An automated and mobile magnetoresistive biosensor system for early hepatocellular carcinoma diagnosis

Fully Automated Deep Learning Enabled Miniature Mass Spectrometry System for Psychoactive Therapeutic Drug Monitoring

Advancing precision medicine requires efficient small molecule biomarker detection in biofluids, yet existing methods encounter challenges in complexity, portability, and throughput. This study presents an integrated miniature blood processing and mass spectrometry (MS) analysis system, which incorporates automated magnetic solid-phase extraction, self-aspiration sampling miniature mass spectrometer, and deep learning algorithms for automated quantitative analysis. It achieves full automation from sample preparation to detection, demonstrating the capability to analyze serum psychoactive drugs with a 15-second/MS acquisition and 8-sample parallel processing within 30 minutes (including pretreatment). This has significantly increased detection throughput and facilitated the establishment of the standard curve. The novel dual-target ion parallel tandem MS analysis technique, combined with a U-net peak area recognition algorithm, achieved over 98% identification accuracy with less than 0.2% area prediction deviation. Quantitative analysis showed high correlation coefficients >0.99 in medically relevant ranges, supported by relative standard deviation < 10% and average back-calculated accuracy deviation < 3.5%. Clinical validation revealed strong concordance with LC-MS/MS. The system's integration of automated sample processing, miniature MS hardware, and AI-driven data analysis establishes a paradigm for high-throughput clinical detection. The advantages of accuracy, automation, intelligence, miniaturization, and high throughput suggest significant potential for this system in clinical detection and personalized medicine.

Prevention of liver cancer in the era of next-generation antivirals and obesity epidemic

Preventive interventions are expected to substantially improve the prognosis of patients with primary liver cancer, predominantly HCC and cholangiocarcinoma. HCC prevention is challenging in the face of the evolving etiological landscape, particularly the sharp increase in obesity-associated metabolic disorders, including metabolic dysfunction-associated steatotic liver disease. Next-generation anti-HCV and HBV drugs have substantially reduced, but not eliminated, the risk of HCC and have given way to new challenges in identifying at-risk patients. The recent development of new therapeutic agents and modalities has opened unprecedented opportunities to refine primary, secondary, and tertiary HCC prevention strategies. For primary prevention (before exposure to risk factors), public health policies, such as universal HBV vaccination, have had a substantial prognostic impact. Secondary prevention (after or during active exposure to risk factors) includes regular HCC screening and chemoprevention. Emerging biomarkers and imaging modalities for HCC risk stratification and detection may enable individual risk-based personalized and cost-effective HCC screening. Clinical studies have suggested the potential utility of lipid-lowering, antidiabetic/obesity, and anti-inflammatory agents for secondary prevention, and some of them are being evaluated in prospective clinical trials. Computational and experimental studies have identified potential chemopreventive strategies directed at diverse molecular, cellular, and systemic targets for etiology-specific and/or agnostic interventions. Tertiary prevention (in conjunction with curative-intent therapies for HCC) is an area of active research with the development of new immune-based neoadjuvant/adjuvant therapies. Cholangiocarcinoma prevention may advance with recent efforts to elucidate risk factors. These advances will collectively lead to substantial improvements in liver cancer mortality rates.

Recent Advances in Biosensor Technology for Early-Stage Detection of Hepatocellular Carcinoma-Specific Biomarkers: An Overview

Hepatocellular carcinoma is currently the most common malignancy of the liver. It typically occurs due to a series of oncogenic mutations that lead to aberrant cell replication. Most commonly, hepatocellular carcinoma (HCC) occurs as a result of pre-occurring liver diseases, such as hepatitis and cirrhosis. Given its aggressive nature and poor prognosis, the early screening and diagnosis of HCC are crucial. However, due to its plethora of underlying risk factors and pathophysiologies, patient presentation often varies in the early stages, with many patients presenting with few, if any, specific symptoms in the early stages. Conventionally, screening and diagnosis are performed through radiological examination, with diagnosis confirmed by biopsy. Imaging modalities tend to be limited by their requirement of large, expensive equipment; time-consuming operation; and a lack of accurate diagnosis, whereas a biopsy's invasive nature makes it unappealing for repetitive use. Recently, biosensors have gained attention for their potential to detect numerous conditions rapidly, cheaply, accurately, and without complex equipment and training. Through their sensing platforms, they aim to detect various biomarkers, such as nucleic acids, proteins, and even whole cells extracted by a liquid biopsy. Numerous biosensors have been developed that may detect HCC in its early stages. We discuss the recent updates in biosensing technology, highlighting its competitive potential compared to conventional methodology and its prospects as a tool for screening and diagnosis.

Automation and Computerization of (Bio)sensing Systems

Sensing systems necessitate automation to reduce human effort, increase reproducibility, and enable remote sensing. In this perspective, we highlight different types of sensing systems with elements of automation, which are based on flow injection and sequential injection analysis, microfluidics, robotics, and other prototypes addressing specific real-world problems. Finally, we discuss the role of computer technology in sensing systems. Automated flow injection and sequential injection techniques offer precise and efficient sample handling and dependable outcomes. They enable continuous analysis of numerous samples, boosting throughput, and saving time and resources. They enhance safety by minimizing contact with hazardous chemicals. Microfluidic systems are enhanced by automation to enable precise control of parameters and increase of analysis speed. Robotic sampling and sample preparation platforms excel in precise execution of intricate, repetitive tasks such as sample handling, dilution, and transfer. These platforms enhance efficiency by multitasking, use minimal sample volumes, and they seamlessly integrate with analytical instruments. Other sensor prototypes utilize mechanical devices and computer technology to address real-world issues, offering efficient, accurate, and economical real-time solutions for analyte identification and quantification in remote areas. Computer technology is crucial in modern sensing systems, enabling data acquisition, signal processing, real-time analysis, and data storage. Machine learning and artificial intelligence enhance predictions from the sensor data, supporting the Internet of Things with efficient data management.

Well plate-based LF-NMR/colorimetric dual-mode homogeneous immunosensor for Vibrio parahaemolyticus detection

A 96-well plate-based low-field nuclear magnetic resonance (LF-NMR)/colorimetric dual-mode homogeneous immunosensor was developed for the detection of pathogen bacteria, using Vibrio parahaemolyticus (VP) as a detection template. The signal unit MNS@Ab2 is graphene oxide (GO) simultaneously loaded with VP antibody and Fe3O4 nanoparticles. A 96-well plate coated with VP antibody captures the target VP, which then binds the signal unit to form the immunocomplex. After acidolysed, Fe3O4 nanoparticles are transformed into Fe3+ and Fe2+, so the non-homogeneous system is transformed into a homogeneous one. The addition of KMnO4 can not only convert Fe2+ into Fe3+ but also provide Mn2+, improving the detection sensitivity. And, colorimetric analysis can be achieved by the quantitative reduction of KMnO4. Under the optimal experimental conditions, the limit of detection was 60 CFU/mL with good selectivity, stability, precision, accuracy, and consistency, providing a simple and reliable detection platform for pathogenic bacteria in food.

A GMR enzymatic assay for quantifying nuclease and peptidase activity

Hydrolytic enzymes play crucial roles in cellular processes, and dysregulation of their activities is implicated in various physiological and pathological conditions. These enzymes cleave substrates such as peptide bonds, phosphodiester bonds, glycosidic bonds, and other esters. Detecting aberrant hydrolase activity is vital for understanding disease mechanisms and developing targeted therapeutic interventions. This study introduces a novel approach to measuring hydrolase activity using giant magnetoresistive (GMR) spin valve sensors. These sensors change resistance in response to magnetic fields, and here, they are functionalized with specific substrates for hydrolases conjugated to magnetic nanoparticles (MNPs). When a hydrolase cleaves its substrate, the tethered magnetic nanoparticle detaches, causing a measurable shift in the sensor's resistance. This design translates hydrolase activity into a real-time, activity-dependent signal. The assay is simple, rapid, and requires no washing steps, making it ideal for point-of-care settings. Unlike fluorescent methods, it avoids issues like autofluorescence and photobleaching, broadening its applicability to diverse biofluids. Furthermore, the sensor array contains 80 individually addressable sensors, allowing for the simultaneous measurement of multiple hydrolases in a single reaction. The versatility of this method is demonstrated with substrates for nucleases, Bcu I and DNase I, and the peptidase, human neutrophil elastase. To demonstrate a clinical application, we show that neutrophil elastase in sputum from cystic fibrosis patients hydrolyze the peptide-GMR substrate, and the cleavage rate strongly correlates with a traditional fluorogenic substrate. This innovative assay addresses challenges associated with traditional enzyme measurement techniques, providing a promising tool for real-time quantification of hydrolase activities in diverse biological contexts.

Rapid, Point-of-Care Host-Based Gene Expression Diagnostics Using Giant Magnetoresistive Biosensors

Host-based gene expression analysis is a promising tool for a broad range of clinical applications, including rapid infectious disease diagnostics and real-time disease monitoring. However, the complex instrumentation requirements and slow turnaround-times associated with traditional gene expression analysis methods have hampered their widespread adoption at the point-of-care (POC). To overcome these challenges, we have developed an automated and portable platform that utilizes polymerase chain reaction (PCR) and giant magnetoresistive (GMR) biosensors to perform rapid multiplexed, targeted gene expression analysis at the POC. As proof-of-concept, we utilized our platform to amplify and measure the expression of four genes (HERC5, HERC6, IFI27, and IFIH1) that were previously shown to be upregulated in hosts infected with influenza viruses. The compact instrument conducted highly automated PCR amplification and GMR detection to measure the expression of the four genes in multiplex, then utilized Bluetooth communication to relay results to users on a smartphone application. To validate the platform, we tested 20 cDNA samples from symptomatic patients that had been previously diagnosed as either influenza-positive or influenza-negative using a RT-PCR virology panel. A non-parametric Mann-Whitney test revealed that day 0 (day of symptom onset) gene expression was significantly different between the two groups (p < 0.0001, n = 20). Hence, we preliminarily demonstrated that our platform could accurately discriminate between symptomatic influenza and non-influenza populations based on host gene expression in ∼30 min. This study not only establishes the potential clinical utility of our proposed assay and device for influenza diagnostics but it also paves the way for broadscale and decentralized implementation of host-based gene expression diagnostics at the POC.

Longitudinal analysis of anti-SARS-CoV-2 neutralizing antibody (NAb) titers in vaccinees using a novel giant magnetoresistive (GMR) assay

The COVID-19 pandemic has highlighted the need to monitor important correlates of immunity on a population-wide level. To this end, we have developed a competitive assay to assess neutralizing antibody (NAb) titer on the giant magnetoresistive (GMR) biosensor platform. We compared the clinical performance of our biosensor with established techniques such as Ortho's VITROS Anti-SARS-CoV-2 IgG Quantitative Antibody test. Results obtained between the VITROS test and the GMR assay showed correlation (r = -0.93). We then validated the assay with patient plasma samples that had been tested using focus reduction neutralization testing (FRNT). The results obtained from our GMR assay exhibit a previously identified trend of increased NAb titers 2 weeks post-vaccination. We further evaluated NAb titers 6 months post-vaccination and observed waning neutralizing antibody titers over that time in vaccinated patients. In addition, we calibrated our assay to an arbitrary unit (IU/mL) using World Health Organization (WHO) reference plasma provided by the National Institute of Biological Standards and Control (NIBSC). Our biosensor provides highly specific and sensitive results in serum and plasma with analytical, clinical, and point-of-care (POC) applications due to quick turnaround times on samples and the cost-effectiveness of the platform.

A Time-Division Multiplexing Multi-Channel Micro-Electrochemical Workstation with Carbon-Based Material Electrodes for Online L-Trosine Detection

In the background of the rapid development of artificial intelligence, big data, IoT, 5G/6G, and other technologies, electrochemical sensors pose higher requirements for high-throughput detection. In this study, we developed a workstation with up to 10 channels, which supports both parallel signal stimulation and online electrochemical analysis functions. The platform was wired to a highly integrated Bluetooth chip used for wireless data transmission and can be visualized on a smartphone. We used this electrochemical test platform with carbon-graphene oxide/screen-printed carbon electrodes (CB-GO/SPCE) for the online analysis of L-tyrosine (Tyr), and the electrochemical performance and stability of the electrodes were examined by differential pulse voltammetry (DPV). The CB-GO-based screen-printed array electrodes with a multichannel electrochemical platform for Tyr detection showed a low detection limit (20 μM), good interference immunity, and 10-day stability in the range of 20-200 μM. This convenient electrochemical analytical device enables high-throughput detection and has good economic benefits that can contribute to the improvement of the accuracy of electrochemical analysis and the popularization of electrochemical detection methods in a wide range of fields.

Risk stratification and early detection biomarkers for precision HCC screening

Hepatocellular carcinoma (HCC) mortality remains high primarily due to late diagnosis as a consequence of failed early detection. Professional societies recommend semi-annual HCC screening in at-risk patients with chronic liver disease to increase the likelihood of curative treatment receipt and improve survival. However, recent dynamic shift of HCC etiologies from viral to metabolic liver diseases has significantly increased the potential target population for the screening, whereas annual incidence rate has become substantially lower. Thus, with the contemporary HCC etiologies, the traditional screening approach might not be practical and cost-effective. HCC screening consists of (i) definition of rational at-risk population, and subsequent (ii) repeated application of early detection tests to the population at regular intervals. The suboptimal performance of the currently available HCC screening tests highlights an urgent need for new modalities and strategies to improve early HCC detection. In this review, we overview recent developments of clinical, molecular, and imaging-based tools to address the current challenge, and discuss conceptual framework and approaches of their clinical translation and implementation. These encouraging progresses are expected to transform the current "one-size-fits-all" HCC screening into individualized precision approaches to early HCC detection and ultimately improve the poor HCC prognosis in the foreseeable future.

Advances in point-of-care genetic testing for personalized medicine applications

Breakthroughs within the fields of genomics and bioinformatics have enabled the identification of numerous genetic biomarkers that reflect an individual's disease susceptibility, disease progression, and therapy responsiveness. The personalized medicine paradigm capitalizes on these breakthroughs by utilizing an individual's genetic profile to guide treatment selection, dosing, and preventative care. However, integration of personalized medicine into routine clinical practice has been limited-in part-by a dearth of widely deployable, timely, and cost-effective genetic analysis tools. Fortunately, the last several decades have been characterized by tremendous progress with respect to the development of molecular point-of-care tests (POCTs). Advances in microfluidic technologies, accompanied by improvements and innovations in amplification methods, have opened new doors to health monitoring at the point-of-care. While many of these technologies were developed with rapid infectious disease diagnostics in mind, they are well-suited for deployment as genetic testing platforms for personalized medicine applications. In the coming years, we expect that these innovations in molecular POCT technology will play a critical role in enabling widespread adoption of personalized medicine methods. In this work, we review the current and emerging generations of point-of-care molecular testing platforms and assess their applicability toward accelerating the personalized medicine paradigm.

Point-of-Care Testing of Enzyme Polymorphisms for Predicting Hypnotizability and Postoperative Pain

Hypnotizability is a stable trait that moderates the benefit of hypnosis for treating pain, but limited availability of hypnotizability testing deters widespread use of hypnosis. Inexpensive genotyping of four single-nucleotide polymorphisms in the catechol-o-methyltransferase (COMT) gene was performed using giant magnetoresistive biosensors to determine if hypnotizable individuals can be identified for targeted hypnosis referrals. For individuals with the proposed optimal COMT diplotypes, 89.5% score highly on the Hypnotic Induction Profile (odds ratio, 6.12; 95% CI, 1.26-28.75), which identified 40.5% of the treatable population. Mean hypnotizability scores of the optimal group were significantly higher than the total population (P = 0.015; effect size = 0.60), an effect that was present in women (P = 0.0015; effect size = 0.83), but not in men (P = 0.28). In an exploratory cohort, optimal individuals also reported significantly higher postoperative pain scores (P = 0.00030; effect size = 1.93), indicating a greater need for treatment.

Giant Magnetoresistance Biosensors for Food Safety Applications

Nowadays, the increasing number of foodborne disease outbreaks around the globe has aroused the wide attention of the food industry and regulators. During food production, processing, storage, and transportation, microorganisms may grow and secrete toxins as well as other harmful substances. These kinds of food contamination from microbiological and chemical sources can seriously endanger human health. The traditional detection methods such as cell culture and colony counting cannot meet the requirements of rapid detection due to some intrinsic shortcomings, such as being time-consuming, laborious, and requiring expensive instrumentation or a central laboratory. In the past decade, efforts have been made to develop rapid, sensitive, and easy-to-use detection platforms for on-site food safety regulation. Herein, we review one type of promising biosensing platform that may revolutionize the current food surveillance approaches, the giant magnetoresistance (GMR) biosensors. Benefiting from the advances of nanotechnology, hundreds to thousands of GMR biosensors can be integrated into a fingernail-sized area, allowing the higher throughput screening of food samples at a lower cost. In addition, combined with on-chip microfluidic channels and filtration function, this type of GMR biosensing system can be fully automatic, and less operator training is required. Furthermore, the compact-sized GMR biosensor platforms could be further extended to related food contamination and the field screening of other pathogen targets.

From saliva to SNP: non-invasive, point-of-care genotyping for precision medicine applications using recombinase polymerase amplification and giant magnetoresistive nanosensors

Genetic testing is considered a cornerstone of the precision medicine paradigm. Genotyping of single nucleotide polymorphisms (SNPs) has been shown to provide insights into several important issues, including therapy selection and drug responsiveness. However, a scarcity of widely deployable and cost-effective genotyping tools has limited the integration of precision medicine into routine clinical practice. The objective of our work was to develop a portable, cost-effective, and automated platform that performs SNP genotyping at the point-of-care (POC). Using recombinase polymerase amplification (RPA) and giant magnetoresistive (GMR) nanosensors, we present a highly automated and multiplexed point-of-care platform that utilizes direct saliva for the qualitative genotyping of four SNPs (rs4633, rs4680, rs4818, rs6269) along the catechol-O-methyltransferase gene (COMT), which is associated with the modulation of pain sensitivity and perioperative opioid use. Using this approach, we successfully amplify, detect, and genotype all four of the SNPs, demonstrating 100% accordance between the experimental results obtained using the automated RPA and GMR genotyping assay and the results obtained using a COMT PCR genotyping assay that was formerly validated using pyrosequencing. This automated, portable, and multiplexed RPA and GMR assay shows great promise as a solution for SNP genotyping at the POC and reinforces the broad applications of magnetic nanotechnology in biomedicine.

Ion-selective electrode-based potentiometric immunoassays for the quantitative monitoring of alpha-fetoprotein by coupling rolling cycle amplification with silver nanoclusters

This work reports an ion-selective electrode-based potentiometric immunoassay for AFP detection coupling rolling cycle amplification with silver nanoclusters.