INTRODUCTION:Respiratory viral co-detection has become increasingly frequent with the widespread use of multiplex molecular panels. However, detecting two or more respiratory viruses in a single sample does not necessarily indicate active coinfection, etiologic equivalence, or the need to escalate antiviral or antibacterial therapy. AREAS COVERED:This critical perspective examines respiratory viral co-detection as a diagnostic stewardship and anti-infective decision-making challenge. It proposes an interpretive framework that distinguishes molecular co-detection from probable coinfection, sequential infection, prolonged nucleic acid shedding, and clinically actionable co-detection. The article discusses how symptom timing, syndromic compatibility, local viral circulation, host vulnerability, and therapeutic availability should guide interpretation. It also addresses the limitations of Ct values as surrogate markers of viral burden, the potential contribution of host-response biomarkers, the influence of vaccination and immunoprophylaxis, and the implications of viral interactions for clinical reasoning and antiviral trial design. EXPERT OPINION:Multiplex panels provide the greatest value when interpreted as tools for therapeutic prioritization, antibacterial stewardship, infection control, and risk stratification rather than as flat lists of equivalent etiologies. Future antiviral studies should incorporate co-detection as a prespecified modifier of clinical and treatment outcomes.
INTRODUCTION:Estrogen receptor-positive (ER+), HER2-negative breast cancer is the most common breast cancer subtype. While adjuvant endocrine therapy reduces recurrence risk, identifying which patients benefit from the addition of chemotherapy remains a key clinical challenge. The Oncotype DX® 21-gene Recurrence Score assay (Exact Sciences, via Genomic Health, Inc.) was developed to address this by quantifying distant recurrence risk and informing chemotherapy decisions in early-stage ER+/HER2- disease. AREAS COVERED:This diagnostic profile reviews the development, validation, and clinical evidence for Oncotype DX, including findings from the TAILORx and RxPONDER prospective trials and the subsequent development of hybrid tools integrating genomic and clinicopathological data. Alternative multiparameter molecular tests (MammaPrint, Prosigna, EndoPredict, Breast Cancer Index) are summarized and compared. We review international guideline recommendations, decision impact studies, cost-effectiveness evidence, and ongoing trials. EXPERT OPINION:Oncotype DX has strong prognostic evidence and has meaningfully reduced chemotherapy use, though its case as a biomarker predictive of therapeutic effect from chemotherapy rests on trial designs with important limitations. Its independent prognostic contribution beyond comprehensive clinicopathological assessment requires further clarification, and cost-effectiveness varies substantially by indication and healthcare setting.
INTRODUCTION:Infectious lung diseases, such as pneumonia, tuberculosis, COVID-19, influenza, and emerging fungal infections, are major causes of illness and death worldwide. Traditional methods have serious limitations such as diagnostic delays, antimicrobial resistance, and non-targeted therapy. Theranostics, unifying diagnosis and therapy, offers a precision medicine solution for real-time, individualized pulmonary care. AREAS COVERED:This review explores biotechnological and nanotechnological synergies in pulmonary theranostics. Biotech tools include CRISPR-Cas for pathogen detection, non-coding RNAs (ncRNAs) as biomarkers/modulators, and monoclonal antibodies (mAbs) for targeted neutralization. Nanotech platforms feature nanosensors and SERS for early diagnosis, plus diverse nanocarriers enabling targeted drug/gene/vaccine delivery, controlled release, and imaging. Case studies across infectious lung diseases demonstrate real-world applications. We also address safety, manufacturing scalability, regulatory complexity, and economic barriers. EXPERT OPINION:This convergence marks a paradigm shift toward personalized pulmonary medicine. Future success demands smart, multi-stimuli-responsive nanoplatforms, AI-driven predictive modeling, and closed-loop systems linking real-time diagnostics to adaptive therapies. Translational priorities include standardized preclinical models, clear combination-product regulations, and cost-effectiveness data. Ultimately, interdisciplinary collaboration among material scientists, molecular biologists, clinicians, and regulatory experts is essential to bridge bench-to-bedside gaps and realize clinical impact.
INTRODUCTION:The use of Artificial Intelligence (AI), especially Machine learning (ML) and Deep learning (DL), has led to a major shift in medical diagnosis. AI can assist medical professionals in medical diagnosis by its unique ability to analyze complex data from multiple sources, including medical images, gene sequences, and Electronic Health Records (EHRs). AREAS COVERED:Its application in other clinical processes, such as risk classification, diagnostic workflows, and disease risk prediction from patient symptoms, can also speed up diagnosis, reduce costs, and improve diagnostic outcomes. EXPERT OPINION:However, its effective use in the clinic necessitates addressing concerns about data privacy, rigorous validation, and the development of methods to reduce bias caused by medical data. By addressing these limitations, AI can be very effective in increasing medical professionals' knowledge and, consequently, improving patient outcomes.
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.
INTRODUCTION:Endometrial cancer is the most common gynecological malignancy in high-income countries. Although postmenopausal bleeding is its cardinal presenting symptom, only 5-10% of women with postmenopausal bleeding have malignancy. There is therefore a need for accurate, minimally invasive diagnostic tests. Proteins detectable in proximal biofluids, particularly cervicovaginal fluid (CVF), represent promising biomarkers because they reflect the functional biology of the tumor and can be measured using clinically translatable immunoassays. AREAS COVERED:This review critically evaluates the evidence for CVF protein biomarkers in the early detection of endometrial cancer. Three protein signatures show the greatest promise: a five-protein panel (HPT, LGALS3BP, FGA, LY6D, IGHM; AUC 0.95), a 12-protein inflammatory panel (AUC 0.91), and an 11-protein multivariate panel (AUC 0.92), all approaching or meeting thresholds for clinical consideration. We also discuss the biological relevance of these proteins and highlight the methodological, analytical and translational challenges that must be addressed before clinical implementation. EXPERT OPINION:CVF provides a unique, minimally invasive sampling medium owing to the anatomical continuity between the uterine cavity and lower genital tract. While current evidence is encouraging, most candidate biomarkers remain exploratory and require rigorous validation in large, prospective multicentre studies before incorporation into routine clinical practice.
INTRODUCTION:Polycystic ovary syndrome (PCOS) was recently renamed polyendocrine metabolic ovarian syndrome (PMOS). AREAS COVERED:We review the renaming process, the potential advantages, and the challenges associated with this global effort. A large consortium of experts and patient representatives debated whether renaming was justified, what principles should guide a new name, and how such a change could be implemented without disrupting clinical care, research, education, or patient communication. Surveys indicated that awareness of the broader features of the syndrome improved in the last years after dissemination strategies and patient advocacy initiatives, but important gaps remained, particularly around the risk of comorbidities. EXPERT OPINION:New perspectives emerge with renaming PCOS into PMOS after a carefully planned effort to improve scientific accuracy, patient understanding, and clinical communication while minimizing confusion during implementation. The new terminology emphasizes the syndrome's endocrine and metabolic nature and removes the misleading reference to 'polycystic' ovaries. Similar to previous successful nomenclature updates in gynecology, this gradual transition aims to enhance education, interdisciplinary care, research, and long-term management, ultimately supporting more accurate diagnosis and improved patient outcomes.
INTRODUCTION:Respiratory tract infections (RTIs) are among the most common causes of medical consultation in children. Although the majority of upper respiratory tract infections are viral and self-limiting, bacterial pathogens remain responsible for a relevant proportion of cases and may require targeted antimicrobial therapy. Accurate microbiological diagnosis is therefore essential to guide clinical management and support antimicrobial stewardship. AREAS COVERED:This review discusses the etiology and clinical presentation of pediatric respiratory infections and examines current diagnostic approaches, including traditional culture-based methods and nucleic acid amplification tests (NAATs). The advantages of molecular diagnostics-such as rapid turnaround time, high sensitivity, and improved pathogen detection-are highlighted alongside their role in antimicrobial stewardship and public health surveillance. At the same time, important limitations are explored, including difficulties in distinguishing colonization from active infection, challenges in polymicrobial detection, absence of host-response information, and barriers related to cost and accessibility. Emerging technologies and future perspectives in pediatric molecular diagnostics are also addressed. EXPERT OPINION:While molecular diagnostics have transformed pathogen detection, their clinical interpretation remains complex. Future diagnostic strategies should integrate molecular data with quantitative pathogen measurements, host-response biomarkers, and clinical phenotyping to better distinguish infection from colonization. Interdisciplinary research, real-world implementation studies, and cost-effectiveness evaluations will be essential to translate technological advances into meaningful improvements in pediatric infectious disease care.
INTRODUCTION:Molecular diagnostics focusing on the detection and analysis of nucleic acids are indispensable tools for early pathogen identification, transmission monitoring, and genomic surveillance during pandemics. Recent technological advances have broadened the diagnostic landscape, incorporating PCR-based methods, isothermal amplification, high-CRISPR-based amplification detection, and sequencing. Despite their diagnostic potential, widespread implementation remains limited by high validation costs, time and logistical constraints, the need for specialized professional knowledge, and a lack of adaptability in resource-limited settings. Artificial intelligence (AI) is increasingly recognized as a promising but challenging approach, offering tools that streamline assay development, automate data interpretation, and optimize real-time diagnostic performance. AREAS COVERED:This review introduces recently published AI tools with potential to enhance the in-silico design validation process of oligonucleotides for molecular assays. These cover tools for initial assay design and optimization to validation and continuous assay updates. The limitations, including concerns regarding data accuracy, the lack of transparency in data processing ('black box' models), and unresolved licensing and regulatory issues, are highlighted for each tool and as expert opinion. EXPERT OPINION:Collectively, these challenges currently confine most AI-based approaches to research settings and prevent their routine implementation in clinical molecular diagnostics. Their widespread adoption depends on addressing remaining technical, regulatory, and practical challenges.
Introduction PD-L1 expression today represents a crucial biomarker in the selection of patients eligible for immune checkpoint inhibitor therapies (PD-1/PD-L1), particularly in tumors such as NSCLC, urothelial carcinoma, and TNBC. Its role in modulating immune response and the tumor microenvironment makes this topic of growing relevance in clinical oncological practice. Areas covered This review examines the most recent literature on histological and plasma PD-L1 expression, comparative studies between antibodies and IHC cutoffs, integration of liquid biopsy and new biomarkers (e.g. CPS, ctDNA). A targeted literature search was conducted using PubMed/MEDLINE, Scopus, and Web of Science, covering publications from January 2010 to March 2025. Meta-analyses and clinical studies related to TNBC, NSCLC, and urothelial carcinoma are included, with insights into therapeutic resistance and combination strategies. Expert opinion While SP263 demonstrates strong analytical performance and reproducibility, analytical concordance does not equate to clinical interchangeability. PD-L1 testing should remain assay-, tissue-, and indication-specific, supported by regulatory approval and clinical outcome data. Future integration of digital tools and multimodal biomarkers may improve standardization and predictive accuracy.
INTRODUCTION:Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis and limited availability of reliable biomarkers. Extracellular vesicles (EVs) are membrane-bound nanoparticles released by cells that carry nucleic acids, proteins, and lipids reflective of their cellular origin. Their stability and accessibility through minimally invasive sampling make them promising liquid biopsy biomarkers. AREAS COVERED:This review summarizes current evidence supporting EVs as diagnostic and prognostic biomarkers in NSCLC. We discuss the clinical relevance of EV-associated molecular signatures, including miRNAs, other non-coding RNAs, and proteins, in early detection, disease stratification, and outcome prediction. Recent advances in EV isolation and characterization technologies, particularly microfluidic and high-throughput platforms, are highlighted. We also examine key barriers to clinical translation, including biological heterogeneity, methodological variability, and the lack of standardized protocols. EXPERT OPINION:EVs have the potential to transform NSCLC management by enabling minimally invasive diagnosis, real-time disease monitoring, and personalized treatment strategies. However, widespread clinical implementation requires standardized methodologies, improved tumor-specific EV enrichment, and large-scale validation studies. Future integration of multi-omics, artificial intelligence, and advanced detection technologies is expected to enhance biomarker performance and facilitate the incorporation of EV-based liquid biopsy approaches into precision oncology.
BACKGROUND:Osteoarthritis (OA) affects over half a billion people globally, representing a major public health burden. Serum neurofilament light chain (sNFL) has recently been implicated in systemic inflammation and metabolic disorders. RESEARCH DESIGN AND METHODS:This dual-cohort study analyzed data from the National Health and Nutrition Examination Survey (NHANES) and the UK Biobank. In NHANES, sNFL was measured via a high-sensitivity immunoassay, while in UKB, NfL was quantified using the Olink Explore 3072 proteomics platform. OA was defined by self-report in NHANES, and a combination of self-report and ICD-10 hospital records in UKB. The associations were evaluated using multivariate logistic regression and RCS. RESULTS:Higher sNFL levels were significantly associated with increased OA odds in both cohorts. In fully adjusted models, each 1-unit increase in log-transformed sNFL corresponded to 85% higher odds in NHANES [OR = 1.85, 95% CI: (1.51, 2.23)] and 28% higher odds in UKB [OR = 1.28, 95% CI: (1.21, 1.36)]. Comparing the highest to lowest quartiles, ORs were 4.41 (95% CI: 2.71, 7.13) and 1.46 (95% CI: 1.34, 1.59), respectively (both p for trend <0.01). CONCLUSIONS:Elevated sNFL levels are independently and consistently associated with a higher prevalence of OA across two distinct national cohorts.
INTRODUCTION:Neisseria gonorrhoeae (gonococcus, GC) has developed resistance to all antimicrobials recommended for gonorrhea treatment, owing to its genetic plasticity and capacity to acquire antimicrobial resistance (AMR). This review examines the crucial role of diagnostics and novel laboratory approaches in mitigating the spread of GC-AMR and in preserving the long-term effectiveness of current and future antimicrobials for gonorrhea. AREAS COVERED:Recent advances in diagnostics and novel laboratory approaches for detection of GC-AMR, enhancing GC-AMR surveillance and clinical management of gonorrhea. EXPERT OPINION:The rapid emergence and global dissemination of multidrug-resistant GC including ceftriaxone-resistant strains poses a grave challenge to current gonorrhea control and prevention strategies. The implementation of rapid diagnostics and novel laboratory approaches can, when used appropriately, support the rapid detection of GC-AMR, ensure timely treatment, reduce transmission, and preserve last-line antibiotics by enabling resistance-guided therapy. These diagnostics and novel laboratory approaches are also crucial for the early detection of emerging resistance to antimicrobials recently approved by the FDA, and other antimicrobials currently under development and anticipated for future clinical use. Integrating culture-based GC-AMR surveillance with rapid molecular assays targeting genetic determinants of AMR offers a comprehensive approach for robust monitoring and timely response to the ever-evolving GC-AMR.
INTRODUCTION:Cerebral amyloid angiopathy (CAA) is a major cause of lobar intracerebral hemorrhage and cognitive decline in older adults. Current diagnosis relies mainly on neuroimaging, which lacks pathophysiological specificity. AREAS COVERED:This narrative review summarizes evidence on cerebrospinal fluid (CSF) and plasma biomarkers in sporadic CAA. In CSF, CAA is typically associated with reduced Aβ42 and Aβ42/Aβ40 ratio, although similar alterations are observed in Alzheimer's disease (AD), limiting diagnostic specificity. Lower Aβ40 levels may reflect vascular amyloid deposition and appear more characteristic of CAA, but alone provide insufficient discrimination. Plasma biomarker studies have yielded inconsistent findings due to methodological and population heterogeneity. Nevertheless, amyloid isoforms, phosphorylated tau species, and neurofilament light chain (NfL) show potential, with NfL correlating with imaging markers and disease burden. The increasing need to distinguish CAA from AD and other cerebral small vessel diseases has driven growing interest in fluid biomarkers. EXPERT OPINION:Despite promising findings, no fluid biomarker currently demonstrates sufficient specificity or validation for routine clinical use in CAA. Significant overlap with AD pathology remains a major limitation. Large longitudinal real-world studies are needed to determine the diagnostic, prognostic, and incremental clinical value of fluid biomarkers in CAA.
INTRODUCTION:We evaluated the diagnostic accuracy of circulating cell-free DNA (cfDNA) and circulating tumor DNA (ctDNA) compared to tissue biopsy in breast cancer across three assay modalities. METHODS:We searched PubMed, Scopus, and Cochrane for studies published from January 2014 to March 2026. Bivariate random effects models pool sensitivity, specificity, and area under the curve (AUC). Registered under (CRD420261333264). RESULTS:Eighteen studies with 4,743 participants were included. Quantitative assays achieved the highest sensitivity of 0.930 (95% CI: 0.603-0.991), specificity of 0.899 (95% CI: 0.802-0.951), and AUC of 0.928. Methylation assays showed a sensitivity of 0.752 (95% CI: 0.595-0.862), specificity of 0.841 (95% CI: 0.737-0.908), and AUC of 0.862. Integrity assays yielded a sensitivity of 0.863 (95% CI: 0.682-0.948), specificity of 0.874 (95% CI: 0.781-0.931), and AUC of 0.927. Substantial statistical heterogeneity (I2) occurred across all subgroups. Overall certainty was low, due to case-control designs and inconsistency. CONCLUSION:While cfDNA cannot replace tissue biopsies, current pooled estimates demonstrate high specificity, suggesting promising potential as an adjunctive diagnostic tool. Quantitative assays show the greatest potential for optimizing patient triage. However, the overall low certainty of evidence highlights an urgent need for standardized prospective studies.
INTRODUCTION:Adjuvant immunotherapy has transformed the management of high-risk resected ccRCC, with pembrolizumab demonstrating improvements in DFS and OS. However, divergent outcomes across recent phase III trials highlight the limitations of clinicopathologic staging alone for guiding postoperative treatment decisions. A substantial proportion of patients may receive adjuvant therapy without deriving meaningful benefit, underscoring the urgent need for biologically informed risk stratification. AREAS COVERED:KIM-1, a circulating biomarker derived from proximal tubular epithelium, has emerged as a promising candidate in this setting. Elevated postoperative KIM-1 levels are consistently associated with inferior oncologic outcomes and may reflect minimal residual disease. Exploratory analyses from IMmotion010 suggest a potential predictive enrichment effect for adjuvant immunotherapy benefit in patients with high baseline KIM-1. Additional biomarkers including sarcomatoid differentiation, specific genomic drivers (PBRM1, BAP1, VHL), circulating tumor DNA, epigenetic signatures, and systemic inflammatory markers, provide complementary insights into tumor biology and host-tumor interaction. EXPERT OPINION:Although none of these biomarkers are currently validated for routine clinical decision-making, integrative models combining clinicopathologic and molecular features may enable more precise selection of patients for adjuvant immunotherapy and help reduce overtreatment in localized ccRCC.
INTRODUCTION:Polycystic ovary syndrome (PCOS) is an endocrine disease involving reproductive dysfunction, with anovulation and diminished oocyte quality, and is related to endometrial dysfunction. Estradiol-to-oocyte ratio (EOR) surfaced as a measure of success in reproductive effects in PCOS during assisted reproductive technical expertise. AREAS COVERED:This review provides a comprehensive summary of current evidence on EOR, its physiological significance, relationship with oocyte maturation, and impact on embryo viability in IVF. We will explore molecular mechanisms of EOR's action in follicular development, integrating data from imaging technologies and biomarker studies. It also discusses its clinical utility in optimizing individualized fertility treatment and improving reproductive prognoses for PCOS patients during IVF. EXPERT OPINION:EOR may empower IVF specialists by enabling more refined assessments, helping them make more personalized and confident treatment decisions for patients (embryo transfer and subsequent cycle protocol). It provides guidance for treatment adjustments in subsequent cycles, especially when prior responses were high in quantity but suboptimal in quality. Incorporating EOR into clinical practice complements clinical expertise and supports the balance between efficacy and safety in managing PCOS-related infertility.
INTRODUCTION:Biomarker-guided stratification is essential for optimizing adjuvant systemic therapy in early-stage breast cancer, requiring a balance between therapeutic benefit and avoidance of overtreatment. AREAS COVERED:This review summarizes established and emerging prognostic and predictive biomarkers guiding adjuvant therapy selection. Evidence was synthesized from structured searches of PubMed, EMBASE, clinical trial databases and author expertise, focusing on morphological and molecular biomarkers, including multigene assays, protein and immune-based markers, mutation profiling, liquid biopsy and artificial intelligence (AI). EXPERT OPINION:Although clinicopathological factors such as tumor size, grade, and nodal status remain fundamental, clinical decision-making is increasingly driven by biologically informed precision. ER and HER2 status continue to underpin prognostic and predictive assessment. In hormone receptor-positive disease, multigene assays refine recurrence risk and chemotherapy benefit, while tools such as HER2DX improve stratification in HER2-positive tumors. Immune and DNA-repair biomarkers inform targeted therapy in HER2-positive and triple-negative subtypes. Mutation profiling of ESR1, PIK3CA, AKT, mTOR, and PTEN increasingly informs targeted treatment, particularly in advanced disease. Emerging approaches, including liquid biopsy, AI, and multi-omics integration, offer dynamic insights but require prospective validation. Future progress depends on assay standardization, equitable access, and validation within adaptive clinical trial frameworks, supporting integrated molecular-clinical and AI-enhanced models for personalized therapy.
INTRODUCTION:Fine-needle aspiration cytology is a widely used minimally invasive tool for salivary gland lesions, though diagnostic challenges arise due to overlapping features between benign and malignant tumors. This systematic review and meta-analysis evaluate its diagnostic performance in salivary gland neoplasms. METHODS:A comprehensive literature search was conducted in PubMed/MEDLINE, Embase, Scopus, and Web of Science. Studies reporting sensitivity, specificity, or sufficient data to construct 2 × 2 tables were included. Data extraction was performed independently by two reviewers, and study quality was assessed using the QUADAS-2 tool. Diagnostic accuracy was pooled using a bivariate random-effects model, and summary receiver operating characteristic curves were generated. Publication bias was evaluated using Deeks' funnel plot. RESULTS:A total of 56 studies were included, of which 32 were eligible for meta-analysis. The pooled sensitivity of FNAC was 0.79 (95% CI: 0.75-0.83), and specificity was 0.94 (95% CI: 0.93-0.96). The summary analysis demonstrated good discriminative ability with an area under the curve of 0.89. No significant publication bias was detected. CONCLUSIONS:FNAC demonstrates high diagnostic accuracy, with high specificity and moderate sensitivity, supporting its role as a reliable first-line diagnostic tool in salivary gland neoplasms.
