Global Health Applications Research Articles

Sample-to-answer detection of miRNA from whole blood using thermally responsive alkane partitions.

Circulating miRNA offers a tremendous opportunity as a biomarker paradigm for many applications in disease diagnostics, including point-of-care diagnostics for global health needs. However, despite the numerous miRNA detection schemes reported, there still does not exist a solution for highly sensitive sample-to-answer detection of miRNA directly from complex samples, such as whole blood. We recently developed thermally responsive alkane partitions (TRAPs), which - when combined with magnetic microbeads - enable the complete assay automation from whole blood. Here we apply TRAPs with ligation-LAMP to automate the detection of miRNA in whole blood samples. MBs and a TRAP enable the automated purification of miRNA from blood, while a novel displacement-ligation method is utilized to trigger the ligation-LAMP reaction, which is streamlined into one step by a second TRAP. Using easily manufacturable TRAP-enabled assay cassettes and a custom low-cost handheld instrument, we report the specific detection of miR-155 at concentrations as low as 15fM in whole blood with no intermediate steps by the user. This new approach creates the opportunity for point-of-care miRNA-based diagnostics with global health applications.

Multi-mode photoluminescence inks based on lanthanide-doped multilevel core-shell microspheres for advanced anti-counterfeiting applications

Development of advanced luminescent nanomaterials and technologies is of great significance for anticounterfeiting applications in global economy, security, and human health. In this work, we have designed two types of anti-counterfeit materials. (1) The dual excitation mode core–shell microsphere is based on SiO2 core, with the GdVO4:Yb,Er upconversion luminescent inner layer, SiO2 shell separator, and Gd2O3:Eu@SiO2 downconversion luminescent layer are sequentially deposited on it via co-precipitation method. The microspheres have a five-layer core–shell structure with an overall diameter of ∼ 146 nm and enables the spatial separation of Er3+ and Eu3+, which prevents the cross-relaxation of Er3+. The microspheres were prepared into an upconversion/downconversion excitation mode luminescent ink, with inkjet-printed patterns that only extract information when excited by 254 nm and 980 nm excitation. (2) The core–shell-shell SiO2@AIPA-S-Si-Tb@SiO2 microspheres have been synthesized by using organic ligands ((HOOC)2C6H3NHCONH(CH2)3Si(OCH2CH3)3) (defined as AIPA-S-Si) connected with Tb3+ ions and silica through covalent bond. The microspheres have a sandwich structure with an overall diameter of ∼ 100 nm and show bright green light. The sandwich structure and five-layer core–shell structure was mixed proportionally to obtain orange-red, white, and yellow emission ink under 254 nm, green emission under 310 nm, and green emission under 980 nm excitation.

A handheld luminometer with sub-attomole limit of detection for distributed applications in global health.

Luminescence is ubiquitous in biology research and medicine. Conceptually simple, the detection of luminescence nonetheless faces technical challenges because relevant signals can exhibit exceptionally low radiant power densities. Although low light detection is well-established in centralized laboratory settings, the cost, size, and environmental requirements of high-performance benchtop luminometers are not compatible with geographically-distributed global health studies or resource-constrained settings. Here we present the design and application of a ~$700 US handheld, battery-powered luminometer with performance on par with high-end benchtop instruments. By pairing robust and inexpensive Silicon Photomultiplier (SiPM) sensors with a low-profile shutter system, our design compensates for sensor non-idealities and thermal drift, achieving a limit of detection of 1.6E-19 moles of firefly luciferase. Using these devices, we performed two pilot cross-sectional serology studies to assess sars-cov-2 antibody levels: a cohort in the United States, as well as a field study in Bangladesh. Results from both studies were consistent with previous work and demonstrate the device's suitability for distributed applications in global health.

Characterizing the use of contextual factors in engineering design: an exploration of global health designer practice

Abstract Incorporating contextual factors into engineering design processes is recommended to develop solutions that function appropriately in their intended use contexts. In global health settings, failing to tailor solutions to their broader context has led to many product failures. Since prior work has thus far not investigated the use of contextual factors in global health design practice, we conducted semi-structured interviews with 15 experienced global health design practitioners. Our analysis identified 351 instances of participants incorporating contextual factors in their previous design experiences, which we categorized into a taxonomy of contextual factors, including 9 primary and 32 secondary classifications. We summarized and synthesized key patterns within all the identified contextual factor categories. Next, this study presents a descriptive model for incorporating contextual factors developed from our findings, which identifies that participants actively sought contextual information and made conscious decisions to adjust their solutions, target markets and implementation plans to accommodate contextual factors iteratively throughout their design processes. Our findings highlight how participants sometimes conducted formal evaluations while other times they relied on their own experience, the experience of a team member or other stakeholder engagement strategies. The research findings can ultimately inform design practice and engineering pedagogy for global health applications.

Formulation and Scale-Up of Fast-Dissolving Lumefantrine Nanoparticles for Oral Malaria Therapy

Lumefantrine (LMN) is one of the first-line drugs in the treatment of malaria due to its long circulation half-life, which results in enhanced effectiveness against drug-resistant strains of malaria. However, LMN's therapeutic efficacy is diminished due to its low bioavailability when dosed as a crystalline solid. The goal of this work was to produce low-cost, highly bioavailable, stable LMN powders for oral delivery that would be suitable for global health applications. We report the development of a LMN nanoparticle formulation and the translation of that formulation from laboratory to industrial scale. We applied Flash NanoPrecipitation (FNP) to develop nanoparticles with 90% LMN loading and sizes of 200-260 nm. The integrated process involves nanoparticle formation, concentration by tangential flow ultrafiltration, and then spray drying to obtain a dry powder. The final powders are readily redispersible and stable over accelerated aging conditions (50°C, 75% RH, open vial) for at least 4 weeks and give equivalent and fast drug release kinetics in both simulated fed and fasted state intestinal fluids, making them suitable for pediatric administration. The nanoparticle-based formulations increase the bioavailability of LMN 4.8-fold in vivo when compared to the control crystalline LMN. We describe the translation of the laboratory-scale process at Princeton University to the clinical manufacturing scale at WuXi AppTec.

Moving beyond narrow definitions of gene drive: Diverse perspectives and frames enable substantive dialogue among science and humanities teachers in the United States and United Kingdom.

Gene drive is an emerging biotechnology with applications in global health, conservation and agriculture. Scientists are preparing for field trials, triggering debate about when and how to release gene-drive organisms. These decisions depend on public understandings of gene drive, which are shaped by language. While some studies on gene drive communication assume the need to persuade publics of expert definitions of gene drive, we highlight the importance of meaning-making in communication and engagement. We conducted focus groups with humanities and science teachers in the United Kingdom and United States to explore how different media framings stimulated discussions of gene drive. We found diversity in the value of these framings for public debate. Interestingly, the definition favoured by gene drive scientists was the least popular among participants. Rather than carefully curating language, we need opportunities for publics to make sense and negotiate the meanings of a technology on their own terms.

Chatbot for Health Care and Oncology Applications Using Artificial Intelligence and Machine Learning: Systematic Review.

BackgroundChatbot is a timely topic applied in various fields, including medicine and health care, for human-like knowledge transfer and communication. Machine learning, a subset of artificial intelligence, has been proven particularly applicable in health care, with the ability for complex dialog management and conversational flexibility.ObjectiveThis review article aims to report on the recent advances and current trends in chatbot technology in medicine. A brief historical overview, along with the developmental progress and design characteristics, is first introduced. The focus will be on cancer therapy, with in-depth discussions and examples of diagnosis, treatment, monitoring, patient support, workflow efficiency, and health promotion. In addition, this paper will explore the limitations and areas of concern, highlighting ethical, moral, security, technical, and regulatory standards and evaluation issues to explain the hesitancy in implementation.MethodsA search of the literature published in the past 20 years was conducted using the IEEE Xplore, PubMed, Web of Science, Scopus, and OVID databases. The screening of chatbots was guided by the open-access Botlist directory for health care components and further divided according to the following criteria: diagnosis, treatment, monitoring, support, workflow, and health promotion.ResultsEven after addressing these issues and establishing the safety or efficacy of chatbots, human elements in health care will not be replaceable. Therefore, chatbots have the potential to be integrated into clinical practice by working alongside health practitioners to reduce costs, refine workflow efficiencies, and improve patient outcomes. Other applications in pandemic support, global health, and education are yet to be fully explored.ConclusionsFurther research and interdisciplinary collaboration could advance this technology to dramatically improve the quality of care for patients, rebalance the workload for clinicians, and revolutionize the practice of medicine.

Train-the-Trainer as an Effective Approach to Building Global Networks of Experts in Genomic Surveillance of Antimicrobial Resistance (AMR).

Advanced genomics and sequencing technologies are increasingly becoming critical for global health applications such as pathogen and antimicrobial resistance (AMR) surveillance. Limited resources challenge capacity development in low- and middle-income countries (LMICs), with few countries having genomics facilities and adequately trained staff. Training research and public health experts who are directly involved in the establishment of such facilities offers an effective, but limited, solution to a growing need. Instead, training them to impart their knowledge and skills to others provides a sustainable model for scaling up the much needed capacity and capability for genomic sequencing and analysis locally with global impact. We designed and developed a Train-the-Trainer course integrating pedagogical aspects with genomic and bioinformatics activities. The course was delivered to 18 participants from 12 countries in Africa, Asia, and Latin America. A combination of teaching strategies culminating in a group project created a foundation for continued development at home institutions. Upon follow-up after 6 months, at least 40% of trainees had initiated training programs and collaborations to build capacity at local, national, and regional level. This work provides a framework for implementing a training and capacity building program for the application of genomics tools and resources in AMR surveillance.

A Review of Artificial Intelligence, Big Data, and Blockchain Technology Applications in Medicine and Global Health

Artificial intelligence (AI) programs are applied to methods such as diagnostic procedures, treatment protocol development, patient monitoring, drug development, personalized medicine in healthcare, and outbreak predictions in global health, as in the case of the current COVID-19 pandemic. Machine learning (ML) is a field of AI that allows computers to learn and improve without being explicitly programmed. ML algorithms can also analyze large amounts of data called Big data through electronic health records for disease prevention and diagnosis. Wearable medical devices are used to continuously monitor an individual’s health status and store it in cloud computing. In the context of a newly published study, the potential benefits of sophisticated data analytics and machine learning are discussed in this review. We have conducted a literature search in all the popular databases such as Web of Science, Scopus, MEDLINE/PubMed and Google Scholar search engines. This paper describes the utilization of concepts underlying ML, big data, blockchain technology and their importance in medicine, healthcare, public health surveillance, case estimations in COVID-19 pandemic and other epidemics. The review also goes through the possible consequences and difficulties for medical practitioners and health technologists in designing futuristic models to improve the quality and well-being of human lives.

The preparation of antibacterial eco-friendly bio-based PTT-based β-cyclodextrin by complexation of copper and zinc ions

There has been an increasing focus on antibacterial textiles owing to their widespread applications in global public health. In this study, we prepared antibacterial bio-based poly (trimethylene terephthalate) (PTT) by multi-crosslinking with citric acid among PTT and β-cyclodextrin (β-CD), and then adsorbing zinc and copper ions. The results show that β-cyclodextrin was successfully grafted onto the surface of PTT. The adsorption amounts of Zn2+ and Cu2+ on β-CD/PTT were investigated by ICP and FE-SEM, which showed that Zn2+ and Cu2+ penetrated the fabric surface. Moreover, under optimal adsorption conditions, the adsorption capacity of Zn2+ and Cu2+ are about 34 mg/g and 50 mg/g, respectively. During antibacterial test, the bactericidal rates of β-CD/Cu2+/PTT reached 90.75% for E. coli and 85.36% for S. aureus, and the bactericidal rates of β-CD/Zn2+/PTT are 80.48% for E. coli and 73.10% for S. aureus. Functionalized PTT fabrics with eco-environmental and sustainable performance may have promising application in the field of antibacterial fabrics.

Recent Advances in Aptamer-Based Biosensors for Global Health Applications

Since aptamers were first reported in the early 2000s, research on their use for the detection of health-relevant analytical targets has exploded. This review article provides a brief overview of the most recent developments in the field of aptamer-based biosensors for global health applications. The review provides a description of general aptasensing principles and follows up with examples of recent reports of diagnostics-related applications. These applications include detection of proteins and small molecules, circulating cancer cells, whole-cell pathogens, extracellular vesicles, and tissue diagnostics. The review also discusses the main challenges that this growing technology faces in the quest of bringing these new devices from the laboratory to the market.

3D printed spectrophotometer for drug monitoring in tuberculosis patients for global health applications

3D printed spectrophotometer for drug monitoring in tuberculosis patients for global health applications

AL-PHA beads: Bioplastic-based protease biosensors for global health applications

Proteases are multi-functional proteolytic enzymes that have complex roles in human health and disease. Therefore, the development of protease biosensors can be beneficial to global health applications. To this end, we developed Advanced proteoLytic detector PolyHydroxyAlkanoates (AL-PHA) beads – a library of over 20 low-cost, biodegradable, bioplastic-based protease biosensors. Broadly, these biosensors utilise PhaC-reporter fusion proteins that are bound to microbially manufactured polyhydroxyalkanoate beads. In the presence of a specific protease, superfolder green fluorescent reporter proteins are cleaved from the AL-PHA beads – resulting in a loss of bead fluorescence. The Tobacco Etch Virus (TEV) AL-PHA biosensor detected the proteolytic activity of at least 1.85 pM of AcTEV. AL-PHA beads were also engineered to detect cercarial elastase from Schistosoma mansoni-derived cercarial transformation fluid (SmCTF) samples, as well as cancer-associated metalloproteinases in extracellular vesicle and cell-conditioned media samples. We envision that AL-PHA beads could be further developed for use in resource-limited settings.

Real-time spatial health surveillance: Mapping the UK COVID-19 epidemic

Introduction The COVID-19 pandemic has highlighted the need for robust data linkage systems and methods for identifying outbreaks of disease in near real-time. Objectives The primary objective of this study was to develop a real-time geospatial surveillance system to monitor the spread of COVID-19 across the UK. Methods Using self-reported app data and the Secure Anonymised Information Linkage (SAIL) Databank, we demonstrate the use of sophisticated spatial modelling for near-real-time prediction of COVID-19 prevalence at small-area resolution to inform strategic government policy areas. Results We demonstrate that using a combination of crowd-sourced app data and sophisticated geo-statistical techniques it is possible to predict hot spots of COVID-19 at fine geographic scales, nationally. We are also able to produce estimates of their precision, which is an important pre-requisite to an effective control strategy to guard against over-reaction to potentially spurious features of ’best guess’ predictions. Conclusion In the UK, important emerging risk-factors such as social deprivation or ethnicity vary over small distances, hence risk needs to be modelled at fine spatial resolution to avoid aggregation bias. We demonstrate that existing geospatial statistical methods originally developed for global health applications are well-suited to this task and can be used in an anonymised databank environment, thus preserving the privacy of the individuals who contribute their data.

Human-centered design for medical devices and diagnostics in global health

So much lifesaving medical technology exists in the world, yet so little of it benefits communities with low resources. Purchase price is only one barrier. The World Health Organization found nearly three quarters of devices provided by industrialized countries are not used when they reach low resource communities. Most medical devices and diagnostics fail to operate effectively in environments with power fluctuations, high temperatures, high humidity, dust, insect infiltration, poor availability of spare parts, high-cost consumables, and low staff-to-patient ratio. To provide robust, well-designed products for low-resource environments, devices need to be developed to address the needs of the local clinics, hospitals, and communities. Human-Centered Design (HCD) is a set of tools, processes, and mindsets that can help a team uncover the essential needs of diverse stakeholders involved in the success of medical technology for global health. This paper provides an overview of the HCD techniques we have found most useful in developing medical technology for global health applications. To illustrate the HCD techniques and their benefits, we present a case study of Design that Matters’ Firefly phototherapy. The device is now treating newborn jaundice in low-resource hospitals in over 20 low and middle-income countries.

Combinatorial Immunophenotyping of Cell Populations with an Electronic Antibody Microarray.

Immunophenotyping is widely used to characterize cell populations in basic research and to diagnose diseases from surface biomarkers in the clinic. This process usually requires complex instruments such as flow cytometers or fluorescence microscopes, which are typically housed in centralized laboratories. Microfluidics are combined with an integrated electrical sensor network to create an antibody microarray for label-free cell immunophenotyping against multiple antigens. The device works by fractionating the sample via capturing target subpopulations in an array of microfluidic chambers functionalized against different antigens and by electrically quantifying the cell capture statistics through a network of code-multiplexed electrical sensors. Through a combinatorial arrangement of antibody sequences along different microfluidic paths, the device can measure the prevalence of different cell subpopulations in a sample from computational analysis of the electrical output signal. The device performance is characterized by analyzing heterogeneous samples of mixed tumor cell populations and then the technique is applied to determine leukocyte subpopulations in blood samples and the results are validated against complete blood cell count and flow cytometry results. Label-free immunophenotyping of cell populations against multiple targets on a disposable electronic chip presents opportunities in global health and telemedicine applications for cell-based diagnostics and health monitoring.

Donald A. B. Lindberg (1933-2019).

Visionary medical informaticist who laid the groundwork for PubMed

Глобальная визуальная трансформация информационных систем здравоохранения на примере британского госпиталя женского здоровья

Objective. This essay describes the development of a wholly new form of timeline structured iconographic interface for the electronic patient record (EPR). This provides a fast and highly efficient means through which to view complex medical records from multiple data sources, with global health applications. Methods. Using a simple concept as the design framework, we have worked from first principles of agile and iterative software development to upcycle large quantities of electronic clinical data into a visually intuitive and efficient EPR format, with a wide range of practical clinical applications. The system was built within the existing Clinical Data Estate (CDE) and IT systems of a UK NHS University Hospital, by a small volunteer team at negligible cost. Results. Over ten years, we have developed the system from initial concept to a live EPR interface at the centre of our CDE for some 5,000 authorised users, to display some 2.5 million individual patient e-records in real time. We have also built a derivative exemplar data system for the “whole of life” study of chronic diseases of childhood and adulthood, using a dynamic data set of 18,000 locally treated breast cancer cases within our Women’s Health service. Conclusions. Agile software development puts the true user of information at the centre of digital design. When combined with the key principles of e-data visualisation, it can produce transformative clinical systems. The early sharing of insights and solutions will help accelerate beneficial change in our understanding of individual and population health.

Synthetic molecular recognition nanosensor paint for microalbuminuria

Microalbuminuria is an important clinical marker of several cardiovascular, metabolic, and other diseases such as diabetes, hypertension, atherosclerosis, and cancer. The accurate detection of microalbuminuria relies on albumin quantification in the urine, usually via an immunoturbidity assay; however, like many antibody-based assessments, this method may not be robust enough to function in global health applications, point-of-care assays, or wearable devices. Here, we develop an antibody-free approach using synthetic molecular recognition by constructing a polymer to mimic fatty acid binding to the albumin, informed by the albumin crystal structure. A single-walled carbon nanotube, encapsulated by the polymer, as the transduction element produces a hypsochromic (blue) shift in photoluminescence upon the binding of albumin in clinical urine samples. This complex, incorporated into an acrylic material, results in a nanosensor paint that enables the detection of microalbuminuria in patient samples and comprises a rapid point-of-care sensor robust enough to be deployed in resource-limited settings.

Protein Biomarker Detection with Carbon Nanotube-Based Sensors

Proteins are widely used biomarkers in disease diagnosis. A vast majority of clinical methods for the detection of the marker proteins use antibodies. Such methods are sub-optimal to function in global health applications and point-of-care assays. We are developing single-walled carbon nanotube-based optical sensors for straight-forward, rapid and sensitive measurement of proteins for accurate disease diagnosis. Single-walled carbon nanotubes, with intrinsic photoluminescence and high optical sensitivity towards molecular interactions, upon the surface modification with polymeric materials provide unmatched basis for the development of optical sensors.