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At least 19 recordsLinked to original sources

PubMed2026

A smartphone-integrated plasmonic biosensor for amplification-free detection of African swine fever virus.

African Swine Fever Virus (ASFV) poses a catastrophic threat to global swine production, with recent outbreaks across Europe, Asia, and the Caribbean, significantly elevating the biosecurity risk to the United States' billion-dollar pork industry. Current diagnostic gold standards are laboratory-dependent and introduce critical delays in outbreak response. To address this gap, a plasmonic biosensor based on functionalized gold nanoparticles (GNPs) was developed for the rapid, amplification-free detection of ASFV. GNPs were surface-functionalized with 11-mercaptoundecanoic acid (MUDA) and combined in situ with ASFV-specific oligonucleotide probes targeting a conserved region of the p72 (B646L) gene. The detection mechanism relies on acid-induced aggregation: hybridization of target ASFV DNA to the probe generates a rigid duplex that shields the nanoparticles from acid-induced destabilization, maintaining a ruby-red color, whereas in the absence of target DNA the GNPs aggregate, producing a visible red-to-blue color shift. The optimized plasmonic biosensor demonstrated 100% analytical specificity, with no cross-reactivity against a panel of 19 non-target bacterial genomic DNA samples representative of the swine environment. Detection limits determined by the IUPAC 3σ criterion were 285 copies per reaction for Probe 1 and 402 copies per reaction for Probe 2, within the same order of magnitude as the qPCR reference assay run on the same dilution series (approximately 312 copies per reaction) under the experimental conditions used here. A smartphone-based Bio-Analytics App employing an RGB color-conversion algorithm served as a quantitative reader, yielding signal-to-noise ratios (S/N) that strongly correlated with benchtop spectrophotometric readings (A520/A620 ratio, R2 = 0.96) and achieved diagnostic concordance with qPCR binary calls. This platform offers a robust and low-cost (∼$2 per test), amplification-free approach to ASFV screening with potential for point-of-need deployment, subject to future validation in clinical specimens.

Journal Article↗

PubMed2026

Aptamer-Based Platforms for Human Aging Biomarkers: Multiplexed Proteomics, Biosensors and Translational Perspectives.

Aptamer-based multiplexed proteomic platforms, especially the SOMAmer-based SomaScan assay, are widely used for large-scale discovery of circulating biomarkers relevant to human aging. This review summarizes 42 original research articles published from 2020 through 2026 in which aptamers or aptamer-derived biosensors were used to characterize aging-related biomarkers in human samples or clinically relevant human-disease contexts. The eligible literature falls into several thematic areas: whole-plasma and organ-specific proteomic aging clocks; inflammaging and senescence-associated secretory phenotype (SASP) markers; cardiovascular, metabolic, renal, hepatic, musculoskeletal and neurodegenerative biomarker panels; and aptasensor platforms for detection of individual analytes. Only a small number of studies have compared aptamer- and antibody-based platforms in the same specimens; we tabulate these and show that median between-platform agreement is low to moderate, which constrains the pooling of findings across technologies. We also make explicit an interpretive point that is usually left implicit: because proteomic clocks are trained against chronological age, their correlation with chronological age measures fit to the training target rather than biological validity, and the informative quantity is the residual age gap. In the reviewed literature, SomaScan-based studies are concentrated in cardiovascular, neurodegenerative, frailty, and proteomic aging-clock research, whereas de novo SELEX campaigns targeting aging-specific epitopes and longitudinal human validation of wearable aptasensors were not identified. The main barriers to translation are cross-platform discordance, limited replication across ancestries, under-reported pre-analytical variability, cost, and the research-use-only status of most assays.

Humans↗

PubMed2026

PRDX1 as a novel urinary biomarker for bladder cancer: Development of an integrated fiber optic sensing platform.

In this study, integrated proteomic and transcriptomic analyses identified peroxiredoxin 1 (PRDX1) as a novel urinary biomarker for bladder cancer (BC). PRDX1 was significantly upregulated in BC tissues and was associated with poorer overall survival. In vitro experiments further demonstrated that PRDX1 promotes malignant phenotypes of BC cells, including proliferation, migration, and invasion. Silencing PRDX1 in BC cells significantly reduced the invasiveness and proliferation ability.To address the clinical need for rapid and non-invasive detection, we developed an innovative optical fiber biosensor based on surface plasmon resonance (SPR) technology for the quantitative detection of urinary PRDX1. The biosensor exhibited excellent analytical performance, including high sensitivity (limit of detection: 0.06 ng/mL), a wide linear range (0-25 ng/mL), rapid response (∼14 s), as well as good stability and selectivity. In clinical validation involving 97 BC patients and 30 healthy controls, the biosensor demonstrated outstanding diagnostic performance, with an area under the receiver operating characteristic curve (AUC) of 0.91 and an overall diagnostic accuracy of 86.6%, outperforming conventional enzyme-linked immunosorbent assay (ELISA). Collectively, this study not only identifies PRDX1 as a promising biomarker for non-invasive diagnosis and prognostic evaluation of BC, but also establishes an efficient SPR-based optical fiber sensing platform, providing new insights into both clinical detection and the functional role of PRDX1 in BC progression.

Humans↗

PubMed2025

Electrochemical Duplex Detection of E2 and E6 Genes of Human Papillomavirus Type 16 and Determination of Physical Status in High-Risk Cervical Carcinoma.

Human papillomavirus type 16 (HPV-16) is a key driver in the development of cervical carcinoma, with the integration of its genome into the host DNA marking a critical step in disease progression. Monitoring the physical state of HPV-16, particularly the transition from episomal to integrated forms, is essential for evaluating the risk of malignancy development in cervix. This study presents the development of a duplex electrochemical biosensor for the simultaneous detection of the E2 and E6 genes of HPV-16. Using a one-step sandwich hybridization assay, the biosensor was able to detect HPV-16 E2 and E6 genes with a sensitivity of 8 copies/mL and 12 copies/mL respectively and distinguish between the episomal and integrated forms based on the E2/E6 ratio (cut-off 0.77, 100% sensitivity/specificity). The sensor was validated with 30 clinical cervical tissue samples, providing results comparable to qPCR method. This novel biosensor offers a rapid and efficient platform for the detection and monitoring of HPV-16, with potential applications in cervical cancer screening and prognosis.

Humans↗

PubMed2026

Metal-organic frameworks nanozyme-integrated portable microneedle patch for visual bacterial monitoring in meat.

Foodborne microbial contamination is a major global health concern, with conventional methods often being time-consuming and complex. Herein, we developed a novel portable biosensor by integrating microneedle patch technology and a metal-organic framework (Fe/Cu-NBDC MOF) nanozyme, enabling rapid, on-site, visual detection of bacteria in meat. The sensing system works by encapsulating aptamer-functionalized MOF nanozymes within a hydrogel patch, where their catalytic sites are initially blocked by the aptamer. In the presence of Staphylococcus aureus (S. aureus) as the target, the specific aptamer's binding to bacteria exposes numerous catalytic sites, further activating the chromogenic reaction of the tetramethylbenzidine‑hydrogen peroxide (TMB-H₂O₂) system, enabling visual detection of S. aureus. The biosensor demonstrates a detection limit of 82 CFU/mL with excellent specificity to successfully apply to commercial mutton. By integrating sampling, enrichment, and visual detection into a single compact device, this platform offers a practical, efficient solution for rapid on-site screening of foodborne pathogens.

Biosensing Techniques↗

PubMed2026

Colorimetric gold nanosensors for monitoring protein aggregation: implications for Alzheimer's disease.

Alzheimer's disease (AD) is the leading cause of dementia worldwide. It remains a major public health challenge due to the lack of early diagnostic tools and effective disease-modifying therapies. Molecularly, AD is characterized by extracellular amyloid-β (Aβ) plaques and intracellular Tau tangles, as well as soluble oligomers that are likely the neurotoxic species. However, the transient and heterogeneous nature of these oligomers makes them difficult to detect using conventional biosensing approaches. Nanomaterial-based colorimetric biosensors have emerged as promising platforms for detecting protein aggregates and discovering aggregation inhibitors. Specifically, the localized surface plasmon resonance properties of metallic nanomaterials can enable rapid, label-free, and visually detectable colorimetric sensing of molecular interactions. These features can be leveraged to monitor protein aggregation processes in real time and achieve high-throughput screening of aggregation inhibitors, which may collectively enable early detection and timely intervention of AD progression. This Review Article presents the design and engineering of gold-nanomaterial-based colorimetric biosensors for monitoring protein aggregation and highlights the current challenges and emerging opportunities for applying these nanosensors to combat AD.

Journal Article↗

PubMed2025

Leveraging bioorthogonal conjugation for alpha synuclein fibril surveillance.

Alpha synuclein (α-syn) amyloid fibrils are associated with various neurodegenerative diseases. To better understand the molecular and cellular basis for α-syn fibril persistence and spread, we implemented a fluorophore labeling strategy to surveil pre-formed α-syn fibrils in solution and in cells. We leveraged amber codon mediated incorporation of a tetrazine-based artificial amino acid (TetV2.0) to install a cyclooctene-conjugated Janeliaflour, JF549, at four sites on human α-syn: residues 4, 60, 96 and 136. Fast coupling occurred under mild buffer conditions and in the presence of the disease-associated cofactor and cytotoxic lipid, psychosine. Labeled fibrils retained their polymorphic features, seeded the growth of new fibrils in vitro, and induced the seeding of positive puncta in α-syn FRET biosensor HEK293T cells. This allowed simultaneous tracking of exogenous and endogenous α-syn aggregates in biosensor cells, and their localization within the cells. In doing so, our approach facilitates more detailed mechanistic investigation of α-syn aggregates.

Synuclein↗

PubMed2026

Dual functional genomics reveals a broad and convergent landscape of asciminib resistance in BCR::ABL1.

BACKGROUND: Drug resistance is a constantly evolving challenge. The allosteric inhibitor asciminib is a novel therapy for chronic myelogenous leukemia (CML) that targets the myristoyl pocket of the BCR::ABL1 kinase. While it can overcome resistance to active-site inhibitors like imatinib, new resistance mutations to asciminib are emerging. The complete landscape of these mutations, particularly those outside the kinase domain or those arising from epistatic interactions between mutations, are not well understood. METHODS: This study employed a dual functional genomics approach in CML cell line models. A high-throughput adenosine base editing (ABE) screen was used to identify broad hotspots of asciminib resistance across the entire BCR::ABL1 protein. Deep mutational scanning (DMS) was then used to create a high-resolution map of all possible amino acid changes within these hotspots. An "edit-on-edit" screen was performed to investigate epistasis by introducing a library of mutations into a cell line that was pre-edited to incorporate the common imatinib-resistance mutation, Y253H. Finally, a novel Förster resonance energy transfer (FRET) biosensor was developed to measure the conformational state of BCR::ABL1 in live cells and link it to drug sensitivity. RESULTS: The screens identified 279 asciminib resistance mutations and revealed resistance hotspots distributed across the SH3, SH2, and kinase domains, in contrast to imatinib resistance, which is largely confined to the kinase domain. The study uncovered a potent epistatic interaction between a mutation in the SH3 domain (V73A) and a mutation in the kinase domain P-loop (Y253H), which synergistically conferred high-level resistance. The FRET biosensor demonstrated that asciminib resistance mutations tend to destabilize the "closed" inactive conformation of the ABL1 kinase. CONCLUSIONS: The landscape of asciminib resistance is broader and more complex than previously appreciated, involving mutations across multiple domains that disrupt ABL1 autoinhibition. Epistasis between mutations acquired during sequential therapies can create unexpected and potent resistance. However, these diverse genetic resistance mechanisms converge on a single biophysical measurement of the openness of the active ABL1 conformation. This provides a unified framework for understanding asciminib resistance and underscores the need for routine clinical resistance monitoring to include the SH3 and SH2 domains in first line and later line therapy.

Fusion Proteins, bcr-abl↗

PubMed2025

Aggregation-induced Electrochemiluminescence of AgNCs Enhanced with AuNPs@MXene Composites for Ultrasensitive Detection of microRNA.

MXene, a two-dimensional nanomaterial, has metal conductivity, high electronegativity, functionalized with surface groups, which make it widely applicable in catalysis and biosensing. However, studies on the principle of enhanced electrochemiluminescence (ECL) by MXene composites and the improvement of their performance in catalyzing the ECL reaction are still in their infancy. In this study, gold nanoparticles (AuNPs) are obtained by mild reductive reduction and loaded in situ on the Ti3C2Tx MXene surface to form the composites (AuNPs@MXene). In oxygenated PBS test buffer, AuNPs@MXene enhance the ECL emission of silver nanoclusters (AgNCs) with aggregation-induced electrochemiluminescence (AIECL) properties as luminophore. Approximately 7.5-fold enhancement of ECL signals is obtained by using two ECL enhancement strategies: an efficient AIECL emitter and a co-reaction accelerator. The special nucleic acid structure with "Three Way Junction (TWJ)" enables an ultra-sensitive detection of microRNA, providing an efficient and ultra-sensitive method for microRNA detection. The biosensor achieves a wide detection range of microRNA-21 from 100 aM to 1 nM, with a low detection limit of 31 aM, and exhibits excellent stability, selectivity and high reproducibility in real samples.

MicroRNAs↗

PubMed2026

From host response to genomic targets: electrochemical biosensing of tuberculosis biomarkers.

Tuberculosis (TB) remains one of the leading causes of death from a single infectious agent worldwide, with timely diagnosis continuing to be a major challenge, particularly in resource-limited settings. Conventional TB diagnostic methods are limited by low sensitivity, long turnaround times, and an inability to reliably differentiate latent from active disease. Biomarker-based diagnostic strategies have therefore gained increasing attention as they offer the potential to improve early detection, disease differentiation, and treatment monitoring. Herein, we examine electrochemical biosensing strategies for TB diagnostics using a biomarker-class-driven framework, covering host-response biomarkers (IFN-γ and TNF-α), pathogen-derived antigens (ESAT6, CFP10, CFP10-ESAT6, MPT64, Ag85, HspX and LpqH), cell-wall signatures and whole-cell markers (LAM and whole cell Mtb), and genomic markers (Mtb DNA and IS6110). Through structured comparison of recognition elements, biointerface designs, signal amplification strategies, electrochemical techniques, matrices, and validation levels, this review identifies the most promising technical approaches for different TB biomarker classes. It further highlights key translational bottlenecks, including limited clinical validation, buffer-based testing, complex multistep amplification, redox-probe dependence, matrix fouling, and insufficient evidence of manufacturability. This review therefore provides practical guidance for developing electrochemical TB biosensors that are analytically sensitive, clinically relevant, and suitable for decentralized diagnostic applications.

Biosensing Techniques↗

PubMed2026

Artificial neural network data fusion-mediated dual-mode sensor based on Fe3O4@PdIr for Salmonellatyphimurium detection in food.

Salmonella Typhimurium (S. typhimurium) is a major foodborne pathogen that poses a serious threat to public health. In this study, a colorimetric/electrochemical dual-mode biosensor assisted by artificial neural network (ANN) was developed for the sensitive detection of S. typhimurium. Fe3O4@PdIr nanocomposites with enhanced peroxidase-like activity and electrochemical performance were prepared and conjugated with an aptamer specific to S. typhimurium to obtain Fe3O4@PdIr-Apt. Through the sandwich binding of Fe3O4@PdIr-Apt and Apt to the target, the nanocomposites were attached to microplates or Au electrodes, thereby generating colorimetric and electrochemical signals. The ANN model deeply resolved the complex nonlinear relationship between the dual signals, enabling mutual correction and ultimately performing data fusion to output a single detection result, which significantly reduced the mean square error while improving detection sensitivity and reliability. This sensor exhibited a wide linear range of 2.7-2.7 × 108 CFU/mL and a low detection limit of 1.66 CFU/mL. Additionally, this method was successfully applied to the detection of S. typhimurium in pork and milk, with a recovery rate of 95.19% ∼ 104.07%. It indicated that the constructed sensor holds great practical potential for S. typhimurium detection.

Neural Networks, Computer↗

PubMed2026

Bridging Organ-on-a-Chip and Omics: A Multi-Dimensional Frontier in Biomedical Research.

Organ-on-a-Chip (OOC) technology offers a powerful platform for replicating human tissue-specific microenvironments, thereby narrowing the translational gap between conventional biomedical models and actual human physiology. Concurrently, omics technologies deliver comprehensive molecular-level insights into biological systems. This review highlights the transformative potential of integrating OOC platforms with high-throughput omics methodologies. We systematically examine the classification, structural configurations, and engineering principles underlying OOC systems, alongside the defining attributes of key omics domains-genomics, transcriptomics, proteomics, and metabolomics. The convergence of dynamic OOC models with advanced omics technologies enables high-resolution, multi-dimensional analyses across numerous biomedical applications, including drug metabolism, disease mechanisms, environmental toxicity assessments, and host-microbiome interactions. This interdisciplinary integration is driving a paradigm shift in precision and translational medicine. However, several challenges remain to be addressed, such as the development of whole-organ mimetics, adaptation of sample collection techniques, and real-time artificial intelligence-based integration of biosensor data with multi-omics datasets. Addressing these hurdles will be vital for unlocking the full potential of this technological synergy in biomedical science.

Multiomics↗

PubMed2025

Bacteriophages as a modern diagnostic tool: innovations, applications and challenges.

Bacteriophages, viruses that specifically infect bacteria, have emerged as a valuable tool in diagnostics due to their unique specificity and adaptability. This review explores the diverse applications of bacteriophages in diagnostic methods, from traditional phage typing to advanced molecular techniques such as phage display and PCR-based diagnostics. It highlights their use in identifying bacterial strains, monitoring fermentation processes, and diagnosing critical conditions like tuberculosis, MRSA infections, and cancer. Innovations such as phage-based biosensors and reporter phages enhance the speed and precision of diagnostics, offering significant advantages over traditional methods. Challenges, including bacterial resistance and immune responses to phages, are also discussed alongside strategies for mitigation, such as phage cocktails and engineering. Integrating phage technology with modern bioscience holds promise for addressing antibiotic resistance and revolutionizing clinical and industrial diagnostics. This comprehensive analysis underscores the potential of bacteriophages to transform the diagnostic landscape while identifying areas requiring further research and development.

Bacteriophages↗

PubMed2026

In silico analysis of metal resistance genes in Pseudomonas extremaustralis 2E-UNGS: Genomic insights and safety assessment for wastewater biotreatment.

Pseudomonas extremaustralis 2E-UNGS is a non-pathogenic strain isolated from the polluted Reconquista River basin (Buenos Aires Metropolitan Area, Argentina), with a 20-year history of study focused on its survival strategies that have enabled its application in various processes such as waste biotreatment and biosensing. Regarding bacterial-metal interactions, P. extremaustralis 2E-UNGS is capable of biosorbing Cd(II), Zn(II), and Cu(II), and biotransforming Cr(VI) to Cr(III), facilitating both the removal of these metals from aqueous systems and their use in biosensor development. The complete circular chromosome (6,372,594 bp) has been annotated in the NCBI GenBank under accession number NZ_CP091043.1. The aim of this work was to perform an in-depth exploration of the P. extremaustralis 2E-UNGS genome to support the optimization of sustainable bioprocesses within the One Health framework. To this end, the integration of experimental evidence with a detailed in silico analysis of key genes involved in metal-microorganism interactions, antibiotic resistance, and their interconnections provides valuable insights for the optimization of future biotechnological applications. Considering its antibiotic resistance profile, together with the activation of efflux pumps induced by metal stimuli-particularly observed under Zn(II) exposure-P. extremaustralis 2E-UNGS can be regarded as suitable for the design of confined bioreactor processes, minimizing the risk of potential accidental environmental releases. Therefore, modulation of gene expression emerges as a promising approach to enhance the efficiency of metal-loaded wastewater biotreatments.

Pseudomonas↗

PubMed2026

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans↗

PubMed2026

Advanced mitigation strategies for acrylamide formation in foods: Mechanistic insights, emerging innovations, and future perspectives.

Acrylamide is a heat-induced contaminant formed predominantly in carbohydrate-rich foods during high-temperature processing, posing significant concerns due to its potential carcinogenic, neurotoxic, and genotoxic effects. This review critically examines the mechanisms of acrylamide formation, emphasizing the role of the Maillard reaction and key precursors such as asparagine and reducing sugars, along with the influence of processing conditions including temperature, time, pH, and moisture. Various mitigation strategies are comprehensively discussed, ranging from raw material selection and genetic approaches to enzymatic treatments such as asparaginase and the application of natural and chemical inhibitors. Advances in processing technologies, including optimization of conventional thermal methods and emerging non-thermal techniques such as cold plasma and ultrasound, are evaluated for their effectiveness. The review also highlights the role of food additives, functional ingredients, and fermentation in reducing acrylamide formation. Furthermore, recent developments in analytical techniques, including chromatographic methods, biosensors, and artificial intelligence-based predictive models, are explored for improved detection and control. Risk assessment, toxicological implications, and global regulatory frameworks are also examined. Finally, future perspectives focusing on genetic engineering, personalized nutrition, and digital technologies such as AI and blockchain are discussed to support sustainable and industry-applicable mitigation strategies.

Acrylamide↗

PubMed2026

Integrated salivary proteomic and metabolomic analyses reveal molecular characterization and novel biomarker panels of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a respiratory disorder characterized by chronic inflammation, oxidative stress, and metabolic dysregulation. The lack of convenient and easily-accessible non-invasive diagnostic approaches remains a major clinical challenge. This study applied an integrated saliva-based proteomic and untargeted metabolomic strategy to identify potential biomarkers for COPD classification. Comprehensive multi-omics analyses identified 225 differentially abundant proteins and 60 differentially abundant metabolites between patients with COPD and healthy controls, including 24 biologically relevant endogenous metabolites. Functional enrichment analyses revealed pronounced dysregulation of mitochondrial energy metabolism, redox homeostasis, lipid remodeling, and inflammatory-related pathways in COPD. By integrating salivary proteomic and metabolomic biomarkers, a stepwise feature selection combined with LASSO logistic regression was used to construct diagnostic models, yielding an optimized biomarker panel consisting of 11 proteins and 2 endogenous metabolites. This integrated model achieved excellent diagnostic performance, with an area under the ROC curve of 0.96. Collectively, these findings demonstrate that integrated salivary proteomic and metabolomic profiling provides a robust, non-invasive approach for COPD classification and offers a promising foundation for the development of biosensor-based diagnostic platforms and early disease detection. SIGNIFICANCE: Chronic obstructive pulmonary disease (COPD) remains a major global health burden. Current diagnostic approaches rely largely on spirometry and clinical assessment, which are limited in sensitivity for early-stage disease and unsuitable for large-scale screening. This study employs an integrated saliva-based proteomic and metabolomic strategy to identify non-invasive biomarkers for COPD classification. Our findings reveal coordinated dysregulation of mitochondrial energy metabolism, redox homeostasis, and lipid remodeling in COPD, highlighting the interconnected roles of metabolic reprogramming, oxidative stress, and inflammation in disease pathophysiology. Notably, a robust diagnostic panel comprising 11 proteins and 2 endogenous metabolites was established, achieving excellent classification performance (AUC of 0.96). To our knowledge, the integrated application of salivary proteomics and metabolomics for COPD diagnosis remains largely unexplored, underscoring the significance and translational potential of our findings.

Humans↗

PubMed2026

Seeing and Feeling DNA Methylation: Single-Molecule Biophysics Meets Machine Learning.

DNA methylation at 5-methylcytosine (5mC) is crucial for embryonic development and cellular function, while aberrant patterns strongly drive disease onset and progression. Its reversible nature offers substantial therapeutic potential, emphasizing the need for precise, context-specific genome wide 5mC mapping. Conventional techniques such as bisulfite sequencing and ensemble biosensor assays are hindered by DNA degradation, amplification bias, high cost, and inability to resolve single-molecule structural and mechanical effects of methylation. This review examines advances in single-molecule biophysical methods (nanopore sensing, smFRET, optical/magnetic tweezers, and AFM) that provide direct, label-free/minimally invasive 5mC detection, along with quantitative insights into DNA conformation, mechanics, and protein-DNA interactions. These techniques complement traditional methylome mapping by linking genomic localization to molecular mechanisms. Emerging machine-learning approaches are revolutionizing analysis, particularly in nanopore sensing, while promising applications in smFRET, tweezers, and AFM address throughput and reproducibility challenges. Their convergence promises scalable, high-resolution epigenetic profiling, advancing precision epigenomics toward clinical application.

DNA Methylation↗