Development of miniaturized, portable magnetic resonance relaxometry system for point-of-care medical diagnosis

Machine learning-enabled high-throughput industry screening of edible oils

Long-term consumption of mixed fraudulent edible oils increases the risk of developing of chronic diseases which has been a threat to the public health globally. The complicated global supply-chain is making the industry malpractices had often gone undetected. In order to restore the confidence of consumers, traceability (and accountability) of every level in the supply chain is vital. In this work, we shown that machine learning (ML) assisted windowed spectroscopy (e.g., visible-band, infra-red band) produces high-throughput, non-destructive, and label-free authentication of edible oils (e.g., olive oils, sunflower oils), offers the feasibility for rapid analysis of large-scale industrial screening. We report achieving high-level of discriminant (AUC > 0.96) in the large-scale (n ≈ 11,500) of adulteration in olive oils. Notably, high clustering fidelity of 'spectral fingerprints' achieved created opportunity for (hypothesis-free) self-sustaining large database compilation which was never possible without machine learning. (137 words).

Nutritional load in post-prandial oxidative stress and the pathogeneses of diabetes mellitus

Diabetes mellitus affected more than 500 million of people globally, with an annual mortality of 1.5 million directly attributable to diabetic complications. Oxidative stress, in particularly in post-prandial state, plays a vital role in the pathogenesis of the diabetic complications. However, oxidative status marker is generally poorly characterized and their mechanisms of action are not well understood. In this work, we proposed a new framework for deep characterization of oxidative stress in erythrocytes (and in urine) using home-built micro-scale NMR system. The dynamic of post-prandial oxidative status (against a wide variety of nutritional load) in individual was assessed based on the proposed oxidative status of the red blood cells, with respect to the traditional risk-factors such as urinary isoprostane, reveals new insights into our understanding of diabetes. This new method can be potentially important in drafting guidelines for sub-stratification of diabetes mellitus for clinical care and management.

A Brief Review on Medicinal Plants-At-Arms against COVID-19

COVID-19 pandemic caused by the novel SARS-CoV-2 has impacted human livelihood globally. Strenuous efforts have been employed for its control and prevention; however, with recent reports on mutated strains with much higher infectivity, transmissibility, and ability to evade immunity developed from previous SARS-CoV-2 infections, prevention alternatives must be prepared beforehand in case. We have perused over 128 recent works (found on Google Scholar, PubMed, and ScienceDirect as of February 2023) on medicinal plants and their compounds for anti-SARS-CoV-2 activity and eventually reviewed 102 of them. The clinical application and the curative effect were reported high in China and in India. Accordingly, this review highlights the unprecedented opportunities offered by medicinal plants and their compounds, candidates as the therapeutic agent, against COVID-19 by acting as viral protein inhibitors and immunomodulator in (32 clinical trials and hundreds of in silico experiments) conjecture with modern science. Moreover, the associated foreseeable challenges for their viral outbreak management were discussed in comparison to synthetic drugs.

Novel time-domain NMR-based traits for rapid, label-free Olive oils profiling

Olive oil is one of the oldest and essential edible oils in the market. The classification of olive oils (e.g. extra virgin, virgin, refined) is often influenced by factors ranging from its complex inherent physiochemical properties (e.g. fatty acid profiles) to the undisclosed manufacturing processes. Therefore, olive oils have been the target of adulteration due to its profitable margin. In this work, we demonstrate that multi-parametric time-domain NMR relaxometry can be used to rapidly (in minutes) identify and classify olive oils in label-free and non-destructive manner. The subtle differences in molecular microenvironment of the olive oils induce substantial changes in the relaxation mechanism in the time-domain NMR regime. We demonstrated that the proposed NMR-relaxation based detection (AUC = 0.95) is far more sensitive and specific than the current gold-standards in the field i.e. near-infrared spectroscopy (AUC = 0.84) and Ultraviolet-visible spectroscopy (AUC = 0.73), respectively. We further show that, albeit the inherent complexity of olive plant natural phenotypic variations, the proposed NMR-relaxation based traits may be a viable mean (AUC = 0.71) in tracing the regions of origin for olive trees, in agreement with their geographical orientation.

Review of Microdevices for Hemozoin-Based Malaria Detection

Despite being preventable and treatable, malaria still puts almost half of the world's population at risk. Thus, prompt, accurate and sensitive malaria diagnosis is crucial for disease control and elimination. Optical microscopy and immuno-rapid tests are the standard malaria diagnostic methods in the field. However, these are time-consuming and fail to detect low-level parasitemia. Biosensors and lab-on-a-chip devices, as reported to different applications, usually offer high sensitivity, specificity, and ease of use at the point of care. Thus, these can be explored as an alternative for malaria diagnosis. Alongside malaria infection inside the human red blood cells, parasites consume host hemoglobin generating the hemozoin crystal as a by-product. Hemozoin is produced in all parasite species either in symptomatic and asymptomatic individuals. Furthermore, hemozoin crystals are produced as the parasites invade the red blood cells and their content relates to disease progression. Hemozoin is, therefore, a unique indicator of infection, being used as a malaria biomarker. Herein, the so-far developed biosensors and lab-on-a-chip devices aiming for malaria detection by targeting hemozoin as a biomarker are reviewed and discussed to fulfil all the medical demands for malaria management towards elimination.

Multi-Omics Advancements towards Plasmodium vivax Malaria Diagnosis

Plasmodium vivax malaria is one of the most lethal infectious diseases, with 7 million infections annually. One of the roadblocks to global malaria elimination is the lack of highly sensitive, specific, and accurate diagnostic tools. The absence of diagnostic tools in particular has led to poor differentiation among parasite species, poor prognosis, and delayed treatment. The improvement necessary in diagnostic tools can be broadly grouped into two categories: technologies-driven and omics-driven progress over time. This article discusses the recent advancement in omics-based malaria for identifying the next generation biomarkers for a highly sensitive and specific assay with a rapid and antecedent prognosis of the disease. We summarize the state-of-the-art diagnostic technologies, the key challenges, opportunities, and emerging prospects of multi-omics-based sensors.

The Future in Sensing Technologies for Malaria Surveillance: A Review of Hemozoin-Based Diagnosis

Early and effective malaria diagnosis is vital to control the disease spread and to prevent the emergence of severe cases and death. Currently, malaria diagnosis relies on optical microscopy and immuno-rapid tests; however, these require a drop of blood, are time-consuming, or are not specific and sensitive enough for reliable detection of low-level parasitaemia. Thus, there is an urge for simpler, prompt, and accurate alternative diagnostic methods. Particularly, hemozoin has been increasingly recognized as an attractive biomarker for malaria detection. As the disease proliferates, parasites digest host hemoglobin, in the process releasing toxic haem that is detoxified into an insoluble crystal, the hemozoin, which accumulates along with infection progression. Given its magnetic, optical, and acoustic unique features, hemozoin has been explored for new label-free diagnostic methods. Thereby, herein, we review the hemozoin-based malaria detection methods and critically discuss their challenges and potential for the development of an ideal diagnostic device.

Visualization and Measurements of Blood Cells Flowing in Microfluidic Systems and Blood Rheology: A Personalized Medicine Perspective

Hemorheological alterations in the majority of metabolic diseases are always connected with blood rheology disturbances, such as the increase of blood and plasma viscosity, cell aggregation enhancement, and reduction of the red blood cells (RBCs) deformability. Thus, the visualizations and measurements of blood cells deformability flowing in microfluidic devices (point-of-care devices) can provide vital information to diagnose early symptoms of blood diseases and consequently to be used as a fast clinical tool for early detection of biomarkers. For instance, RBCs rigidity has been correlated with myocardial infarction, diabetes mellitus, hypertension, among other blood diseases. In order to better understand the blood cells behavior in microfluidic devices, rheological properties analysis is gaining interest by the biomedical committee, since it is strongly dependent on the interactions and mechanical cells proprieties. In addition, the development of blood analogue fluids capable of reproducing the rheological properties of blood and mimic the RBCs behavior at in vitro conditions is crucial for the design, performance and optimization of the microfluidic devices frequently used for personalized medicine. By combining the unique features of the hemorheology and microfluidic technology for single-cell analysis, valuable advances in personalized medicine for new treatments and diagnosis approach can be achieved.

Molecular phenotyping of oxidative stress in diabetes mellitus with point-of-care NMR system

Diabetes mellitus is one of the fastest-growing health burdens globally. Oxidative stress, which has been implicated in the pathogenesis of diabetes complication (e.g., cardiovascular event), remains poorly understood. We report a new approach to rapidly manipulate and evaluate the redox states of blood using a point-of-care NMR system. Various redox states of the hemoglobin were mapped out using the newly proposed (pseudo) two-dimensional map known as T1-T2 magnetic state diagram. We exploit the fact that oxidative stress changes the subtle molecular motion of water proton in the blood, and thus inducing a measurable shift in magnetic resonance relaxation properties. We demonstrated the clinical utilities of this technique to rapidly stratify diabetes subjects based on their oxidative status in conjunction to the traditional glycemic level to improve the patient stratification and thus the overall outcome of clinical diabetes care and management.

Machine learning assistive rapid, label-free molecular phenotyping of blood with two-dimensional NMR correlational spectroscopy

Translation of the findings in basic science and clinical research into routine practice is hampered by large variations in human phenotype. Developments in genotyping and phenotyping, such as proteomics and lipidomics, are beginning to address these limitations. In this work, we developed a new methodology for rapid, label-free molecular phenotyping of biological fluids (e.g., blood) by exploiting the recent advances in fast and highly efficient multidimensional inverse Laplace decomposition technique. We demonstrated that using two-dimensional T1-T2 correlational spectroscopy on a single drop of blood (<5 μL), a highly time- and patient-specific 'molecular fingerprint' can be obtained in minutes. Machine learning techniques were introduced to transform the NMR correlational map into user-friendly information for point-of-care disease diagnostic and monitoring. The clinical utilities of this technique were demonstrated through the direct analysis of human whole blood in various physiological (e.g., oxygenated/deoxygenated states) and pathological (e.g., blood oxidation, hemoglobinopathies) conditions.

Rapid phenotyping towards personalized malaria medicine

Malaria is major public health concerns which continues to claim the lives of more than 435,000 people each year. The challenges with anti-malarial drug resistance and detection of low parasitaemia forms an immediate barrier to achieve the fast-approaching United Nations Sustainable Development Goals of ending malaria epidemics by 2030. In this Opinion article, focusing on the recent published technologies, in particularly the nuclear magnetic resonance (NMR)-based diagnostic technologies, the authors offer their perspectives and highlight ways to bring these point-of-care technologies towards personalized medicine. To this end, they advocate an open sourcing initiative to rapidly close the gap between technological innovations and field implementation.

Design and implementation of a low-cost, tabletop MRI scanner for education and research prototyping

While access to a laboratory MRI system is ideal for teaching MR physics as well as many aspects of signal processing, providing multiple MRI scanners can be prohibitively expensive for educational settings. To address this need, we developed a small, low-cost, open-interface tabletop MRI scanner for academic use. We constructed and tested 20 of these scanners for parallel use by teams of 2-3 students in a teaching laboratory. With simplification and down-scaling to a 1 cm FOV, fully-functional scanners were achieved within a budget of $10,000 USD each. The design was successful for teaching MR principles and basic signal processing skills and serves as an accessible testbed for more advanced MR research projects. Customizable GUIs, pulse sequences, and reconstruction code accessible to the students facilitated tailoring the scanner to the needs of laboratory exercise. The scanners have been used by >800 students in 6 different courses and all designs, schematics, sequences, GUIs, and reconstruction code is open-source.

Perspective: Cellular and Molecular Profiling Technologies in Personalized Oncology

Cancer is a leading cause of death worldwide and therefore one of the most important public health concerns. In this contribution, we discuss recent key enabling technological innovations (and their challenges), including biomarker-based technologies, that potentially allow for decentralization (e.g., self-monitoring) with the increasing availability of point-of-care technologies in the near future. These technological innovations are moving the field one step closer toward personalized oncology.

Omics Meeting Onics: Towards the Next Generation of Spectroscopic-Based Technologies in Personalized Medicine

This article aims to discuss the recent development of integrated point-of-care spectroscopic-based technologies that are paving the way for the next generation of diagnostic monitoring technologies in personalized medicine. Focusing on the nuclear magnetic resonance (NMR) technologies as the leading example, we discuss the emergence of -onics technologies (e.g., photonics and electronics) and how their coexistence with -omics technologies (e.g., genomics, proteomics, and metabolomics) can potentially change the future technological landscape of personalized medicine. The idea of an open-source (e.g., hardware and software) movement is discussed, and we argue that technology democratization will not only promote the dissemination of knowledge and inspire new applications, but it will also increase the speed of field implementation.

An autonomous, highly portable NMR spectrometer based on a low-cost System-on-Chip (SoC)

This paper describes the development of a portable and self-optimizing NMR spectrometer based on a miniaturized custom analog front-end and a System-on-Chip (SoC)-based digital back-end. The SoC integrates a field-programmable gate array (FPGA) fabric with a hard processor running a Linux operating system, thus enabling fully-autonomous operation without the need for an external computer. In the proposed approach, data captured by the FPGA fabric during regular operation is transported to the hard processor using an integrated on-chip bus for further processing. The processed results are then used to automatically estimate parameter values that optimize a suitable cost function, such as signal-to-noise ratio (SNR) per unit time. Finally, the optimized values of both electrical and NMR-related tuning parameters (e.g., preamplifier gain and frequency response, pulse length and amplitude, operating frequency, etc.) are programmed back into the front-end and back-end hardware. Experimental NMR results from various samples in a ∼0.1 T permanent magnet are presented to verify the operation of the proposed spectrometer. These demonstrate on-board Laplace inversion and automated frequency tuning to compensate for temperature changes. Preliminary ¹⁴N NQR results are also presented.

Point-of-Care Testing of Pathogenic Bacteria at the Single-Colony Level via Gas Pressure Readout Using Aptamer-Coated Magnetic CuFe2O4 and Vancomycin-Capped Platinum Nanoparticles

Pressure measurements are performed everyday with simple devices, and in the field of analytical chemistry the pressure-based signaling strategy offers two important advantages, signal amplification and particular applicability in point-of-care settings. Herein, by using vancomycin (Van)-functionalized platinum nanoparticles (PtNPs@Van) and aptamer-coated magnetic CuFe₂O₄ nanoprobes dual-recognition units integrated with a catalyzed breakdown of H₂O₂ for O₂ generation, we demonstrated that gas pressure can be used as a readout means for highly sensitive pathogenic bacteria identification and quantification. Using Staphylococcus aureus ( S. aureus) as a test case, integration of the molecular dual-recognition component with the catalyzed gas-generation reaction leads to a significant pressure change (Δ P), and the correlation between the concentration of S. aureus and the Δ P signal was found to be linear from 5.0 to 1.0 × 10⁴ cfu/mL with a detection limit of 1.0 cfu/mL. Other nontarget bacteria show negative results, verifying the high specificity of the present strategy. When employed to assay S. aureus in saliva and milk samples, the approach shows recoveries from 93.3% to 107.1% with relative standard derivation (RSD) less than 8.8%. By the integration of catalyzed gas-generation reaction with the designed molecular recognition event, obviously the pressure-based signaling strategy could facilitate pathogenic bacteria identification and quantification not only in the laboratory but also in point-of-care settings, which could have great potential in the application of food safety and infectious disease diagnosis.

Key Enabling Technologies for Point-of-Care Diagnostics

A major trend in biomedical engineering is the development of reliable, self-contained point-of-care (POC) devices for diagnostics and in-field assays. The new generation of such platforms increasingly addresses the clinical and environmental needs. Moreover, they are becoming more and more integrated with everyday objects, such as smartphones, and their spread among unskilled common people, has the power to improve the quality of life, both in the developed world and in low-resource settings. The future success of these tools will depend on the integration of the relevant key enabling technologies on an industrial scale (microfluidics with microelectronics, highly sensitive detection methods and low-cost materials for easy-to-use tools). Here, recent advances and perspectives will be reviewed across the large spectrum of their applications.

gr-MRI: A software package for magnetic resonance imaging using software defined radios

The goal of this work is to develop software that enables the rapid implementation of custom MRI spectrometers using commercially-available software defined radios (SDRs). The developed gr-MRI software package comprises a set of Python scripts, flowgraphs, and signal generation and recording blocks for GNU Radio, an open-source SDR software package that is widely used in communications research. gr-MRI implements basic event sequencing functionality, and tools for system calibrations, multi-radio synchronization, and MR signal processing and image reconstruction. It includes four pulse sequences: a single-pulse sequence to record free induction signals, a gradient-recalled echo imaging sequence, a spin echo imaging sequence, and an inversion recovery spin echo imaging sequence. The sequences were used to perform phantom imaging scans with a 0.5Tesla tabletop MRI scanner and two commercially-available SDRs. One SDR was used for RF excitation and reception, and the other for gradient pulse generation. The total SDR hardware cost was approximately $2000. The frequency of radio desynchronization events and the frequency with which the software recovered from those events was also measured, and the SDR's ability to generate frequency-swept RF waveforms was validated and compared to the scanner's commercial spectrometer. The spin echo images geometrically matched those acquired using the commercial spectrometer, with no unexpected distortions. Desynchronization events were more likely to occur at the very beginning of an imaging scan, but were nearly eliminated if the user invoked the sequence for a short period before beginning data recording. The SDR produced a 500kHz bandwidth frequency-swept pulse with high fidelity, while the commercial spectrometer produced a waveform with large frequency spike errors. In conclusion, the developed gr-MRI software can be used to develop high-fidelity, low-cost custom MRI spectrometers using commercially-available SDRs.

Translating Molecular Recognition into a Pressure Signal to enable Rapid, Sensitive, and Portable Biomedical Analysis

Herein, we demonstrate that a very familiar, yet underutilized, physical parameter—gas pressure—can serve as signal readout for highly sensitive bioanalysis. Integration of a catalyzed gas-generation reaction with a molecular recognition component leads to significant pressure changes, which can be measured with high sensitivity using a low-cost and portable pressure meter. This new signaling strategy opens up a new way for simple, portable, yet highly sensitive biomedical analysis in a variety of settings.

Enhancing malaria diagnosis through microfluidic cell enrichment and magnetic resonance relaxometry detection

Despite significant advancements over the years, there remains an urgent need for low cost diagnostic approaches that allow for rapid, reliable and sensitive detection of malaria parasites in clinical samples. Our previous work has shown that magnetic resonance relaxometry (MRR) is a potentially highly sensitive tool for malaria diagnosis. A key challenge for making MRR based malaria diagnostics suitable for clinical testing is the fact that MRR baseline fluctuation exists between individuals, making it difficult to detect low level parasitemia. To overcome this problem, it is important to establish the MRR baseline of each individual while having the ability to reliably determine any changes that are caused by the infection of malaria parasite. Here we show that an approach that combines the use of microfluidic cell enrichment with a saponin lysis before MRR detection can overcome these challenges and provide the basis for a highly sensitive and reliable diagnostic approach of malaria parasites. Importantly, as little as 0.0005% of ring stage parasites can be detected reliably, making this ideally suited for the detection of malaria parasites in peripheral blood obtained from patients. The approaches used here are envisaged to provide a new malaria diagnosis solution in the near future.

An ultra-low cost NMR device with arbitrary pulse programming

Ultra-low cost, general purpose electronics boards featuring microprocessors or field programmable gate arrays (FPGA) are reaching capabilities sufficient for direct implementation of NMR spectrometers. We demonstrate a spectrometer based on such a board, implemented with a minimal need for the addition of custom electronics and external components. This feature allows such a spectrometer to be readily implemented using typical knowledge present in an NMR laboratory. With FPGA technology, digital tasks are performed with precise timing, without the limitation of predetermined hardware function. In this case, the FPGA is used for programming of arbitrarily timed pulse sequence events, and to digitally generate required frequencies. Data acquired from a 0.53T permanent magnet serves as a demonstration of the flexibility of pulse programming for diverse experiments. Pulse sequences applied include a spin-lattice relaxation measurement using a pulse train with small-flip angle pulses, and a Carr-Purcell-Meiboom-Gill experiment with phase cycle. Mixing of NMR signals with a digitally generated, 4-step phase-cycled reference frequency is further implemented to achieve sequential quadrature detection. The flexibility in hardware implementation permits tailoring this type of spectrometer for applications such as relaxometry, polarimetry, diffusometry or NMR based magnetometry.

Micromagnetic resonance relaxometry for rapid label-free malaria diagnosis

We report a new technique for sensitive, quantitative and rapid detection of Plasmodium spp.-infected red blood cells (RBCs) by means of magnetic resonance relaxometry (MRR). During the intraerythrocytic cycle, malaria parasites metabolize large amounts of cellular hemoglobin and convert it into hemozoin crystallites. We exploit the relatively large paramagnetic susceptibility of these hemozoin particles, which induce substantial changes in the transverse relaxation rate of proton nuclear magnetic resonance of RBCs, to infer the 'parasite load' in blood. Using an inexpensive benchtop 0.5-Tesla MRR system, we show that with minimal sample preparatory steps and without any chemical or immunolabeling, a parasitemia level of fewer than ten parasites per microliter in a volume below 10 μl of whole blood is detected in a few minutes. We demonstrate this method both for cultured Plasmodium falciparum parasites and in vivo with Plasmodium berghei-infected mice.

NMR–DMF: a modular nuclear magnetic resonance–digital microfluidics system for biological assays

We present a modular nuclear magnetic resonance–digital microfluidics (NMR–DMF) system as a portable diagnostic platform for miniaturized biological assays.

Magic-angle spinning solid-state multinuclear NMR on low-field instrumentation

Mobile and cost-effective NMR spectroscopy exploiting low-field permanent magnets is a field of tremendous development with obvious applications for arrayed large scale analysis, field work, and industrial screening. So far such demonstrations have concentrated on relaxation measurements and lately high-resolution liquid-state NMR applications. With high-resolution solid-state NMR spectroscopy being increasingly important in a broad variety of applications, we here introduce low-field magic-angle spinning (MAS) solid-state multinuclear NMR based on a commercial ACT 0.45 T 62 mm bore Halbach magnet along with a homebuilt FPGA digital NMR console, amplifiers, and a modified standard 45 mm wide MAS probe for 7 mm rotors. To illustrate the performance of the instrument and address cases where the low magnetic field may offer complementarity to high-field NMR experiments, we demonstrate applications for (23)Na MAS NMR with enhanced second-order quadrupolar coupling effects and (31)P MAS NMR where reduced influence from chemical shift anisotropy at low field may facilitate determination of heteronuclear dipole-dipole couplings.