Pub Date : 2026-05-15Epub Date: 2026-03-06DOI: 10.1016/j.cca.2026.120945
Shaozhe Yang , Rongxiang Li , Bo Xu , Yongyong Wu , Junfeng Li , Xiuhong Fu
Preimplantation genetic testing (PGT) is a critical tool in reproductive medicine for selecting genetically healthy embryos, thereby reducing the risk of congenital disabilities. However, conventional PGT relies on invasive embryo biopsy, which carries risks of embryo damage and diagnostic challenges related to mosaicism. Non-invasive preimplantation genetic testing (niPGT), which analyzes embryonic cell-free DNA (cfDNA) from spent culture medium or blastocoel fluid, has emerged as a promising and safer alternative. This review provides a comprehensive overview of the principles, clinical applications, challenges, and future prospects of niPGT. Although some initial studies have indicated a correlation between niPGT for aneuploidy and the overall embryo or inner cell mass, its potential as an embryo sorting tool is hindered in clinical practice by the lack of reliability in its results. This issue could result in inaccurate assessments of viable embryos. Key challenges hindering its widespread adoption include low cfDNA yield leading to amplification failure, maternal and exogenous DNA contamination, the diagnostic dilemma of embryonic mosaicism, and a profound lack of standardized laboratory protocols. Future progress in the field will depend on technological innovations in cfDNA analysis, the integration of multi-omics data with artificial intelligence for comprehensive embryo assessment, and, most critically, large-scale clinical validation through randomized controlled trials. Establishing standardized guidelines and robust ethical frameworks is imperative for the responsible transition of niPGT from a promising research method to a reliable clinical tool.
{"title":"Clinical application progress and prospects of non-invasive preimplantation genetic testing (niPGT): A review","authors":"Shaozhe Yang , Rongxiang Li , Bo Xu , Yongyong Wu , Junfeng Li , Xiuhong Fu","doi":"10.1016/j.cca.2026.120945","DOIUrl":"10.1016/j.cca.2026.120945","url":null,"abstract":"<div><div>Preimplantation genetic testing (PGT) is a critical tool in reproductive medicine for selecting genetically healthy embryos, thereby reducing the risk of congenital disabilities. However, conventional PGT relies on invasive embryo biopsy, which carries risks of embryo damage and diagnostic challenges related to mosaicism. Non-invasive preimplantation genetic testing (niPGT), which analyzes embryonic cell-free DNA (cfDNA) from spent culture medium or blastocoel fluid, has emerged as a promising and safer alternative. This review provides a comprehensive overview of the principles, clinical applications, challenges, and future prospects of niPGT. Although some initial studies have indicated a correlation between niPGT for aneuploidy and the overall embryo or inner cell mass, its potential as an embryo sorting tool is hindered in clinical practice by the lack of reliability in its results. This issue could result in inaccurate assessments of viable embryos. Key challenges hindering its widespread adoption include low cfDNA yield leading to amplification failure, maternal and exogenous DNA contamination, the diagnostic dilemma of embryonic mosaicism, and a profound lack of standardized laboratory protocols. Future progress in the field will depend on technological innovations in cfDNA analysis, the integration of multi-omics data with artificial intelligence for comprehensive embryo assessment, and, most critically, large-scale clinical validation through randomized controlled trials. Establishing standardized guidelines and robust ethical frameworks is imperative for the responsible transition of niPGT from a promising research method to a reliable clinical tool.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"587 ","pages":"Article 120945"},"PeriodicalIF":2.9,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147372279","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}
Small extracellular vesicles (sEVs) have rapidly emerged as versatile mediators of intercellular communication with significant potential to transform the diagnosis and treatment of neurodegenerative diseases (NDDs). Increasing evidence shows that sEVs not only participate in the propagation of pathogenic proteins but also serve as accessible, CNS-informative carriers of molecular signatures that reflect neuronal, glial, and systemic disease processes. This dual role positions sEVs at the intersection of biomarker discovery and therapeutic innovation. In the diagnostic domain, advances in immunoaffinity capture, single-vesicle analysis, and multi-omics profiling have enabled increasingly precise characterization of neuron-, astrocyte-, and microglia-derived sEVs, revealing candidate markers for Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and related disorders. However, translation remains limited by methodological heterogeneity, a lack of large-scale validation, and the need for standardized pre-analytical and analytical pipelines aligned with the ISEV/MISEV guidelines. On the therapeutic front, native and engineered sEVs, particularly those derived from mesenchymal and neural stem cells, demonstrate promising neuroprotective effects, including the modulation of neuroinflammation; the enhancement of synaptic resilience; and the delivery of antioxidant, anti-amyloid, or gene-modifying cargo across the blood–brain barrier. Scalable GMP manufacturing, cargo-loading strategies, targeting specificity, and long-term safety remain key challenges for clinical translation. This narrative review synthesizes current advances in sEV-based biomarkers and therapeutics, outlines technological and regulatory barriers, and proposes a translational roadmap spanning mechanistic discovery, platform standardization, and integration into precision-medicine frameworks. Collectively, emerging data position sEVs as powerful tools capable of reshaping the diagnostic and therapeutic landscape of NDDs, provided that coordinated multidisciplinary efforts address the remaining gaps in validation, scalability, and regulatory readiness.
{"title":"Small extracellular vesicles as emerging biomarkers and therapeutic targets in neurodegenerative diseases","authors":"Askarova Zebo Zafarjonovna , Elmuratova Aysulu , Sanoeva Matlyuba , Hamroyev Rashid , Jurakulov Bakhrom Azamatovich , Ahmadjonov Ahmadjon , Amirullayeva Barno , Azimova Mayram Kurbanovna , Mahsudali Rohataliyev Mahmudali ugli , Iskandarova Shaxodat , Turakulov Rustam , Matrizaeva Gulnara Jumaniyazovna , Alisher Ishankulov","doi":"10.1016/j.cca.2026.120932","DOIUrl":"10.1016/j.cca.2026.120932","url":null,"abstract":"<div><div>Small extracellular vesicles (sEVs) have rapidly emerged as versatile mediators of intercellular communication with significant potential to transform the diagnosis and treatment of neurodegenerative diseases (NDDs). Increasing evidence shows that sEVs not only participate in the propagation of pathogenic proteins but also serve as accessible, CNS-informative carriers of molecular signatures that reflect neuronal, glial, and systemic disease processes. This dual role positions sEVs at the intersection of biomarker discovery and therapeutic innovation. In the diagnostic domain, advances in immunoaffinity capture, single-vesicle analysis, and multi-omics profiling have enabled increasingly precise characterization of neuron-, astrocyte-, and microglia-derived sEVs, revealing candidate markers for Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and related disorders. However, translation remains limited by methodological heterogeneity, a lack of large-scale validation, and the need for standardized pre-analytical and analytical pipelines aligned with the ISEV/MISEV guidelines. On the therapeutic front, native and engineered sEVs, particularly those derived from mesenchymal and neural stem cells, demonstrate promising neuroprotective effects, including the modulation of neuroinflammation; the enhancement of synaptic resilience; and the delivery of antioxidant, anti-amyloid, or gene-modifying cargo across the blood–brain barrier. Scalable GMP manufacturing, cargo-loading strategies, targeting specificity, and long-term safety remain key challenges for clinical translation. This narrative review synthesizes current advances in sEV-based biomarkers and therapeutics, outlines technological and regulatory barriers, and proposes a translational roadmap spanning mechanistic discovery, platform standardization, and integration into precision-medicine frameworks. Collectively, emerging data position sEVs as powerful tools capable of reshaping the diagnostic and therapeutic landscape of NDDs, provided that coordinated multidisciplinary efforts address the remaining gaps in validation, scalability, and regulatory readiness.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"587 ","pages":"Article 120932"},"PeriodicalIF":2.9,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147321407","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 : 2026-05-15Epub Date: 2026-03-04DOI: 10.1016/j.cca.2026.120942
Xiaoli Liu , Ruolan Guo , Zhan Qi , Yaodong Zhang , Xiaotun Ren , Wei Li , Xuyun Hu , Chanjuan Hao
Background
Vanishing White Matter disease (VWM) is a rare autosomal recessive leukoencephalopathy caused by biallelic variants in any of the five subunits of eukaryotic initiation factor 2B (EIF2B1–5), with varied clinical manifestations, including progressive neurological deterioration, cerebellar ataxia, and white matter abnormalities on MRI. Early and accurate diagnosis is crucial for medical interventions and genetic counseling.
Methods
We aimed to characterize the prevalence and spectrum of pathogenic variants of VWM in the Chinese population through Genetic screening for VWM mutations in 36,820 Chinese newborns from 31 hospitals across 14 provinces using next-generation sequencing. Pathogenic and likely pathogenic variants were identified and classified according to ACMG guidelines. Prevalence rates and variant spectra were analyzed.
Results
Among screened newborns, 114 carriers with 36 distinct pathogenic and likely pathogenic variants were identified, including 18 novel variants. The overall carrier frequency was 1 in 323. EIF2B2 showed the highest carrier frequency (1 in 498), with c.254 T > A/p.Val85Glu being a hotspot variant (61/74 carriers, 82.4%). The estimated prevalence rate of VWM in China was 1.12/1,000,000.
Conclusions
This large-scale screening provides valuable insights into the genetic landscape of VWM in the Chinese population, contributing to improved genetic counseling, early diagnosis, and management strategies. These findings contribute to enhancing the understanding and management of VWM in China.
背景：消失白质病（VWM）是一种罕见的常染色体隐性白质脑病，由真核起始因子2B （EIF2B1-5）的5个亚基中的任何一个双等位基因变异引起，临床表现多样，包括进行性神经功能恶化、小脑性共济失调和MRI上的白质异常。早期和准确的诊断对于医疗干预和遗传咨询至关重要。方法：我们旨在通过使用下一代测序技术对来自14个省份31家医院的36,820名中国新生儿的VWM突变进行遗传筛查，以表征中国人群中VWM致病变异的患病率和谱。根据ACMG指南确定致病和可能致病的变异并进行分类。分析了患病率和变异谱。结果：在筛查的新生儿中，114名携带者被鉴定出36种不同的致病和可能的致病变异，其中18种是新变异。总体载波频率为1 / 323。EIF2B2的载频最高（1 / 498），为c.254 T > A/p。Val85Glu是热点变型（61/74携带者，82.4%）。估计中国VWM患病率为1.12/ 100万。结论：这项大规模筛查为了解中国人群VWM的遗传格局提供了有价值的见解，有助于改进遗传咨询、早期诊断和管理策略。这些发现有助于加强对中国VWM的认识和管理。
{"title":"Genetic screening of EIF2B genes reveals mutation spectrum and predicted prevalence of vanishing white matter disease in Chinese population","authors":"Xiaoli Liu , Ruolan Guo , Zhan Qi , Yaodong Zhang , Xiaotun Ren , Wei Li , Xuyun Hu , Chanjuan Hao","doi":"10.1016/j.cca.2026.120942","DOIUrl":"10.1016/j.cca.2026.120942","url":null,"abstract":"<div><h3>Background</h3><div>Vanishing White Matter disease (VWM) is a rare autosomal recessive leukoencephalopathy caused by biallelic variants in any of the five subunits of eukaryotic initiation factor 2B (<em>EIF2B1–5</em>), with varied clinical manifestations, including progressive neurological deterioration, cerebellar ataxia, and white matter abnormalities on MRI. Early and accurate diagnosis is crucial for medical interventions and genetic counseling.</div></div><div><h3>Methods</h3><div>We aimed to characterize the prevalence and spectrum of pathogenic variants of VWM in the Chinese population through Genetic screening for VWM mutations in 36,820 Chinese newborns from 31 hospitals across 14 provinces using next-generation sequencing. Pathogenic and likely pathogenic variants were identified and classified according to ACMG guidelines. Prevalence rates and variant spectra were analyzed.</div></div><div><h3>Results</h3><div>Among screened newborns, 114 carriers with 36 distinct pathogenic and likely pathogenic variants were identified, including 18 novel variants. The overall carrier frequency was 1 in 323. <em>EIF2B2</em> showed the highest carrier frequency (1 in 498), with c.254 T > A/p.Val85Glu being a hotspot variant (61/74 carriers, 82.4%). The estimated prevalence rate of VWM in China was 1.12/1,000,000.</div></div><div><h3>Conclusions</h3><div>This large-scale screening provides valuable insights into the genetic landscape of VWM in the Chinese population, contributing to improved genetic counseling, early diagnosis, and management strategies. These findings contribute to enhancing the understanding and management of VWM in China.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"587 ","pages":"Article 120942"},"PeriodicalIF":2.9,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147369087","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 : 2026-05-15Epub Date: 2026-03-05DOI: 10.1016/j.cca.2026.120946
Bowen Su , Yanpeng Zhang , Xiaomin Shi
Patient-based real-time quality control (PBRTQC) serves as a vital supplement to quality management in clinical laboratories. Its core principle is to monitor the testing process in real time and continuously through patient test data. As artificial intelligence (AI) technology develops rapidly, AI has provided novel pathways for the innovation of PBRTQC algorithms and drives its transition from a traditional statistics-driven model to intelligent monitoring. This review systematically summarizes the progress of AI-driven PBRTQC algorithm optimization. Meanwhile, it provides a detailed account of the clinical applications of the AI-PBRTQC monitoring platform. These applications encompass timely quality control early warning, homogeneous monitoring across multiple settings, precise quality control in complex clinical settings, anomaly traceability and subsequent correction. In addition, this review offers an in-depth analysis of the challenges that arise during the practical implementation of AI-PBRTQC. These include technical limitations, shortage of professional talents, system compatibility barriers, and lagging standardization and regulation. It also explores future development trends and provides valuable references for the intelligent upgrade of PBRTQC.
{"title":"Artificial intelligence algorithm optimization and application in patient-based real-time quality control (PBRTQC)","authors":"Bowen Su , Yanpeng Zhang , Xiaomin Shi","doi":"10.1016/j.cca.2026.120946","DOIUrl":"10.1016/j.cca.2026.120946","url":null,"abstract":"<div><div>Patient-based real-time quality control (PBRTQC) serves as a vital supplement to quality management in clinical laboratories. Its core principle is to monitor the testing process in real time and continuously through patient test data. As artificial intelligence (AI) technology develops rapidly, AI has provided novel pathways for the innovation of PBRTQC algorithms and drives its transition from a traditional statistics-driven model to intelligent monitoring. This review systematically summarizes the progress of AI-driven PBRTQC algorithm optimization. Meanwhile, it provides a detailed account of the clinical applications of the AI-PBRTQC monitoring platform. These applications encompass timely quality control early warning, homogeneous monitoring across multiple settings, precise quality control in complex clinical settings, anomaly traceability and subsequent correction. In addition, this review offers an in-depth analysis of the challenges that arise during the practical implementation of AI-PBRTQC. These include technical limitations, shortage of professional talents, system compatibility barriers, and lagging standardization and regulation. It also explores future development trends and provides valuable references for the intelligent upgrade of PBRTQC.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"587 ","pages":"Article 120946"},"PeriodicalIF":2.9,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147372299","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}
Exosomes are nanosized extracellular vesicles enriched with proteins, lipids, and nucleic acids and are emerging as powerful mediators of intercellular communication with transformative potential for psychiatry. Their ability to cross the blood–brain barrier, reflect the molecular state of parent cells, and deliver functional cargo positions them as uniquely suited tools for precision diagnostics and targeted therapeutics in neuropsychiatric disorders. This narrative review synthesizes current advances in exosome biology, isolation technologies, and multi-omics profiling to evaluate their utility as biomarkers for early detection, disease stratification, and treatment monitoring across major psychiatric conditions, including depression, bipolar disorder, schizophrenia, and neurodevelopmental disorders. We further examine innovative therapeutic strategies leveraging engineered exosomes for targeted delivery of small molecules, RNA therapeutics, and gene-editing systems to neural circuits implicated in psychiatric pathophysiology. Key challenges such as standardization of isolation methods, cargo heterogeneity, and translational scalability are critically discussed alongside emerging solutions from nanotechnology and machine learning–driven biomarker discovery. By integrating mechanistic insights with translational applications, this review highlights exosomes as a promising frontier for precision psychiatry and outlines the roadmap needed to advance them toward clinical implementation.
{"title":"Harnessing exosomes for precision diagnostics and therapies in psychiatry disorders","authors":"Shaxlo Musinovna Xamidova , Achilova Donokhon , Kurbanov Obid , Rakhimova Gulnoz , Tolibov Dilshod , Tillashaykhova Khosiyat , Yazdankulova Gulnigor , Omarova Aynash , Abzairov Takhir , Shamsutdinova Guzel , Zaripova Oysara , Jorayev Shohruh , Вaratova Мexriban","doi":"10.1016/j.cca.2026.120931","DOIUrl":"10.1016/j.cca.2026.120931","url":null,"abstract":"<div><div>Exosomes are nanosized extracellular vesicles enriched with proteins, lipids, and nucleic acids and are emerging as powerful mediators of intercellular communication with transformative potential for psychiatry. Their ability to cross the blood–brain barrier, reflect the molecular state of parent cells, and deliver functional cargo positions them as uniquely suited tools for precision diagnostics and targeted therapeutics in neuropsychiatric disorders. This narrative review synthesizes current advances in exosome biology, isolation technologies, and multi-omics profiling to evaluate their utility as biomarkers for early detection, disease stratification, and treatment monitoring across major psychiatric conditions, including depression, bipolar disorder, schizophrenia, and neurodevelopmental disorders. We further examine innovative therapeutic strategies leveraging engineered exosomes for targeted delivery of small molecules, RNA therapeutics, and gene-editing systems to neural circuits implicated in psychiatric pathophysiology. Key challenges such as standardization of isolation methods, cargo heterogeneity, and translational scalability are critically discussed alongside emerging solutions from nanotechnology and machine learning–driven biomarker discovery. By integrating mechanistic insights with translational applications, this review highlights exosomes as a promising frontier for precision psychiatry and outlines the roadmap needed to advance them toward clinical implementation.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"587 ","pages":"Article 120931"},"PeriodicalIF":2.9,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147321404","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 : 2026-05-15Epub Date: 2026-03-07DOI: 10.1016/j.cca.2026.120962
Han Chen , Gang Xu , Mei-juan Zhang , Fu-rong Ying , Hai-xia Huang , He-huan Liu , Jian-rong Yang
Objectives
To evaluate the performance of magnetic beads extraction method (MGE) for quantifying plasma steroids using liquid chromatography tandem mass spectrometry (LC-MS/MS).
Methods
The evaluation encompassed calibration linearity, limit of detection (LOD), lower limit of the measuring interval (LLMI), specificity and matrix effects, trueness and recovery, intra- and inter-day precisions, repeatability, dilution consistency and stability of 23 plasma steroids extracted by MGE method were evaluated. The 23 plasma steroids were isolated and analyzed through a single sample preparation and two injections by LC-MS/MS.
Results
All 23 steroids were successfully resolved chromatographically within 12.1 min. The automated MGE method exhibited excellent linearity (R2 > 0.995 for all analytes) with coefficients of variation (CVs) ranging from 3.36% to 9.28% at LLMI and from 1.58% to 16.53% at LOD. Additionally, the CVs and average deviation for repeatability were between 0.55% and 7.11%, and − 6.57% to 10.81%, respectively. Both intra-day precision (0.88% to 8.43%) and inter-day precision (0.98% to 6.51%) satisfied the acceptance criteria. The average deviation for trueness and recovery ranged from −13.93% to 9.06%. Moreover, specificity, matrix effect, dilution consistency, and stability were distinctly identified and conformed to guideline requirements. Notably, levels of AD, T, E1, and 17-OHP were significantly elevated in patients with polycystic ovary syndrome (PCOS) (p < 0.05).
Conclusion
The automated MGE method demonstrates high efficiency and reliability for the simultaneous quantification of 23 plasma steroids, offering a promising solution for high-throughput analysis of steroid panels in clinical in the future.
{"title":"Performance evaluation of automated magnetic beads extraction method for the measurement of 23 plasma steroids using dual liquid chromatography-tandem mass spectrometry (LC-MS/MS) method","authors":"Han Chen , Gang Xu , Mei-juan Zhang , Fu-rong Ying , Hai-xia Huang , He-huan Liu , Jian-rong Yang","doi":"10.1016/j.cca.2026.120962","DOIUrl":"10.1016/j.cca.2026.120962","url":null,"abstract":"<div><h3>Objectives</h3><div>To evaluate the performance of magnetic beads extraction method (MGE) for quantifying plasma steroids using liquid chromatography tandem mass spectrometry (LC-MS/MS).</div></div><div><h3>Methods</h3><div>The evaluation encompassed calibration linearity, limit of detection (LOD), lower limit of the measuring interval (LLMI), specificity and matrix effects, trueness and recovery, intra- and inter-day precisions, repeatability, dilution consistency and stability of 23 plasma steroids extracted by MGE method were evaluated. The 23 plasma steroids were isolated and analyzed through a single sample preparation and two injections by LC-MS/MS.</div></div><div><h3>Results</h3><div>All 23 steroids were successfully resolved chromatographically within 12.1 min. The automated MGE method exhibited excellent linearity (R<sup>2</sup> > 0.995 for all analytes) with coefficients of variation (CVs) ranging from 3.36% to 9.28% at LLMI and from 1.58% to 16.53% at LOD. Additionally, the CVs and average deviation for repeatability were between 0.55% and 7.11%, and − 6.57% to 10.81%, respectively. Both intra-day precision (0.88% to 8.43%) and inter-day precision (0.98% to 6.51%) satisfied the acceptance criteria. The average deviation for trueness and recovery ranged from −13.93% to 9.06%. Moreover, specificity, matrix effect, dilution consistency, and stability were distinctly identified and conformed to guideline requirements. Notably, levels of AD, T, E1, and 17-OHP were significantly elevated in patients with polycystic ovary syndrome (PCOS) (<em>p</em> < 0.05).</div></div><div><h3>Conclusion</h3><div>The automated MGE method demonstrates high efficiency and reliability for the simultaneous quantification of 23 plasma steroids, offering a promising solution for high-throughput analysis of steroid panels in clinical in the future.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"587 ","pages":"Article 120962"},"PeriodicalIF":2.9,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388206","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 : 2026-05-15Epub Date: 2026-03-02DOI: 10.1016/j.cca.2026.120937
Obaid Afzal , Pavan Goud , Kavita Goyal , Ali Altharawi , Mubarak A. Alamri , Manal A. Alossaimi , Abdulmalik S.A. Altamimi , Surya Nath Pandey
Hepatocellular carcinoma (HCC) is frequently diagnosed at an advanced stage due to tumor heterogeneity and chronic liver damage, which reduce the performance of single biomarkers and complicate the clinical interpretation of laboratory results. The genotoxic diethylnitrosamine (DENA)-induced hepatocarcinogenesis model provides a stage-resolved and experimentally controlled framework associated with genotoxic stress, inflammation, and fibrosis, along with metabolic adaptation in target tissues and circulating biofluids. This review summarizes multi-omics data from DENA models and translational cohorts, encompassing genomics/epigenomics, transcriptomics, proteomics, metabolomics, and glycomics, as well as liquid biopsy analytes, including cell-free DNA, extracellular vesicle cargo, and circulating tumor cell markers. We integrated the dynamics of injury progression to fibrosis and tumor development at the pathway scale, highlighting multi-analyte biomarker sets that improve the differentiation between advanced fibrosis/cirrhosis and early hepatocellular carcinoma (HCC). Additionally, we examined enabling technologies in analytical techniques, including targeted mass spectrometry (MS), PCR-based methods, and clinically scalable glycoprofiling. Notably, we propose a stage-aware biomarker selection paradigm that emphasizes mechanistic consistency, analytical viability, and clinical actionability to facilitate earlier identification and longitudinal tracking. Finally, we discuss the practical implications of multicenter validation and a harmonized study design to enhance reproducibility and expedite clinical translation.
{"title":"Multi-omics biomarker detection in Diethylnitrosamine (DENA) induced hepatocellular carcinoma","authors":"Obaid Afzal , Pavan Goud , Kavita Goyal , Ali Altharawi , Mubarak A. Alamri , Manal A. Alossaimi , Abdulmalik S.A. Altamimi , Surya Nath Pandey","doi":"10.1016/j.cca.2026.120937","DOIUrl":"10.1016/j.cca.2026.120937","url":null,"abstract":"<div><div>Hepatocellular carcinoma (HCC) is frequently diagnosed at an advanced stage due to tumor heterogeneity and chronic liver damage, which reduce the performance of single biomarkers and complicate the clinical interpretation of laboratory results. The genotoxic diethylnitrosamine (DENA)-induced hepatocarcinogenesis model provides a stage-resolved and experimentally controlled framework associated with genotoxic stress, inflammation, and fibrosis, along with metabolic adaptation in target tissues and circulating biofluids. This review summarizes multi-omics data from DENA models and translational cohorts, encompassing genomics/epigenomics, transcriptomics, proteomics, metabolomics, and glycomics, as well as liquid biopsy analytes, including cell-free DNA, extracellular vesicle cargo, and circulating tumor cell markers. We integrated the dynamics of injury progression to fibrosis and tumor development at the pathway scale, highlighting multi-analyte biomarker sets that improve the differentiation between advanced fibrosis/cirrhosis and early hepatocellular carcinoma (HCC). Additionally, we examined enabling technologies in analytical techniques, including targeted mass spectrometry (MS), PCR-based methods, and clinically scalable glycoprofiling. Notably, we propose a stage-aware biomarker selection paradigm that emphasizes mechanistic consistency, analytical viability, and clinical actionability to facilitate earlier identification and longitudinal tracking. Finally, we discuss the practical implications of multicenter validation and a harmonized study design to enhance reproducibility and expedite clinical translation.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"587 ","pages":"Article 120937"},"PeriodicalIF":2.9,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147353931","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 : 2026-05-15Epub Date: 2026-03-04DOI: 10.1016/j.cca.2026.120941
Qhelen Mayline Chandra , Davini Clister , Princella Halim , Aminah Dalimunthe , Muhammad Ichwan , Dina Keumala Sari , Chindy Umaya , Nahida Aktary , Amama Rani , Moon Nyeon Park , Bonglee Kim , Rony Abdi Syahputra
Cardiovascular disease (CVD) remains the leading cause of mortality worldwide despite major advances in pharmacotherapy. Emerging evidence reveals a pivotal role for the gut–heart axis, wherein gut microbiota are and their metabolites influence CV physiology, pathology, and drug responsiveness. Dysbiosis in conditions such as hypertension, atherosclerosis, and heart failure has been associated with altered production of bioactive metabolites including trimethylamine N-oxide, short-chain fatty acids, bile acids, and tryptophan derivatives. These metabolites have been shown to modulate inflammation, endothelial function, lipid metabolism, and myocardial remodeling. This review synthesizes current knowledge on microbiome–drug interactions in CV pharmacology, including how gut bacteria may metabolize drugs (e.g., digoxin, aspirin, warfarin) and how CV agents can shape microbial communities. We further explore microbiome-targeted therapeutic strategies—probiotics, prebiotics, postbiotics, fecal microbiota transplantation, and small-molecule inhibitors of harmful metabolites—highlighting their mechanisms, preclinical evidence, and translational potential. Integrating microbiome profiling with multi-omics platforms and artificial intelligence may enable personalized treatment strategies that optimize CV outcomes. While the gut–heart axis presents an exciting frontier for drug innovation, challenges remain in establishing causality, addressing inter-individual microbiome variability, managing confounding factors such as diet and medication use, and meeting regulatory requirements. Harnessing this bidirectional relationship holds promise for transforming CV pharmacotherapy from a one-size-fits-all approach to precision medicine grounded in host–microbe interactions.
{"title":"Harnessing the gut–heart axis for cardiovascular drug innovation: microbiome, metabolites, and personalized treatment strategies","authors":"Qhelen Mayline Chandra , Davini Clister , Princella Halim , Aminah Dalimunthe , Muhammad Ichwan , Dina Keumala Sari , Chindy Umaya , Nahida Aktary , Amama Rani , Moon Nyeon Park , Bonglee Kim , Rony Abdi Syahputra","doi":"10.1016/j.cca.2026.120941","DOIUrl":"10.1016/j.cca.2026.120941","url":null,"abstract":"<div><div>Cardiovascular disease (CVD) remains the leading cause of mortality worldwide despite major advances in pharmacotherapy. Emerging evidence reveals a pivotal role for the gut–heart axis, wherein gut microbiota are and their metabolites influence CV physiology, pathology, and drug responsiveness. Dysbiosis in conditions such as hypertension, atherosclerosis, and heart failure has been associated with altered production of bioactive metabolites including trimethylamine N-oxide, short-chain fatty acids, bile acids, and tryptophan derivatives. These metabolites have been shown to modulate inflammation, endothelial function, lipid metabolism, and myocardial remodeling. This review synthesizes current knowledge on microbiome–drug interactions in CV pharmacology, including how gut bacteria may metabolize drugs (e.g., digoxin, aspirin, warfarin) and how CV agents can shape microbial communities. We further explore microbiome-targeted therapeutic strategies—probiotics, prebiotics, postbiotics, fecal microbiota transplantation, and small-molecule inhibitors of harmful metabolites—highlighting their mechanisms, preclinical evidence, and translational potential. Integrating microbiome profiling with multi-omics platforms and artificial intelligence may enable personalized treatment strategies that optimize CV outcomes. While the gut–heart axis presents an exciting frontier for drug innovation, challenges remain in establishing causality, addressing inter-individual microbiome variability, managing confounding factors such as diet and medication use, and meeting regulatory requirements. Harnessing this bidirectional relationship holds promise for transforming CV pharmacotherapy from a one-size-fits-all approach to precision medicine grounded in host–microbe interactions.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"587 ","pages":"Article 120941"},"PeriodicalIF":2.9,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147369066","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 : 2026-05-15Epub Date: 2026-03-06DOI: 10.1016/j.cca.2026.120934
Juncheng Lin , Yuyuan Wang , Biyun Zeng , Zhibing Chen , Xiaocong Lin , Tao Zeng
Cancer remains a leading cause of global mortality, with early diagnosis being pivotal for improving treatment outcomes. Traditional tissue biopsy is limited by its invasiveness, inability to capture tumor heterogeneity, and failure to support dynamic monitoring. Liquid biopsy has emerged as a non-invasive alternative, enabling the analysis of circulating tumor biomarkers (e.g., ctDNA, miRNAs, exosomes) in bodily fluids. However, current liquid biopsy technologies (e.g., NGS, ddPCR) suffer from high costs, complex workflows, poor standardization, and insufficient sensitivity for low-abundance biomarkers. The CRISPR-Cas systems, particularly Cas12a and Cas13a, have revolutionized molecular diagnostics due to their programmable sequence recognition, robust signal amplification via trans-cleavage/collateral cleavage activity, and compatibility with point-of-care testing (POCT). Cas12a targets DNA molecules, enabling sensitive detection of gene mutations and DNA methylation, while Cas13a specifically recognizes RNA, facilitating direct analysis of miRNAs and viral RNAs. Additionally, these systems have been extended to non-nucleic acid biomarkers (e.g., proteins, exosomes) through signal conversion strategies. This review summarizes the latest advances in CRISPR-Cas12a/Cas13a-based biosensors for cancer molecular diagnosis, including the detection of gene mutations, epigenetic modifications, miRNAs, tumor-associated viruses, and non-nucleic acid biomarkers. We critically analyze current challenges (e.g., PAM dependence, matrix interference, multiplexing limitations, clinical validation gaps) and discuss future perspectives, such as engineering PAM-less Cas variants, integrating nanotechnology, microfluidics, and artificial intelligence/artificial intelligence (AI), and advancing clinical standardization. This review aims to provide a comprehensive reference for the development and clinical translation of CRISPR-based cancer diagnostic technologies.
{"title":"CRISPR-Cas12a/Cas13a in cancer molecular diagnosis","authors":"Juncheng Lin , Yuyuan Wang , Biyun Zeng , Zhibing Chen , Xiaocong Lin , Tao Zeng","doi":"10.1016/j.cca.2026.120934","DOIUrl":"10.1016/j.cca.2026.120934","url":null,"abstract":"<div><div>Cancer remains a leading cause of global mortality, with early diagnosis being pivotal for improving treatment outcomes. Traditional tissue biopsy is limited by its invasiveness, inability to capture tumor heterogeneity, and failure to support dynamic monitoring. Liquid biopsy has emerged as a non-invasive alternative, enabling the analysis of circulating tumor biomarkers (e.g., ctDNA, miRNAs, exosomes) in bodily fluids. However, current liquid biopsy technologies (e.g., NGS, ddPCR) suffer from high costs, complex workflows, poor standardization, and insufficient sensitivity for low-abundance biomarkers. The CRISPR-Cas systems, particularly Cas12a and Cas13a, have revolutionized molecular diagnostics due to their programmable sequence recognition, robust signal amplification via trans-cleavage/collateral cleavage activity, and compatibility with point-of-care testing (POCT). Cas12a targets DNA molecules, enabling sensitive detection of gene mutations and DNA methylation, while Cas13a specifically recognizes RNA, facilitating direct analysis of miRNAs and viral RNAs. Additionally, these systems have been extended to non-nucleic acid biomarkers (e.g., proteins, exosomes) through signal conversion strategies. This review summarizes the latest advances in CRISPR-Cas12a/Cas13a-based biosensors for cancer molecular diagnosis, including the detection of gene mutations, epigenetic modifications, miRNAs, tumor-associated viruses, and non-nucleic acid biomarkers. We critically analyze current challenges (e.g., PAM dependence, matrix interference, multiplexing limitations, clinical validation gaps) and discuss future perspectives, such as engineering PAM-less Cas variants, integrating nanotechnology, microfluidics, and artificial intelligence/artificial intelligence (AI), and advancing clinical standardization. This review aims to provide a comprehensive reference for the development and clinical translation of CRISPR-based cancer diagnostic technologies.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"587 ","pages":"Article 120934"},"PeriodicalIF":2.9,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147376198","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 : 2026-05-15Epub Date: 2026-03-02DOI: 10.1016/j.cca.2026.120926
Qamar Abuhassan , Jamal I. Al-Nabulsi , Subbulakshmi Ganesan , Subhashree Ray , V. Ramesh Kumar , Vipasha Sharma , Ashish Singh Chauhan , Zafar Aminov
Liquid crystal (LC)-based biosensors are emerging as a powerful and versatile platform for the detection of a wide range of biomarkers. This review comprehensively examines the fundamental principles underpinning these sensors, where the precise orientation of LCs is perturbed by biological binding events, translating molecular interactions into macroscopic optical signals visible under polarized light. This review article provides an overview of LC-based diagnostic technologies. We begin by introducing the fundamental materials science of LCs and the core optical detection methods that underpin their sensing capabilities. Subsequently, we critically examine their emerging applications in clinical diagnostics, with a focused analysis of their use in detecting major diseases such as cancer, diabetes, neurological disorders, and various infectious agents. We discuss recent advancements in the design of LC biosensors for detecting proteins, nucleic acids, and small molecules, highlighting their exceptional sensitivity and label-free operation. Finally, we offer a perspective on the future development and commercialization potential of LC biosensors in the evolving diagnostic landscape.
{"title":"Liquid crystal-based biosensors for clinical diagnostics","authors":"Qamar Abuhassan , Jamal I. Al-Nabulsi , Subbulakshmi Ganesan , Subhashree Ray , V. Ramesh Kumar , Vipasha Sharma , Ashish Singh Chauhan , Zafar Aminov","doi":"10.1016/j.cca.2026.120926","DOIUrl":"10.1016/j.cca.2026.120926","url":null,"abstract":"<div><div>Liquid crystal (LC)-based biosensors are emerging as a powerful and versatile platform for the detection of a wide range of biomarkers. This review comprehensively examines the fundamental principles underpinning these sensors, where the precise orientation of LCs is perturbed by biological binding events, translating molecular interactions into macroscopic optical signals visible under polarized light. This review article provides an overview of LC-based diagnostic technologies. We begin by introducing the fundamental materials science of LCs and the core optical detection methods that underpin their sensing capabilities. Subsequently, we critically examine their emerging applications in clinical diagnostics, with a focused analysis of their use in detecting major diseases such as cancer, diabetes, neurological disorders, and various infectious agents. We discuss recent advancements in the design of LC biosensors for detecting proteins, nucleic acids, and small molecules, highlighting their exceptional sensitivity and label-free operation. Finally, we offer a perspective on the future development and commercialization potential of LC biosensors in the evolving diagnostic landscape.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"587 ","pages":"Article 120926"},"PeriodicalIF":2.9,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147353954","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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