Diagnostic Platform Research Articles

Salivary Molecular Spectroscopy with Machine Learning Algorithms for a Diagnostic Triage for Amelogenesis Imperfecta.

Amelogenesis imperfecta (AI) is a genetic disease characterized by poor formation of tooth enamel. AI occurs due to mutations, especially in AMEL, ENAM, KLK4, MMP20, and FAM83H, associated with changes in matrix proteins, matrix proteases, cell-matrix adhesion proteins, and transport proteins of enamel. Due to the wide variety of phenotypes, the diagnosis of AI is complex, requiring a genetic test to characterize it better. Thus, there is a demand for developing low-cost, noninvasive, and accurate platforms for AI diagnostics. This case-control pilot study aimed to test salivary vibrational modes obtained in attenuated total reflection fourier-transformed infrared (ATR-FTIR) together with machine learning algorithms: linear discriminant analysis (LDA), random forest, and support vector machine (SVM) could be used to discriminate AI from control subjects due to changes in salivary components. The best-performing SVM algorithm discriminates AI better than matched-control subjects with a sensitivity of 100%, specificity of 79%, and accuracy of 88%. The five main vibrational modes with higher feature importance in the Shapley Additive Explanations (SHAP) were 1010 cm-1, 1013 cm-1, 1002 cm-1, 1004 cm-1, and 1011 cm-1 in these best-performing SVM algorithms, suggesting these vibrational modes as a pre-validated salivary infrared spectral area as a potential biomarker for AI screening. In summary, ATR-FTIR spectroscopy and machine learning algorithms can be used on saliva samples to discriminate AI and are further explored as a screening tool.

Passive Immunotherapy of Cynomolgus Monkeys with Anti-Rotavirus IgY.

Immunoglobulins Y (IgY) purified from egg yolks of hens represents an attractive, cost-effective alternative for the development of new diagnostic and therapeutic platforms. In this study, we evaluated the therapeutic efficacy of rotavirus-specific IgY in a cynomolgus monkey (Macaca fascicularis) model. Animals were experimentally infected with human rotavirus Group A (RVA), the most common cause of severe acute diarrhoea among young children worldwide. Animals were administered human RVA (3.1 × 107 FFU/mL) by oral gavage, challenged with 2.5 mg of anti-RVA IgY orally, and monitored for five days according to clinical, haematological and biochemical parameters; serum electrolyte levels; viral shedding; and histopathological changes. Immunotherapy with anti-RVA IgY had a protective effect against severe rotavirus-induced enteritis in four of the ten treated monkeys, as evidenced by histopathological findings. Although only one animal had diarrhoea, all but one exhibited virus shedding regardless of the treatment.

Paper-Based procalcitonin and Interleukin-6 test strip with Spectrum-Based optical reader for enterovirus severity differentiation in children

Infectious diseases significantly impact global health, necessitating prompt diagnosis to mitigate life-threatening sepsis risk. Identifying patients at risk of severe neurological complications from enterovirus infections is challenging due to nonspecific initial presentations. Point-of-care testing (POCT) has emerged as a transformative tool, with low-cost lateral-flow colorimetric assays showing promise in deployable POCT devices. We developed a PCT/IL-6 rapid diagnostic system integrating lateral flow assay (LFA) test strips and a portable optical spectrum reader, allowing simultaneous semi-quantitative measurement of serum PCT and IL-6 within 30 min at the point of care. The system demonstrated a strong correlation with traditional ELISA and effectively differentiated severe pediatric enterovirus cases using serum samples. IL-6 showed superior discriminatory ability over PCT in identifying patients with severe neurological complications. This novel diagnostic platform holds great potential for early sepsis recognition and infectious disease management, especially in resource-limited settings.

Revolutionizing ELISA: A one-step blocking approach using lipid bilayer coatings

Enzyme-linked immunosorbent assay (ELISA) is an essential technique for biomolecule detection in diagnostics and research, but traditional protocols are time-consuming and variable. Conventional blocking agents like bovine serum albumin (BSA) pose ethical issues and potential assay interference. This study presents a one-step lipid-blocking approach to simplify the ELISA procedure. Compared to conventional blockers, the Lipid Universal Coating Assembly (LUCA) antifouling blocker showed comparable sensitivity while significantly reducing processing time and steps. Furthermore, it showed improved co-blocking efficacy and signal intensity in conventional protocols when combined with minimal BSA concentrations. Stability tests under accelerated aging confirmed the robustness of the LUCA antifouling blocker. Additionally, it effectively facilitated antibody detection for COVID-19 antigens in direct ELISA and human IL-6 antigen in Sandwich ELISA, suggesting its versatile applicability. Taken together, our findings reveal that one-step lipid blocking not only streamlines the ELISA process but also maintains high sensitivity and specificity, providing an efficient, user-friendly, and environmentally friendly alternative to traditional ELISA blockers and a robust platform for rapid diagnostics.

Microneedles-Based Theranostic Platform: From the Past to the Future.

Fully integrated theranostic devices are highly esteemed in clinical applications, offering immense potential in real-time disease monitoring and personalized care. Microneedles (MNs), as innovative and wearable devices, boast important advantages in biosensing and therapy, thus holding significant promise in the advancement of diagnostic and therapeutic platforms. Encouragingly, advancements in electrochemical sensing technology, micronano fabrication, and biocompatible materials are propelling momentum for MNs-based closed-loop systems, enhancing detection capabilities, biocompatibility, and cost-effectiveness. Moreover, the notable progress in integrating MN chips with other biochips signifies a frontier for growth. Successful clinical trials in target molecule monitoring and drug delivery domains herald excellent clinical translational prospects for the aforementioned theranostic platform. Finally, we delineate both challenges and opportunities in the development of integrated diagnostic and therapeutic MN systems, including continuous monitoring, intelligent control algorithms, safety, and regulatory considerations.

CRISPR-based platform for clinical diagnosis of Neisseria gonorrhoeae and simultaneous tracking of ceftriaxone-resistant FC428 clone

The global dissemination of the ceftriaxone-resistant Neisseria gonorrhoeae FC428 clone poses substantial challenges in the control and treatment of gonorrhoea, resulting in heightened morbidity rates and the increased risk of public health emergencies. However, currently, the identification of N. gonorrhoeae FC428 clone is labor-intensive and laboratory-based, which is not suitable for rapid on-site analyses and effective decision making. Herein, an Equipment-free CRISPR/Cas12a assisted RPA platform is developed for rapid duplex detection (E-card), which provides a solution for early and effective clinical diagnosis of N. gonorrhoeae, particularly the simultaneous tracking of ceftriaxone-resistant FC428 clone to allow reasonable and timely antimicrobial therapy. The E-card achieves 1 copy/reaction for N. gonorrhoeae screening and 10 copies/reaction for ceftriaxone-resistant FC428 clone detection within 40 min. The accuracy of N. gonorrhoeae and FC428 identification has been validated by concordance rates of 100 % and 98 % between the E-card platform and PCR-sequencing, respectively. This convenient CRISPR-based disposable molecular diagnostic platform can serve as a powerful tool to rapid detection of N. gonorrhoeae and its ceftriaxone-resistant FC428 clone, enabling effective assessment of infection, effective medicine decision making and the mitigation of health burdens.

Evaluation of Hi-C Sequencing for Detection of Gene Fusions in Hematologic and Solid Tumor Pediatric Cancer Samples.

Hi-C sequencing is a DNA-based next-generation sequencing method that preserves the 3D genome conformation and has shown promise in detecting genomic rearrangements in translational research studies. To evaluate Hi-C as a potential clinical diagnostic platform, analytical concordance with routine laboratory testing was assessed using primary pediatric leukemia and sarcoma specimens. Archived viable and non-viable frozen leukemic cells and formalin-fixed paraffin-embedded (FFPE) tumor specimens were analyzed. Pediatric acute myeloid leukemia (AML) and alveolar rhabdomyosarcoma (A-RMS) specimens with known genomic rearrangements were subjected to Hi-C to assess analytical concordance. Subsequently, a discovery cohort consisting of AML and acute lymphoblastic leukemia (ALL) cases without known genomic rearrangements based on prior clinical diagnostic testing was evaluated to determine whether Hi-C could detect rearrangements. Using a standard sequencing depth of 50 million raw read-pairs per sample, or approximately 5X raw genomic coverage, we observed 100% concordance between Hi-C and previous clinical cytogenetic and molecular testing. In the discovery cohort, a clinically relevant gene fusion was detected in 45% of leukemia cases (5/11). This study provides an institutional proof of principle evaluation of Hi-C sequencing to medical diagnostic testing as it identified several clinically relevant rearrangements, including those that were missed by current clinical testing workflows.

Enhancing Agriculture through AloT and Data Analytics Middleware

Middleware in Agriculture delves into the data analytics role of systematic Artificial Intelligence of Things (AIoT) in convergence agriculture with smart farming. AIoT devices, remote diagnostic data analytics platforms, data analytics, formal recognition, and vision learning have generated both the amount and nature of work in rural areas. The reason for the developing changes in the global population by age is the bias in the distribution of food resources, as well as changes in climate change and the soil condition of compost. Data scientists are soon attempting to dive convergence Internet of Things (IoT) advances in savvy cultivating to support ranchers in producing better seeds, crop assurance, and manures utilizing AIoT convergence technology[1]. This distinguishes consumer-provider-administrator as a service subscriber roleon the platform, which goes for earning the nation's economy and the profitability of ranchers. The central regions where AIoT begins to emerge are agricultural robots, scrutiny, and soil and yield observation. While middleware technology for data analysis is applied, there is a great advantage of analyzing regional observation data at a real-time level. Based on this analysis method, it will spread to high-tech industries connected to production, processing, and consumption, which are subdivided areas of each precision agriculture. In this sense, ranchers are utilizing sensors for data analysis and soil information in a detailed way to gather a model that the executives dynamic platforms might use for further examination. Through an outline of real-time data analytics AIoT applications in the farming convergence industry, this paper tries a trust data basement forecast to the farming protocols[2]. It starts with a roadmap to the AIoT and an investigation of real-time data strategies utilized in the horticultural industry data analytics using Universal Middleware, service platforms, vision learning, and dynamic statistics. This study advances a dynamic platform examination of the literature on data resources and how AIoT is utilized in farming convergence. This study looked at the unstructured systems of modern agriculture, divided these processes into devices and services, and presented a systematic formalization model. It should contribute to the integration of segmented data connectivity in the AIoT field. The enhanced research model contributes to the discovery of numerous untapped additional services between devices and services.

Unveiling the Quest: Crafting an Enzyme-Linked Immunosorbent Assay (ELISA) Technique to Uncover COVID-19 Antibodies.

The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has had a profound impact on global health. Rapid and accurate diagnostic tools are crucial for effective disease control and management. The enzyme-linked immunosorbent assay (ELISA) has emerged as a reliable and widely used method for detecting COVID-19 antibodies in patients, which develop in response to SARS-CoV-2 infection. While the ELISA technique is effective in identifying the presence of antibodies and thus confirming exposure to the virus, its role in predicting the clinical course and severity of the disease is limited. ELISA primarily confirms prior exposure to the virus or vaccination status, but it does not directly correlate antibody levels with the severity or progression of the disease. The variability in clinical outcomes is influenced by factors such as viral load, patient co-morbidities, genetic predispositions, and the timing of the immune response. ELISA has diverse applications in epidemiology, vaccination assessment, and therapeutic development. It determines antibody prevalence, aids in surveillance, and evaluates vaccine effectiveness and antibody protection duration. ELISA quantitatively measures antibody levels, providing insights into the immune response and treatment efficacy. Challenges include specialized facilities and personnel, cross-reactivity, and false results. Multiplex assays and integration with other diagnostics are future directions. In summary, ELISA is an essential tool in COVID-19 diagnostics, enabling precise assessment of the immune response and contributing to effective strategies. The development of point-of-care devices that integrate ELISA technology could enable rapid and accessible testing in various settings. Additionally, integrating ELISA with other diagnostic platforms could enhance the overall diagnostic capabilities for COVID-19. Despite challenges, ongoing advancements in ELISA technology, and its integration with other diagnostic approaches, hold promise for further improving COVID-19 diagnostics and management strategies.

I-Biomarker CaDx: A circulating miRNA-based multi-cancer detection test with generative and explainable AI for colorectal cancer.

64 Background: Colorectal cancer (CRC), the second most deadly cancer, underscores the critical need for early detection to significantly improve treatment outcomes and survival rates. Colonoscopy, flexible sigmoidoscopy, and the fecal immunochemical tests (FIT), often fail to capture early disease, significantly decreasing the survival chance. Circulating miRNA is a promising non-invasive biomarker for various cancers, including CRC. The i-Biomarker CaDx (patent pending) is an innovative multi-cancer early detection and diagnosis platform, covering 32 cancer types with an impressive accuracy rate of 99-100%. This study focuses on the effectiveness of i-Biomarker CaDx for CRC, employing significant data collection and leveraging insights from Generative AI (GenAI) and Explainable Artificial Intelligence (XAI). Methods: We collected various available datasets (e.g. GSE106817, etc.) encompassing 305 colorectal cancer patients and a matching number of healthy controls. Microarray was employed to profile circulating miRNAs. We used various classification paradigms, e.g., decision trees, neural networks, etc. Hyperparameter optimization was conducted, and the best-performing classifiers were amalgamated in the final model, weighted by their respective efficacies. We assessed i-Biomarker CaDx's performance through cross-validation and independent test sets. The XAI provided detailed insights into miRNA variations associated with personalized diagnostic. GenAI integrated the test into the screening and early detection best practice workflows and performs Functional Analysis. Results: i-Biomarker CaDx shows exceptional diagnostic accuracy of 99-100%, surpassing conventional colorectal cancer diagnostic methods like colonoscopy, flexible sigmoidoscopy, and FIT. It can also be used for personalized treatment response monitoring. I-Biomarker effectively deciphers intricate miRNA relationships relevant to colorectal cancer using XAI. Thus, our analyses shed light on miRNA patterns and their associations with colorectal cancer, enhancing the understanding of the underlying molecular complexities of the disease. It goes further by explaining the personalized cellular and molecular mechanisms involved, and it will be integrated into the corresponding medical workflows. Conclusions: Our AI-powered multi-cancer early diagnostic platform demonstrates outstanding performance in detecting CRC, surpassing traditional diagnostic methods like colonoscopy, flexible sigmoidoscopy, and FIT. XAI allows for in-depth exploration of miRNA alterations and their impact on CRC, enriching our interpretations at both the population and individual levels. These findings underscore the substantial potential of i-Biomarker CaDx as a transformative, non-invasive diagnostic tool for CRC.

Development of a low-cost diagnostics platform for the identification of HBV DNA using CRISPR/Cas13a system

Development of a low-cost diagnostics platform for the identification of HBV DNA using CRISPR/Cas13a system

Lab-in-a-Vial Rapid Test for Internet of Things-Embedded Point-of-Healthcare Protein Biomarker Detection in Bodily Fluids.

Amateurs often struggle with detecting and quantifying protein biomarkers in body fluids due to the high expertise required. This study introduces a Lab-in-a-Vial (LV) rapid diagnostic platform, featuring hydrangea-like platinum nanozymes (PtNH), for rapid, accurate detection and quantification of protein biomarkers on-site within 15min. This method significantly enhances detection sensitivity for various biomarkers in body fluids, surpassing traditional methods such as enzyme-linked immunosorbent assays (ELISA) and lateral flow assays (LFA) by ≈250 to 1300 times. The LV platform uses a glass vial coated with specific bioreceptors such as antigens or antibodies, enabling rapid in vitro evaluation of disease risk from small fluid samples, similar to a personal ELISA-like point-of-care test (POCT). It overcomes challenges in on-site biomarker detection, allowing both detection and quantification through a portable wireless spectrometer for healthcare internet of things (H-IoT). The platform's effectiveness and adaptability are confirmed using IgG/IgM antibodies from SARS-CoV-2 infected patients and nuclear matrix protein (NMP22) from urothelial carcinoma (UC) patients as biomarkers. These tests demonstrated its accuracy and flexibility. This approach offers vast potential for diverse disease applications, provided that the relevant protein biomarkers in bodily fluids are identified.

Development and application of a novel recombinase polymerase amplification-Pyrococcus furiosus argonaute system for rapid detection of goose parvovirus

Rapid and accurate detection of goose parvovirus (GPV) is crucial for controlling outbreaks and mitigating their economic impact on the poultry industry. This study introduces recombinase polymerase amplification combined with the Pyrococcus furiosus argonaute (RPA-PfAgo) system, a novel diagnostic platform designed to address the limitations of traditional GPV detection methods. Capitalizing on the rapid DNA amplification of RPA and stringent nucleic acid cleavage by the PfAgo protein, the RPA-PfAgo system offers high specificity and sensitivity in detecting GPV. Our optimization efforts included primer and probe configurations, reaction parameters, and guided DNA selection, culminating in a detection threshold of 102 GPV DNA copies per microlitre. The specificity of the proposed method was rigorously validated against a spectrum of avian pathogens. Clinical application to lung tissues from GPV-infected geese yielded a detection concordance of 100%, surpassing that of qPCR and PCR in both rapidity and operational simplicity. The RPA-PfAgo system has emerged as a revolutionary diagnostic modality for managing this disease, as it is a promising rapid, economical, and onsite GPV detection method amenable to integration into broad-scale disease surveillance frameworks. Future explorations will extend the applicability of this method to diverse avian diseases and assess its field utility across various epidemiological landscapes.

Carbon Nanocomposites-based Electrochemical Sensors and Biosensors for Biomedical Diagnostics.

Detection of emergent biomolecules or biomarkers remains crucial for early diagnosis in advancing healthcare monitoring and biomedicine. The possibility for rapid detection, real-time monitoring, high sensitivity, low detection limit, good selectivity, and low cost is central, among other significant issues for advancing point-of-care diagnosis. Carbon-based nanocomposites have been employed as sensing materials for various biomarkers due to their high surface-to-volume ratio, high electrical conductivity, chemical stability, and biocompatibility. The carbon nanomaterials, such as carbon nanotubes (CNTs), graphene (GR), carbon quantum dots (CQDs), carbon fibres (CFs), and their nanocomposites have broadly integrated with numerous sensing electrode materials for the detection of biomarkers under various experimental settings. The present review includes the recent advances in the development of carbon nanomaterials-based electrochemical sensors and biosensors for biomedical applications. The preparation, electrode preparation, effective utilization of carbon-derived nanomaterials, and their sensing performances towards numerous biomarkers have been highlighted. The state-of-the-merit, challenges, and prospects for designing carbon nanocomposites-based electrochemical sensor/biosensor platforms for biomedical diagnostics have also been described.

Metagenomic sequencing in the diagnosis of resistance to antimicrobials

The purpose of the article is to analyze the literature on antimicrobial resistance and the metagenomic sequencing method. In total, 32 articles published in the years 2019–2024 and some previously published classic works were analyzed. Antimicrobial resistance (AMR) is one of the most serious threats to public health, animal health and environmental well-being globally, generating high costs. Metagenomic sequencing allows the detection of all genes in a sample, providing a complete picture of AMR. By sequencing it is possible to assess the location and transmissibility of the AMR genes. As surveillance networks and metagenomic sequencing, as one of the rapid diagnostic platforms, are implemented globally, it will be possible to detect and limit infectious outbreaks at a much earlier stage, thus saving lives and substantially reducing costs. In the near future, metagenomic sequencing will no longer be a luxury but a necessity as we engage in the ongoing fight against infectious diseases.

Gallium oxide (Ga2O3) energy dependent scintillation response to fast neutrons and flash gamma-rays.

Gallium oxide is a newly emerged ultrawide bandgap (4.9eV) semiconductor that is suitable as a combined electronics and radiation detection platform. We have experimentally demonstrated fast neutron and gamma-ray scintillation from Czochralski-grown β-Ga2O3 in a recent series (October 2023) of experiments at the unmoderated pulsed neutron spallation source located at the Los Alamos Neutron Science Center. Using the neutron time-of-flight (TOF) technique and a fast-gated intensified CCD camera, we observed energy-dependent neutron scintillation for neutron energies ranging from 1 to 400MeV, including the 14.1MeV neutron energy relevant to D-T fusion. Neutron flux is quantified and calibrated by cascading the scintillator after the fission chamber, enabling a detailed analysis of temporal and energy-dependent characteristics of the scintillation events. A pronounced scintillation signal from the spallation gamma flash with a temporal full width of half maximum of ∼4ns is indicative of the material's rapid response. Neutron energy dependent scintillation is observed using the TOF method at a 22.6-m distance from the neutron source. These results highlight the possibility of developing a Ga2O3 based fusion neutron diagnostic platform integrated with both scintillation and electronics functions on the integrated chip scale.

Mini-Program Enabled IoT Intelligent Molecular Diagnostic Device for Co-Detection and Spatiotemporal Mapping of Infectious Disease Pathogens.

Effective detection of infectious pathogens is crucial for disease prevention and control. We present an innovative Internet of Things (IoT) molecular diagnostic device featuring a WeChat mini-program for simultaneous detection and spatiotemporal mapping of respiratory pathogens. Leveraging social software's widespread usage, our device integrates seamlessly with WeChat, eliminating the need for app downloads and installations. Through a comprehensive detection system, including a user-friendly mini-program, a portable Point-of-Care fluorescence detector, and a diagnostic information management platform (EzDx Cloud), we demonstrate high sensitivity and specificity in detecting common respiratory viruses. Our SARS-CoV-2/H1N1 combo test kit, developed using a novel one-tube/one-step loop-mediated isothermal amplification-CRISPR method, shows remarkable performance. We address challenges in at-home nucleic acid testing by providing a cost-effective solution capable of detecting multiple pathogens simultaneously. Our system's versatility accommodates various assays operating at different temperatures and fluorescence intensities, offering significant advantages over traditional methods. Moreover, integration with EzDx Cloud facilitates disease monitoring and early warning systems, enhancing public health management. This study highlights the potential of our IoT molecular diagnostic device in revolutionizing infectious disease detection and control, with wide-ranging applications in both human and animal population.

Refining the Schistosoma haematobium recombinase polymerase amplification (Sh-RPA) assay: moving towards point-of-care use in endemic settings

BackgroundUrogenital schistosomiasis is caused by the parasitic trematode Schistosoma haematobium. Sensitive and specific point-of-care diagnostics are needed for elimination of this disease. Recombinase polymerase amplification (RPA) assays meet these criteria, and an assay to diagnose S. haematobium has been developed (Sh-RPA). However, false-positive results can occur, and optimisation of reaction conditions to mitigate these is needed. Ease of use and compatibility of DNA extraction methods must also be considered.MethodsUsing synthetic DNA, S. haematobium genomic DNA (gDNA), and urine samples from clinical cases, Sh-RPA reactions incorporating different betaine concentrations (0 M, 1 M, 2.5 M, 12.5 M) and the sample-to-water ratios were tested to determine effects on assay specificity and sensitivity. In addition, five commercial DNA extraction kits suitable for use in resource-limited settings were used to obtain gDNA from single S. haematobium eggs and evaluated in terms of DNA quality, quantity, and compatibility with the Sh-RPA assay. All samples were also evaluated by quantitative polymerase chain reaction (qPCR) to confirm DNA acquisition.ResultsThe analytical sensitivity of the Sh-RPA with all betaine concentrations was ≥ 10 copies of the synthetic Dra1 standard and 0.1 pg of S. haematobium gDNA. The addition of betaine improved Sh-RPA assay specificity in all reaction conditions, and the addition of 2.5 M of betaine together with the maximal possible sample volume of 12.7 µl proved to be the optimum reaction conditions. DNA was successfully isolated from a single S. haematobium egg using all five commercial DNA extraction kits, but the Sh-RPA performance of these kits varied, with one proving to be incompatible with RPA reactions.ConclusionsThe addition of 2.5 M of betaine to Sh-RPA reactions improved reaction specificity whilst having no detrimental effect on sensitivity. This increases the robustness of the assay, advancing the feasibility of using the Sh-RPA assay in resource-limited settings. The testing of commercial extraction kits proved that crude, rapid, and simple methods are sufficient for obtaining DNA from single S. haematobium eggs, and that these extracts can be used with Sh-RPA in most cases. However, the observed incompatibility of specific kits with Sh-RPA highlights the need for each stage of a molecular diagnostic platform to be robustly tested prior to implementation.Graphical

Beta-Barrel Nanopores as Diagnostic Sensors: An Engineering Perspective.

Biological nanopores are ultrasensitive and highly attractive platforms for disease diagnostics, including the sequencing of viral and microbial genes and the detection of biomarkers and pathogens. To utilize biological nanopores as diagnostic sensors, they have been engineered through various methods resulting in the accurate and highly sensitive detection of biomarkers and disease-related biomolecules. Among diverse biological nanopores, the β-barrel-containing nanopores have advantages in nanopore engineering because of their robust structure, making them well-suited for modifications. In this review, we highlight the engineering approaches for β-barrel-containing nanopores used in single-molecule sensing for applications in early diagnosis and prognosis. In the highlighted studies, β-barrel nanopores can be modified by genetic mutation to change the structure; alter charge distributions; or add enzymes, aptamers, and protein probes to enhance sensitivity and accuracy. Furthermore, this review discusses challenges and future perspectives for advancing nanopore-based diagnostic sensors.

Liposome-embedded PtCu nanozymes for improved immunoassay of accurate myocardial infarction

Herein, we developed a platinum-copper nano-enzyme-linked immunosorbent assay (NLISA) based split diagnostic platform for the ultrasensitive detection of cardiac troponin I (cTnI). The PtCu nanozyme synthesized by one-pot synthesis exhibited ultra-high peroxidase-like activity (35.17 U mg−1), which was about 4.5 times higher than that of the unmodified Pt nanozyme (8.83 U mg−1). Due to the efficient peroxidase-like activity of the copper-platinum complexed nanozyme, transduction and sequential amplification of cTnI biological signals were achieved in combination with a liposome-embedded amplification strategy. The encapsulation efficiency was calculated by introducing a liposomal bilayer model, which showed that the introduction of a single liposomal molecule could amplify the signal up to 870-fold, thus promising a high sensitivity test. Notably, the dynamic response of cTnI was in the range of 0.1–5000 pg mL−1 with an ultra-low detection limit (0.048 pg mL−1). The developed NLISA analysis system provides a new way to discover efficient and sensitive alternatives to ELISA kits, which can meet the practical needs of community healthcare testing conditions and rapid testing in hospitals.