{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T21:04:29Z","timestamp":1791839069291,"version":"4.3.4"},"reference-count":45,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2026,6,21]],"date-time":"2026-06-21T00:00:00Z","timestamp":1782000000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biosensors"],"abstract":"<jats:p>The development of new technologies enabling rapid, frequent, and reagent-free monitoring of kidney function is recognized as being of paramount importance. In this work, mid-(MIR) and near-infrared (NIR) spectroscopy were compared for the prediction of key renal biomarkers\u2014creatinine, urea and albumin\u2014using 54 serum solutions mimicking the biochemical profiles of five stages of chronic kidney disease (CKD). MIR spectra were acquired in a high-throughput microplate platform after a simple dehydration step, while the NIR spectra were obtained directly from liquid serum using a fiber optic probe. After evaluating several spectral pre-processing methods and targeted spectral regions, excellent regression models (R2 &gt; 0.9 for the best models) were obtained for the three biomarkers. MIR provided highly accurate urea predictions, whereas optimized NIR sub-regions enabled excellent estimation of creatinine and albumin. Both MIR and NIR, associated with supervised classification methods, enabled us to successfully distinguish healthy from diseased profiles and to identify the diseases state with AUC &gt; 0.93. These findings highlight the complementary value of MIR and NIR spectroscopy for kidney disease assessment and their potential integration into point-of-care diagnostic systems.<\/jats:p>","DOI":"10.3390\/bios16060347","type":"journal-article","created":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T18:35:05Z","timestamp":1782239705000},"page":"347","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Prediction of Chronic Kidney Disease Based on Simulated Serum Analysis by Vibrational Spectroscopy"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-6543-8205","authenticated-orcid":false,"given":"Diogo","family":"Serrano","sequence":"first","affiliation":[{"name":"iBB\u2014Institute for Bioengineering and Biosciences, i4HB\u2014The Associate Laboratory Institute for Health and Bioeconomy, IST\u2014Instituto Superior T\u00e9cnico, Universidade de Lisboa, Av. Rovisco Pais, n\u00ba1, 1049-001 Lisbon, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4295-9271","authenticated-orcid":false,"given":"Paulo","family":"Zoio","sequence":"additional","affiliation":[{"name":"iBB\u2014Institute for Bioengineering and Biosciences, i4HB\u2014The Associate Laboratory Institute for Health and Bioeconomy, IST\u2014Instituto Superior T\u00e9cnico, Universidade de Lisboa, Av. Rovisco Pais, n\u00ba1, 1049-001 Lisbon, Portugal"},{"name":"ISEL\u2014Instituto Superior de Engenharia de Lisboa, Instituto Polit\u00e9cnico de Lisboa, R. Conselheiro Em\u00eddio Navarro n\u00ba1, 1959-007 Lisbon, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8429-6977","authenticated-orcid":false,"given":"Lu\u00eds P.","family":"Fonseca","sequence":"additional","affiliation":[{"name":"iBB\u2014Institute for Bioengineering and Biosciences, i4HB\u2014The Associate Laboratory Institute for Health and Bioeconomy, IST\u2014Instituto Superior T\u00e9cnico, Universidade de Lisboa, Av. Rovisco Pais, n\u00ba1, 1049-001 Lisbon, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5264-9755","authenticated-orcid":false,"given":"Cec\u00edlia R. C.","family":"Calado","sequence":"additional","affiliation":[{"name":"iBB\u2014Institute for Bioengineering and Biosciences, i4HB\u2014The Associate Laboratory Institute for Health and Bioeconomy, IST\u2014Instituto Superior T\u00e9cnico, Universidade de Lisboa, Av. Rovisco Pais, n\u00ba1, 1049-001 Lisbon, Portugal"},{"name":"ISEL\u2014Instituto Superior de Engenharia de Lisboa, Instituto Polit\u00e9cnico de Lisboa, R. Conselheiro Em\u00eddio Navarro n\u00ba1, 1959-007 Lisbon, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"S117","DOI":"10.1016\/j.kint.2023.10.018","article-title":"KDIGO 2024 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease","volume":"105","author":"Stevens","year":"2024","journal-title":"Kidney Int."},{"key":"ref_2","unstructured":"World Health Organization (2025). Reducing the Burden of Noncommunicable Diseases Through Promotion of Kidney Health and Strengthening Prevention and Control of Kidney Disease. World Health Assembly Resolution WHA78.6, World Health Organization. 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