Pub Date : 2025-12-29DOI: 10.1016/j.cca.2025.120811
Biqing Chen , Zengkun Wang , Jiayin Gao, Haizhu Sun, Yinghan Zhao, Yan Liu, Jianyu Liu, Xiaohong Qiu
The occurrence and progression of endometrial cancer are closely associated with metabolic reprogramming, in which polyamine metabolites play a critical role in tumor cell proliferation and invasion. In this study, we developed a label free surface enhanced Raman scattering (SERS) detection platform based on gold nanostars (AuNS), integrated with machine learning algorithms, to achieve highly sensitive detection and precise identification of polyamine metabolites related to endometrial cancer. In complex biological matrices such as serum, the platform yielded stable and reproducible spectral fingerprints, with a detection limit at the nanogram level. Furthermore, by constructing a polyamine metabolite spectral database and introducing machine learning models, both the classification accuracy and AUC values exceeded 95 %, enabling effective discrimination of different metabolic states and mixed systems. Taken together, the AuNS SERS strategy combined with machine learning provides a rapid, non-invasive, and intelligent detection tool for the early diagnosis and metabolic subtyping of endometrial cancer, with significant clinical application potential.
{"title":"Label-free gold nanostar-based SERS with machine learning: A platform for detecting endometrial cancer-associated polyamine metabolites","authors":"Biqing Chen , Zengkun Wang , Jiayin Gao, Haizhu Sun, Yinghan Zhao, Yan Liu, Jianyu Liu, Xiaohong Qiu","doi":"10.1016/j.cca.2025.120811","DOIUrl":"10.1016/j.cca.2025.120811","url":null,"abstract":"<div><div>The occurrence and progression of endometrial cancer are closely associated with metabolic reprogramming, in which polyamine metabolites play a critical role in tumor cell proliferation and invasion. In this study, we developed a label free surface enhanced Raman scattering (SERS) detection platform based on gold nanostars (AuNS), integrated with machine learning algorithms, to achieve highly sensitive detection and precise identification of polyamine metabolites related to endometrial cancer. In complex biological matrices such as serum, the platform yielded stable and reproducible spectral fingerprints, with a detection limit at the nanogram level. Furthermore, by constructing a polyamine metabolite spectral database and introducing machine learning models, both the classification accuracy and AUC values exceeded 95 %, enabling effective discrimination of different metabolic states and mixed systems. Taken together, the AuNS SERS strategy combined with machine learning provides a rapid, non-invasive, and intelligent detection tool for the early diagnosis and metabolic subtyping of endometrial cancer, with significant clinical application potential.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"582 ","pages":"Article 120811"},"PeriodicalIF":2.9,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145877424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis and the limited sensitivity of conventional biomarkers. The emergence of nanomaterial-based biosensors offers transformative potential for precision diagnostics by integrating advanced physicochemical properties with molecular recognition strategies. This narrative review current progress in next-generation nanomaterial biosensors, including carbon nanostructures, metal–organic frameworks, quantum dots, and plasmonic nanoparticles, highlighting their roles in enhancing the sensitivity, specificity, and multiplexed detection of HCC-associated biomarkers such as alpha-fetoprotein, glypican-3, and circulating nucleic acids. We discuss innovative design principles, translational challenges, and clinical validation pathways, emphasizing how nanomaterial-enabled platforms can bridge the gap between laboratory innovation and bedside application. By critically evaluating technological advances and unmet clinical needs, this review underscores the promise of nanomaterial biosensors in enabling earlier detection, personalized monitoring, and improved prognostic assessment of HCC, ultimately advancing precision oncology.
{"title":"Next-generation nano-biosensors for hepatocellular carcinoma","authors":"Qamar Abuhassan , Kamel Saleh , R. Roopashree , Jaya Bhanu Kanwar , T. Sudhakar , Vipasha Sharma , Ashish Singh Chauhan , Saida Khaitova","doi":"10.1016/j.cca.2025.120805","DOIUrl":"10.1016/j.cca.2025.120805","url":null,"abstract":"<div><div>Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis and the limited sensitivity of conventional biomarkers. The emergence of nanomaterial-based biosensors offers transformative potential for precision diagnostics by integrating advanced physicochemical properties with molecular recognition strategies. This narrative review current progress in next-generation nanomaterial biosensors, including carbon nanostructures, metal–organic frameworks, quantum dots, and plasmonic nanoparticles, highlighting their roles in enhancing the sensitivity, specificity, and multiplexed detection of HCC-associated biomarkers such as alpha-fetoprotein, glypican-3, and circulating nucleic acids. We discuss innovative design principles, translational challenges, and clinical validation pathways, emphasizing how nanomaterial-enabled platforms can bridge the gap between laboratory innovation and bedside application. By critically evaluating technological advances and unmet clinical needs, this review underscores the promise of nanomaterial biosensors in enabling earlier detection, personalized monitoring, and improved prognostic assessment of HCC, ultimately advancing precision oncology.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"582 ","pages":"Article 120805"},"PeriodicalIF":2.9,"publicationDate":"2025-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145854671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-26DOI: 10.1016/j.cca.2025.120810
Waleed Hassan Almalki , Imran Kazmi , Alzarea Sami I , Omar Awad Alsaidan , A. Rekha , Nadeem Sayyed , Surya Nath Pandey , Sachin Kumar Singh , Gaurav Gupta , Salem Salman Almujri
Nephrolithiasis is a common urological condition characterized by kidney stone formation and complex metabolic imbalances. Uromodulin (Tamm-Horsfall protein, THP) is the principal urinary glycoprotein and a promising risk-stratifying biomarker and long-term follow-up marker for nephrolithiasis. This review examines the dual action of THP in stone disease. The normal glycosylated form of THP can inhibit the formation of calcium oxalate crystals, whereas structurally modified or hypoglycosylated THP can promote crystal adhesion and aggregation. We provide a critical comparison between conventional immunoassays and emerging THP biosensors with respect to analytical performance, selectivity, and preanalytical requirements for the measurement of urine with reasonable reliability. Electrochemical and optical biosensors, as well as nanomaterials, are increasingly being used in biosensors, with graphene, gold nanoparticles (AuNPs), and tantalum oxide. Non-Faradaic impedance (Ta2O5-passivated interdigitated electrodes) has been demonstrated to detect a 0.5 ng/mL LOD in artificial urine, and printed impedance sensors and AuNP-based lateral-flow formats have a typical LOD of 25 to 80 ng/mL and have been demonstrated using minimally processed urine (e.g., centrifugation and/or dilution), instead of crude samples. Since urinary THP is usually in the mg L−1 range, sub-ng/mL sensitivity cannot be understood in standard terms of detectability, but in terms of special use-cases (e.g., highly diluted samples, low-THP phenotypes, or quantitative low-end monitoring), it can be detected. In conclusion, we examined several significant limitations to translation, including biological variability (such as hydration status, infection, and circadian variations), the influence of the matrix, the lack of calibration and traceability, and the imperative for prospective clinical validation. Although microfluidics and digital presentation facilitate point-of-care tracking, the integration of AI/ML is not yet prevalent.
{"title":"Tamm-Horsfall protein biosensors for management of nephrolithiasis","authors":"Waleed Hassan Almalki , Imran Kazmi , Alzarea Sami I , Omar Awad Alsaidan , A. Rekha , Nadeem Sayyed , Surya Nath Pandey , Sachin Kumar Singh , Gaurav Gupta , Salem Salman Almujri","doi":"10.1016/j.cca.2025.120810","DOIUrl":"10.1016/j.cca.2025.120810","url":null,"abstract":"<div><div>Nephrolithiasis is a common urological condition characterized by kidney stone formation and complex metabolic imbalances. Uromodulin (Tamm-Horsfall protein, THP) is the principal urinary glycoprotein and a promising risk-stratifying biomarker and long-term follow-up marker for nephrolithiasis. This review examines the dual action of THP in stone disease. The normal glycosylated form of THP can inhibit the formation of calcium oxalate crystals, whereas structurally modified or hypoglycosylated THP can promote crystal adhesion and aggregation. We provide a critical comparison between conventional immunoassays and emerging THP biosensors with respect to analytical performance, selectivity, and preanalytical requirements for the measurement of urine with reasonable reliability. Electrochemical and optical biosensors, as well as nanomaterials, are increasingly being used in biosensors, with graphene, gold nanoparticles (AuNPs), and tantalum oxide. Non-Faradaic impedance (Ta<sub>2</sub>O<sub>5</sub>-passivated interdigitated electrodes) has been demonstrated to detect a 0.5 ng/mL LOD in artificial urine, and printed impedance sensors and AuNP-based lateral-flow formats have a typical LOD of 25 to 80 ng/mL and have been demonstrated using minimally processed urine (e.g., centrifugation and/or dilution), instead of crude samples. Since urinary THP is usually in the mg L<sup>−1</sup> range, sub-ng/mL sensitivity cannot be understood in standard terms of detectability, but in terms of special use-cases (e.g., highly diluted samples, low-THP phenotypes, or quantitative low-end monitoring), it can be detected. In conclusion, we examined several significant limitations to translation, including biological variability (such as hydration status, infection, and circadian variations), the influence of the matrix, the lack of calibration and traceability, and the imperative for prospective clinical validation. Although microfluidics and digital presentation facilitate point-of-care tracking, the integration of AI/ML is not yet prevalent.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"582 ","pages":"Article 120810"},"PeriodicalIF":2.9,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145849115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-26DOI: 10.1016/j.cca.2025.120803
Bandita Dutta, Rina Ray Ray
Chronic microbial diseases, often driven by biofilm formation, pose a persistent global health burden due to their complex diagnosis, resistance mechanisms, and prolonged disease courses. Conventional diagnostic methods are time-consuming and often insufficient for early, precise detection and prognosis. Recent advances in molecular diagnostics, including PCR, hybridization, next-generation sequencing, and CRISPR-based assays, have enabled rapid, non-invasive, and highly sensitive detection of pathogens and resistance markers. Complementary “omics” technologies, like genomics, proteomics, and metabolomics, provide deeper insights into disease pathways, aiding in personalized treatment strategies. Furthermore, the integration of artificial intelligence (AI) and big data analytics enhances the interpretation of complex molecular datasets, enabling pattern recognition, risk prediction, and tailored therapeutic decisions. This manuscript reviews current tools and emerging technologies for the diagnosis and prognosis of chronic microbial diseases, highlighting the transformative potential of AI-driven precision medicine to improve patient outcomes through early detection, individualized treatment, and better disease management.
{"title":"Integrating molecular diagnostics and artificial intelligence in chronic microbial disease","authors":"Bandita Dutta, Rina Ray Ray","doi":"10.1016/j.cca.2025.120803","DOIUrl":"10.1016/j.cca.2025.120803","url":null,"abstract":"<div><div>Chronic microbial diseases, often driven by biofilm formation, pose a persistent global health burden due to their complex diagnosis, resistance mechanisms, and prolonged disease courses. Conventional diagnostic methods are time-consuming and often insufficient for early, precise detection and prognosis. Recent advances in molecular diagnostics, including PCR, hybridization, next-generation sequencing, and CRISPR-based assays, have enabled rapid, non-invasive, and highly sensitive detection of pathogens and resistance markers. Complementary “omics” technologies, like genomics, proteomics, and metabolomics, provide deeper insights into disease pathways, aiding in personalized treatment strategies. Furthermore, the integration of artificial intelligence (AI) and big data analytics enhances the interpretation of complex molecular datasets, enabling pattern recognition, risk prediction, and tailored therapeutic decisions. This manuscript reviews current tools and emerging technologies for the diagnosis and prognosis of chronic microbial diseases, highlighting the transformative potential of AI-driven precision medicine to improve patient outcomes through early detection, individualized treatment, and better disease management.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"582 ","pages":"Article 120803"},"PeriodicalIF":2.9,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145848962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-26DOI: 10.1016/j.cca.2025.120804
M. Arockia Babu , A. Rekha , Kavita Goyal , Soumya V. Menon , Subhashree Ray , Prerna Uniyal , Chandana Maji , Abida Khan
Endothelial glycocalyx (eGC) degradation contributes to vascular and pulmonary dysfunction in acute lung injury (ALI). This study provides a comprehensive review of the structure of the endothelial glycocalyx (eGC) and the mechanisms underlying its injury. Additionally, it evaluates biomarkers indicative of glycocalyx disruption that have been investigated for clinical use, including syndecan-1, heparan sulfate, and hyaluronan. These biomarkers have been studied in both circulating and airway compartments, with some studies reporting signal size-dependent variations in their levels. Laboratory measurement methods, specifically immunoassays and mass spectrometry, are examined with an emphasis on preanalytical variables, analytical performance, interference, and existing deficiencies in standardization, calibration, and traceability. These deficiencies contribute to the challenges in achieving comparability across different studies. Subsequently, we assessed the evidence regarding the clinical utility of risk stratification and outcome prediction in the context of ALI/ARDS and sepsis heterogeneity, focusing on cohort characteristics, sampling intervals, and sample types. In conclusion, we propose the implementation of novel glycocalyx-stabilizing treatments and future advancements, such as multi-marker panels and their integration with microvascular imaging. Generally, the standardization of protocols and establishment of reporting systems are essential prerequisites for the incorporation of these biomarkers into routine clinical laboratory and intensive care unit workflows as reliable tools.
{"title":"Endothelial Glycocalyx biomarkers in acute lung injury","authors":"M. Arockia Babu , A. Rekha , Kavita Goyal , Soumya V. Menon , Subhashree Ray , Prerna Uniyal , Chandana Maji , Abida Khan","doi":"10.1016/j.cca.2025.120804","DOIUrl":"10.1016/j.cca.2025.120804","url":null,"abstract":"<div><div>Endothelial glycocalyx (eGC) degradation contributes to vascular and pulmonary dysfunction in acute lung injury (ALI). This study provides a comprehensive review of the structure of the endothelial glycocalyx (eGC) and the mechanisms underlying its injury. Additionally, it evaluates biomarkers indicative of glycocalyx disruption that have been investigated for clinical use, including syndecan-1, heparan sulfate, and hyaluronan. These biomarkers have been studied in both circulating and airway compartments, with some studies reporting signal size-dependent variations in their levels. Laboratory measurement methods, specifically immunoassays and mass spectrometry, are examined with an emphasis on preanalytical variables, analytical performance, interference, and existing deficiencies in standardization, calibration, and traceability. These deficiencies contribute to the challenges in achieving comparability across different studies. Subsequently, we assessed the evidence regarding the clinical utility of risk stratification and outcome prediction in the context of ALI/ARDS and sepsis heterogeneity, focusing on cohort characteristics, sampling intervals, and sample types. In conclusion, we propose the implementation of novel glycocalyx-stabilizing treatments and future advancements, such as multi-marker panels and their integration with microvascular imaging. Generally, the standardization of protocols and establishment of reporting systems are essential prerequisites for the incorporation of these biomarkers into routine clinical laboratory and intensive care unit workflows as reliable tools.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"582 ","pages":"Article 120804"},"PeriodicalIF":2.9,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145838151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-25DOI: 10.1016/j.cca.2025.120807
Yuhang Deng , Fenghao Xie , Yongjie Guan , Wenqing Wu , Sumei Han , Haoqin Jiang , Ming Guan
Background
To clarify the cerebrospinal fluid (CSF) and plasma correlation for tryptophan and its major metabolites in real clinical setting, and to explore their expression across common types of neurological disorders.
Methods
181 paired CSF and plasma samples from patients with neurological diseases and 67 plasma samples from healthy controls were collected. Tryptophan, serotonin, 5-hydroxyindoleacetic acid (5-HIAA), melatonin, and kynurenic acid (KYNA) in those samples were measured using LC-MS/MS. Age- and sex-effects on plasma levels of those analytes were evaluated in healthy control. Pearson correlation analysis was used to assess CSF and plasma correlation. Patients were grouped into neurodegenerative, demyelinating, tumors, and infectious diseases for group comparisons.
Results
CSF and plasma correlation were weak but still statistically significant for most analytes (r = 0.15–0.3, p < 0.05); but no significant correlation was observed for 5-HIAA. In healthy controls plasma tryptophan and was higher in males than in females, but 5-HIAA was higher in females. The plasma concentrations of these analytes showed no significant differences among different diseases, nor between the disease groups and the control group. However, the level of 5-HIAA were significantly lower in all disease groups compared with the control group. By contrast, CSF tryptophan and KYNA levels in patients with CNS tumors were significantly higher than in patients with other diseases.
Conclusions
Plasma tryptophan and its metabolites do not reliably reflect their CSF levels. The selective elevation of CSF tryptophan and KYNA in tumor patients may reflect tumor-associated changes in metabolism, but their biological significance requires further investigation.
背景：明确脑脊液（CSF）和血浆中色氨酸及其主要代谢物在真实临床环境中的相关性，并探讨其在常见类型神经系统疾病中的表达。方法收集181例神经系统疾病患者配对脑脊液和血浆样本，67例健康对照者血浆样本。采用LC-MS/MS检测色氨酸、血清素、5-羟基吲哚乙酸（5-HIAA）、褪黑素和犬尿酸（KYNA）含量。在健康对照中评估了年龄和性别对这些分析物血浆水平的影响。Pearson相关性分析评价脑脊液与血浆的相关性。将患者分为神经退行性疾病、脱髓鞘疾病、肿瘤疾病和感染性疾病进行组间比较。结果scsf与血浆相关性较弱，但多数分析结果仍有统计学意义（r = 0.15 ~ 0.3, p < 0.05）；但5-HIAA无显著相关性。在健康对照中，男性血浆色氨酸含量高于女性，但5-HIAA在女性中较高。这些分析物的血浆浓度在不同疾病之间没有显着差异，在疾病组和对照组之间也没有显着差异。但与对照组相比，各疾病组5-HIAA水平均显著降低。相比之下，中枢神经系统肿瘤患者脑脊液色氨酸和KYNA水平明显高于其他疾病患者。结论血浆色氨酸及其代谢物不能可靠地反映脑脊液水平。肿瘤患者脑脊液色氨酸和KYNA的选择性升高可能反映了肿瘤相关的代谢变化，但其生物学意义有待进一步研究。
{"title":"Plasma and cerebrospinal fluid correlation for tryptophan and its metabolites and their expression in neurodegenerative, demyelinating, infectious diseases and CNS tumors","authors":"Yuhang Deng , Fenghao Xie , Yongjie Guan , Wenqing Wu , Sumei Han , Haoqin Jiang , Ming Guan","doi":"10.1016/j.cca.2025.120807","DOIUrl":"10.1016/j.cca.2025.120807","url":null,"abstract":"<div><h3>Background</h3><div>To clarify the cerebrospinal fluid (CSF) and plasma correlation for tryptophan and its major metabolites in real clinical setting, and to explore their expression across common types of neurological disorders.</div></div><div><h3>Methods</h3><div>181 paired CSF and plasma samples from patients with neurological diseases and 67 plasma samples from healthy controls were collected. Tryptophan, serotonin, 5-hydroxyindoleacetic acid (5-HIAA), melatonin, and kynurenic acid (KYNA) in those samples were measured using LC-MS/MS. Age- and sex-effects on plasma levels of those analytes were evaluated in healthy control. Pearson correlation analysis was used to assess CSF and plasma correlation. Patients were grouped into neurodegenerative, demyelinating, tumors, and infectious diseases for group comparisons.</div></div><div><h3>Results</h3><div>CSF and plasma correlation were weak but still statistically significant for most analytes (<em>r</em> = 0.15–0.3, <em>p</em> < 0.05); but no significant correlation was observed for 5-HIAA. In healthy controls plasma tryptophan and was higher in males than in females, but 5-HIAA was higher in females. The plasma concentrations of these analytes showed no significant differences among different diseases, nor between the disease groups and the control group. However, the level of 5-HIAA were significantly lower in all disease groups compared with the control group. By contrast, CSF tryptophan and KYNA levels in patients with CNS tumors were significantly higher than in patients with other diseases.</div></div><div><h3>Conclusions</h3><div>Plasma tryptophan and its metabolites do not reliably reflect their CSF levels. The selective elevation of CSF tryptophan and KYNA in tumor patients may reflect tumor-associated changes in metabolism, but their biological significance requires further investigation.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"582 ","pages":"Article 120807"},"PeriodicalIF":2.9,"publicationDate":"2025-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145838150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-25DOI: 10.1016/j.cca.2025.120809
Jiahui Sun , Yuqing Jia , Xiaoxuan Wang , Zhengguo Cao , Guangxun Zhu
Chronic diseases remain major global health burdens, and early detection is essential for preventing progression and reducing complications. Saliva, a non-invasive, information-rich, and easily preserved biofluid, offers a viable alternative to invasive and costly traditional screening methods such as cytopathology and tissue biopsy. Recent advances in multi-omics technologies—including proteomics, transcriptomics, genomics, metabolomics, microbiomics, and exosome profiling—have uncovered diverse salivary biomarkers linked to oral and systemic diseases. However, the high dimensionality and complexity of these datasets require robust computational methods to extract clinically meaningful patterns. Machine learning (ML), as a key component of artificial intelligence (AI), provides such analytical capability by integrating heterogeneous data and improving biomarker-based classification performance. This review summarizes studies from 2010 to 2025 on AI-enabled saliva diagnostics, outlining major biomarker categories—including proteins, nucleic acids, metabolites, exosomes, and microbial signatures and commonly used algorithms. Key performance metrics such as accuracy (ACC), area under the receiver operating characteristic curve (AUC), sensitivity (SE), and specificity (SP) are discussed, together with methodological limitations. Current evidence supports the strong potential of ML-assisted salivary biomarker analysis to enhance early disease screening. These advances may help establish saliva as an accessible tool for large-scale prevention, particularly in resource-limited or high-risk settings.
{"title":"Revolutionizing salivary biomarkers through machine learning and artificial intelligence","authors":"Jiahui Sun , Yuqing Jia , Xiaoxuan Wang , Zhengguo Cao , Guangxun Zhu","doi":"10.1016/j.cca.2025.120809","DOIUrl":"10.1016/j.cca.2025.120809","url":null,"abstract":"<div><div>Chronic diseases remain major global health burdens, and early detection is essential for preventing progression and reducing complications. Saliva, a non-invasive, information-rich, and easily preserved biofluid, offers a viable alternative to invasive and costly traditional screening methods such as cytopathology and tissue biopsy. Recent advances in multi-omics technologies—including proteomics, transcriptomics, genomics, metabolomics, microbiomics, and exosome profiling—have uncovered diverse salivary biomarkers linked to oral and systemic diseases. However, the high dimensionality and complexity of these datasets require robust computational methods to extract clinically meaningful patterns. Machine learning (ML), as a key component of artificial intelligence (AI), provides such analytical capability by integrating heterogeneous data and improving biomarker-based classification performance. This review summarizes studies from 2010 to 2025 on AI-enabled saliva diagnostics, outlining major biomarker categories—including proteins, nucleic acids, metabolites, exosomes, and microbial signatures and commonly used algorithms. Key performance metrics such as accuracy (ACC), area under the receiver operating characteristic curve (AUC), sensitivity (SE), and specificity (SP) are discussed, together with methodological limitations. Current evidence supports the strong potential of ML-assisted salivary biomarker analysis to enhance early disease screening. These advances may help establish saliva as an accessible tool for large-scale prevention, particularly in resource-limited or high-risk settings.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"582 ","pages":"Article 120809"},"PeriodicalIF":2.9,"publicationDate":"2025-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145838152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Optimal dosing of cephalosporins in pediatric ICU patients is difficult due to high inter-individual variability in β-lactam pharmacokinetics, limited blood volume, and the lack of validated microsampling-compatible clinical assays. We developed and validated a rapid and reliable liquid chromatography-tandem mass spectrometry method to measure cefazolin concentrations in lithium-heparin plasma, plasma ultrafiltrate (unbound fraction), and capillary whole blood collected with volumetric absorptive microsampling (VAMS). This method was applied in a pilot cohort of pediatric patients. Samples were protein precipitated with cryo-cooled organic solvents, separated by reversed-phase liquid chromatography (reversed-phase HPLC) using a polar C18 column, and detected by multiple reaction monitoring (MRM) on a hybrid triple quadrupole-linear ion trap (QTRAP) mass spectrometer. Cefotaxime-D3 was used as the internal standard, and calibration curves (0.5–200 mg/L) were established for each matrix. The method was validated in accordance with ICH M10 bioanalytical guidelines for selectivity, linearity, accuracy, precision, carry-over, matrix effect, recovery, process efficiency, stability, and VAMS-specific factors (hematocrit and drying time). The total run time was 3 min, including the internal standard, with an LLOQ of 0.5 mg/L across all matrices. The coefficients of determination (R2) were > 0.995, IS-normalized matrix factors were close to 1.0, and accuracy and precision were within ±15 % at all quality control levels. Cefazolin remained stable under all preanalytical conditions studied. VAMS values were unaffected by changes in hematocrit within clinically relevant ranges. The feasibility of the multi-matrix analytical method in routine practice has been demonstrated. The multi-matrix, microsampling-compatible LC-MS/MS assay described is sensitive and specific for TDM and PK/PD studies, aimed at defining precise dosing regimens for cefazolin in neonatal and pediatric critical care settings.
{"title":"Rapid, robust LC–MS/MS quantification of cefazolin in whole blood microsamples, plasma, and plasma ultrafiltrate: Analytical method validation and preliminary clinical application in pediatric population","authors":"Arkadiusz Kocur , Agnieszka Czajkowska , Mateusz Moczulski , Anna Częczek , Małgorzata Mikaszewska-Sokolewicz","doi":"10.1016/j.cca.2025.120808","DOIUrl":"10.1016/j.cca.2025.120808","url":null,"abstract":"<div><div>Optimal dosing of cephalosporins in pediatric ICU patients is difficult due to high inter-individual variability in β-lactam pharmacokinetics, limited blood volume, and the lack of validated microsampling-compatible clinical assays. We developed and validated a rapid and reliable liquid chromatography-tandem mass spectrometry method to measure cefazolin concentrations in lithium-heparin plasma, plasma ultrafiltrate (unbound fraction), and capillary whole blood collected with volumetric absorptive microsampling (VAMS). This method was applied in a pilot cohort of pediatric patients. Samples were protein precipitated with cryo-cooled organic solvents, separated by reversed-phase liquid chromatography (reversed-phase HPLC) using a polar C18 column, and detected by multiple reaction monitoring (MRM) on a hybrid triple quadrupole-linear ion trap (QTRAP) mass spectrometer. Cefotaxime-D<sub>3</sub> was used as the internal standard, and calibration curves (0.5–200 mg/L) were established for each matrix. The method was validated in accordance with ICH M10 bioanalytical guidelines for selectivity, linearity, accuracy, precision, carry-over, matrix effect, recovery, process efficiency, stability, and VAMS-specific factors (hematocrit and drying time). The total run time was 3 min, including the internal standard, with an LLOQ of 0.5 mg/L across all matrices. The coefficients of determination (R<sup>2</sup>) were > 0.995, IS-normalized matrix factors were close to 1.0, and accuracy and precision were within ±15 % at all quality control levels. Cefazolin remained stable under all preanalytical conditions studied. VAMS values were unaffected by changes in hematocrit within clinically relevant ranges. The feasibility of the multi-matrix analytical method in routine practice has been demonstrated. The multi-matrix, microsampling-compatible LC-MS/MS assay described is sensitive and specific for TDM and PK/PD studies, aimed at defining precise dosing regimens for cefazolin in neonatal and pediatric critical care settings.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"582 ","pages":"Article 120808"},"PeriodicalIF":2.9,"publicationDate":"2025-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145846279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-24DOI: 10.1016/j.cca.2025.120806
Hsiuying Wang
Anti-N-methyl-d-aspartate receptor encephalitis (anti-NMDARE) is a severe autoimmune disorder in which the immune system attacks NMDA receptors in the brain. Early diagnosis is critical for effective intervention, and it often hinges on detecting specific antibodies. Clinical biomarkers, including electroencephalography (EEG), play a vital role in facilitating early identification. The hallmark EEG patterns of anti-NMDARE are the extreme delta brush pattern and generalized rhythmic delta activity. This paper reviews the EEG features characteristic of anti-NMDARE. In addition to EEG, the potential of microRNA (miRNA) biomarkers in diagnosing and prognosticating anti-NMDARE has garnered attention. This study reveals that both EEG and miRNA biomarkers may provide useful insights for the diagnosis and prognosis of anti-NMDARE, underscoring the importance of combining EEG and miRNA biomarkers for a more accurate and timely clinical assessment.
{"title":"Electroencephalography, microRNA, and anti-NMDA receptor encephalitis","authors":"Hsiuying Wang","doi":"10.1016/j.cca.2025.120806","DOIUrl":"10.1016/j.cca.2025.120806","url":null,"abstract":"<div><div>Anti-<em>N</em>-methyl-<span>d</span>-aspartate receptor encephalitis (anti-NMDARE) is a severe autoimmune disorder in which the immune system attacks NMDA receptors in the brain. Early diagnosis is critical for effective intervention, and it often hinges on detecting specific antibodies. Clinical biomarkers, including electroencephalography (EEG), play a vital role in facilitating early identification. The hallmark EEG patterns of anti-NMDARE are the extreme delta brush pattern and generalized rhythmic delta activity. This paper reviews the EEG features characteristic of anti-NMDARE. In addition to EEG, the potential of microRNA (miRNA) biomarkers in diagnosing and prognosticating anti-NMDARE has garnered attention. This study reveals that both EEG and miRNA biomarkers may provide useful insights for the diagnosis and prognosis of anti-NMDARE, underscoring the importance of combining EEG and miRNA biomarkers for a more accurate and timely clinical assessment.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"582 ","pages":"Article 120806"},"PeriodicalIF":2.9,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145843220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-24DOI: 10.1016/j.cca.2025.120798
Alaa H. Habib , Ziaullah Mirza Sain , Misbahuddin Rafeeq , Mohammed Matoog Karami , Hadeel A. Alsufyani , Johar Iqbal , Kamel Chaieb , Hisham N. Altayb , Muhammad Shahid Nadeem , Fahad A. Al-Abbasi , Imran Kazmi
β-Galactosidase (β-Gal) has emerged as a potential biomarker for the diagnosis of colon cancer. An increasing number of studies have been conducted to detect this enzyme in biological fluids and tissues, thereby aiding patient stratification. This review follows the developmental history of the evolution of fluorescent β-Gal biosensors from the initial design to the latest developments of using the sensors in clinical laboratories. We are highly critical of the evolution of β-Gal detection systems, where traditional probes are replaced by sophisticated Near-Infrared (NIR)-emitting probes, ratiometric sensors, and self-immolating linker structures. Rather than an isolated study, we show a chronological examination of how the probe chemistry was developed to address the constraints in the analytical performance (e.g., limit of detection, linearity, precision) and specificity toward interfering biological substrates. In addition, we review the association of β-Gal biosensing with other known colon cancer biomarkers and comment on its possible application in determining certain cancer development phases. The preanalytical standardization controls (the type of specimen used, the effect of anticoagulants, and interference of hemolysis) are critical factors to be considered to ensure reliable measurements. The hybridization of β-Gal biosensing with microfluidic technology, point-of-care diagnostics, and high-throughput level assays is suggested as the future of fast, sensitive, and quantitative testing. Although the available information is mostly preclinical, new data indicate that these biosensors can assist in risk stratification of colorectal cancer and therapy response monitoring. Lastly, we are dealing with the challenges of translation, such as assay harmonization, clinical decision limits, and standardization needed to transition these tools from research into routine laboratory practice. The current review establishes β-Gal fluorescent biosensors as promising research instruments with high potential to become laboratory medicine instruments to improve the detection of colorectal cancer and patient outcomes.
{"title":"Fluorescent β-galactosidase biosensors for colon cancer","authors":"Alaa H. Habib , Ziaullah Mirza Sain , Misbahuddin Rafeeq , Mohammed Matoog Karami , Hadeel A. Alsufyani , Johar Iqbal , Kamel Chaieb , Hisham N. Altayb , Muhammad Shahid Nadeem , Fahad A. Al-Abbasi , Imran Kazmi","doi":"10.1016/j.cca.2025.120798","DOIUrl":"10.1016/j.cca.2025.120798","url":null,"abstract":"<div><div>β-Galactosidase (β-Gal) has emerged as a potential biomarker for the diagnosis of colon cancer. An increasing number of studies have been conducted to detect this enzyme in biological fluids and tissues, thereby aiding patient stratification. This review follows the developmental history of the evolution of fluorescent β-Gal biosensors from the initial design to the latest developments of using the sensors in clinical laboratories. We are highly critical of the evolution of β-Gal detection systems, where traditional probes are replaced by sophisticated Near-Infrared (NIR)-emitting probes, ratiometric sensors, and self-immolating linker structures. Rather than an isolated study, we show a chronological examination of how the probe chemistry was developed to address the constraints in the analytical performance (e.g., limit of detection, linearity, precision) and specificity toward interfering biological substrates. In addition, we review the association of β-Gal biosensing with other known colon cancer biomarkers and comment on its possible application in determining certain cancer development phases. The preanalytical standardization controls (the type of specimen used, the effect of anticoagulants, and interference of hemolysis) are critical factors to be considered to ensure reliable measurements. The hybridization of β-Gal biosensing with microfluidic technology, point-of-care diagnostics, and high-throughput level assays is suggested as the future of fast, sensitive, and quantitative testing. Although the available information is mostly preclinical, new data indicate that these biosensors can assist in risk stratification of colorectal cancer and therapy response monitoring. Lastly, we are dealing with the challenges of translation, such as assay harmonization, clinical decision limits, and standardization needed to transition these tools from research into routine laboratory practice. The current review establishes β-Gal fluorescent biosensors as promising research instruments with high potential to become laboratory medicine instruments to improve the detection of colorectal cancer and patient outcomes.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"582 ","pages":"Article 120798"},"PeriodicalIF":2.9,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145843189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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