Demand-Driven Multi-Target Sample Preparation on Resource-Constrained Digital Microfluidic Biochips

Microfluidic lab-on-chips offer promising technology for the automation of various biochemical laboratory protocols on a minuscule chip. Sample preparation (SP) is an essential part of any biochemical experiments, which aims to produce dilution of a sample or a mixture of multiple reagents in a certain ratio. One major objective in this area is to prepare dilutions of a given fluid with different concentration factors, each with certain volume, which is referred to as the demand-driven multiple-target (DDMT) generation problem. SP with microfluidic biochips requires proper sequencing of mix-split steps on fluid volumes and needs storage units to save intermediate fluids while producing the desired target ratio. The performance of SP depends on the underlying mixing algorithm and the availability of on-chip storage, and the latter is often limited by the constraints imposed during physical design. Since DDMT involves several target ratios, solving it under storage constraints becomes even harder. Furthermore, reduction of mix-split steps is desirable from the viewpoint of accuracy of SP, as every such step is a potential source of volumetric split error. In this article, we propose a storage-aware DDMT algorithm that reduces the number of mix-split operations on a digital microfluidic lab-on-chip. We also present the layout of the biochip with -storage cells and their allocation technique for . Simulation results reveal the superiority of the proposed method compared to the state-of-the-art multi-target SP algorithms.

In-Situ Integration of 3D C-MEMS Microelectrodes with Bipolar Exfoliated Graphene for Label-Free Electrochemical Cancer Biomarkers Aptasensor

The electrochemical label-free aptamer-based biosensors (also known as aptasensors) are highly suitable for point-of-care applications. The well-established C-MEMS (carbon microelectromechanical systems) platforms have distinguishing features which are highly suitable for biosensing applications such as low background noise, high capacitance, high stability when exposed to different physical/chemical treatments, biocompatibility, and good electrical conductivity. This study investigates the integration of bipolar exfoliated (BPE) reduced graphene oxide (rGO) with 3D C-MEMS microelectrodes for developing PDGF-BB (platelet-derived growth factor-BB) label-free aptasensors. A simple setup has been used for exfoliation, reduction, and deposition of rGO on the 3D C-MEMS microelectrodes based on the principle of bipolar electrochemistry of graphite in deionized water. The electrochemical bipolar exfoliation of rGO resolves the drawbacks of commonly applied methods for synthesis and deposition of rGO, such as requiring complicated and costly processes, excessive use of harsh chemicals, and complex subsequent deposition procedures. The PDGF-BB affinity aptamers were covalently immobilized by binding amino-tag terminated aptamers and rGO surfaces. The turn-off sensing strategy was implemented by measuring the areal capacitance from CV plots. The aptasensor showed a wide linear range of 1 pM–10 nM, high sensitivity of 3.09 mF cm−2 Logc−1 (unit of c, pM), and a low detection limit of 0.75 pM. This study demonstrated the successful and novel in-situ deposition of BPE-rGO on 3D C-MEMS microelectrodes. Considering the BPE technique’s simplicity and efficiency, along with the high potential of C-MEMS technology, this novel procedure is highly promising for developing high-performance graphene-based viable lab-on-chip and point-of-care cancer diagnosis technologies.

Nanophotonics: An Emerging and Promising Approach for COVID-19 Diagnostic Technology

The public health crisis initiated by the emergence of the COVID-19 pandemic emphasizes the need for rapid and accurate diagnostic tests to monitor large populations through community mass testing. Many testing techniques have been implemented to prevent disease spread, critical to pandemic control. Polymerase chain reaction (PCR) tests for detecting viral RNA and immunoassay tests for detecting SARS-CoV-2 antibodies are currently used to diagnose COVID-19. PCR tests are time-consuming, with a 24–48 hours turnaround time. Samples undergoing PCR detection must also be sent to a laboratory to be processed by highly specialized workers, preventing a point-of-care diagnosis from being provided. Popular immunoassay tests have drawbacks as well. Enzyme-linked immunosorbent assays (ELISAs) are extremely labor-intensive and expensive, whereas lateral flow assays (LFAs) are primarily used for antigen detection. In this work, we propose a photonic SARS-CoV-2 detection method based on a ring resonator. We calculate the sensor performance using the finite-difference eigenmode (FDE) method. The sensor sensitivity in ring resonator resonance frequency is 29 nm/RIU, with an intrinsic detection level (iLOD) of 6.89 × 10-5 RIU. We envision ring resonator-based lab-on-chip devices being widely used for applications such as early diagnosis, with the added benefit of being ultra-compact and easily handled by non-specialists.

Raspberry PI Based ECG Data Acquisition System by Using Block Chain

There have been revolutionary developments in the healthcare industry with the advancement of technology over the past years. Technology has widespread health records that may have been digitized into electronic health records. Internet of Things, Cloud Computing, Block chain technology, lab-on-chip, non-invasive and minimally invasive surgeries and so on has simplified several dreadful diseases. The research as well as healthcare industry has been greatly impacted by these new technologies. In such case accessibility of health data from one provider to another at the right time remains a major challenge, especially when patients are in a critical condition having access to fragmented health records from multiple sources into a single chain. The proposed system aims to exchange health information on a block chain platform to build a smart e-health system. In this system, block chain is a clinical data repository that provides patients a complete, distributed ledger record containing records of all the events and seamless access to their electronic health records through healthcare providers. As an important feature, this system provides high security and integrity through cryptographic hash functions.

Simultaneous Detection of Relative Humidity and Temperature Based on Silicon On-Chip Cascaded Photonic Crystal Nanobeam Cavities

In this paper, we propose and numerically demonstrate a novel cascaded silicon-on-insulator (SOI) photonic crystal nanobeam cavity (PCNC) dual-parameter sensor for the simultaneous detection of relative humidity (RH) and temperature. The structure consists of two independent PCNCs supporting two different resonant modes: a dielectric-mode and an air-mode, respectively. The dielectric-mode nanobeam cavities (cav1) are covered with SU-8 cladding to increase the sensitivity ratio contrast between RH sensing and temperature sensing. The air-mode nanobeam cavities (cav2) are coated with a water-absorbing polyvinyl-alcohol (PVA) layer that converts the change in RH into a change in refractive index (RI) under different ambient RH levels, thereby inducing a wavelength shift. Due to the positive thermo-optic (TO) coefficient of silicon and the negative TO coefficient of SU-8 cladding, the wavelength responses take the form of a red shift for cav2 and a blue shift for cav1 as the ambient temperature increases. By using 3D finite-difference time-domain (3D-FDTD) simulations, we prove the feasibility of simultaneous sensing by monitoring a single output transmission spectrum and applying the sensor matrix. For cav1, the RH and temperature sensitivities are 0 pm/%RH and −37.9 pm/K, while those of cav2 are −389.2 pm/%RH and 58.6 pm/K. The sensitivity ratios of temperature and RH are −1.5 and 0, respectively, which is the reason for designing two different resonant modes and also implies great potential for realizing dual-parameter sensing detection. In particular, it is also noteworthy that we demonstrate the ability of the dual-parameter sensor to resist external interference by using the dual wavelength matrix method. The maximum RH and temperature detection errors caused by the deviation of resonance wavelength 1 pm are only 0.006% RH and 0.026 K, which indicates that it achieves an excellent anti-interference ability. Furthermore, the structure is very compact, occupying only 32 μm × 4 μm (length × width). Hence, the proposed sensor shows promising prospects for compact lab-on-chip integrated sensor arrays and sensing with multiple parameters.

Validation of a Lab-on-Chip Assay for Measuring Sorafenib Effectiveness on HCC Cell Proliferation

Hepatocellular carcinoma (HCC) is a highly lethal cancer, and although a few drugs are available for treatment, therapeutic effectiveness is still unsatisfactory. New drugs are urgently needed for hepatocellular carcinoma (HCC) patients. In this context, reliable preclinical assays are of paramount importance to screen the effectiveness of new drugs and, in particular, measure their effects on HCC cell proliferation. However, cell proliferation measurement is a time-consuming and operator-dependent procedure. The aim of this study was to validate an engineered miniaturized on-chip platform for real-time, non-destructive cell proliferation assays and drug screening. The effectiveness of Sorafenib, the first-line drug mainly used for patients with advanced HCC, was tested in parallel, comparing the gold standard 96-well-plate assay and our new lab-on-chip platform. Results from the lab-on-chip are consistent in intra-assay replicates and comparable to the output of standard crystal violet proliferation assays for assessing Sorafenib effectiveness on HCC cell proliferation. The miniaturized platform presents several advantages in terms of lesser reagents consumption, operator time, and costs, as well as overcoming a number of technical and operator-dependent pitfalls. Moreover, the number of cells required is lower, a relevant issue when primary cell cultures are used. In conclusion, the availability of inexpensive on-chip assays can speed up drug development, especially by using patient-derived samples to take into account disease heterogeneity and patient-specific characteristics.

Development of Epoxy Resin-Based Elastomeric Microfluidic Devices Using CO2 Laser Ablation for DNA-Amplification Point-Of-Care (POC) Applications: Assessment of Microchannels' Dimensions and Quality

Microfluidic devices are a rising technology to automatize chemical and biological operations. In this context, laser ablation has significant potential for polymer-based microfluidic platforms' fast and economical manufacturing. Nevertheless, the manufacturing of epoxy-based microfluidic chips is considered highly cost full due to demand for cleanroom facilities that utilize expensive equipment and lengthy processes. Therefore, this study targeted investigating the feasibility of epoxy resins to be fabricated as a lab-on-chip using carbon dioxide laser ablation. The chemical structural properties and thermal stability of the plain epoxy resins were characterized by Fourier transform infrared spectral analysis (FT-IR) and thermogravimetric analysis (TGA). Moreover, a specific migration test was performed to quantify potential migrants by gas chromatography coupled to mass spectrometry (GC-MS) to prove that the cured epoxy resin would not release unreacted monomers to the biological solution test, which caused inhibition of the sensitive biological reactions. By investigating the impact of this process on microchannels' dimensions and quality, a laser technique using CO2 laser was used in vector mode to engrave into a transparent epoxy resin chip. The resulting microchannels were characterized using 3D Laser microscopy. The outcomes of this study showed considerable potential for laser ablation in machining the epoxy-based chips, whereas the microchannels were produced with minor bulges' height (0.027 µm) with no clogging. Moreover, a reasonable depth of 99.31 µm with roughness (Ra) of 14.52 µm was obtained at a laser speed of 5 mm/s and laser power of 1.8 W. This process can produce epoxy resin-based microfluidic chips without the need for cleanroom facilities that require expensive equipment and lengthy process.