Publications
105 results found
Pennisi I, Rodriguez Manzano J, Moniri A, et al., 2021, Translation of a host blood RNA Signature distinguishing bacterial from viral infection into a platform suitable for development as a point-of-care test, JAMA Pediatrics, Vol: 175, Pages: 417-419, ISSN: 2168-6203
Li HK, Kaforou M, Rodriguez-Manzano J, et al., 2021, Discovery and Validation of a 3-Gene Transcriptional Signature to Distinguish COVID-19 and Other Viral Infections from Bacterial Sepsis in Adults; A Case-Control then Observational Cohort Study, Publisher: Elsevier BV
Moser N, Rodriguez-Manzano J, Georgiou P, 2021, ProtonDx: Accurate, Rapid and Lab-Free Detection of SARS-CoV-2 and Other Respiratory Pathogens, IEEE CIRCUITS AND SYSTEMS MAGAZINE, Vol: 21, Pages: 84-88, ISSN: 1531-636X
Yu L-S, Rodriguez-Manzano J, Moser N, et al., 2020, Rapid detection of azole-resistant Aspergillus fumigatus in clinical and environmental isolates using lab-on-a-chip diagnostic system, Journal of Clinical Microbiology, Vol: 58, Pages: 1-11, ISSN: 0095-1137
Aspergillus fumigatus has widely evolved resistance to the most commonly used class of antifungal chemicals, the azoles. Current methods for identifying azole resistance are time-consuming and depend on specialized laboratories. There is an urgent need for rapid detection of these emerging pathogens at point-of-care to provide the appropriate treatment in the clinic and to improve management of environmental reservoirs to mitigate the spread of antifungal resistance. Our study demonstrates the rapid and portable detection of the two most relevant genetic markers linked to azole resistance, the mutations TR34 and TR46, found in the promoter region of the gene encoding the azole target, cyp51A. We developed a lab-on-a-chip platform consisting of: (1) tandem-repeat loop-mediated isothermal amplification, (2) state-of-the-art complementary metal-oxide-semiconductor microchip technology for nucleic-acid amplification detection and, (3) and a smartphone application for data acquisition, visualization and cloud connectivity. Specific and sensitive detection was validated with isolates from clinical and environmental samples from 6 countries across 5 continents, showing a lower limit-of-detection of 10 genomic copies per reaction in less than 30 minutes. When fully integrated with a sample preparation module, this diagnostic system will enable the detection of this ubiquitous fungus at the point-of-care, and could help to improve clinical decision making, infection control and epidemiological surveillance.
Keeble L, Moser N, Rodriguez-Manzano J, et al., 2020, ISFET-Based Sensing and Electric Field Actuation of DNA for On-Chip Detection: A Review, IEEE SENSORS JOURNAL, Vol: 20, Pages: 11044-11065, ISSN: 1530-437X
Alexandrou G, Moser N, Rodriguez-Manzano J, et al., 2020, Detection of breast cancer ESR1 p.E380Q mutation on an ISFET lab-on-chip platform, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 1-5, ISSN: 0271-4302
This paper presents a method for detection of ESR1 p.E380Q, a common Breast Cancer (BC) mutation, using an ISFET (Ion-Sensitive Field-Effect Transistor) based Lab-on-Chip (LoC) platform. The LoC contains an ISFET array that can detect pH changes during DNA amplification, specifically Loop-Mediated Isothermal Amplification (LAMP). Synthetic ESR1 DNA was detected in a comparison pH-LAMP assay, carried out on the LoC platform as well as a conventional qPCR instrument. Positive detection of the allele arises due to bespoke allele-specific primers that target one base-pair difference between the wild-type and mutant alleles. The LoC and qPCR demonstrate comparable results detecting the mutant allele with mutant primers in around 25 minutes. The sensing microchip technology coupled with the molecular methods of isothermal chemistries and primer design allow this platform to be tested at a Point-of-Care setting for breast cancer patients, offering mutational tracking platform of circulating tumour DNA in liquid biopsies to assist patient stratification and allow tailored treatments.
Moniri A, Miglietta L, Holmes A, et al., 2020, High-level multiplexing in digital PCR with intercalating dyes by coupling real-time kinetics and melting curve analysis., Analytical Chemistry, Vol: 92, Pages: 14181-14188, ISSN: 0003-2700
Digital polymerase chain reaction (dPCR) is a mature technique that has enabled scientific breakthroughs in several fields. However, this technology is primarily used in research environments with high-level multiplexing representing a major challenge. Here, we propose a novel method for multiplexing, referred to as amplification and melting curve analysis (AMCA), which leverages the kinetic information in real-time amplification data and the thermodynamic melting profile using an affordable intercalating dye (EvaGreen). The method trains a system comprised of supervised machine learning models for accurate classification, by virtue of the large volume of data from dPCR platforms. As a case study, we develop a new 9-plex assay to detect mobilised colistin resistant (mcr) genes as clinically relevant targets for antimicrobial resistance. Over 100,000 amplification events have been analysed, and for the positive reactions, the AMCA approach reports a classification accuracy of 99.33 ± 0.13%, an increase of 10.0% over using melting curve analysis. This work provides an affordable method of high-level multiplexing without fluorescent probes, extending the benefits of dPCR in research and clinical settings.
Moniri A, Miglietta L, Malpartida Cardenas K, et al., 2020, Amplification curve analysis: Data-driven multiplexing using real-time digital PCR, Analytical Chemistry, Vol: 92, Pages: 13134-13143, ISSN: 0003-2700
Information about the kinetics of PCR reactions are encoded in the amplification curve. However, in digital PCR (dPCR), this information is typically neglected by collapsing each amplification curve into a binary output (positive/negative). Here, we demonstrate that the large volume of raw data obtained from realtime dPCR instruments can be exploited to perform data-driven multiplexing in a single fluorescent channel using machine learning methods, by virtue of the information in the amplification curve. This new approach, referred to as amplification curve analysis (ACA), was shown using an intercalating dye (EvaGreen), reducing the cost and complexity of the assay and enabling the use of melting curve analysis for validation. As a case study, we multiplexed 3 carbapenem-resistant genes to show the impact of this approach on global challenges such as antimicrobial resistance. In the presence of single targets, we report a classification accuracy of 99.1% (N = 16188) which represents a 19.7% increase compared to multiplexing based on the final fluorescent intensity. Considering all combinations of amplification events (including coamplifications), the accuracy was shown to be 92.9% (N = 10383). To support the analysis, we derived a formula to estimate the occurrence of co-amplification in dPCR based on multivariate Poisson statistics, and suggest reducing the digital occupancy in the case of multiple targets in the same digital panel. The ACA approach takes a step towards maximizing the capabilities of existing real-time dPCR instruments and chemistries, by extracting more information from data to enable data-driven multiplexing with high accuracy. Furthermore, we expect that combining this method with existing probe-based assays will increase multiplexing capabilities significantly. We envision that once emerging point-of-care technologies can reliably capture real-time data from isothermal chemistries, the ACA method will facilitate the implementation of dPCR outs
Pennisi I, Rodriguez Manzano J, Miscourides N, et al., 2020, A method for determining a diagnostic outcome
Rodriguez Manzano J, Moniri A, Miglietta L, et al., 2020, Identifying a target nucleic acid
Moniri A, Terracina D, Rodriguez-Manzano J, et al., 2020, Real-time forecasting of sEMG features for trunk muscle fatigue using machine learning, IEEE Transactions on Biomedical Engineering, Vol: 68, Pages: 718-727, ISSN: 0018-9294
Objective: Several features of the surface electromyography (sEMG) signal are related to muscle activity and fatigue. However, the time-evolution of these features are non-stationary and vary between subjects. The aim of this study is to investigate the use of adaptive algorithms to forecast sMEG feature of the trunk muscles. Methods: Shallow models and a deep convolutional neural network (CNN) were used to simultaneously learn and forecast 5 common sEMG features in real-time to provide tailored predictions. This was investigated for: up to a 25 second horizon; for 14 different muscles in the trunk; across 13 healthy subjects; while they were performing various exercises. Results: The CNN was able to forecast 25 seconds ahead of time, with 6.88% mean absolute percentage error and 3.72% standard deviation of absolute percentage error, across all the features. Moreover, the CNN outperforms the best shallow model in terms of a figure of merit combining accuracy and precision by at least 30% for all the 5 features. Conclusion: Even though the sEMG features are non-stationary and vary between subjects, adaptive learning and forecasting, especially using CNNs, can provide accurate and precise forecasts across a range of physical activities. Significance: The proposed models provide the groundwork for a wearable device which can forecast muscle fatigue in the trunk, so as to potentially prevent low back pain. Additionally, the explicit realtime forecasting of sEMG features provides a general model which can be applied to many applications of muscle activity monitoring, which helps practitioners and physiotherapists improve therapy.
Rodriguez-Manzano J, Malpartida-Cardenas K, Moser N, et al., 2020, A handheld point-of-care system for rapid detection of SARS-CoV-2 in under 20 minutes
<jats:title>Abstract</jats:title><jats:p>The COVID-19 pandemic is a global health emergency characterized by the high rate of transmission and ongoing increase of cases globally. Rapid point-of-care (PoC) diagnostics to detect the causative virus, SARS-CoV-2, are urgently needed to identify and isolate patients, contain its spread and guide clinical management. In this work, we report the development of a rapid PoC diagnostic test (< 20 min) based on reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) and semiconductor technology for the detection of SARS-CoV-2 from extracted RNA samples. The developed LAMP assay was tested on a real-time benchtop instrument (RT-qLAMP) showing a lower limit of detection of 10 RNA copies per reaction. It was validated against 183 clinical samples including 127 positive samples (screened by the CDC RT-qPCR assay). Results showed 90.55% sensitivity and 100% specificity when compared to RT-qPCR and average positive detection times of 15.45 ± 4.43 min. For validating the incorporation of the RT-LAMP assay onto our PoC platform (RT-eLAMP), a subset of samples was tested (n=40), showing average detection times of 12.89 ± 2.59 min for positive samples (n=34), demonstrating a comparable performance to a benchtop commercial instrument. Paired with a smartphone for results visualization and geo-localization, this portable diagnostic platform with secure cloud connectivity will enable real-time case identification and epidemiological surveillance.</jats:p><jats:sec><jats:title>One Sentence Summary</jats:title><jats:p>We demonstrate isothermal detection of SARS-CoV-2 in under 20 minutes from extracted RNA samples with a handheld Lab-on-Chip platform.</jats:p></jats:sec>
Rodriguez Manzano J, Moser N, Malpartida Cardenas K, et al., 2020, Rapid detection of mobilized colistin resistance using a nucleic acid based lab-on-a-chip diagnostic system, Scientific Reports, Vol: 10, ISSN: 2045-2322
The increasing prevalence of antimicrobial resistance is a serious threat to global public health. One of the most concerning trends is the rapid spread of Carbapenemase-Producing Organisms (CPO), where colistin has become the last-resort antibiotic treatment. The emergence of colistin resistance, including the spread of mobilized colistin resistance (mcr) genes, raises the possibility of untreatable bacterial infections and motivates the development of improved diagnostics for the detection of colistin-resistant organisms. This work demonstrates a rapid response for detecting the most recently reported mcr gene, mcr−9, using a portable and affordable lab-on-a-chip (LoC) platform, offering a promising alternative to conventional laboratory-based instruments such as real-time PCR (qPCR). The platform combines semiconductor technology, for non-optical real-time DNA sensing, with a smartphone application for data acquisition, visualization and cloud connectivity. This technology is enabled by using loop-mediated isothermal amplification (LAMP) as the chemistry for targeted DNA detection, by virtue of its high sensitivity, specificity, yield, and manageable temperature requirements. Here, we have developed the first LAMP assay for mcr−9 - showing high sensitivity (down to 100 genomic copies/reaction) and high specificity (no cross-reactivity with other mcr variants). This assay is demonstrated through supporting a hospital investigation where we analyzed nucleic acids extracted from 128 carbapenemase-producing bacteria isolated from clinical and screening samples and found that 41 carried mcr−9 (validated using whole genome sequencing). Average positive detection times were 6.58 ± 0.42 min when performing the experiments on a conventional qPCR instrument (n = 41). For validating the translation of the LAMP assay onto a LoC platform, a subset of the samples were tested (n = 20), showing average detection times o
Kalofonou M, Malpartida-Cardenas K, Alexandrou G, et al., 2020, A novel hotspot specific isothermal amplification method for detection of thecommon PIK3CA p.H1047R breast cancer mutation, Scientific Reports, Vol: 10, ISSN: 2045-2322
Breast cancer (BC) is a common cancer in women worldwide. Despite advances in treatment, up to 30% of women eventually relapse and die of metastatic breast cancer. Liquid biopsy analysis of circulating cell-free DNA fragments in the patients’ blood can monitor clonality and evolving mutations as a surrogate for tumour biopsy. Next generation sequencing platforms and digital droplet PCR can be used to profile circulating tumour DNA from liquid biopsies; however, they are expensive and time consuming for clinical use. Here, we report a novel strategy with proof-of-concept data that supports the usage of loop-mediated isothermal amplification (LAMP) to detect PIK3CA c.3140 A > G (H1047R), a prevalent BC missense mutation that is attributed to BC tumour growth. Allele-specific primers were designed and optimized to detect the p.H1047R variant following the USS-sbLAMP method. The assay was developed with synthetic DNA templates and validated with DNA from two breast cancer cell-lines and two patient tumour tissue samples through a qPCR instrument and finally piloted on an ISFET enabled microchip. This work sets a foundation for BC mutational profiling on a Lab-on-Chip device, to help the early detection of patient relapse and to monitor efficacy of systemic therapies for personalised cancer patient management.
Cacho-Soblechero M, Malpartida-Cardenas K, Cicatiello C, et al., 2020, A dual-sensing thermo-chemical ISFET array for DNA-based diagnostics., IEEE Transactions on Biomedical Circuits and Systems, Vol: 14, Pages: 477-489, ISSN: 1932-4545
This paper presents a 32x32 ISFET array with in-pixel dual-sensing and programmability targeted for on-chip DNA amplification detection. The pixel architecture provides thermal and chemical sensing by encoding temperature and ion activity in a single output PWM, modulating its frequency and its duty cycle respectively. Each pixel is composed of an ISFET-based differential linear OTA and a 2-stage sawtooth oscillator. The operating point and characteristic response of the pixel can be programmed, enabling trapped charge compensation and enhancing the versatility and adaptability of the architecture. Fabricated in 0.18 μm standard CMOS process, the system demonstrates a quadratic thermal response and a highly linear pH sensitivity, with a trapped charge compensation scheme able to calibrate 99.5% of the pixels in the target range, achieving a homogeneous response across the array. Furthermore, the sensing scheme is robust against process variations and can operate under various supply conditions. Finally, the architecture suitability for on-chip DNA amplification detection is proven by performing Loop-mediated Isothermal Amplification (LAMP) of phage lambda DNA, obtaining a time-to-positive of 7.71 minutes with results comparable to commercial qPCR instruments. This architecture represents the first in-pixel dual thermo-chemical sensing in ISFET arrays for Lab-on-a-Chip diagnostics.
Witters D, Jue E, Schoepp NG, et al., 2020, Autonomous and portable device for rapid sample-to-answer molecular diagnostics at the point-of-care, Pages: 1219-1220
In this work, we demonstrate a novel prototype of an autonomous, equipment-free, and handheld device that integrates sample preparation, on-board storage of liquid and dry reagents, nucleic acid amplification, and cellphone based detection in point-of-care (POC) and limited resource settings (LRS). We demonstrate sample preparation from urine samples within 4 min and minimal hands-on time (<1 min), as well as amplification of target nucleic acids within 15 min on-device. The proposed prototype was validated for the detection of Neisseria gonorrhoeae in urine samples within 20 min.
Alexandrou G, Rodriguez-Manzano J, Malpartida-Cardenas K, et al., 2020, In-silico automated allele-specific primer design for loop-mediated isothermal amplification, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, ISSN: 0271-4302
Keeble L, Moser N, Rodriguez-Manzano J, et al., 2020, A Combined ISFET-Electric Field Actuation System for Enhanced Detection of DNA: A Proof-of-Concept, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, ISSN: 0271-4302
Georgiou P, Moniri A, Rodriguez Manzano J, 2019, A method for analysis of real-time amplification data, WO2019234247A1
This disclosure relates to methods, systems, computer programs and computer- readable media for the multidimensional analysis of real-time amplification data. A framework is presented that shows that the benefits of standard curves extend beyond absolute quantification when observed in a multidimensional environment. Relating to the field of Machine Learning, the disclosed method combines multiple extracted features (e.g. linear features) in order to analyse real-time amplification data using a multidimensional view. The method involves two new concepts: the multidimensional standard curve and its 'home', the feature space. Together they expand the capabilities of standard curves, allowing for simultaneous absolute quantification, outlier detection and providing insights into amplification kinetics. The new methodology thus enables enhanced quantification of nucleic acids, single-channel multiplexing, outlier detection, characteristic patterns in the multidimensional space related to amplification kinetics and increased robustness for sample identification and quantification.
Georgiou P, Yu L-S, Malpartida-Cardenas K, et al., 2019, Method for detecting a tandem repeat, WO2019234252A1
The present application relates to methods for detecting a tandem repeat in a nucleic acid sequence under isothermal conditions using primers.
Georgiou P, Malpartida Cardenas K, Yu L-S, et al., 2019, Method for detecting a single nucleotide polymorphism (snp) using lamp and blocking primers, WO2019234251A1
The present application relates to methods for detecting a first allele of a single nucleotide polymorphism (SNP) in a nucleic acid sequence under isothermal conditions using primers specific for said first allele, in particular using Loop mediated isothermal amplification (LAMP), wherein the amplification of a second allele is prevented by using blocking primers.
Georgiou P, Moniri A, Moser N, et al., 2019, Devices and method for detecting an amplification event, WO2019234451A1
A method is disclosed herein for detecting an amplification reaction in a solution containing a biological sample using an array of ion sensors. The amplification reaction is indicative of the presence of a nucleic acid. The method comprises monitoring a signal from each respective sensor of the array of ion sensors, detecting a change in the signal from a first sensor of the array of ion sensors, and comparing the signal from the first sensor with the signal of at least one neighbouring sensor, the at least one neighbouring sensor being proximate to the first sensor in the array. The method further comprises determining, based on the comparing, that an amplification event has occurred in the solution in the vicinity of the first sensor.
Terracina D, Moniri A, Rodriguez-Manzano J, et al., 2019, Real-time forecasting and classification of trunk muscle fatigue using surface electromyography, IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, Pages: 1-4, ISSN: 2163-4025
Low Back Pain (LBP) affects the vast majority of the population at some point in their lives. People with LBP show altered trunk muscle activity and enhanced fatigability of trunk muscles is associated with the development and future risk of LBP. Therefore, a system that can forecast trunk muscle activity and detect fatigue can help subjects, practitioners and physiotherapists in the diagnosis, monitoring and recovery of LBP. In this paper, we present a novel approach in order to determine whether subjects are fatigued, or transitioning to fatigue, 25 seconds ahead of time using surface Electromyography (sEMG) from 14 trunk muscles. This is achieved using a three-step approach: A) extracting features related to fatigue from sEMG, B) forecasting the features using a real-time adaptive filter and C) performing dimensionality reduction (from 70 to 2 features) and then classifying subjects using a supervised machine learning algorithm. The forecasting classification accuracy across 13 patients is 99.1% ± 0.004 and the area under the micro and macro ROC curve is 0.935 ± 0.036 and 0.940 ±0.034 as determined by 10-fold cross validation. The proposed approach enables a computationally efficient solution which could be implemented in a wearable device for preventing muscle injury.
Malpartida-Cardenas K, Miscourides N, Rodriguez-Manzano J, et al., 2019, Quantitative and rapid Plasmodium falciparum malaria diagnosis and artemisinin-resistance detection using a CMOS Lab-on-Chip platform, Biosensors and Bioelectronics, Vol: 145, ISSN: 0956-5663
Early and accurate diagnosis of malaria and drug-resistance is essential to effective disease management. Available rapid malaria diagnostic tests present limitations in analytical sensitivity, drug-resistance testing and/or quantification. Conversely, diagnostic methods based on nucleic acid amplification stepped forwards owing to their high sensitivity, specificity and robustness. Nevertheless, these methods commonly rely on optical measurements and complex instrumentation which limit their applicability in resource-poor, point-of-care settings. This paper reports the specific, quantitative and fully-electronic detection of Plasmodium falciparum, the predominant malaria-causing parasite worldwide, using a Lab-on-Chip platform developed in-house. Furthermore, we demonstrate on-chip detection of C580Y, the most prevalent single-nucleotide polymorphism associated to artemisinin-resistant malaria. Real-time non-optical DNA sensing is facilitated using Ion-Sensitive Field-Effect Transistors, fabricated in unmodified complementary metal-oxide-semiconductor (CMOS) technology, coupled with loop-mediated isothermal amplification. This work holds significant potential for the development of a fully portable and quantitative malaria diagnostic that can be used as a rapid point-of-care test.
Toumazou C, Baig Mirza K, Rodriguez Manzano J, 2019, Molecule detection using aptamer nucleic acid duplex, WO2019138255A1
The present invention relates to the detection of molecules of a target type in a sample. A method of detecting molecules of a target type in a sample comprises providing an aptamer-nucleic acid duplex, contacting the sample with the aptamer-nucleic acid duplex, wherein the aptamer is capable of selectively dissociating from the nucleic acid to selectively bind to a molecule of the target type in the sample, amplifying any dissociated nucleic acid and detecting any amplified nucleic acid. The method further comprises using the detected result to indicate the presence of molecules of the target type and/or quantify an amount of molecules of the target type. Also provided is a system for detecting molecules of a target type in a sample.
Malpartida-Cardenas K, Miscourides N, Rodriguez-Manzano J, et al., 2019, Quantitative and rapid <i>Plasmodium falciparum</i> malaria diagnosis and artemisinin-resistance detection using a CMOS Lab-on-Chip platform
<jats:title>Abstract</jats:title><jats:p>Early and accurate diagnosis of malaria and drug-resistance is essential to effective disease management. Available rapid malaria diagnostic tests present limitations in analytical sensitivity, drug-resistant testing and/or quantification. Conversely, diagnostic methods based on nucleic acid amplification stepped forwards owing to their high sensitivity, specificity and robustness. Nevertheless, these methods commonly rely on optical measurements and complex instrumentation which limit their applicability in resource-poor, point-of-care settings. This paper reports the specific, quantitative and fully-electronic detection of <jats:italic>Plas-modium falciparum</jats:italic>, the predominant malaria-causing parasite worldwide, using a Lab-on-Chip platform developed in-house. Furthermore, we demonstrate on-chip detection of C580Y, the most prevalent single-nucleotide polymorphism associated to artemisinin-resistant malaria. Real-time non-optical DNA sensing is facilitated using Ion-Sensitive Field-Effect Transistors, fabricated in unmodified complementary metal-oxide-semiconductor technology, coupled with loop-mediated isothermal amplification. This work holds significant potential for the development of a fully portable and quantitative malaria diagnostic that can be used as a rapid point-of-care test.</jats:p>
Moniri A, Rodriguez-Manzano J, Malpartida-Cardenas K, et al., 2019, Framework for DNA quantification and outlier detection using multidimensional standard curves, Analytical Chemistry, Vol: 91, Pages: 7426-7434, ISSN: 0003-2700
Real-time PCR is a highly sensitive and powerful technology for the quantification of DNA and has become the method of choice in microbiology, bioengineering, and molecular biology. Currently, the analysis of real-time PCR data is hampered by only considering a single feature of the amplification profile to generate a standard curve. The current “gold standard” is the cycle-threshold (Ct) method which is known to provide poor quantification under inconsistent reaction efficiencies. Multiple single-feature methods have been developed to overcome the limitations of the Ct method; however, there is an unexplored area of combining multiple features in order to benefit from their joint information. Here, we propose a novel framework that combines existing standard curve methods into a multidimensional standard curve. This is achieved by considering multiple features together such that each amplification curve is viewed as a point in a multidimensional space. Contrary to only considering a single-feature, in the multidimensional space, data points do not fall exactly on the standard curve, which enables a similarity measure between amplification curves based on distances between data points. We show that this framework expands the capabilities of standard curves in order to optimize quantification performance, provide a measure of how suitable an amplification curve is for a standard, and thus automatically detect outliers and increase the reliability of quantification. Our aim is to provide an affordable solution to enhance existing diagnostic settings through maximizing the amount of information extracted from conventional instruments.
Ming D, Rawson T, Sangkaew S, et al., 2019, Connectivity of rapid-testing diagnostics and surveillance of infectious diseases, Bulletin of the World Health Organization, Vol: 97, Pages: 242-244, ISSN: 0042-9686
The World Health Organization (WHO) developed the ASSURED criteria to describe the ideal characteristics for point-of-care testing in low-resource settings: affordable, sensitive, specific, user-friendly, rapid and robust, equipment-free and deliverable.1 These standards describe. Over the last decade, widespread adoption of point-of-care testing has led to significant changes in clinical decision-making processes. The development of compact molecular diagnostics, such as the GeneXpert® platform, have enabled short turnaround times and allowed profiling of antimicrobial resistance. Although modern assays have increased operational requirements, many devices are robust and can be operated within communities with minimal training. These new generation of rapid tests have bypassed barriers to care and enabled treatment to take place independently from central facilities. Here we describe the importance of connectivity, the automatic capture and sharing of patient healthcare data from testing, in the adoption and roll-out of rapid testing.
Yu L-S, Rodriguez-Manzano J, Malpartida-Cardenas K, et al., 2019, Rapid and sensitive detection of azole-resistant Aspergillus fumigatus by tandem-repeat loop-mediated isothermal amplification, Journal of Molecular Diagnostics, Vol: 21, Pages: 286-295, ISSN: 1525-1578
Invasive human fungal infections caused by multi-azole resistant Aspergillus fumigatus are associated with increasing rates of mortality in susceptible patients. Current methods of diagnosing infections caused by multi-azole resistant A. fumigatus are, however, not well suited for use in clinical point-of-care testing or in the field. Loop-mediated isothermal amplification (LAMP) is a widely used method of nucleic acid amplification with rapid and easy-to-use features, making it suitable for use in different resource settings. Here, we developed a LAMP assay to detect a 34 bp tandem repeat, named TR34-LAMP. TR34 is a high-prevalence allele that, in conjunction with the L98H single nucleotide polymorphism, is associated with the occurrence of multi-azole resistance in A. fumigatus in the environment and in patients. This process was validated with both synthetic double stranded DNA and genomic DNA prepared from azole-resistant isolates of A. fumigatus. Use of our assay resulted in rapid and specific identification of the TR34 allele with high sensitivity, detecting down to 10 genomic copies per reaction within 25 minutes. Fluorescent and colorimetric detections were used for the analysis of 11 clinical isolates as cross validation. These results show that the TR34-LAMP assay has the potential to accelerate the screening of clinical and environmental A. fumigatus to provide a rapid and accurate diagnosis of azole resistance, which current methods struggle to achieve.
Ming D, Rawson T, Sangkaew S, et al., 2019, Connectivity of rapid-testing diagnostics and surveillance of infectious diseases (vol 97, pg 244, 2019), BULLETIN OF THE WORLD HEALTH ORGANIZATION, Vol: 97, ISSN: 0042-9686
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