SEARCH · Search PubMed

Results for “Molecular Diagnostic Techniques”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

708 records · Page 2Linked to original sources

PubMed2026

Diagnostic performance of intraoperative in vivo hyperspectral imaging for meningioma grading and molecular alterations: results from a prospective feasibility study.

OBJECTIVE: Hyperspectral imaging (HSI) is an emerging intraoperative, noninvasive, contrast agent-free imaging modality that enables quantitative assessment of tissue composition. The present study aimed to investigate whether HSI-derived tissue parameters correlate with WHO grade and molecular markers of aggressiveness in cranial meningiomas. METHODS: In this prospective study, intraoperative in vivo HSI was performed using the TIVITA tissue system, capturing spectral signatures between 500 and 1000 nm. Quantitative tissue parameters included tissue oxygen saturation (StO2), near-infrared perfusion index, organ hemoglobin index (OHI), and tissue water index (TWI). HSI parameters were correlated with histopathological WHO grade and molecular alterations, including CDKN2A/B deletion, TERT promoter mutation, and 1p/22q loss. Group differences were analyzed using one-way ANOVA, and diagnostic performance was assessed using receiver operating characteristic (ROC) analysis. RESULTS: Forty-six meningiomas were included, comprising WHO grade 1 (n = 35) and WHO grade 2-3 (n = 11) tumors. TWI was significantly higher in WHO grade 2-3 meningiomas compared with WHO grade 1 tumors (mean 0.49 [SD 0.12] vs 0.38 [SD 0.17], p = 0.048). ROC analysis demonstrated an area under the ROC curve (AUC) of 0.71 (95% CI 0.56-0.86, p = 0.036) for TWI in discriminating higher-grade disease. A TWI cutoff ≥ 0.367 identified all WHO grade 2-3 meningiomas with 100% sensitivity and 100% negative predictive value. In a molecular subgroup (n = 15), OHI appeared higher in tumors with homozygous CDKN2A/B deletion than in nondeleted tumors (mean 0.77 [SD 0.04] vs 0.62 [SD 0.10]). However, only 3 CDKN2A/B-deleted cases were available, and these findings should be considered descriptive. ROC analysis yielded an AUC of 0.89 (95% CI 0.71-1.00). An OHI cutoff ≥ 0.712 identified all three CDKN2A/B-deleted tumors (100% sensitivity), with 83.3% specificity and 86.7% accuracy. CONCLUSIONS: The present investigation demonstrated that HSI-derived tissue water and hemoglobin metrics provide biologically meaningful information in meningiomas. Low tissue water content appeared to rule out higher-grade diseases in this first subset cohort, while elevated hemoglobin showed a potential association with CDKN2A/B deletion in a small exploratory subgroup. These findings support the potential of HSI as a real-time noninvasive tool for intraoperative risk stratification and should be evaluated in large-scale studies. German Clinical Trials Register no. DRKS00036771 (www.drks.de).

Humans↗

PubMed2026

A MIL-88@Ru-based molecularly imprinted electrochemiluminescence sensor for highly selective and sensitive detection of enrofloxacin residues in animal-derived foods.

Using a metal-organic framework (MOF) - supported Ru(bpy)32+ (MIL-88@Ru) composite luminescent material, this study innovatively adopted electropolymerization to fabricate a molecularly imprinted polymer-based electrochemiluminescent (MIP-ECL) sensor for enrofloxacin (ENR) detection in animal-derived foods. Systematic investigation of the ECL luminescence and ENR's quenching mechanism confirmed that the sensor integrates ECL's high sensitivity and MIP's high specificity, enabling rapid and accurate recognition of ENR. Experimental results show a good linear response in the range of 1 nmol/L-20 μmol/L (R2 = 0.99), a limit of detection (LOD) as low as 0.28 nmol/L, as well as excellent selectivity and stability. Recoveries of ENR in all investigated matrices ranged from 97.7% to 106.4%, confirming the reliability of the established method. This ECL-MIP coupling strategy provides a new technical approach and application references for the efficient detection of trace pollutants in food safety and environmental monitoring fields.

Enrofloxacin↗

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

Spatially confined electrochemical strategy with DNA-assembled nanogaps for SNP detection.

Accurate detection of low-abundance single nucleotide polymorphisms (SNPs) against a large excess of homologous wild-type sequences requires both selective molecular recognition and effective transduction of small sequence differences into measurable signals. Here, we report a spatially confined electrochemical strategy that couples sequence-selective recognition with size-dependent mass-transport gating. DNA-hybridization-driven self-assembly of gold nanoparticles (AuNPs) forms a three-dimensional self-assembled electrode (3D-SAE) with a DNA-defined interparticle architecture. Competitive probes (SP/WP) convert single-base recognition into distinct molecular-size states: the SNP-associated pathway preferentially triggers a hybridization chain reaction (HCR), generating bulky AuNP-anchored HCR/methylene blue complexes (Au@HCR/MB) with reduced electrochemical accessibility through the porous 3D-SAE, whereas the wild-type pathway does not trigger HCR and maintains a high-current response from more readily accessible MB-containing species. Thus, sequence recognition is translated into a molecular-size difference and subsequently into an electrochemical signal through differential mass transport. Under buffer conditions, the platform achieved a statistically estimated detection limit of ∼0.47 fM and a quantitative range of 1 fM-100 pM. It discriminated a 0.1% mutant abundance in a fragmented genomic-DNA background. The downstream signal-transduction chemistry is enzyme-free and isothermal. This work establishes a mechanistical recognition-size-conversion-mass-transport-gating architecture for electrochemical nucleic acid analysis.

Polymorphism, Single Nucleotide↗

PubMed2026

The association between normalized creatinine-to-cystatin C ratio and incident circadian syndrome in middle-aged and older adults: a national cohort study.

BACKGROUND: Evidence on the association between the normalized creatinine-to-cystatin C ratio (NCCR) and Circadian Syndrome (CircS) in the general population remains scarce. This study aimed to investigate this relationship using data from middle-aged and elderly participants in the China Health and Retirement Longitudinal Study (CHARLS). METHODS: We conducted a cross-sectional analysis of 5,981 participants (2011 wave) and a prospective cohort analysis of 2,053 participants (2015 wave, median follow-up 4.0 years). CircS was defined as a cluster including elevated blood pressure, dyslipidemia, hyperglycemia, abdominal obesity, depression, and abnormal sleep duration. RESULTS: During follow-up, 552 participants developed incident CircS. A significant inverse association was observed: the risk of new-onset CircS progressively decreased with higher baseline NCCR levels. After adjusting for multiple confounders, each standard deviation increase in NCCR was associated with a 40% reduced odds of CircS (adjusted odds ratio = 0.60, 95% confidence interval: 0.48 to 0.75). Subgroup and dose-response analyses confirmed the robustness of this inverse relationship. CONCLUSIONS: In conclusion, a lower NCCR is independently associated with an elevated risk of developing CircS. These findings support NCCR's role as a practical serum indicator of sarcopenia and implicate muscle loss as a potentially key underlying pathway in the pathogenesis of Circadian Syndrome.

Humans↗

PubMed2026

Upscaling Genotyping by Amplicon Sequencing With GBAS-GUI.

Genotyping by amplicon sequencing (GBAS) is a relatively low-cost approach for generating genotypic data compared with established genomic methods, making it highly scalable and particularly suitable for large-scale genetic monitoring projects. However, most existing analytical pipelines are either marker-specific, insufficiently scalable, or lacking efficient data management systems for the long-term integration of genotypic information, limiting the full potential of GBAS. Here, we address this gap by introducing GBAS-GUI (https://github.com/sonnenbe-dot/GBAS-GUI), a pipeline capable of generating GBAS-based genotypic data for a wide variety of loci at scale. GBAS-GUI integrates a graphical user interface with multiple checkpoints to improve accessibility and robustness. It implements multiprocessing architecture and a relational database that links genotypic data with associated sample metadata to enhance scalability and data management. The pipeline further enables marker screening through automated calculation of polymorphism information content (PIC) and implements a strategy to recover homologous genotypic information from paralogous loci with non-overlapping amplicon length ranges. Using multiple empirical datasets, we demonstrate substantial improvements in processing speed, database management and handling artefacts related to co-amplification of unspecific regions and duplicates of the same genomic region. We further show that incorporating the full sequence information captured by an amplicon increases marker information content beyond what is achievable with length-based genotyping alone and expands the analytical versatility of GBAS. Overall, GBAS-GUI provides a robust, scalable and versatile framework that unlocks the potential of GBAS for large-scale population genetic and phylogeographic studies.

Genotyping Techniques↗

PubMed2026

Cost-Effectiveness and the Economics of Genomic Testing and Molecularly Matched Therapies.

Cost-effectiveness analysis of precision oncology can help guide value-driven care. Next-generation sequencing is increasingly cost-efficient over single gene testing because diagnostic algorithms require multiple individual gene tests to determine biomarker status. Matched targeted therapy is often not cost-effective due to the high cost associated with drug treatment. However, genomic profiling can promote cost-effective care by identifying patients who are unlikely to benefit from therapy. Additional applications of genomic profiling such as universal testing for hereditary cancer syndromes and germline testing in patients with cancer may represent cost-effective approaches compared with traditional history-based diagnostic methods.

Humans↗

PubMed2026

Integrated bioinformatics analysis reveals cross-talking hub genes and therapeutic agents between sepsis and acute myocardial infarction.

BACKGROUND: Sepsis and acute myocardial infarction (AMI) are two significant diseases that may share overlapping etiological mechanisms. This study aims to systematically identify core genes common to both conditions and to explore their potential as therapeutic targets and drug candidates through an integrative analysis of clinical data and bioinformatics. METHODS: The AMI dataset was obtained from the GEO database, and RNA sequencing data were collected from blood samples of patients with sepsis at our hospital. Common genes were identified using differential expression gene analysis (DEG) and weighted gene co-expression network analysis (WGCNA). Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were performed. A protein-protein interaction (PPI) network was constructed, and hub genes were identified using the MCC/Degree algorithm. Diagnostic value was assessed via receiver operating characteristic curve analysis. Immune infiltration patterns, single-cell sequencing data, and molecular docking simulations were employed to evaluate immune relevance and identify potential therapeutic compounds. RESULTS: A total of 417 genes were identified between sepsis and AMI, with enrichment analysis revealing significant involvement in inflammatory responses. Three hub genes-JAK2, MYD88, and TIMP1-were selected for further investigation. ROC curves confirmed their strong diagnostic performance for both diseases. Immune infiltration analysis showed that these core genes were significantly correlated with the infiltration levels of various immune cell types. Molecular docking indicated that quercetin exhibited stable binding affinity with the proteins encoded by these genes. qPCR validation further confirmed the upregulation of these three genes, supporting the anti-inflammatory effects of quercetin as a potential targeted therapy. CONCLUSION: JAK2, MYD88, and TIMP1 were identified as shared core genes in sepsis and AMI. These genes not only serve as potential diagnostic biomarkers but also offer novel targets for developing common therapeutic strategies for both conditions. Furthermore, quercetin emerges as a promising candidate for targeted treatment.

Humans↗

PubMed2026

Diagnostic Value and Limitations of Dermoscopy in Humans and Animals: A Critical Comparative Analysis.

BACKGROUND: Dermoscopy is a noninvasive imaging technique that is well-established in human dermatology, where it enhances the diagnosis of neoplastic, inflammatory, infectious, and alopecic skin disorders. In veterinary dermatology, its use is expanding yet remains heterogeneous and largely descriptive, despite growing evidence of conserved dermoscopic patterns across species. HYPOTHESIS/OBJECTIVES: To review the applications of dermoscopy in veterinary dermatology, and to provide a comparative analysis of dermoscopic features observed in dogs, cats, and horses in relation to corresponding findings in human dermatology. MATERIALS AND METHODS: A systematic review of the literature reporting dermoscopic findings in veterinary dermatology was conducted in accordance with PRISMA guidelines. PubMed, Scopus and Google Scholar were searched for studies published up to 30 July 2025. Eligible studies included original articles describing dermoscopic features in dogs, cats, or horses. Extracted data included species, dermatological condition, dermoscopic findings, device type and histopathological correlation, when available. Levels of evidence were assessed using the Oxford Centre for Evidence-Based Medicine criteria. RESULTS: Thirty studies met the inclusion criteria. Most were descriptive case reports or case series. Dermoscopy was applied to a wide range of conditions, including alopecias, parasitic infestations, dermatophytosis, neoplastic and sebaceous lesions, inflammatory dermatoses, and congenital vascular anomalies. Recurrent dermoscopic features showed strong similarities to those described in human dermatology, although species-specific anatomical differences influenced interpretation. CONCLUSIONS: Dermoscopy represents a valuable adjunct diagnostic tool in veterinary dermatology, with clear translational relevance. Standardisation of terminology and further prospective studies are required to support its broader clinical integration.

Animals↗

PubMed2026

Methylation profiling in CNS tumor diagnostics: a single-centre real-world experience from Central Europe.

Genome-wide DNA methylation profiling has transformed neuro-oncology by providing an objective, machine learning-based taxonomy that mitigates interobserver variability and refines the histo-molecular criteria of the current WHO classification. We evaluate the real-world diagnostic performance and clinical utility of this modality in a prospective, consecutively accrued three-year cohort of 291 central nervous system (CNS) tumors across a mixed adult-pediatric population. Successful profiling was completed in 95.9% of cases. Using the Epignostix classifier, a high-confidence diagnostic match (calibrated score [CS] ≥ 0.84) was achieved in 70.3% of analyzable samples, while 26.5% returned lower-confidence scores (≥ 0.3 to < 0.84) and only 3.2% remained completely unclassifiable (CS < 0.3). When integrated into a comprehensive diagnostic framework, methylation profiling provided clinically useful results in 81.1% of cases, establishing diagnoses in 70 cases submitted for molecular subclassification and resolving diagnostic uncertainty or prompting major revisions in 149 histologically challenging tumors. Within truly ambiguous lesions, integration of methylome data dictated tumor grade modifications in 38.8% of cases (upgrading in 29.4% and downgrading in 9.4%), shifting patient risk stratification. Crucially, over half (52.7%) of the lower-confidence cases yielded meaningful clinical integration when supported by histomorphology and ancillary genetic or immunohistochemical markers, demonstrating that rigid score cutoffs should not dictate assay failure. Discrepant or misleading classifications occurred in 1.9%. Updating bioinformatic pipelines from version 11b4 to 12.8 rescued multiple ambiguous entries, increasing overall clinical utility to 84.1%. These findings demonstrate that integrating computational epigenomics with classical neuropathology enhances diagnostic precision, while highlighting the ongoing need for careful clinical-pathological correlation.

Central nervous system tumors↗

PubMed2026

Comprehensive identification of carboxylic acids by using bromine isotope-based chemical isotope labelling and structure-guided molecular network.

Carboxylic acids (CAs) are important contributors to the flavor quality of sauce-flavor Chinese Baijiu, yet their comprehensive analysis remains challenging due to poor ionization efficiency, weak chromatographic retention, and limited annotation capability. Herein, we developed a workflow for the high-coverage discovery and annotation of CAs in Baijiu by coupling chemical isotope labeling-liquid chromatography-mass spectrometry with a structure-guided molecular network strategy (SGMNS). A bromine-containing derivatization reagent, 1-(3-aminopropyl)-3-bromoquinolin-1-ium bromide (APBQ), was designed and synthesized to exploit the natural isotope distribution of bromine and characteristic MS/MS fragmentation behavior. Following APBQ derivatization, the target CAs showed superior chromatographic retention and favorable analytical performance. Based on isotopic peak pairing in MS1 and diagnostic fragment validation in MS2, 372 potential CA derivatives were discovered from pooled Baijiu samples and 355 of them were validated by diagnostic fragments in MS2 spectra. To address the scarcity of derivatized spectral libraries, SGMNS was employed for annotation using a background network constructed from APBQ-labeled candidates derived from the Expanded Chinese Baijiu Compound Database. The developed method was further applied to profile Baijiu samples, revealing pronounced differences in CA composition across the seven fermentation rounds. Notably, rounds 3 to 5 exhibited the largest numbers of differential CAs. This study provided an effective analytical strategy for large-scale CA profiling, offering new insight into the chemical basis of flavor formation during multi-round fermentation of sauce-flavor Baijiu.

Isotope Labeling↗

PubMed2026

Quantitative susceptibility mapping in neurodegenerative diseases: An umbrella review of iron-related biomarkers and mechanisms.

Pathological iron accumulation is a common pathophysiological hallmark across multiple neurodegenerative diseases (NDDs), motivating the need for accurate, non-invasive quantification methods. Quantitative susceptibility mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique that enables in vivo measurement of tissue magnetic susceptibility (χ), providing a sensitive proxy for iron content. This umbrella review systematically evaluates the diagnostic accuracy, clinical correlations, and distinct iron distribution patterns of QSM in major NDDs, such as Parkinson's disease (PD), Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and atypical Parkinsonism. We included 15 (13/15 were rated Low or Critically Low on AMSTAR 2) systematic reviews and meta-analyses (through July 15, 2026); however, the findings should be interpreted cautiously because of heterogeneity and the low methodological quality. A Corrected Covered Area (CCA) analysis demonstrated only slight overlap of primary studies across the included reviews (CCA = 5.42%). Collectively, the evidence indicates that QSM provides comparable or higher diagnostic sensitivity and reliability than conventional R2* and SWI techniques, particularly for deep gray matter structures. The findings support significant iron overload in the substantia nigra, particularly in the pars compacta, as a robust biomarker for PD that correlates with motor severity and disease duration. Furthermore, regional iron profiling in the basal ganglia is critical for differential diagnosis; specifically, elevated χ in the putamen and globus pallidus effectively distinguishes multiple system atrophy and progressive supranuclear palsy from idiopathic PD. Distinctively, AD and ALS exhibit specific χ alterations in the thalamus, motor cortex, and hippocampus, reflecting divergent iron-related pathophysiological mechanisms, which correlate with cognitive impairment and upper motor neuron signs. Overall, QSM shows diagnostic promise and offers mechanistic insights into iron-related neurodegenerative processes.

Humans↗

PubMed2026

ADAM10's combined influence on the diagnostic usefulness of IL 22, IL 10, IL-17 A, and IL-17D in autism spectrum disorders: Predicted role on gut leakiness as co-morbidity.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with increasing global prevalence but a lack of reliable diagnostic biomarkers. Emerging evidence suggests that immune dysregulation, gut-brain axis dysfunction, and increased intestinal permeability play key roles in ASD pathophysiology. This study investigated the combined diagnostic value of ADAM10 and cytokines (IL-10, IL-22, IL-17 A, and IL-17D). Multivariable logistic regression produces an improved ROC curve that improves diagnostic accuracy over individual markers by combining numerous predictors into a single risk score (linear predictor). The technique, which frequently raises individual marker AUCs, entails modelling a binary result, calculating the probability, and visualizing ROC based on the projected probabilities. In this case-control study, plasma levels of ADAM10, IL-10, IL-22, IL-17 A, and IL-17D were measured in 37 male children with ASD and 37 age-matched controls. Group comparisons, correlation analyses, and receiver operating characteristic (ROC) curve analyses, including combined ROC models, were performed. ADAM10, IL-22, and IL-17 A levels were significantly reduced in children with ASD compared to controls, whereas IL-10 and IL-17D showed no significant differences. ADAM10, IL-17 A, and IL-22 demonstrated good diagnostic performance, with AUC values of 0.886, 0.855, and 0.812, respectively. In contrast, IL-10 and IL-17D showed poor discriminatory ability, with AUC values of 0.524 and 0.599, respectively. Combined ROC analysis markedly improved diagnostic accuracy, with all panels including ADAM10 achieving AUC values above 0.90, and some reaching as high as 0.988, with high sensitivity and specificity. The combination of ADAM10 with selected cytokines significantly enhances diagnostic performance compared to individual markers, supporting a link between immune dysregulation, barrier dysfunction, and gut permeability in ASD.

Humans↗

PubMed2026

Ultrastructural Insights Into the Reproductive Anatomy and Eggs of Cotton Pink Bollworm, Pectinophora gossypiella Saunders (Lepidoptera: Gelechiidae).

The pink bollworm, Pectinophora gossypiella Saunders is a major pest of cotton, notorious for its high reproductive potential and rapid evolution of resistance to Bacillus thuringiensis (Bt) toxins. Despite its economic significance, detailed knowledge of its reproductive anatomy and egg ultrastructure has remained limited, constraining the development of advanced molecular control strategies such as CRISPR/Cas9-based genome editing. The present study provides the first comprehensive characterization of the reproductive system and egg surface morphology of P. gossypiella using stereomicroscopy and scanning electron microscopy (SEM) techniques. The male reproductive system consists of fused, bean-shaped testes, seminal vesicles, duplex and simplex ejaculatory ducts, and paired accessory glands. The female reproductive system comprises paired ovaries with four polytrophic ovarioles per ovary, lateral and common oviducts, accessory glands, corpus bursae, and spermathecal glands. Eggs are oval, dorsoventrally flattened, exhibit a reticulated chorion with distinct micropylar and aeropylar regions. SEM images revealed 6-9 rosette cells encircling a circular micropylar plate, 14-19 first order and 17-23 s order ribs, and 250-291 polygonal surface cells. The structural features of P. gossypiella eggs reveal key sites for sperm entry, aeropylar respiration, and candidate zones for microinjection in gene editing applications. These findings establish a morphological baseline critical for optimizing embryo manipulation and ribonucleoprotein (RNP) delivery in lepidopteran genome editing. This study represents a pioneering effort to integrate classical egg morphology with molecular entomology, thereby advancing precision genetic interventions aimed at resistance management and population suppression in P. gossypiella.

Animals↗

PubMed2026

Investigation of Fatty Acid Metabolism-Associated Molecular CPOX and the Underlying Mechanism in Follicular Lymphoma.

Dysregulated lipid metabolism is a key driver of follicular lymphoma (FL). This study aimed to explore the lipid metabolism-related genes (LMRGs) and clarify the underlying roles and mechanisms in FL. Bioinformatics methods, including differential analysis, WGCNA, machine learning, and Mendelian randomization, were utilized to select the LMRGs in FL. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to investigate the function of the key LMRG. Receiver operator characteristic (ROC) was used to evaluate the diagnostic value of the key gene CPOX. A pan-cancer analysis investigated CPOX's expression level and immune correlations. In vitro experiments using FL cell lines (WSU-FSCCL, DOHH2) validated CPOX expression, and CPOX knockdown in DOHH2 cells was used to assess its impact on viability, migration, invasion, and fatty acid metabolism. CPOX was confirmed to be a risk factor, significantly overexpressed in FL, and exhibited effective diagnostic ability in FL (AUC = 0.731). Functional analysis linked CPOX to mitochondrial function, oxidative phosphorylation, and heme metabolic process. Pan-cancer indicated the dysregulated CPOX across multiple cancers and closely correlation with immune characteristics. Experimentally, CPOX was higher in the more invasive DOHH2 cells; and CPOX knockdown suppressed FL progression and reduced lipid droplet formation, triglyceride, total cholesterol, and free fatty acid levels. In conclusion, this study fills the gap in understanding the significance of lipid metabolism-related molecules in FL, and innovatively proposes that CPOX is a risk factor for FL. Knockdown of CPOX inhibits the FL progression, which is regulated by fatty acid metabolism.

Lymphoma, Follicular↗

PubMed2026

Liquid biopsy-based detection of circulating and exfoliated cholangiocarcinoma tumor cells from blood and bile using heparan sulfate octasaccharides on integrated microfluidic systems.

Early diagnosis of cholangiocarcinoma (CCA) remains challenging because existing diagnostic approaches often lack sufficient sensitivity for reliable detection of early-stage disease. Circulating tumor cells (CTCs) in blood and exfoliated tumor cells (ETCs) in bile represent valuable targets for liquid biopsy-based detection; however, their low abundance and the complexity of clinical sample analysis pose substantial technical challenges for reliable enrichment and identification. Herein, we present a reproducible workflow for isolating and identifying CCA tumor cells from blood for CTCs and bile for ETCs using synthetic cell-surface heparan sulfate (HS) octasaccharide-functionalized magnetic beads (MBs) on integrated microfluidic systems. The method combined sample pre-processing, magnetic bead-based enrichment, controlled low-shear mixing and immunofluorescence-based identification into a unified workflow compatible with distinct clinical sample types. Key operational parameters, including MB concentration, mixing frequency, and pressure settings, were detailed to facilitate consistent performance. Using this workflow, tumor cell capture rates of approximately 70% in bile (for ETCs) and blood (for CTCs) were achieved, with a total processing time of 60-90 min per sample under clinically relevant low-abundance conditions. The platform enables reliable detection of as few as 1 tumor cell per mL of blood or bile. This method provides a practical and adaptable strategy for glycosaminoglycan-mediated liquid biopsy applications and may be extended to other tumor-cell enrichment workflows involving heterogeneous cell-surface interactions.

Humans↗

PubMed2026

Integrated multi-omics profiling of amniotic fluid identifies predictive biomarkers for fetal growth restriction trajectories.

BACKGROUND: Fetal growth restriction (FGR) is a complex condition with highly heterogeneous clinical outcomes, making prenatal distinction between transient and persistent growth failure challenging. This study aims to identify amniotic fluid (AF) biomarkers capable of differentiating distinct FGR trajectories and characterizing persistent growth failure mechanisms. METHODS: Integrated proteomic and metabolomic profiling was performed on AF samples from transient FGR (n = 11), persistent FGR (n = 9), and healthy controls (n = 13). Diagnostic and prognostic models were developed using multivariate analysis. Selected protein candidates were validated via ELISA in an independent cohort (n = 69). RESULTS: Multi-omics analysis revealed distinct molecular signatures for FGR stratification. A two-protein diagnostic panel (PDGFA and phospho-STAT5A) achieved an AUC of 1.000 in the discovery stage and 0.780 in the external validation cohort. For prognostic assessment, a molecular signature including IREB2, HLA-C, and PLXNB2 accurately predicted persistent growth failure from transient recovery (AUC = 0.966). Cross-platform integration highlighted the mass spectrometry-derived WASHC2C as a central hub protein with a significant progressive increase across the control, transient, and persistent groups (p < 0.001). CONCLUSIONS: This study establishes a multi-omics framework for prenatal FGR stratification. Our findings identify distinct molecular signatures reflecting the intrauterine environment and provide high-performance molecular tools for predicting divergent fetal growth trajectories to guide personalized clinical decision-making.

Humans↗

PubMed2026

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics↗