Search Results (4,592)

Polymerase chain reaction (PCR) is the primary method for virus detection; however, its complex preprocessing has prompted research into simpler immunoassay-based approaches. Among these, techniques using antibody-modified magnetic particles, exemplified by digital ELISA, provide ultra-high sensitivity comparable to PCR by efficiently capturing trace viruses and enabling concentration, washing, and transfer to microreactors. In this study, we evaluated the virus capture efficiency of antibody-modified magnetic particles based on quantitative PCR (qPCR). Influenza A virus (H1N1/A/Puerto Rico/8/1934) was tested with 1 μm magnetic beads modified with HA1 antibodies. As quantification becomes unreliable and difficult in an extremely low-concentration range near the detection limit of qPCR, low-concentration viral suspensions (10⁵ copies/mL) were mixed with particle dispersions (up to 5 × 10⁸ particles/mL) for 10 min, followed by magnetic separation and washing, and the remaining virus in each fraction was analyzed by qPCR. At the highest particle concentration, capture rates exceeded 80% relative to the initial suspension, indicating near-complete capturing when considering free nucleic acids. Time-course analysis showed that the capture rate reached saturation within 2 min, with approximately 90% of the saturation at 1 min. Furthermore, kinetic modeling of magnetic bead–virus binding reproduced experimental data. These findings demonstrate that short mixing times with high particle concentrations enable efficient virus capture, contributing to the development of rapid and highly sensitive immunoassay systems. Full article

This paper proposes and experimentally validates a label-free microdroplet concentration detector based on a quad-resonator metamaterial. The device exploits the linear relationship between the dielectric constant of a binary mixed solution and its concentration, mapping concentration information to absorption frequency shifts with a sensitivity of 28.53 GHz/RIU. System modeling was performed through full-wave simulation. Experimental results demonstrate a highly linear relationship between resonance frequency shift and concentration across ethanol, water, and ethanol–water solutions. The relative deviation between simulation and measurement is less than 3%, validating the model’s reliability and the robustness of the detection principle. This detector supports rapid non-contact sample replacement without requiring chemical labeling or specialized packaging. It can be mass-produced on standard PDMS substrates, with each unit reusable for >50 cycles. With a single measurement time of <30 s, it meets high-throughput detection demands. Featuring low power consumption, high precision, and scalability, this device holds broad application prospects in point-of-care diagnostics, online process monitoring, and resource-constrained scenarios. Future work will focus on achieving simultaneous multi-component detection via multi-resonator arrays and integrating chip-level wireless readout modules to further enhance portability and system integration. Full article

Modern TCP/IP networks are increasingly exposed to unpredictable conditions, both from the physical transmission medium and from malicious cyber threats. Traditional stochastic models often fail to capture the non-linear and highly sensitive nature of these disturbances. This work introduces a formal mathematical framework combining classical network modeling with chaos theory to describe perturbations in latency and packet loss, alongside adversarial processes such as denial-of-service, packet injection, or routing attacks. By structuring the problem into four scenarios (quiescent, perturbed, attacked, perturbed-attacked), the model enables a systematic exploration of resilience and emergent dynamics. The integration of artificial intelligence techniques further enhances this approach, allowing automated detection of chaotic patterns, anomaly classification, and predictive analytics. Machine learning models trained on simulation outputs can identify subtle signatures distinguishing chaotic perturbations from cyber attacks, supporting proactive defense and adaptive traffic engineering. This combination of formal modeling, chaos theory, and AI-driven analysis provides network engineers and security specialists with a powerful toolkit to understand, predict, and mitigate complex threats that go beyond conventional probabilistic assumptions. The result is a more robust methodology for safeguarding critical infrastructures in highly dynamic and adversarial environments. Full article

This work proposes new architecture, supported by analytical modelling and computer-aided design (CAD) simulations, for a highly sensitive monolayer graphene-gated AlGaN/GaN HEMT terahertz (THz) detector operating at room temperature (RT). The monolayer graphene gate acts as a surface plasmon absorber for the incident THz radiation. The carrier density perturbation caused by incident THz energy on the monolayer graphene surface is then capacitively coupled to the two-dimensional electron gas (2DEG) channel of the HEMT structure underneath. The channel is partially depleted for increased mobility and nonlinearity with potential asymmetry across the channel for consistent photogeneration. The Drude absorption of THz radiation initiates intraband transitions in monolayer graphene, thereby reducing phonon losses. These reduced phonon losses enable RT THz detection. Based on our simulations, the proposed detector architecture can generate a responsivity of 2.12 × 10⁶ V/W at 1 THz with a broadband bandwidth of 2 THz. Full article

Cerium oxide (CeO₂) nanozymes, also known as nanoceria have emerged as a versatile class of catalytic nanomaterials capable of mimicking key redox enzymes, including oxidases and peroxidases. Their tunable Ce³⁺/Ce⁴⁺ redox cycling, high density of oxygen vacancies, and exceptional resistance to thermal, pH, and storage stress distinguish CeO₂ from conventional enzyme labels, such as horseradish peroxidase (HRP). In immunoassays, CeO₂ enables H₂O₂-free TMB (3,3’,5,5’-tetramethylbenzidine) oxidation, generating strong chromogenic signals with minimal background. Although CeO₂ nanozymes have been explored in colorimetric, chemiluminescent, and photoactive immunoassays, their integration into lateral flow immunoassays (LFIAs) remains limited, with only a few hybrid CeO₂-containing systems reported to date. This mini-review highlights the limitations of conventional peroxidase-based formats and explains how CeO₂’s redox cycling (Ce³⁺/Ce⁴⁺) and oxygen-vacancy-driven catalysis deliver stable, reagent-free signal amplification. Emphasis is placed on the synthetic control of CeO₂, conjugation chemistry with antibodies, and integration into LFIA architectures. CeO₂ enables hydrogen-peroxide-free colorimetric detection with improved robustness and sensitivity, positioning it as a promising catalytic label for point-of-care testing. However, it may aggregate in high-ionic-strength buffers, and its synthesis cost increases for highly uniform, vacancy-engineered materials. Surface functionalization with polymers or dopants and optimized dispersion strategies can mitigate these issues, guiding future practical implementations. Full article

In recent years, the rapid commercialization and widespread adoption of portable and wearable electronic devices have imposed increasingly stringent performance requirements on flexible sensors, including enhanced sensitivity, stability, response speed, comfort, and integration. This trend has driven extensive research and technological advancement in sensor material systems, among which carbon-based materials have emerged as core candidates for high-performance flexible sensors due to their exceptional electrical conductivity, mechanical flexibility, chemical stability, and highly tunable structural features. Meanwhile, new sensing mechanisms and innovative device architectures continue to emerge, demonstrating significant value in real-time health monitoring, early disease detection, and motion-state analysis, thereby expanding the functional boundaries of flexible sensors in the health-care sector. This review focuses on the application progress and future opportunities of carbon-based materials in flexible sensors, systematically summarizing the critical roles and performance-optimization strategies of carbon nanotubes, graphene, carbon fibers, carbon black, and their derivative composites in various sensing systems, including strain and pressure sensing, physiological electrical signal detection, temperature monitoring, and chemical or environmental sensing. In response to the growing demands of modern health-monitoring technologies, this review also examines the practical applications and challenges of flexible sensors—particularly those based on emerging mechanisms and novel structural designs—in areas such as heart-rate tracking, blood-pressure estimation, respiratory monitoring, sweat-component analysis, and epidermal electrophysiological signal acquisition. By synthesizing the current research landscape, technological pathways, and emerging opportunities of carbon-based materials in flexible sensors, and by evaluating the design principles and practical performance of diverse health-monitoring devices, this review aims to provide meaningful reference insights for researchers and support the continued innovation and practical deployment of next-generation flexible sensing technologies. Full article

The demand for rapid and highly sensitive sensing technologies is increasing across diverse fields, including precise disease diagnosis, early-stage screening, and real-time environmental monitoring. Field-effect transistor (FET)-based sensing platforms have shown tremendous potential for detecting target molecules at extremely low concentrations, owing to their ultrahigh sensitivity, label-free and amplification-free operation, and rapid response. In recent years, the rapid advancement of nucleic acid probe design and interfacial engineering has markedly accelerated the development of FET sensors, leading to the emergence of nucleic acid-based FET (NA-FET) biosensors. Beyond their fundamental role in nucleic acid detection, the integration of nucleic acid aptamers and framework nucleic acids has greatly expanded NA-FET biosensors’ applicability to a wide range of analytes and multiplexed detection. At the same time, advances in semiconductor materials have endowed the NA-FET biosensor with highly efficient signal transduction and diverse device architectures, enabling successful proof-of-concept demonstrations for various clinically and environmentally relevant molecular biomarkers. Furthermore, the integration into portable, wearable, and implantable devices has laid a solid foundation for their future development into real-world applications. This review summarizes recent cutting-edge progress in NA-FET biosensors, highlights key design strategies and performance improvements, and discusses current challenges, future development directions, and their prospects for practical applications. Full article

Background/Objectives: Fluvoxamine (FLU) is a selective serotonin reuptake inhibitor and one of the most potent agonists of the sigma-1 receptor. Emerging evidence shows that FLU exerts protective effects in multiple organs, making it a promising candidate for topical ocular therapy. Developing an FLU eyedrop for glaucoma can address a significant treatment gap with potentially fewer side effects compared with conventional therapies. To optimise formulation development, precise quantification of FLU in ocular compartments such as aqueous humour, as well as systemic circulation, is essential to characterise drug absorption, ocular bioavailability, and safety. Methods: We developed and validated a UHPLC-MS method for FLU detection in aqueous humour and serum using simple sample preparation steps. Results: The 11-min-long reverse phase chromatography followed by SRM-based mass spectrometry detection provides a highly selective and sensitive FLU detection method. Our method was proved to be linear in the 0.0625–1.5 µg/mL range and was validated according to the EMA guidelines. Conclusions: The simplicity of sample preparation, the tolerable matrix effects, and the favourable detection parameters provide a robust tool for preclinical pharmacokinetic and pharmacodynamic studies of FLU’s ocular protective effects. Full article

Underwater laser signal attenuation challenges conventional detection, while single-photon LiDAR (SPL) with high sensitivity shows promise. Existing underwater SPL studies primarily focus on isolated parameters, while the coupled effects of environmental and system parameters remain insufficiently investigated. In this work, a 532 nm underwater SPL system was developed to systematically explore multi-parameter coupling mechanisms in laboratory water tanks, including air and three turbidity levels, three detection distances, four laser energy levels, three integration times, and seven targets. This provides quantitative guidance for optimizing SPL systems in complex underwater environments. The results show that the SPL system maintained sub-nanosecond ranging precision, with the standard deviation (SD) of the ranging measurement at 50 cm being 0.0117 ns under low turbidity (0.11 m⁻¹) with 50% laser energy, while under high turbidity (4.2 m⁻¹) conditions, it increased to 0.0338 ns. At 100 cm, the SD was 0.0187 ns in low turbidity and rose to 0.0877 ns in high turbidity. Furthermore, the inversion error of the highly reflectivity minerals was kept within 3%, and the inversion value of reflectivity decreased exponentially with the increase of turbidity. Moreover, there is an important discovery for the phenomenon of the forward shift of photon flight time detected for highly reflectivity targets. Longer integration times effectively enhanced the signal-to-noise ratio (SNR) under severe attenuation, whereas excessive laser energy risked detector saturation. These findings provide a systematic characterization of how multifactor coupling governs SPL signal dynamics. The results validate the feasibility of SPL for complex underwater detection and offer theoretical insights and technical guidance for future marine applications in resource exploration, environmental monitoring, and national security. Full article

The ability of an animal to perceive its visual environment underpins many behaviors essential to survival, including navigation, foraging, predator avoidance, and recognition of conspecific individuals, making vision a critical element of both reproductive success and survival itself. In insects, eyes have evolved widely, shaped by different habitats and lifestyles, with striking examples such as the high-resolution diurnal vision of dragonflies, which enables rapid detection of prey and environmental features, in contrast with the highly sensitive nocturnal optical system of hawkmoths, which specializes in capturing even single photons. At the core of this diversity is a fundamental trade-off: at one extreme lies sensitivity, the ability to perceive visual stimuli, even under poor lighting conditions. At the other extreme, acuity, is the ability to resolve fine spatial details. This review seeks to synthesize current knowledge of insect visual systems, from their evolutionary origins to the developmental processes so far identified, from cellular organization to their role in behavior, to provide insights for designing novel, targeted, and sustainable vision-based technologies for the control of pest insects. Full article

Rapid detection of β-lactamase activity is becoming increasingly important as β-lactam resistance spreads at an alarming rate and conventional diagnostics often require several hours to deliver actionable results. Over the past decade, methods based on luminescence, bioluminescence, chemiluminescence, and fluorescence have become powerful tools for the functional assessment of resistance resulting from β-lactamase activity. These approaches provide highly sensitive, activity-based readouts, often within minutes, and frequently rely on simple optical instrumentation. In this review, we summarize recent developments in luminescent probe design between 2015 and 2025, with emphasis on reaction mechanisms, analytical performance, and the ability of these systems to discriminate between different β-lactamases, including narrow-spectrum enzymes, AmpC, ESBL, and carbapenemases. We also discuss their applications in bacterial cultures, clinical isolates, complex biological matrices and, in some cases, in vivo models. While luminescent assays are not yet positioned to replace standard susceptibility testing, they offer a practical and increasingly robust complement to culture-based and molecular methods. The emerging trends highlighted here, such as self-immobilizing fluorogenic probes, chemiluminescent relay systems, nanomaterial-based sensors and AI-assisted mobile platforms, suggest that luminescent β-lactamase detection could play a meaningful role in future rapid diagnostics and resistance surveillance. Full article

Artificial Intelligence (AI) and Precision Medicine are increasingly influencing pediatric pharmacotherapy, where age-dependent pharmacokinetic variability demands highly individualized therapeutic strategies. This review examines current applications of AI in pediatric precision medicine and evaluates their clinical relevance and translational challenges. Recent evidence shows substantial progress across multiple domains. In pharmacogenomics, predictive models have reached R² = 0.95 for drug exposure. Tools for adverse drug reaction detection report sensitivities of 81.5% and specificities of 79.5%. Clinical decision support systems for pediatric epilepsy have achieved diagnostic accuracies of 93.4%. Real-world implementations have been associated with a 75% reduction in prescription distribution errors and a 65% improvement in adverse drug reaction detection. Despite these advances, clinical translation remains limited: only 0.38% of pediatric AI models progress to testing in real patients, and 77% of published studies carry a high risk of bias. These gaps highlight the need for rigorous validation, improved data quality, and careful consideration of ethical and algorithmic constraints. Overall, AI has the potential to shift pediatric pharmacotherapy from empirically driven decisions toward predictive, precision-based approaches. Achieving this goal will require well-designed pediatric studies and sustained interdisciplinary collaboration to ensure safe and effective integration into clinical practice. Full article

African swine fever (ASF), caused by the African swine fever virus (ASFV), is a highly contagious and fatal disease. Accurate detection in the early stages of an outbreak relies on molecular methods, but serological monitoring at the population level is also crucial for assessing the extent of exposure and past infections. This experiment developed an indirect enzyme-linked immunosorbent assay (ELISA) to detect antibodies against ASFV, using three ASFV RNA polymerase subunits (H359L, C147L, and D339L) as coating antigens. The recombinant proteins were successfully expressed in Escherichia coli and purified. Using a checkerboard titration method, we systematically optimized key assay parameters, determining the optimal coating conditions to be a mixture of H359L, C147L, and D339L at a volume ratio of 1:2:2, with individual concentrations of 1 μg/mL, 0.4 μg/mL, and 0.5 μg/mL, respectively. Other optimized parameters included a serum dilution of 1:200, a blocking buffer containing 5% skim milk, and specific incubation conditions for the secondary antibody and substrate. The cut-off value was established at 0.430 ($\overline{x}$ + 4SD) based on 30 negative sera. The established triple-antigen indirect ELISA exhibited high sensitivity (detecting positives at dilutions up to 1:3200) and excellent specificity (no cross-reactivity with antisera against CSFV, PRRSV, PRV, PCV2, and PEDV. Both intra and inter assay repeatability were confirmed, with coefficients of variation ranging from 1.020% to 7.600%. Validation with 123 clinical serum samples demonstrated a 96.75% concordance rate with a commercial kit. In conclusion, the three-antigen indirect ELISA established in this study exhibits high specificity and sensitivity, making it suitable for serological surveillance and exposure assessment of ASFV antibodies. It can be combined with molecular detection for epidemiological investigations and integrated prevention and control measures. Full article

Herbicides are widely used agrochemicals and are increasingly recognised as contaminants of emerging concern in aquatic environments due to their extensive application, environmental persistence, and potential ecological and human health impacts. Their determination in water presents significant analytical challenges, as these compounds occur at trace to ultra-trace levels and encompass a wide range of chemical properties, including highly polar and ionic species as well as transformation products. This review provides a critical overview of recent advances in separation technologies for the analysis of herbicides in water, based on peer-reviewed studies published between 2020 and 2025 retrieved from the PubMed and Scopus databases. The discussion focuses on developments in sample preparation, extraction strategies, chromatographic separation, and detection techniques, with particular attention to analytical performance and sustainability. The reviewed studies demonstrate that solid-phase extraction remains central to achieving the lowest detection limits, while miniaturised and greener extraction approaches are increasingly adopted to reduce solvent consumption and simplify workflows. Advances in chromatographic separation and detection, especially liquid chromatography coupled to tandem mass spectrometry, have further enhanced sensitivity and selectivity for a broad range of herbicides. Overall, this review highlights current analytical capabilities and emerging trends, outlining future directions for reliable and sustainable monitoring of herbicides in aquatic environments. Full article

Invasive pulmonary fungal infections remain a major cause of morbidity and mortality among immunocompromised and critically ill patients. Rapid and accurate diagnosis is crucial for improving outcomes, yet conventional methods such as culture and histopathology suffer from limited sensitivity and slow turnaround times. Recently, significant progress has been made in the development and standardization of serological and molecular biomarkers that enhance the early detection of the key pulmonary fungal diseases, particularly invasive pulmonary aspergillosis and pneumocystosis. Diagnostic tools for mucormycosis, however, remain scarce. PCR tools have strong potential to significantly improve early detection, but they are not yet widely implemented, and standardized commercial assays remain limited. Accessible antigen-based tests with robust performance are highly anticipated and expected to become available soon. This review summarizes the current evidence regarding the optimal use of galactomannan, β-D-glucan and PCR-based assays, emphasizing how their performance varies according to the pathogen, the type of specimen and the host population. Specific challenges, such as differentiating colonization from infection in non-HIV Pneumocystis pneumonia or interpreting galactomannan and PCR in patients receiving mold-active prophylaxis, are highlighted. We also discuss how combining biomarkers can enhance diagnostic accuracy and support timely therapeutic decisions. A clear understanding of the strengths, limitations and appropriate interpretation of these diagnostic tools is crucial in an era of increasing host complexity, shifting fungal epidemiology, and expanding antifungal options. Full article