEwen","year":"2006","journal-title":"Metabolism"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1111\/psyg.12319","article-title":"Sleep disorders in the elderly: A growing challenge","volume":"18","author":"Gulia","year":"2018","journal-title":"Psychogeriatrics"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1432","DOI":"10.1016\/j.socscimed.2009.08.041","article-title":"Age, cohort and period effects in the prevalence of sleep disturbances among older people: The impact of economic downturn","volume":"69","author":"Dregan","year":"2009","journal-title":"Soc. Sci. Med."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1016\/0197-4580(96)00005-X","article-title":"Topography of Brain Atrophy During Normal Aging and Alzheimer\u2019s Disease","volume":"17","author":"Double","year":"1996","journal-title":"Neurobiol. Aging"},{"key":"ref_12","first-page":"180","article-title":"Self-reported sleep quality predicts poor cognitive performance in healthy older adults","volume":"64","author":"Nebes","year":"2009","journal-title":"J. Gerontol. Ser. B Psychol. Sci. Soc. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"695","DOI":"10.1212\/WNL.0000000000005303","article-title":"Resistance vs. resilience to Alzheimer disease","volume":"90","author":"Vemuri","year":"2018","journal-title":"Neurology"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.neurobiolaging.2016.01.012","article-title":"Impact of lifestyle dimensions on brain pathology and cognition","volume":"40","author":"Schreiber","year":"2016","journal-title":"Neurobiol. Aging"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"809","DOI":"10.3389\/fnins.2018.00809","article-title":"Complexity of Wake Electroencephalography Correlates With Slow Wave Activity After Sleep Onset","volume":"12","author":"Hou","year":"2018","journal-title":"Front. Neurosci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"510091","DOI":"10.3389\/fnins.2020.00337","article-title":"Editorial: Advances in Multi-Scale Analysis of Brain Complexity","volume":"14","author":"Yang","year":"2020","journal-title":"Front. Neurosci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"605","DOI":"10.1080\/15402002.2018.1435545","article-title":"Associations Among Trajectories of Sleep Disturbance, Depressive Symptomology and 24-Hour Urinary Cortisol in HIV+ Women Following a Stress Management Intervention","volume":"17","author":"McIntosh","year":"2019","journal-title":"Behav. Sleep Med."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"229402","DOI":"10.3389\/fphys.2016.00576","article-title":"More severe insomnia complaints in people with stronger long-range temporal correlations in wake resting-state EEG","volume":"7","author":"Colombo","year":"2016","journal-title":"Front. Physiol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"5174815","DOI":"10.1155\/2018\/5174815","article-title":"Systematic review on resting-state EEG for Alzheimer\u2019s disease diagnosis and progression assessment","volume":"2018","author":"Cassani","year":"2018","journal-title":"Dis. Markers"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Sanei, S., and Chambers, J.A. (2007). EEG Signal Processing, John Wiley & Sons.","DOI":"10.1002\/9780470511923"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/0375-9601(85)90444-X","article-title":"Evidence of chaotic dynamics of brain activity during the sleep cycle","volume":"11","author":"Babloyantz","year":"1985","journal-title":"Phys. Lett. A"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Chialvo, D.R. (2018). Life at the edge: Complexity and criticality in biological function. arXiv.","DOI":"10.5506\/APhysPolB.49.1955"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"700171","DOI":"10.3389\/fnins.2021.700171","article-title":"Revisiting Nonlinear Functional Brain Co-activations: Directed, Dynamic, and Delayed","volume":"15","author":"Cifre","year":"2021","journal-title":"Front. Neurosci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"992","DOI":"10.12688\/f1000research.7698.1","article-title":"Dynamical systems, attractors, and neural circuits [version 1; referees: 3 approved]","volume":"5","author":"Miller","year":"2016","journal-title":"F1000Research"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Faust, O., and Bairy, M.G. (2012). Nonlinear analysis of physiological signals: A review. J. Mech. Med. Biol., 12.","DOI":"10.1142\/S0219519412400155"},{"key":"ref_26","unstructured":"Qian, B., and Rasheed, K. (2007, January 24\u201326). Hurst exponent and financial market predictability. Proceedings of the IASTED Conference on Financial Engineering and Applications, Berkeley, CA, USA."},{"key":"ref_27","first-page":"197","article-title":"Effect of Total Sleep Deprivation on the Dimensional Complexity of the Waking EEG sleep deprivation and waking EEG","volume":"24","author":"Jeong","year":"2001","journal-title":"Sleep"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"596122","DOI":"10.3389\/fnagi.2020.596122","article-title":"Brain Entropy Mapping in Healthy Aging and Alzheimer\u2019s Disease","volume":"12","author":"Wang","year":"2020","journal-title":"Front. Aging Neurosci."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Keshmiri, S. (2020). Entropy and the Brain: An Overview. Entropy, 22.","DOI":"10.3390\/e22090917"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1037\/pne0000287","article-title":"Early Detection of Alzheimer\u2019s and Parkinson\u2019s Diseases Using Multiband Nonlinear EEG Analysis","volume":"15","author":"Silva","year":"2022","journal-title":"Psychol. Neurosci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"6975","DOI":"10.1109\/JSEN.2022.3155345","article-title":"Discrimination of Wakefulness From Sleep Stage I Using Nonlinear Features of a Single Frontal EEG Channel","volume":"22","author":"Shahbakhti","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.neurobiolaging.2018.07.004","article-title":"Resting-state EEG power and connectivity are associated with alpha peak frequency slowing in healthy aging","volume":"71","author":"Scally","year":"2018","journal-title":"Neurobiol. Aging"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"375","DOI":"10.3389\/fnagi.2018.00375","article-title":"Poor Sleep Quality Associates with Decreased Functional and Structural Brain Connectivity in Normative Aging: A MRI Multimodal Approach","volume":"10","author":"Amorim","year":"2018","journal-title":"Front. Aging Neurosci."},{"key":"ref_34","unstructured":"Crook-Rumsey, M. (2020). Neurophysiology of Prospective Memory in Typical and Atypical Ageing, Nottingham Trent University."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/0165-1781(89)90047-4","article-title":"The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research","volume":"28","author":"Buysse","year":"1989","journal-title":"Psychiatry Res."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1076\/clin.12.1.43.1726","article-title":"Hopkins verbal learning test\u2014Revised: Normative data and analysis of inter-form and test-retest reliability","volume":"12","author":"Benedict","year":"1998","journal-title":"Clin. Neuropsychol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1002\/gps.830","article-title":"Utility of TICS-M for the assessment of cognitive function in older adults","volume":"18","author":"Budge","year":"2003","journal-title":"Int. J. Geriatr. Psychiatry"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.jneumeth.2003.10.009","article-title":"EEGLAB: An open-source toolbox for analysis of single-trial EEG dynamics","volume":"134","author":"Delorme","year":"2004","journal-title":"J. Neurosci. Methods"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1830","DOI":"10.1109\/TBME.2015.2503400","article-title":"A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data from Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects","volume":"63","author":"Doborjeh","year":"2016","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_40","unstructured":"Vetterli, M., and Kovacevic, J. (1995). Wavelets and Subband Coding, Prentice Hall."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"3384","DOI":"10.1109\/JBHI.2021.3069789","article-title":"Lacsogram: A New EEG Tool to Diagnose Alzheimer\u2019s Disease","volume":"25","author":"Rodrigues","year":"2021","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_42","unstructured":"Malvar, H.S. (1992). Signal Processing with Lapped Transforms, Artech House, Inc."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1109\/79.952805","article-title":"Wavelets, approximation, and compression","volume":"18","author":"Vetterli","year":"2001","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_44","first-page":"1","article-title":"A practical test for noisy chaotic dynamics","volume":"3\u20134","year":"2015","journal-title":"SoftwareX"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2266","DOI":"10.1016\/j.clinph.2005.06.011","article-title":"Nonlinear dynamical analysis of EEG and MEG: Review of an emerging field","volume":"116","author":"Stam","year":"2005","journal-title":"Clin. Neurophysiol."},{"key":"ref_46","first-page":"2309","article-title":"Analysis of EEG signals using nonlinear dynamics and chaos: A review","volume":"9","year":"2015","journal-title":"Appl. Math. Inf. Sci."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"5047","DOI":"10.1111\/ejn.15800","article-title":"Brain Entropy, Fractal Dimensions and Predictability: A Review of Complexity Measures for EEG in Healthy and Neuropsychiatric Populations","volume":"56","author":"Lau","year":"2021","journal-title":"Eur. J. Neurosci."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/0167-2789(93)90009-P","article-title":"A practical method for calculating largest Lyapunov exponents from small data sets","volume":"65","author":"Collins","year":"1993","journal-title":"Phys. D Nonlinear Phenom."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/j.jfranklin.2006.08.004","article-title":"Optimal fractal-scaling analysis of human EEG dynamic for depth of anesthesia quantification","volume":"344","author":"Gifani","year":"2007","journal-title":"J. Franklin Inst."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/S0010-4825(01)00031-2","article-title":"Detrended ductuation analysis of EEG in sleep apnea using MIT\/BIH polysomnography data","volume":"32","author":"Lee","year":"2002","journal-title":"Comput. Biol. Med."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/0010-4825(88)90041-8","article-title":"Fractals and the analysis of waveforms","volume":"18","author":"Katz","year":"1988","journal-title":"Comput. Biol. Med."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.bspc.2016.05.004","article-title":"Discrimination and classification of focal and non-focal EEG signals using entropy-based features in the EMD-DWT domain","volume":"29","author":"Das","year":"2016","journal-title":"Biomed. Signal Process Control"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"6573","DOI":"10.3390\/e16126573","article-title":"Automatic sleep stages classification using EEG entropy features and unsupervised pattern analysis techniques","volume":"16","author":"Peluffo","year":"2014","journal-title":"Entropy"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"47","DOI":"10.3389\/fnins.2016.00047","article-title":"Classification of single normal and Alzheimer\u2019s disease individuals from cortical sources of resting state EEG rhythms","volume":"10","author":"Babiloni","year":"2016","journal-title":"Front. Neurosci."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1159\/000486870","article-title":"Healthy and Pathological Brain Aging: From the Perspective of Oscillations, Functional Connectivity, and Signal Complexity","volume":"75","author":"Ishii","year":"2018","journal-title":"Neuropsychobiology"},{"key":"ref_56","first-page":"3","article-title":"Electroencephalography in the elderly","volume":"52","author":"Davidson","year":"2012","journal-title":"Neurodiagnostic J."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1402","DOI":"10.1111\/j.1460-9568.2004.03580.x","article-title":"The frontal predominance in human EEG delta activity after sleep loss decreases with age","volume":"20","author":"Knoblauch","year":"2004","journal-title":"Eur. J. Neurosci."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"803507","DOI":"10.3389\/fnins.2021.803507","article-title":"Sleep Quality and Electroencephalogram Delta Power","volume":"15","author":"Long","year":"2021","journal-title":"Front. Neurosci."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1175","DOI":"10.5664\/jcsm.9156","article-title":"Differences in sleep measures and waking electroencephalography of patients with insomnia according to age and sex","volume":"17","author":"Hong","year":"2021","journal-title":"J. Clin. Sleep Med."},{"key":"ref_60","unstructured":"Barracca, N. (2022, May 10). The Brain-Sleep Connection: GCBH Recommendations on Sleep and Brain Health. Available online: https:\/\/www.ageuk.org.uk\/globalassets\/age-ni\/documents\/reports-and-publications\/reports-and-briefings\/health--wellbeing\/gcbh\/gcbh_sleep-brain-connection.pdf."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/9\/2811\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:35:04Z","timestamp":1760106904000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/9\/2811"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,28]]},"references-count":60,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2024,5]]}},"alternative-id":["s24092811"],"URL":"https:\/\/doi.org\/10.3390\/s24092811","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2024,4,28]]}}}