Organs-on-a-chip represent a transformative advancement in biotechnology, offering a sophisticated alternative to traditional animal testing and conventional cell culture methods. These microdevices, exemplified by Emulate's Liver-Chip S1, replicate human organ microenvironments at a microscopic scale using layered polydimethylsiloxane with integrated channels housing multiple cell types. The technology employs microfluidics and perfusion mechanisms that mimic physiological conditions, creating an in vivo-like environment that enhances cellular function and drug response prediction. This elegant engineering solution enables three-dimensional tissue-tissue interaction studies, providing more accurate and predictive data for pharmaceutical development while substantially reducing reliance on animal models.

Recent advances in antibiotic susceptibility testing represent a significant evolution in clinical microbiology and infectious disease management. This collection of research encompasses innovative approaches including nucleic acid-based mass spectrometry for rapid tuberculosis identification, transformer-based resistance gene detection from nanopore signals, and fluorogenic methods for colistin susceptibility determination. Additional developments feature molecular assays for direct carbapenemase gene detection and comprehensive reviews examining classical, molecular, and artificial intelligence-enhanced diagnostic techniques. These next-generation technologies address critical clinical needs by enabling faster, more accurate pathogen identification and drug resistance profiling, ultimately supporting personalized treatment strategies and combating the growing threat of antimicrobial resistance in healthcare settings worldwide.

Johan Elf's research group investigates the fundamental physical and chemical principles governing molecular-level cellular processes, particularly in bacterial cells. Focusing on transcriptional regulation, protein synthesis, and cell division, the team develops quantitative physics-based models and validates them through advanced experimental techniques. A core research objective involves creating sensitive biophysical measurement tools capable of observing individual macromolecules within living cells at high spatial and temporal resolution. Through interdisciplinary collaboration among physicists, biologists, chemists, programmers, and engineers, the group bridges biochemistry and physiology to address central biological questions: gene regulation mechanisms, chromosomal organization, and bacterial growth and division. The research has yielded innovative diagnostic applications for infectious diseases, while ongoing investigations explore how regulatory proteins locate specific DNA sequences within genomes.

Vascular and inflammatory diseases share dysfunction of endothelial and epithelial barriers under combined mechanical and inflammatory stress, yet traditional models fail to replicate this complex microenvironment, hampering drug development and clinical translation. Organ-on-a-chip technologies represent promising alternatives to animal testing by emulating physiological conditions, though current approaches lack robust biomechanical readouts and functional validation of drug candidates under physiologically relevant flow conditions. This Research Topic consolidates a multimodal paradigm wherein mechanics-aware organ-on-a-chip platforms serve as integrated testing systems for vascular and inflammatory disease research, encompassing vessel, endothelium, epidermis, lung, and gut-on-chip models combined with computational hemodynamic modeling to enhance throughput and information content in drug evaluation pipelines.

The tumor microenvironment functions as a dynamic ecosystem that orchestrates carcinogenesis, therapeutic resistance, and immune evasion. This comprehensive review examines the cellular and acellular architecture of the TME, including cancer-associated fibroblasts, tumor-associated macrophages, and remodeled extracellular matrix. The authors analyze molecular mechanisms underlying TME-mediated pathogenesis, encompassing metabolic reprogramming, epigenetic dysregulation, and microbiome interactions that collectively drive immunosuppression. The review highlights emerging therapeutic strategies, including precision nanotechnologies, next-generation immunotherapies such as logic-gated CAR-T cells and bispecific engagers, metabolic modulators, stromal normalization, and microbiome interventions. Advanced tools including patient-derived organoids, tumor-on-a-chip systems, and artificial intelligence-powered multi-omics enable personalized therapeutic forecasting, offering transformative approaches to overcome intratumoral heterogeneity and therapeutic challenges.

These sensors can be functionalized with antibodies, aptamers, or enzymes for label-free detection of cancer biomarkers, pathogens, viruses, toxins, and heavy ...

A portable CRISPR-Cas9 diagnostic combined LAMP amplification with a microfluidic graphene heater to detect nucleic acids using smartphone power. The low ...

Viral diseases disproportionately affect populations in low- and middle-income countries, yet molecular diagnostics remain confined to centralized laboratories, creating critical gaps in disease surveillance and outbreak response. This comprehensive review examines the landscape of viral diagnostics, highlighting significant global inequities in test availability and access. The authors assess five key molecular diagnostic platforms, including PCR-based technologies, isothermal amplification, CRISPR-based diagnostics, synthetic biology, and portable sequencing, evaluating their potential for decentralized deployment. The analysis establishes essential performance criteria for context-appropriate diagnostic solutions and identifies critical implementation considerations, including simplified sample processing, viral diversity management, and integrated connectivity. Advancing from centralized laboratory testing to decentralized diagnostic approaches is essential for improving clinical outcomes and pandemic preparedness globally, requiring needs-driven design and rigorous validation across diverse healthcare settings.

CRISPR-based diagnostics are uniquely positioned to enable rapid, affordable, and highly accurate nucleic acid testing at both the point-of-care and the point- ...

Quantum dots represent a transformative nanotechnology platform with significant potential in medical applications. These semiconductor nanocrystals function as fluorescent biological labels, enabling advanced diagnostic and therapeutic capabilities across multiple disease areas, particularly oncology and neurodegenerative disorders such as Alzheimer's. Recent research demonstrates their utility in cancer detection, tumor imaging, and targeted therapy approaches. The technology has evolved substantially since early fluorescent imaging applications, with ongoing developments in quantum computing enhancing diagnostic precision. However, clinical translation faces challenges related to toxicology, physicochemical properties, and environmental factors affecting biocompatibility. Current investigations focus on optimizing quantum dot formulations for improved safety profiles and therapeutic efficacy, positioning this emerging technology as a promising frontier in precision medicine and personalized healthcare solutions.

Researchers have developed an innovative droplet microfluidic platform to accelerate antibiotic discovery from complex environmental microbial communities. The approach combines bacterial cultivation in picoliter droplets with multiplexed phenotypic screening using dual fluorescently labeled reporter strains representing both Gram-positive and Gram-negative bacteria. By simultaneously monitoring independent survival signals, the system efficiently detects and isolates bioactive compounds with diverse inhibition profiles. Proof-of-concept studies successfully identified a model Streptomyces strain and screened soil-derived microbial communities, demonstrating the platform's practical utility. This advancement addresses the critical gap in antibiotic discovery pipelines, offering a powerful tool to combat rising antimicrobial resistance through rapid screening of environmental samples for novel bioactive compounds with varied mechanisms of action.

Urinary tract infections caused by E. coli represent a significant clinical burden, compounded by rising antimicrobial resistance that demands rapid pathogen identification and susceptibility testing. This study presents an innovative smartphone-integrated electrochemical platform capable of detecting E. coli within thirty minutes and simultaneously assessing susceptibility to four antibiotics in five hours—substantially faster than conventional methods requiring two to five days. The portable device utilizes an indium tin oxide-based immunosensor functionalized with gold nanoparticles and monoclonal antibodies, achieving sensitive detection across clinically relevant bacterial concentrations. Integration of microfluidic reservoirs and on-chip heating enables controlled bacterial incubation with real-time electrochemical analysis, offering a compact, multiplexed diagnostic solution to address antimicrobial resistance and improve clinical outcomes for UTI patients.

Biosensors represent a transformative approach to detecting multiple respiratory viral pathogens simultaneously, offering significant advantages over traditional diagnostic methods. This comprehensive review examines the latest advancements in multiplex biosensor technology, published in Archives of Microbiology in June 2026. The article explores how biosensors enable rapid, accurate, and cost-effective identification of various respiratory viruses in clinical settings. By integrating multiple detection capabilities into single platforms, these tools enhance diagnostic efficiency and support timely clinical decision-making. The review provides valuable insights for researchers and healthcare professionals seeking innovative solutions to improve respiratory pathogen detection and disease management protocols.

Cancer represents a significant global health challenge, claiming approximately ten million lives annually with disproportionate mortality in resource-limited regions lacking adequate diagnostic infrastructure. Traditional oncology approaches, relying on invasive tissue-based diagnosis and imaging, are constrained by time intensity and inability to capture tumor heterogeneity. The observation that early-stage cancers demonstrate substantially improved survival rates has catalyzed a shift toward precision oncology, integrating molecular profiling with clinical and imaging data. This transformation is driven by two converging technological advances: highly sensitive, non-invasive biomarker platforms and exponential artificial intelligence development. Digital biomarkers, derived from biological samples, medical imaging, or wearable devices, enable continuous non-invasive monitoring through liquid biopsy and imaging analysis. Machine learning integration with these biomarkers transitions oncology from reactive to proactive, extracting actionable insights from complex biological data to enhance early detection and treatment selection.

Quantum nanomaterials, particularly semiconductor and carbon quantum dots, are transforming precision medicine through their exceptional optical, electronic, and magnetic properties derived from quantum confinement effects. These materials enable diagnostic and therapeutic applications at the molecular and subcellular level, offering size-dependent fluorescence, sharp emission spectra, and ultra-high sensitivity. In diagnostics, quantum dots facilitate early disease detection through sensitive biomarker analysis, supporting personalized medicine approaches. Therapeutically, they serve as drug and gene carriers, photosensitizers for photodynamic and photothermal therapies, and multifunctional theranostic platforms integrating both imaging and treatment modalities. Their unique properties position quantum nanomaterials as invaluable tools for advancing modern medical practice.

# Summary Researchers have developed an innovative single-tube asymmetric ERA-CRISPR/Cas12a diagnostic system that represents a significant advancement in molecular detection technology. This integrated approach leverages the synergistic benefits of enzymatic amplification and CRISPR-based detection to substantially improve diagnostic sensitivity while simultaneously minimizing false-positive results. The streamlined single-tube format enhances practical applicability and reduces operational complexity. By addressing key limitations of existing CRISPR-based diagnostic methods, this development substantially expands their utility across diverse clinical and research applications, particularly in resource-limited settings where simplicity and reliability are paramount.

Nucleic acid-based biosensing represents a transformative frontier in diagnostic technology, offering unprecedented sensitivity and specificity for detecting biological targets. This comprehensive review examines cutting-edge advances in leveraging DNA and RNA molecules as biosensing elements, exploring innovative approaches that enhance detection capabilities across medical, environmental, and industrial applications. The integration of nanotechnology with nucleic acid systems enables miniaturized devices with improved performance metrics. These developments promise to revolutionize disease diagnosis, pathogen detection, and biomarker identification, while reducing analysis time and costs. The open-access publication contributes valuable insights to the scientific community, advancing understanding of nucleic acid biosensing's potential to address critical healthcare and research challenges.

Pancreatic ductal adenocarcinoma remains a particularly lethal cancer due to diagnostic delays and nonspecific symptoms. Liquid biopsy shows promise as a noninvasive screening tool, yet sample heterogeneity poses significant challenges. Machine learning and artificial intelligence techniques offer solutions by identifying high-value biomarkers from complex datasets. This systematic review examined 18 studies following PRISMA-ScR guidelines, analyzing AI-powered liquid biopsy approaches for early PDAC detection. Blood samples dominated the research (15 studies), while random forests and support vector machines emerged as the most utilized algorithms. Deep learning methods received limited exploration. Significant limitations include inconsistent reporting of model performance metrics and small cohort sizes, highlighting the need for standardized methodologies in this emerging field.

AOA Dx has developed a promising lipid-protein biomarker diagnostic for early ovarian cancer detection, addressing a significant gap in women's health innovation. Co-founder Anna Jeter highlights that women's health has been historically underinvestigated despite representing half the population, with ovarian cancer diagnostics remaining largely unchanged since the introduction of CA-125 in 1987. Early detection is critical, as over 90% of women survive stage 1 ovarian cancer, yet approximately 80% of cases are diagnosed at advanced stages. Through a partnership with McGill University, the company investigated multi-omics approaches to identify biological signals missed by existing diagnostics, representing a meaningful advancement in oncology diagnostics and precision medicine for women's health.

The FDA regulates artificial intelligence and machine learning-based Software as Medical Devices (SaMD) under a standardized risk-based framework applicable to all medical devices. In 2024, the FDA cleared 168 AI/ML-enabled devices, all classified as Class II (moderate-risk), predominantly through the 510(k) pathway. These SaMD applications span diagnostics, quantification, and triage functions, yet none have achieved Class III high-risk status to date. The FDA's regulatory approach prioritizes premarket safety and effectiveness review of AI algorithms while transitioning toward comprehensive product lifecycle management, including postmarket algorithm modifications. Software functioning in clinical diagnosis, treatment, or patient management qualifies as regulated medical devices unless explicitly exempted, and follows established authorization pathways based on assessed risk levels.