{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T03:44:37Z","timestamp":1782704677759,"version":"3.54.5"},"reference-count":24,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T00:00:00Z","timestamp":1782432000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"MMWR Ltd."}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: Biological ageing is accompanied by progressive alterations in mitochondrial metabolism, microvascular function, and thermoregulation. These processes collectively influence tissue heat production and dissipation, reflecting integrated metabolic, vascular, and thermoregulatory activity measurable at the physiological level. Passive microwave radiometry (MWR) provides a non-invasive, radiation-free method for detecting deep-tissue bioenergy emissions, complementing surface infrared thermography. To evaluate a thermophysiological Bioenergetic Index (BEI), derived from deep-tissue microwave emission, surface temperature, and their spatial and deep\u2013surface relationships, as a candidate age-referenced thermophysiological marker associated with chronological ageing. Methods: Breast thermophysiology measurements from 36,391 women aged 20\u201380 years were analysed using data collected during routine clinical assessments. Supervised machine-learning models were trained exclusively on thermal features, with chronological age used only as the prediction target. Model performance was assessed using mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). In addition, data were aggregated into 5-year age bins to evaluate population-level ageing trajectories. Results: At the individual level, models predicted chronological age with MAE \u2248 3.5 years, RMSE \u2248 5.4 years, and R2 \u2248 0.76. Aggregation into 5-year age bins revealed a robust nonlinear ageing trajectory characterised by midlife decline and late-life stabilisation. The increased correspondence at the grouped level reflects reconstruction of the population-level ageing trajectory rather than improved individual-level prediction accuracy, as averaging reduces inter-individual variability. Conclusions: These findings demonstrate a strong ageing-related signal in female breast thermophysiology and support thermophysiology as a candidate age-referenced physiological marker, pending longitudinal and outcome-based validation. The present analysis is cross-sectional and requires longitudinal validation before diagnostic or prognostic interpretation.<\/jats:p>","DOI":"10.3390\/diagnostics16131994","type":"journal-article","created":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T02:16:44Z","timestamp":1782699404000},"page":"1994","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Thermophysiological BioEnergy Index as a Biomarker of Biological Ageing: A Large-Scale Microwave Radiometry Study"],"prefix":"10.3390","volume":"16","author":[{"given":"Igor","family":"Goryanin","sequence":"first","affiliation":[{"name":"School of Informatics, University of Edinburgh, Edinburgh EH8 9YL, UK"},{"name":"IQANOVA Ltd., Edinburgh EH10 5LZ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0997-8721","authenticated-orcid":false,"given":"Larion","family":"Popov","sequence":"additional","affiliation":[{"name":"MMWR Ltd., Edinburgh EH10 5LZ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9925-9271","authenticated-orcid":false,"given":"Alexander","family":"Tarakanov","sequence":"additional","affiliation":[{"name":"Independent Researcher, Rostov-on-Don 344022, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4353-8962","authenticated-orcid":false,"given":"Sergey G.","family":"Vesnin","sequence":"additional","affiliation":[{"name":"MMWR Ltd., Edinburgh EH10 5LZ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-1943-0430","authenticated-orcid":false,"given":"Christoforos","family":"Galazis","sequence":"additional","affiliation":[{"name":"MMWR Ltd., Edinburgh EH10 5LZ, UK"},{"name":"Department of Bioengineering, Imperial College, London SW7 2AZ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8764-2441","authenticated-orcid":false,"given":"Batyr","family":"Osmonov","sequence":"additional","affiliation":[{"name":"Medical Center, Kyrgyz State Medical Academy Named After I.K. Akhunbaev, Bishkek 720020, Kyrgyzstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bob","family":"Damms","sequence":"additional","affiliation":[{"name":"MMWR Ltd., Edinburgh EH10 5LZ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexander","family":"Losev","sequence":"additional","affiliation":[{"name":"Independent Researcher, Volgograd 400062, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sanja","family":"Mogy","sequence":"additional","affiliation":[{"name":"Mogy Clinics, 1236 Trzin, Slovenia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Irina V.","family":"Goryanin","sequence":"additional","affiliation":[{"name":"MMWR Ltd., Edinburgh EH10 5LZ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1038\/s43587-022-00252-6","article-title":"A complex systems approach to aging biology","volume":"2","author":"Cohen","year":"2022","journal-title":"Nat. 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