Flow Rate and Raspberry Pi-based Paper Microfluidic Blood Coagulation Assay Device

Development of a real-time and multitasking system for long-term monitoring of aqueous metallic elements using plasma spectroscopy

In this work, we integrated a Raspberry Pi (RPi) board, an open-sourced hardware, with a spectrometer, a high voltage DC power source, and a plasma system to develop a multi-tasking monitoring system for metallic elements in solution. In this system, RPi precisely controls voltage pulses, synchronizes them with the spectrometer, and performs real-time analysis using data acquired in real-time. This integration enables continuous monitoring of multiple metallic elements in solutions of varying conductivities. Synchronization of voltage pulses and spectrometer triggering is crucial for reliable measurements and prolongs the lifetime of the electrode. This multitasking capability significantly improves the quality of the overall spectroscopic data and enables operation in a long-term manner. Two operating modes are proposed, namely regular detection mode (RDM) and event-based mode (EBM). RDM is used to identify the existence of metallic elements and EBM is used for quantification upon detection. A 24-h long-term test shown in this work demonstrates the system capability in of utilizing RDM to monitor the presence of Pb and Mg every 30 min. Injection of Pb- and/or Mg-containing solutions is performed to activate EBM for quantification analysis. Instant warning messages can be sent upon metal detection showcasing the system potential for real-time monitoring and efficient quantification. We believe this work can contribute to multiple fields such as environmental monitoring, industrial quality control, or process monitoring.

Open Hardware for Microfluidics: Exploiting Raspberry Pi Singleboard Computer and Camera Systems for Customisable Laboratory Instrumentation

The integration of Raspberry Pi miniature computer systems with microfluidics has revolutionised the development of low-cost and customizable analytical systems in life science laboratories. This review explores the applications of Raspberry Pi in microfluidics, with a focus on imaging, including microscopy and automated image capture. By leveraging the low cost, flexibility and accessibility of Raspberry Pi components, high-resolution imaging and analysis have been achieved in direct mammalian and bacterial cellular imaging and a plethora of image-based biochemical and molecular assays, from immunoassays, through microbial growth, to nucleic acid methods such as real-time-qPCR. The control of image capture permitted by Raspberry Pi hardware can also be combined with onboard image analysis. Open-source hardware offers an opportunity to develop complex laboratory instrumentation systems at a fraction of the cost of commercial equipment and, importantly, offers an opportunity for complete customisation to meet the users' needs. However, these benefits come with a trade-off: challenges remain for those wishing to incorporate open-source hardware equipment in their own work, including requirements for construction and operator skill, the need for good documentation and the availability of rapid prototyping such as 3D printing plus other components. These advances in open-source hardware have the potential to improve the efficiency, accessibility, and cost-effectiveness of microfluidic-based experiments and applications.

Assessment of fibrinolytic status in whole blood using a dielectric coagulometry microsensor

Rapid assessment of the fibrinolytic status in whole blood at the point-of-care/point-of-injury (POC/POI) is clinically important to guide timely management of uncontrolled bleeding in patients suffering from hyperfibrinolysis after a traumatic injury. In this work, we present a three-dimensional, parallel-plate, capacitive sensor - termed ClotChip - that measures the temporal variation in the real part of blood dielectric permittivity at 1 MHz as the sample undergoes coagulation within a microfluidic channel with <10 μL of total volume. The ClotChip sensor features two distinct readout parameters, namely, lysis time (LT) and maximum lysis rate (MLR) that are shown to be sensitive to the fibrinolytic status in whole blood. Specifically, LT identifies the time that it takes from the onset of coagulation for the fibrin clot to mostly dissolve in the blood sample during fibrinolysis, whereas MLR captures the rate of fibrin clot lysis. Our findings are validated through correlative measurements with a rotational thromboelastometry (ROTEM) assay of clot viscoelasticity, qualitative/quantitative assessments of clot stability, and scanning electron microscope imaging of clot ultrastructural changes, all in a tissue plasminogen activator (tPA)-induced fibrinolytic environment. Moreover, we demonstrate the ClotChip sensor ability to detect the hemostatic rescue that occurs when the tPA-induced upregulated fibrinolysis is inhibited by addition of tranexamic acid (TXA) - a potent antifibrinolytic drug. This work demonstrates the potential of ClotChip as a diagnostic platform for rapid POC/POI assessment of fibrinolysis-related hemostatic abnormalities in whole blood to guide therapy.

Laboratory Ozonolysis Using an Integrated Batch-DIY Flow System for Renewable Material Production

Flow chemistry offers a solution for replacing batch methods in chemical preparation where intermediates or products may pose toxicity or instability hazards. Ozonolysis offers an ideal opportunity for flow chemistry solutions, but multiple barriers to entry exist for use of these methods, including equipment cost and performance optimization. To address these challenges, we developed a programmable DIY syringe pump system to use for a continuous flow multireactor process using 3D-printed parts, off-the-shelf stepper motors, and an Arduino microcontroller. Reaction kinetics of ozonide formation informed the use of an integrated batch-flow approach, where ozone addition to an olefin was timed to coincide with fluid movement of a single-syringe pump, followed by downstream Pinnick oxidation and reductive quench in flow. The system was demonstrated by continuous preparation of azelaic acid from ozonolysis of palmitoleic acid, a process limited to low production volumes via batch chemistry. High total production of azelaic acid with 80% yield was obtained from an algae oil sourced unsaturated fatty acid: a product with important applications in medicine, cosmetics, and polymers. This low-cost, scalable approach offers the potential for rapid prototyping and distributed chemical production.

Point of care whole blood microfluidics for detecting and managing thrombotic and bleeding risks

Point-of-care diagnostics of platelet and coagulation function present demanding challenges. Current clinical diagnostics often use centrifuged plasmas or platelets and frozen plasma standards, recombinant protein standards, or even venoms. Almost all commercialized tests of blood do not recreate the in vivo hemodynamics where platelets accumulate to high densities and thrombin is generated from a procoagulant surface. Despite numerous drugs that target platelets, insufficient coagulation, or excess coagulation, POC blood testing is essentially limited to viscoelastic methods that provide a clotting time, clot strength, and clot lysis, while used mostly in trauma centers with specialized capabilities. Microfluidics now allows small volumes of whole blood (<1 mL) to be tested under venous or arterial shear rates with multi-color readouts to follow platelet function, thrombin generation, fibrin production, and clot stability. Injection molded chips containing pre-patterned fibrillar collagen and lipidated tissue factor can be stored dry for 6 months at 4C, thus allowing rapid blood testing on single-use disposable chips. Using only a small imaging microscope and micropump, these microfluidic devices can detect platelet inhibitors, direct oral anticoagulants (DOACs) and their reversal agents. POC microfluidics are ideal for neonatal surgical applications that involve small blood samples, rapid DOAC testing in stroke or bleeding or emergency surgery situations with patients presenting high risk cofactors for either bleeding or thrombosis.

Sensing Optimum in the Raw: Leveraging the Raw-Data Imaging Capabilities of Raspberry Pi for Diagnostics Applications

Single-board computers (SBCs) and microcontroller boards (MCBs) are extensively used nowadays as prototyping platforms to accomplish innovative tasks. Very recently, implementations of these devices for diagnostics applications are rapidly gaining ground for research and educational purposes. Among the available solutions, Raspberry Pi represents one of the most used SBCs. In the present work, two setups based on Raspberry Pi and its CMOS-based camera (a 3D-printed device and an adaptation of a commercial product named We-Lab) were investigated as diagnostic instruments. Different camera elaboration processes were investigated, showing how direct access to the 10-bit raw data acquired from the sensor before downstream imaging processes could be beneficial for photometric applications. The developed solution was successfully applied to the evaluation of the oxidative stress using two commercial kits (d-ROM Fast; PAT). We suggest the analysis of raw data applied to SBC and MCB platforms in order to improve results.

Smartphone based on-chip fluorescence imaging and capillary flow velocity measurement for detecting ROR1+ cancer cells from buffy coat blood samples on dual-layer paper microfluidic chip

Diagnosis of hematological cancer requires complete white blood cell count, followed by flow cytometry with multiple markers, and cytology. It requires substantial time and specialized training. A dual-layer paper microfluidic chip was developed as a quicker, low-cost, and field-deployable alternative to detect ROR1+ (receptor tyrosine-like orphan receptor one) cancer cells from the undiluted and untreated buffy coat blood samples. The first capture layer consisted of a GF/D glass fiber substrate, preloaded with cancer specific anti-ROR1 conjugated fluorescent particles to its center for cancer cell capture and direct smartphone fluorescence imaging. The second flow layer was comprised of a grade 1 cellulose chromatography paper with wax-printed four channels for wicking and capillary flow-based detection. The flow velocity was used as measure of antigen concentration in the buffy coat sample. In this manner, intact cells and their antigens were separated and independently analyzed by both imaging and flow velocity analyses. A custom-made smartphone-based fluorescence microscope and automated image processing and particle counter software were developed to enumerate particles on paper, with the limit of detection of 1 cell/μL. Flow velocity analysis showed even greater sensitivity, with the limit of detection of 0.1 cells/μL in the first 6 s of assay. Comparison with capillary flow model revealed great alignment with experimental data and greater correlation to viscosity than interfacial tension. Our proposed device is able to capture and on-chip image ROR1+ cancer cells within a complex sample matrix (buffy coat) while simultaneously quantifying cell concentration in a point-of-care manner.

A DIY Low-Cost Wireless Wind Data Acquisition System Used to Study an Arid Coastal Foredune

Environmental studies on coastal dune systems are faced with a considerable cost barrier due to the cost of the instrumentation and sensory equipment required for data collection. These systems play an important role in coastal areas as a protection against erosion and as providers of stability to coastal sedimentary deposits. The DIY (Do-It-Yourself) approach to data acquisition can reduce the cost of these environmental studies. In this paper, a low-cost DIY wireless wind data acquisition system is presented which reduces the cost barrier inherent to these types of studies. The system is deployed for the analysis of the foredune of Maspalomas, an arid dune field situated on the south coast of Gran Canaria (Canary Islands, Spain), for the specific purpose of studying the dynamics of a dune type (tongue dunes), which is typical of this environment. The results obtained can be of interest for the study of these coastal environments at both the local level, for the management of this particular dune field, and at the general level for other similar dune fields around the world.

Development of Low-Cost Point-of-Care Technologies for Cervical Cancer Prevention Based on a Single-Board Computer

Cervical cancer disproportionally affects women in low- and middle-income countries, in part due to the difficulty of implementing existing cervical cancer screening and diagnostic technologies in low-resource settings. Single-board computers offer a low-cost alternative to provide computational support for automated point-of-care technologies. Here we demonstrate two new devices for cervical cancer prevention that use a single-board computer: 1) a low-cost imaging system for real-time detection of cervical precancer and 2) a low-cost reader for real-time interpretation of lateral flow-based molecular tests to detect cervical cancer biomarkers. Using a Raspberry Pi computer to provide real-time image collection and processing, we developed: 1) a low-cost, portable high-resolution microendoscope system (PiHRME); and 2) a low-cost automatic lateral flow test reader (PiReader). The PiHRME acquired high-resolution ([Formula: see text]) images of the cervix at half the cost of existing high-resolution microendoscope systems; image analysis algorithms based on convolutional neural networks were implemented to provide real-time image interpretation. The PiReader acquired and analyzed images of a point-of-care human papillomavirus (HPV) serology test with the same contrast and accuracy as a standard flatbed high-resolution scanner coupled to a laptop computer, for less than one-fifth of the cost. Raspberry Pi single-board computers provide a low-cost means to implement point-of-care tools with automatic image analysis. This work demonstrates the promise of single-board computers to develop and translate low-cost, point-of-care technologies for use in low-resource settings.