Rapid and multi-target genotyping of Helicobacter pylori with digital microfluidics.

Helicobacter pylori (H. pylori) infection correlates closely with gastric diseases such as gastritis, ulcers, and cancer, influencing more than half of the world's population. Establishing a rapid, precise, and automated platform for H. pylori diagnosis is an urgent clinical need and would significantly benefit therapeutic intervention. Recombinase polymerase amplification (RPA)-CRISPR recently emerged as a promising molecular diagnostic assay due to its rapid detection capability, high specificity, and mild reaction conditions. In this work, we adapted the RPA-CRISPR assay on a digital microfluidics (DMF) system for automated H. pylori detection and genotyping. The system can achieve multi-target parallel detection of H. pylori nucleotide conservative genes (ureB) and virulence genes (cagA and vacA) across different samples within 30 min, exhibiting a detection limit of 10 copies/rxn and no false positives. We further conducted tests on 80 clinical saliva samples and compared the results with those derived from real-time quantitative polymerase chain reaction, demonstrating 100% diagnostic sensitivity and specificity for the RPA-CRISPR/DMF method. By automating the assay process on a single chip, the DMF system can significantly reduce the usage of reagents and samples, minimize the cross-contamination effect, and shorten the reaction time, with the additional benefit of losing the chance of experiment failure/inconsistency due to manual operations. The DMF system together with the RPA-CRISPR assay can be used for early detection and genotyping of H. pylori with high sensitivity and specificity, and has the potential to become a universal molecular diagnostic platform.

Optoelectronically navigated nano-kirigami microrotors.

With the rapid development of micro/nanofabrication technologies, the concept of transformable kirigami has been applied for device fabrication in the microscopic world. However, most nano-kirigami structures and devices were typically fabricated or transformed at fixed positions and restricted to limited mechanical motion along a single axis due to their small sizes, which significantly limits their functionalities and applications. Here, we demonstrate the precise shaping and position control of nano-kirigami microrotors. Metallic microrotors with size of ~10 micrometers were deliberately released from the substrates and readily manipulated through the multimode actuation with controllable speed and direction using an advanced optoelectronic tweezers technique. The underlying mechanisms of versatile interactions between the microrotors and electric field are uncovered by theoretical modeling and systematic analysis. This work reports a novel methodology to fabricate and manipulate micro/nanorotors with well-designed and sophisticated kirigami morphologies, providing new solutions for future advanced optoelectronic micro/nanomachinery.

Tweezer PCR: A Highly Specific Method for Accurate Identification of Low-Abundance Mutations.

Somatic mutation is a valuable biomarker for tracking tumor progression and migration due to its distinctive feature in various tumors and its wide distribution throughout body fluids. However, accurately detecting somatic mutations from the abundant DNA of noncancerous origins remains a practical challenge in the clinic. Herein, we developed an ultraspecific method, called tweezer PCR, for detecting low-abundance mutations inspired by the design of DNA origami. The high specificity of tweezer PCR relies on a tweezer-shaped primer containing six basic functional units: a primer, a hairpin, a linker, a blocker, a spacer, and a toehold. After optimizing the structure of the tweezer-shaped primer and enhancing its specificity by adding additional Mg2+ and Na+, tweezer PCR distinguished as low as 20 copies of mutations from 2 million copies of wild-type templates per test. By testing synthesized plasmids and plasma samples gathered from nonsmall-cell lung cancer patients, tweezer PCR showed higher specificity and robustness for detecting low-copy-number mutations in contrast with digital droplet PCR. Additionally, the need for conventional instruments makes tweezer PCR a practically accessible method for testing low-abundance mutations. Because of its numerous advantages, we believe that tweezer PCR offers a precise, robust, and pragmatic tool for cancer screening, prognosis, and genotyping in the clinic.

A Versatile Continuum Gripping Robot with a Concealable Gripper.

Continuum robots with their inherent compliance provide the potential for crossing narrow unstructured workspace and safely grasping various objects. However, the display gripper increases the size of the robots, and therefore, it tends to get stuck in constrained environments. This paper proposes a versatile continuum grasping robot (CGR) with a concealable gripper. The CGR can capture large objects with respect to the robot's scale using the continuum manipulator and can grasp various objects using the end concealable gripper especially in narrow and unstructured workspaces. To perform the cooperative operation of the concealable gripper and the continuum manipulator, a global kinematic model based on screw theory and a motion planning approach referred to as "multi-node synergy method" for the CGR are presented. The simulation and experimental results show that objects of different shapes and sizes can be captured by the same CGR even in complex and narrow environments. Finally, in the future, the CGR is expected to serve for satellite capture in harsh space environments such as high vacuum, strong radiation, and extreme temperatures.

Machine Learning System for Lung Neoplasms Distinguished Based on Scleral Data.

Lung cancer remains the most commonly diagnosed cancer and the leading cause of death from cancer. Recent research shows that the human eye can provide useful information about one's health status, but few studies have revealed that the eye's features are associated with the risk of cancer. The aims of this paper are to explore the association between scleral features and lung neoplasms and develop a non-invasive artificial intelligence (AI) method for detecting lung neoplasms based on scleral images. A novel instrument was specially developed to take the reflection-free scleral images. Then, various algorithms and different strategies were applied to find the most effective deep learning algorithm. Ultimately, the detection method based on scleral images and the multi-instance learning (MIL) model was developed to predict benign or malignant lung neoplasms. From March 2017 to January 2019, 3923 subjects were recruited for the experiment. Using the pathological diagnosis of bronchoscopy as the gold standard, 95 participants were enrolled to take scleral image screens, and 950 scleral images were fed to AI analysis. Our non-invasive AI method had an AUC of 0.897 ± 0.041(95% CI), a sensitivity of 0.836 ± 0.048 (95% CI), and a specificity of 0.828 ± 0.095 (95% CI) for distinguishing between benign and malignant lung nodules. This study suggested that scleral features such as blood vessels may be associated with lung cancer, and the non-invasive AI method based on scleral images can assist in lung neoplasm detection. This technique may hold promise for evaluating the risk of lung cancer in an asymptomatic population in areas with a shortage of medical resources and as a cost-effective adjunctive tool for LDCT screening at hospitals.

One-Stop Extraction and In Situ RT-qPCR for Ultrasensitive Detection of Highly Diluted SARS-CoV-2 in Large-Volume Samples from Aquatic Environments.

Surveillance of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in aquatic environments attracted attention due to its considerable impacts on human health and ecology, especially in countries with poor sanitation standards. Based on a strategy of one-stop extraction and in situ amplification, we developed an ultrasensitive method that uses a polyacrylamide derivative-modified filter disc (PAD-FD), in which highly diluted RNA can be efficiently concentrated onto the filter disc and directly used for amplification. A newly designed spin column with a cup-like filter base facilitated the non-contact transfer of the affinity filter disc from the column to a PCR tube. The limit of detection of the PAD-FD coupled with RT-qPCR is 10 copies/mL. Using 32 suspected SARS-CoV-2 samples, we demonstrated that the detection rate of our method (62.5%, 20/32) was triple the rate of the commercial kit (18.8%, 6/32). Using a PAD-FD, 56.3% (18/32) and 40.6% (13/32) of the 10-fold-dilution samples with river and tap water, respectively, were detected. Even when diluted 100-fold, 28.1% (9/32) and 37.5% (12/32) were still detected in river and tap water, respectively. We believe that the PAD-FD method offers an accurate testing tool for monitoring viral RNA in aquatic environments, contributing to the forewarning of the SARS-CoV-2 outbreak and the breaking of the transmission chain.

A review on microrobots driven by optical and magnetic fields.

Due to their small sizes, microrobots are advantageous for accessing hard-to-reach spaces for delivery and measurement. However, their small sizes also bring challenges in on-board powering, thus usually requiring actuation by external energy. Microrobots actuated by external energy have been applied to the fields of physics, biology, medical science, and engineering. Among these actuation sources, light and magnetic fields show advantages in high precision and high biocompatibility. This paper reviews the recent advances in the design, actuation, and applications of microrobots driven by light and magnetic fields. For light-driven microrobots, we summarized the uses of optical tweezers, optoelectronic tweezers, and heat-mediated optical manipulation techniques. For magnetically driven microrobots, we summarized the uses of torque-driven microrobots, force-driven microrobots, and shape-deformable microrobots. Then, we compared the two types of field-driven microrobots and reviewed their advantages and disadvantages. The paper concludes with an outlook for the joint use of optical and magnetic field actuation in microrobots.

Miniaturized microfluidic-based nucleic acid analyzer to identify new biomarkers of biopsy lung cancer samples for subtyping.

Identifying new biomarkers is necessary and important to diagnose and treat malignant lung cancer. However, existing protein marker detection methods usually require complex operation steps, leading to a lag time for diagnosis. Herein, we developed a rapid, minimally invasive, and convenient nucleic acid biomarker recognition method, which enabled the combined specific detection of 11 lung cancer typing markers in a microliter reaction system after only one sampling. The primers for the combined specific detection of 11 lung cancer typing markers were designed and screened, and the microfluidic chip for parallel detection of the multiple markers was designed and developed. Furthermore, a miniaturized microfluidic-based analyzer was also constructed. By developing a microfluidic chip and a miniaturized nucleic acid analyzer, we enabled the detection of the mRNA expression levels of multiple biomarkers in rice-sized tissue samples. The miniaturized nucleic acid analyzer could detect ≥10 copies of nucleic acids. The cell volume of the typing reaction on the microfluidic chip was only 0.94 µL, less than 1/25 of that of the conventional 25-µL Eppendorf tube PCR method, which significantly reduced the testing cost and significantly simplified the analysis of multiple biomarkers in parallel. With a simple injection operation and reverse transcription loop-mediated isothermal amplification (RT-LAMP), real-time detection of 11 lung cancer nucleic acid biomarkers was performed within 45 min. Given these compelling features, 86 clinical samples were tested using the miniaturized nucleic acid analyzer and classified according to the cutoff values of the 11 biomarkers. Furthermore, multi-biomarker analysis was conducted by a machine learning model to classify different subtypes of lung cancer, with an average area under the curve (AUC) of 0.934. This method shows great potential for the identification of new nucleic acid biomarkers and the accurate diagnosis of lung cancer.

A nature-inspired hierarchical branching structure pressure sensor with high sensitivity and wide dynamic range for versatile medical wearables.

Pressure-sensing capability is essential for flexible electronic devices, which require high sensitivity and a wide detection range to simplify the system. However, the template-based pressure sensor is powerless to detect high pressure due to the rapid deformation saturation of microstructures. Herein, we demonstrated that a nature-inspired hierarchical branching (HB) structure can effectively address this problem. Finite element analysis demonstrates that the HB structure permits a step-by-step mobilization of microstructure deformation, resulting in a dramatically improved sensitivity (up to 2 orders of magnitude) when compared with the traditional monolayer structure. Experiments show that the HB structure enables pressure sensors to have a lower elastic modulus (1/3 of that of monolayer sensors), a high sensitivity of 13.1 kPa-1 (almost 14 times higher than the monolayer sensor), and a wide dynamic range (0-800 kPa, the minimum detection pressure is 1.6 Pa). The maximum frequency that the sensor can detect is 250 Hz. The response/recovery time is 0.675/0.55 ms respectively. Given this performance, the HB sensor enables high-resolution detection of the weak radial artery pulse wave characteristics in different states, indicating its potential to noninvasively reveal cardiovascular status and the effectiveness of related interventions, such as exercise and drug intervention. As a proof of concept, we also verified that the HB sensor can serve as a versatile platform to support diverse applications from low to high pressure.

Rapid, Highly Sensitive, and Label-Free Pathogen Assay System Using a Solid-Phase Self-Interference Recombinase Polymerase Amplification Chip and Hyperspectral Interferometry.

Recombinase polymerase amplification (RPA) is a useful pathogen identification method. Several label-free detection methods for RPA amplicons have been developed in recent years. However, these methods still lack sensitivity, specificity, efficiency, or simplicity. In this study, we propose a rapid, highly sensitive, and label-free pathogen assay system based on a solid-phase self-interference RPA chip (SiSA-chip) and hyperspectral interferometry. The SiSA-chips amplify and capture RPA amplicons on the chips, rather than irrelevant amplicons such as primer dimers, and the SiSA-chips are then analysed by hyperspectral interferometry. Optical length increases of SiSA-chips are used to demonstrate RPA detection results, with a limit of detection of 1.90 nm. This assay system can detect as few as six copies of the target 18S rRNA gene of Plasmodium falciparum within 20 min, with a good linear relationship between the detection results and the concentration of target genes (R2 = 0.9903). Single nucleotide polymorphism (SNP) genotyping of the dhfr gene of Plasmodium falciparum is also possible using the SiSA-chip, with as little as 1% of mutant gene distinguished from wild-type loci (m/wt). This system offers a high-efficiency (20 min), high-sensitivity (6 copies/reaction), high-specificity (1% m/wt), and low-cost (∼1/50 of fluorescence assays for RPA) diagnosis method for pathogen DNA identification. Therefore, this system is promising for fast identification of pathogens to help diagnose infectious diseases, including SNP genotyping.

Microfluidic Chip with Two-Stage Isothermal Amplification Method for Highly Sensitive Parallel Detection of SARS-CoV-2 and Measles Virus.

A two-stage isothermal amplification method, which consists of a first-stage basic recombinase polymerase amplification (RPA) and a second-stage fluorescence loop-mediated isothermal amplification (LAMP), as well as a microfluidic-chip-based portable system, were developed in this study; these enabled parallel detection of multiplex targets in real time in around one hour, with high sensitivity and specificity, without cross-contamination. The consumption of the sample and the reagent was 2.1 µL and 10.6 µL per reaction for RPA and LAMP, respectively. The lowest detection limit (LOD) was about 10 copies. The clinical amplification of about 40 nasopharyngeal swab samples, containing 17 SARS-CoV-2 (severe acute respiratory syndrome coronavirus) and 23 measles viruses (MV), were parallel tested by using the microfluidic chip. Both clinical specificity and sensitivity were 100% for MV, and the clinical specificity and sensitivity were 94.12% and 95.83% for SARS-CoV-2, respectively. This two-stage isothermal amplification method based on the microfluidic chip format offers a convenient, clinically parallel molecular diagnostic method, which can identify different nucleic acid samples simultaneously and in a timely manner, and with a low cost of the reaction reagent. It is especially suitable for resource-limited areas and point-of-care testing (POCT).

Microfluidic Biosensor for Rapid Nucleic Acid Quantitation Based on Hyperspectral Interferometric Amplicon-Complex Analysis.

Nucleic acid detection plays a vital role in both biomedical research and clinical medicine. The temperature circulation changes of the widely used polymerase chain reaction technique are time-consuming and technically challenging for system development. Recombinase polymerase amplification (RPA) is an isothermal method for rapid nucleic acid detection. However, current RPA amplicon detection methods are complicated and expensive and easily generate false positives, restricting the promotion of RPA techniques. In this work, a hyperspectral interferometric amplicon-complex quantitation method is presented, combined with asymmetric dipole complex strategy optical scattering analysis. GelRed dye was utilized to form amplicon-complex particles, and the Fourier domain spectrum computation contributed to complex scattering quantitation. With this method, a supporting microfluidic chip and automatic system were developed to achieve integrated, rapid, quantitative, and miniscule nucleic acid detection. The Plasmodium falciparumdhfr gene was utilized as an example for targeted nucleic acid quantitation and single nucleotide polymorphism detection. The total reaction time was decreased to merely 20 min, and the limit of detection was only 3.17 ng/µL. The minimum measurable concentration of target was 1.68 copies/µL, 31.67 times more sensitive than turbidity detection, and the single reaction chamber was only 9.33 µL. No scattering increase occurred for template-free control, and thus, false positives caused by primer dimers and nonspecific products could be avoided. The experimental results prove that the provided method and system can detect single-base mutations in the dhfr gene and is a reasonable technique for rapid, automatic, and low-cost nucleic acid detection.

Label-Free and Quantitative Dry Mass Monitoring for Single Cells during In Situ Culture.

Quantitative measurement of single cells can provide in-depth information about cell morphology and metabolism. However, current live-cell imaging techniques have a lack of quantitative detection ability. Herein, we proposed a label-free and quantitative multichannel wide-field interferometric imaging (MWII) technique with femtogram dry mass sensitivity to monitor single-cell metabolism long-term in situ culture. We demonstrated that MWII could reveal the intrinsic status of cells despite fluctuating culture conditions with 3.48 nm optical path difference sensitivity, 0.97 fg dry mass sensitivity and 2.4% average maximum relative change (maximum change/average) in dry mass. Utilizing the MWII system, different intrinsic cell growth characteristics of dry mass between HeLa cells and Human Cervical Epithelial Cells (HCerEpiC) were studied. The dry mass of HeLa cells consistently increased before the M phase, whereas that of HCerEpiC increased and then decreased. The maximum growth rate of HeLa cells was 11.7% higher than that of HCerEpiC. Furthermore, HeLa cells were treated with Gemcitabine to reveal the relationship between single-cell heterogeneity and chemotherapeutic efficacy. The results show that cells with higher nuclear dry mass and nuclear density standard deviations were more likely to survive the chemotherapy. In conclusion, MWII was presented as a technique for single-cell dry mass quantitative measurement, which had significant potential applications for cell growth dynamics research, cell subtype analysis, cell health characterization, medication guidance and adjuvant drug development.

Quantitative and specific detection of viable pathogens on a portable microfluidic chip system by combining improved propidium monoazide (PMAxx) and loop-mediated isothermal amplification (LAMP).

An accurate and specific detection of viable Candida albicans (C. albicans) in vaginal discharge is crucial for the diagnosis of vulvovaginal candidiasis (VVC) and assessment of antifungal effects. In this study, improved propidium monoazide (PMAxx) and loop-mediated isothermal amplification (LAMP) were used for the first time to distinguish between viable and dead C. albicans. A portable microfluidic chip system was developed to detect multiple viable pathogens in parallel. The consumption of samples and reagents in per reaction cell were only 0.94 µL, less than 1/25 of the conventional 25 µL Eppendorf tubular test method, both significantly reducing testing cost and greatly simplifying the detection of multiple viable pathogens. The concentration of PMAxx was optimized against C. albicans at 4.0 log CFU mL-1 to 5.0 log CFU mL-1, and 1 µM PMAxx was proven to be suitable for the detection of C. albicans in clinical samples. When testing mixtures containing different ratios of viable to dead C. albicans, PMAxx-LAMP could circumvent the signal arising from dead cells and, therefore, reflected the abundance of viable cells precisely. Furthermore, the suitability of this technique to evaluate the effects of antifungal agents, including clotrimazole, miconazole, and tioconazole, was assessed. Finally, the viability of Escherichia coli (E. coli) and C. albicans were detected on the portable microfluidic chip system. PMAxx-LAMP based portable microfluidic chip system was determined to be a feasible technique for assessing the viability of multiple pathogens in gynecology and might provide insights into new VVC treatment strategies.

Single cell capture, isolation, and long-term in-situ imaging using quantitative self-interference spectroscopy.

Single cell research with microfluidic chip is of vital importance in biomedical studies and clinical medicine. Simultaneous microfluidic cell manipulations and long-term cell monitoring needs further investigations due to the lack of label-free quantitative imaging techniques and systems. In this work, single cell capture, isolation and long-term in-situ monitoring was realized with a microfluidic cell chip, compact cell incubator and quantitative self-interference spectroscopy. The proposed imaging method could obtain quantitative and dynamic refractive index distribution in living cells. And the designed microfluidic chip could capture and isolate single cells. The customized incubator could support cell growth conditions when single cell was captured in microfluidic chip. According to the results, single cells could be trapped, transferred and pushed into the culture chamber with the microfluidic chip. The incubator could culture single cells in the chip for 120 h. The refractive index sensitivity of the proposed quantitative imaging method was 0.0282 and the relative error was merely 0.04%.

Deep Learning Algorithm for Automated Detection of Polycystic Ovary Syndrome Using Scleral Images.

The high prevalence of polycystic ovary syndrome (PCOS) among reproductive-aged women has attracted more and more attention. As a common disorder that is likely to threaten women's health physically and mentally, the detection of PCOS is a growing public health concern worldwide. In this paper, we proposed an automated deep learning algorithm for the auxiliary detection of PCOS, which explores the potential of scleral changes in PCOS detection. The algorithm was applied to the dataset that contains the full-eye images of 721 Chinese women, among which 388 are PCOS patients. Inputs of the proposed algorithm are scleral images segmented from full-eye images using an improved U-Net, and then a Resnet model was applied to extract deep features from scleral images. Finally, a multi-instance model was developed to achieve classification. Various performance indices such as AUC, classification accuracy, precision, recall, precision, and F1-score were adopted to assess the performance of our algorithm. Results show that our method achieves an average AUC of 0.979 and a classification accuracy of 0.929, which indicates the great potential of deep learning in the detection of PCOS.

Biomimetic Upconversion Nanoparticles and Gold Nanoparticles for Novel Simultaneous Dual-Modal Imaging-Guided Photothermal Therapy of Cancer.

Multimodal imaging-guided near-infrared (NIR) photothermal therapy (PTT) is an interesting and promising cancer theranostic method. However, most of the multimodal imaging systems provide structural and functional information used for imaging guidance separately by directly combining independent imaging systems with different detectors, and many problems arise when trying to fuse different modal images that are serially taken by inviting extra markers or image fusion algorithms. Further, most imaging and therapeutic agents passively target tumors through the enhanced permeability and retention (EPR) effect, which leads to low utilization efficiency. To address these problems and systematically improve the performance of the imaging-guided PTT methodology, we report a novel simultaneous dual-modal imaging system combined with cancer cell membrane-coated nanoparticles as a platform for PTT-based cancer theranostics. A novel detector with the ability to detect both high-energy X-ray and low-energy visible light at the same time, as well as a dual-modal imaging system based on the detector, was developed for simultaneous dual-modal imaging. Cancer cell membrane-coated upconversion nanoparticles (CC-UCNPs) and gold nanoparticles (CC-AuNPs) with the capacity for immune evasion and active tumor targeting were engineered for highly specific imaging and high-efficiency PTT therapy. In vitro and in vivo evaluation of macrophage escape and active homologous tumor targeting were performed. Cancer cell membrane-coated nanoparticles (CC-NPs) displayed excellent immune evasion ability, longer blood circulation time, and higher tumor targeting specificity compared to normal PEGylated nanoparticles, which led to highly specific upconversion luminescence (UCL) imaging and PTT-based anti-tumor efficacy. The anti-cancer efficacy of the dual-modal imaging-guided PTT was also evaluated both in vitro and in vivo. Dual-modal imaging yielded precise anatomical and functional information for the PTT process, and complete tumor ablation was achieved with CC-AuNPs. Our biomimetic UCNP/AuNP and novel simultaneous dual-modal imaging combination could be a promising platform and methodology for cancer theranostics.

Fast and Parallel Detection of Four Ebola Virus Species on a Microfluidic-Chip-Based Portable Reverse Transcription Loop-Mediated Isothermal Amplification System.

Considering the lack of official vaccines and medicines for Ebola virus infection, reliable diagnostic methods are necessary for the control of the outbreak and the spread of the disease. We developed a microfluidic-chip-based portable system for fast and parallel detection of four Ebola virus species. The system is based on reverse transcription loop-mediated isothermal amplification (RT-LAMP) and consists of four specific LAMP primers, a disc microfluidic chip, and a portable real-time fluorescence detector. It could specifically and parallelly distinguish four species of the Ebola virus after only one sampling, including the Zaire Ebola virus, the Sudan Ebola virus, the Bundibugyo Ebola virus, and the Tai Forest Ebola virus, without cross-contamination. The limit of detection was as small as 10 copies per reaction, while the total consumption of sample and reagent was 0.94 µL per reaction. The final results could be obtained in 50 min after one addition of sample and reagent mixture. This approach provides simplicity, high sensitivity, and multi-target parallel detection at a low cost, which could enable convenient and effective on-site detections of the Ebola virus in the outdoors, remote areas, and modern hospitals.

Label-free tomography of living cellular nanoarchitecture using hyperspectral self-interference microscopy.

Quantitative phase imaging (QPI) is the most ideal method for achieving long-term cellular tomography because it is label free and quantitative. However, for current QPI instruments, interference signals from different layers overlay with each other and impede nanoscale optical sectioning. Integrated incubators and improved configurations also require further investigation for QPI instruments. In this work, hyperspectral self-reflectance microscopy is proposed to achieve label-free tomography of living cellular nanoarchitecture. The optical description and tomography reconstruction algorithm were proposed so that the quantitative morphological structure of the entire living cell can be acquired with 89.2 nm axial resolution and 1.91 nm optical path difference sensitivity. A cell incubator was integrated to culture living cells for in situ measurement and expensive precise optical components were not needed. The proposed system can reveal native and dynamic cellular nanoscale structure, providing an alternative approach for long-term monitoring and quantitative analysis of living cells.

An interferometric imaging biosensor using weighted spectrum analysis to confirm DNA monolayer films with attogram sensitivity.

Interferometric imaging biosensors are powerful and convenient tools for confirming the existence of DNA monolayer films on silicon microarray platforms. However, their accuracy and sensitivity need further improvement because DNA molecules contribute to an inconspicuous interferometric signal both in thickness and size. Such weaknesses result in poor performance of these biosensors for low DNA content analyses and point mutation tests. In this paper, an interferometric imaging biosensor with weighted spectrum analysis is presented to confirm DNA monolayer films. The interferometric signal of DNA molecules can be extracted and then quantitative detection results for DNA microarrays can be reconstructed. With the proposed strategy, the relative error of thickness detection was reduced from 88.94% to merely 4.15%. The mass sensitivity per unit area of the proposed biosensor reached 20 attograms (ag). Therefore, the sample consumption per unit area of the target DNA content was only 62.5 zeptomoles (zm), with the volume of 0.25 picolitres (pL). Compared with the fluorescence resonance energy transfer (FRET), the measurement veracity of the interferometric imaging biosensor with weighted spectrum analysis is free to the changes in spotting concentration and DNA length. The detection range was more than 1µm. Moreover, single nucleotide mismatch could be pointed out combined with specific DNA ligation. A mutation experiment for lung cancer detection proved the high selectivity and accurate analysis capability of the presented biosensor.