Sweat as a Source of Next-Generation Digital Biomarkers

Recent advancements in non-invasive wearable electrochemical biosensors for biomarker analysis - A review

A biomarker is a molecular indicator that can be used to identify the presence or severity of a disease. It may be produced due to biochemical or molecular changes in normal biological processes. In some cases, the presence of a biomarker itself is an indication of the disease, while in other cases, the elevated or depleted level of a particular protein or chemical substance aids in identifying a disease. Biomarkers indicate the progression of the disease in response to therapeutic interventions. Identifying these biomarkers can assist in diagnosing the disease early and providing proper therapeutic treatment. In recent years, wearable electrochemical (EC) biosensors have emerged as an important tool for early detection due to their excellent selectivity, low cost, ease of fabrication, and improved sensitivity. There are several challenges in developing a fully integrated wearable sensor, such as device miniaturization, high power consumption, incorporation of a power source, and maintaining the integrity and durability of the biomarker for long-term continuous monitoring. This review covers the recent advancements in the fabrication techniques involved in device development, the types of sensing platforms utilized, different materials used, challenges, and future developments in the field of wearable biosensors.

Sweat as a source of non-invasive biomarkers for clinical diagnosis: An overview

Sweat has excellent potential as one of the sources of non-invasive biomarkers for clinical diagnosis. It is relatively easy to collect and process and may contain different disease-specific markers and drug metabolites, making it ideal for various clinical applications. This article discusses the anatomy of sweat glands and their role in sweat production, as well as the history and development of multiple sweat sample collection and analysis techniques. Another primary focus of this article is the application of sweat detection in clinical disease diagnosis and other life scenarios. Finally, the limitations and prospects of sweat analysis are discussed.

A review of non-invasive samples and tools in kala-azar diagnosis and test of cure

The recurrence of visceral leishmaniasis (VL), also called kala-azar (KA), in endemic regions of tropical countries like India, is primarily attributed to asymptomatic VL, post-kala azar dermal leishmaniasis (PKDL), and human immunodeficiency virus (HIV) co-infection. To effectively manage VL cases and elimination targets, an early and rapid diagnosis as well as accurate field surveillance is highly essential. The traditional sampling methods like bone marrow (BM), spleen, and lymph node (LN) tissue aspirations are invasive, painful, tedious, and prone to nosocomial infections, require skilled persons and hospital facilities, and are not feasible in rural areas. Therefore, there is an urgent requirement for the adoption of a patient-friendly, non-invasive, non-hospitalized sampling procedure that ensures an effective VL diagnosis. This review aims to meticulously evaluate the most recent scientific research that focuses on the precision, feasibility, and applicability of non-invasive sampling (NIS) and techniques for the diagnosis and test of cure of VL, particularly in resource-limited settings. Apart from that, the non-invasive techniques (NIT) that have shown promising results while monitoring VL treatment response and relapse are also reviewed. The limitations associated with NIT and possible improvements in this regard are discussed as well to improve the diagnosis and management of VL.

Sweat induction using Pilocarpine microneedle patches for sweat testing in healthy adults

BACKGROUND

The sweat test using pilocarpine iontophoresis remains the gold standard for diagnosing cystic fibrosis, but access and reliability are limited by specialized equipment and insufficient sweat volume collected from infants and young children. These shortcomings lead to delayed diagnosis, limited point-of-care applications, and inadequate monitoring capabilities.

METHODS

We created a skin patch with dissolvable microneedles (MNs) containing pilocarpine that eliminates the equipment and complexity of iontophoresis. Upon pressing the patch to skin, the MNs dissolve in skin to release pilocarpine for sweat induction. We conducted a non-randomized pilot trial among healthy adults (clinicaltrials.gov, NCT04732195) with pilocarpine and placebo MN patches on one forearm and iontophoresis on the other forearm, followed by sweat collection using Macroduct collectors. Sweat output and sweat chloride concentration were measured. Subjects were monitored for discomfort and skin erythema.

RESULTS

Fifty paired sweat tests were conducted in 16 male and 34 female healthy adults. MN patches delivered similar amounts of pilocarpine into skin (1.1 ± 0.4 mg) and induced equivalent sweat output (41.2 ± 25.0 mg) compared to iontophoresis (1.2 ± 0.7 mg and 43.8 ± 32.3 mg respectively). Subjects tolerated the procedure well, with little or no pain, and only mild transient erythema. Sweat chloride concentration measurements in sweat induced by MN patches (31.2 ± 13.4 mmol/L) were higher compared to iontophoresis (24.0 ± 13.2 mmol/L). Possible physiological, methodological, and artifactual causes of this difference are discussed.

CONCLUSIONS

Pilocarpine MN patches present a promising alternative to iontophoresis to enable increased access to sweat testing for in-clinic and point-of-care applications.

Integrated metabolomics and proteomics analysis of plasma lipid metabolism in Parkinson's disease

INTRODUCTION

Metabolomics and proteomics are two growing fields of science which may shed light on the molecular mechanisms that contribute to neurodegenerative diseases. Studies focusing on these aspects can reveal specific metabolites and proteins that can halt or reverse the progressive neurodegenerative process leading to dopaminergic cell death in the brain.

AREAS COVERED

In this article, an overview of the current status of metabolomic and proteomic profiling in the neurodegenerative disease such as Parkinson's disease (PD) is presented. We discuss the importance of state-of-the-art metabolomics and proteomics using advanced analytical methodologies and their potential for discovering new biomarkers in PD. We critically review the research to date, highlighting how metabolomics and proteomics can have an important impact on early disease diagnosis, future therapy development and the identification of new biomarkers. Finally, we will discuss interactions between lipids and α-synuclein (SNCA) and also consider the role of SNCA in lipid metabolism.

EXPERT OPINION

Metabolomic and proteomic studies contribute to understanding the biological basis of PD pathogenesis, identifying potential biomarkers and introducing new therapeutic strategies. The complexity and multifactorial nature of this disease requires a comprehensive approach, which can be achieved by integrating just these two omic studies.

Bionanotechnology and bioMEMS (BNM): state-of-the-art applications, opportunities, and challenges

The development of micro- and nanotechnology for biomedical applications has defined the cutting edge of medical technology for over three decades, as advancements in fabrication technology developed originally in the semiconductor industry have been applied to solving ever-more complex problems in medicine and biology. These technologies are ideally suited to interfacing with life sciences, since they are on the scale lengths as cells (microns) and biomacromolecules (nanometers). In this paper, we review the state of the art in bionanotechnology and bioMEMS (collectively BNM), including developments and challenges in the areas of BNM, such as microfluidic organ-on-chip devices, oral drug delivery, emerging technologies for managing infectious diseases, 3D printed microfluidic devices, AC electrokinetics, flexible MEMS devices, implantable microdevices, paper-based microfluidic platforms for cellular analysis, and wearable sensors for point-of-care testing.

Recent Advances in Skin-Interfaced Wearable Sweat Sensors: Opportunities for Equitable Personalized Medicine and Global Health Diagnostics

Recent advances in skin-interfaced wearable sweat sensors enable the noninvasive, real-time monitoring of biochemical signals associated with health and wellness. These wearable platforms leverage microfluidic channels, biochemical sensors, and flexible electronics to enable the continuous analysis of sweat-based biomarkers such as electrolytes, metabolites, and hormones. As this field continues to mature, the potential of low-cost, continuous personalized health monitoring enabled by such wearable sensors holds significant promise for addressing some of the formidable obstacles to delivering comprehensive medical care in under-resourced settings. This Perspective highlights the transformative potential of wearable sweat sensing for providing equitable access to cutting-edge healthcare diagnostics, especially in remote or geographically isolated areas. It examines the current understanding of sweat composition as well as recent innovations in microfluidic device architectures and sensing strategies by showcasing emerging applications and opportunities for innovation. It concludes with a discussion on expanding the utility of wearable sweat sensors for clinically relevant health applications and opportunities for enabling equitable access to innovation to address existing health disparities.

A three-level model for therapeutic drug monitoring of antimicrobials at the site of infection

The silent pandemic of bacterial antimicrobial resistance is a leading cause of death worldwide, prolonging hospital stays and raising health-care costs. Poor incentives to develop novel pharmacological compounds and the misuse of antibiotics contribute to the bacterial antimicrobial resistance crisis. Therapeutic drug monitoring (TDM) based on blood analysis can help alleviate the emergence of bacterial antimicrobial resistance and effectively decreases the risk of toxic drug concentrations in patients' blood. Antibiotic tissue penetration can vary in patients who are critically or chronically ill and can potentially lead to treatment failure. Antibiotics such as β-lactams and glycopeptides are detectable in non-invasively collectable biofluids, such as sweat and exhaled breath. The emergence of wearable sensors enables easy access to these non-invasive biofluids, and thus a laboratory-independent analysis of various disease-associated biomarkers and drugs. In this Personal View, we introduce a three-level model for TDM of antibiotics to describe concentrations at the site of infection (SOI) by use of wearable sensors. Our model links blood-based drug measurement with the analysis of drug concentrations in non-invasively collectable biofluids stemming from the SOI to characterise drug concentrations at the SOI. Finally, we outline the necessary clinical and technical steps for the development of wearable sensing platforms for SOI applications.

Wearable sweat analysis to determine biological age

A real-time, noninvasive, and clinically applicable aging test in humans has yet to be established. Herein we propose a sweat- and wearable-based test to determine biological age. This test would empower users to monitor their aging process and take an active role in managing their lifestyle and health.

Screen-Printed Wearable Sweat Sensor for Cost-Effective Assessment of Human Hydration Status through Potassium and Sodium Ion Detection

Human sweat is intricately linked to human health, and unraveling its secrets necessitates a substantial volume of experimental data. However, conventional sensors fabricated via complex processes such as photolithography offer high detection precision at the expense of prohibitive costs. In this study, we presented a cost-effective and high-performance wearable flexible sweat sensor for real-time monitoring of K+ and Na+ concentrations in human sweat, fabricated using screen printing technology. Initially, we evaluated the electrical and electrochemical stability of the screen-printed substrate electrodes, which demonstrated good consistency with a variation within 10% of the relative standard deviation (RSD), meeting the requirements for reliable detection of K+ and Na+ in human sweat. Subsequently, we employed an "ion-electron" transduction layer and an ion-selective membrane to construct the sensors for detecting K+ and Na+. Comprehensive tests were conducted to assess the sensors' sensitivity, linearity, repeatability, resistance to interference, and mechanical deformation capabilities. Furthermore, we evaluated their long-term stability during continuous monitoring and storage. The test results confirmed that the sensor's performance indicators, as mentioned above, met the requirements for analyzing human sweat. In a 10-day continuous and regular monitoring experiment involving volunteers wearing the sensors, a wealth of data revealed a close relationship between K+ and Na+ concentrations in human sweat and hydration status. Notably, we observed that consistent and regular physical exercise effectively enhanced the body's resistance to dehydration. These findings provided a solid foundation for conducting extensive experiments and further exploring the intricate relationship between human sweat and overall health. Our research paved a practical and feasible path for future studies in this domain.

A non-invasive wearable stress patch for real-time cortisol monitoring using a pseudoknot-assisted aptamer

Stress is part of everyone's life and is exacerbated by traumatic events such as pandemics, disasters, violence, lifestyle changes, and health disorders. Chronic stress has many detrimental health effects and can even be life-threatening. Long-term stress monitoring outside of a hospital is often accomplished by measuring heart rate variability. While easy to measure, this digital biomarker has low specificity, greatly limiting its utility. To address this shortcoming, we report a non-invasive, wearable biomolecular sensor to monitor cortisol levels in sweat. Cortisol is a neuroendocrine hormone that regulates homeostasis as part of the stress pathway. Cortisol is detected using an electrochemical sensor functionalized with a pseudoknot-assisted aptamer and a flexible microfluidic sweat sampling system. The skin-worn microfluidic sampler provides rapid sweat collection while separating old and new sweat. The conformation-switching aptamer provides high specificity towards cortisol while being regenerable, allowing it to monitor temporal changes continuously. The aptamer was engineered to add a pseudoknot, restricting it to only two states, thus minimizing the background signal and enabling high sensitivity. An electrochemical pH sensor allows pH-corrected amperometric measurements. Device operation was demonstrated invitro with a broad linear dynamic range (1 pM - 1 μM) covering the physiological range and a sub-picomolar (0.2 pM) limit of detection in sweat. Real-time, on-body measurements were collected from human subjects using an induced stress protocol, demonstrating in-situ signal regeneration and the ability to detect dynamic cortisol fluctuations continuously for up to 90 min. The reported device has the potential to improve prognosis and enable personalized treatments.

Rapid skin biomarker discovery using hydrogel-phase sampling followed by semi-automated liquid-phase re-extraction high-resolution mass spectrometry

A facile and rapid skin metabolomics protocol is proposed. The liquid microjunction-surface sampling probe system has been partly automated, and used in conjunction with hydrogel probes for skin metabolite analysis. A control device was built to precisely control the segmented solvent flow and analyte re-extraction into the liquid microjunction. This mode provides rapid online re-extraction of the analytes from hydrogel probes. Humectant was added to the hydrogel, and moist heat treatment was used to make the hydrogel probes rugged for sampling in the clinical setting. The developed method was validated for the analysis of choline - a putative biomarker of psoriasis. A linear relationship over six calibration levels from 3.18 × 10^-5 to 3.18 × 10^-4 mol m^-2 has been obtained. The limit of detection was 6.6 × 10^-6 mol m^-2, while the recoveries range from 92 to 109%. The within-run and between-run precision were evaluated and the coefficients of variation range from 1.84 to 7.13%. Furthermore, the developed method has been used to screen patients (n = 10) and healthy participants (control group; n = 10) for psoriasis-related skin metabolites. Metabolomic profiling of the skin excretion-related signals identified potential biomarkers of psoriasis: choline, pipecolic acid, ornithine, urocanic acid, and methionine.

No skin off your back: the sampling and extraction of sebum for metabolomics

INTRODUCTION

Sebum-based metabolomics (a subset of "sebomics") is a developing field that involves the sampling, identification, and quantification of metabolites found in human sebum. Sebum is a lipid-rich oily substance secreted by the sebaceous glands onto the skin surface for skin homeostasis, lubrication, thermoregulation, and environmental protection. Interest in sebomics has grown over the last decade due to its potential for rapid analysis following non-invasive sampling for a range of clinical and environmental applications.

OBJECTIVES

To provide an overview of various sebum sampling techniques with their associated challenges. To evaluate applications of sebum for clinical research, drug monitoring, and human biomonitoring. To provide a commentary of the opportunities of using sebum as a diagnostic biofluid in the future.

METHODS

Bibliometric analyses of selected keywords regarding skin surface analysis using the Scopus search engine from 1960 to 2022 was performed on 12th January 2023. The published literature was compartmentalised based on what the work contributed to in the following areas: the understanding about sebum, its composition, the analytical technologies used, or the purpose of use of sebum. The findings were summarised in this review.

RESULTS

Historically, about 15 methods of sampling have been used for sebum collection. The sample preparation approaches vary depending on the analytes of interest and are summarised. The use of sebum is not limited to just skin diseases or drug monitoring but also demonstrated for other systemic disease. Most of the work carried out for untargeted analysis of metabolites associated with sebum has been in the recent two decades.

CONCLUSION

Sebum has a huge potential beyond skin research and understanding how one's physiological state affects or reflects on the skin metabolome via the sebaceous glands itself or by interactions with sebaceous secretion, will open doors for simpler biomonitoring. Sebum acts as a sink to environmental metabolites and has applications awaiting to be explored, such as biosecurity, cross-border migration, localised exposure to harmful substances, and high-throughput population screening. These applications will be possible with rapid advances in volatile headspace and lipidomics method development as well as the ability of the metabolomics community to annotate unknown species better. A key issue with skin surface analysis that remains unsolved is attributing the source of the metabolites found on the skin surface before meaningful biological interpretation.

Electrochemical Nanosensors for Sensitization of Sweat Metabolites: From Concept Mapping to Personalized Health Monitoring

Sweat contains a broad range of important biomarkers, which may be beneficial for acquiring non-invasive biochemical information on human health status. Therefore, highly selective and sensitive electrochemical nanosensors for the non-invasive detection of sweat metabolites have turned into a flourishing contender in the frontier of disease diagnosis. A large surface area, excellent electrocatalytic behavior and conductive properties make nanomaterials promising sensor materials for target-specific detection. Carbon-based nanomaterials (e.g., CNT, carbon quantum dots, and graphene), noble metals (e.g., Au and Pt), and metal oxide nanomaterials (e.g., ZnO, MnO2, and NiO) are widely used for modifying the working electrodes of electrochemical sensors, which may then be further functionalized with requisite enzymes for targeted detection. In the present review, recent developments (2018-2022) of electrochemical nanosensors by both enzymatic as well as non-enzymatic sensors for the effectual detection of sweat metabolites (e.g., glucose, ascorbic acid, lactate, urea/uric acid, ethanol and drug metabolites) have been comprehensively reviewed. Along with this, electrochemical sensing principles, including potentiometry, amperometry, CV, DPV, SWV and EIS have been briefly presented in the present review for a conceptual understanding of the sensing mechanisms. The detection thresholds (in the range of mM-nM), sensitivities, linear dynamic ranges and sensing modalities have also been properly addressed for a systematic understanding of the judicious design of more effective sensors. One step ahead, in the present review, current trends of flexible wearable electrochemical sensors in the form of eyeglasses, tattoos, gloves, patches, headbands, wrist bands, etc., have also been briefly summarized, which are beneficial for on-body in situ measurement of the targeted sweat metabolites. On-body monitoring of sweat metabolites via wireless data transmission has also been addressed. Finally, the gaps in the ongoing research endeavors, unmet challenges, outlooks and future prospects have also been discussed for the development of advanced non-invasive self-health-care-monitoring devices in the near future.

Diagnosis by Volatile Organic Compounds in Exhaled Breath in Exhaled Breath from Patients with Gastric and Colorectal Cancers

One in three cancer deaths worldwide are caused by gastric and colorectal cancer malignancies. Although the incidence and fatality rates differ significantly from country to country, the rates of these cancers in East Asian nations such as South Korea and Japan have been increasing each year. Above all, the biggest danger of this disease is how challenging it is to recognize in its early stages. Moreover, most patients with these cancers do not present with any disease symptoms before receiving a definitive diagnosis. Currently, volatile organic compounds (VOCs) are being used for the early prediction of several other diseases, and research has been carried out on these applications. Exhaled VOCs from patients possess remarkable potential as novel biomarkers, and their analysis could be transformative in the prevention and early diagnosis of colon and stomach cancers. VOCs have been spotlighted in recent studies due to their ease of use. Diagnosis on the basis of patient VOC analysis takes less time than methods using gas chromatography, and results in the literature demonstrate that it is possible to determine whether a patient has certain diseases by using organic compounds in their breath as indicators. This study describes how VOCs can be used to precisely detect cancers; as more data are accumulated, the accuracy of this method will increase, and it can be applied in more fields.

A systems approach towards remote health-monitoring in older adults: Introducing a zero-interaction digital exhaust

Using connected sensing devices to remotely monitor health is a promising way to help transition healthcare from a rather reactive to a more precision medicine oriented proactive approach, which could be particularly relevant in the face of rapid population ageing and the challenges it poses to healthcare systems. Sensor derived digital measures of health, such as digital biomarkers or digital clinical outcome assessments, may be used to monitor health status or the risk of adverse events like falls. Current research around such digital measures has largely focused on exploring the use of few individual measures obtained through mobile devices. However, especially for long-term applications in older adults, this choice of technology may not be ideal and could further add to the digital divide. Moreover, large-scale systems biology approaches, like genomics, have already proven beneficial in precision medicine, making it plausible that the same could also hold for remote-health monitoring. In this context, we introduce and describe a zero-interaction digital exhaust: a set of 1268 digital measures that cover large parts of a person’s activity, behavior and physiology. Making this approach more inclusive of older adults, we base this set entirely on contactless, zero-interaction sensing technologies. Applying the resulting digital exhaust to real-world data, we then demonstrate the possibility to create multiple ageing relevant digital clinical outcome assessments. Paired with modern machine learning, we find these assessments to be surprisingly powerful and often on-par with mobile approaches. Lastly, we highlight the possibility to discover novel digital biomarkers based on this large-scale approach.

Eccrine Sweat Molecular Model for Development of de novo Biosensors

In this paper, we present a validated, novel, in silico molecular dynamics (MD) model of eccrine sweat with approx. 35k atoms developed using Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) program. CHARMMS36m force field for constituent atoms and SPC/E water model are used to develop this model. The model outputs transport properties such as self-diffusivity computed using mean squared displacement and bulk viscosity computed via Green-Kubo correlations, which are compared with existing literature values and experimental studies and presented. This validated model is intended to serve as a tool to develop eccrine sweat based biosensors.

Evaluation of Sweat-Sampling Procedures for Human Stress-Biomarker Detection

Sweat is a potential biological fluid for the non-invasive analytical assessment of diverse molecules, including biomarkers. Notwithstanding, the sampling methodology is critical, and it must be assessed prior to using sweat for clinical diagnosis. In the current work, the analytical methodology was further developed taking into account the sampling step, in view of the identification and level variations of sweat components that have potential to be stress biomarkers using separation by liquid chromatography and detection by tandem mass spectrometry, in order to attain a screening profile of 26 molecules in just one stage. As such, the molecule identification was used as a test for the evaluation of the sampling procedures, including the location on the body, using patches for long-term sampling and vials for direct sampling, through a qualitative approach. From this evaluation it was possible to conclude that the sampling may be performed on the chest or back skin. Additionally, possible interference was evaluated. The long-term sampling with patches can be used under both rest and exercise conditions with variation of the detected molecule’s levels. The direct sampling, using vials, has the advantage of not having interferences but the disadvantage of only being effective after exercise in order to have enough sample for sweat analysis.

Wearable microfluidic-based e-skin sweat sensors

Electronic skins (e-skins) are soft (deformable and stretchable) state-of-the-art wearable devices that emulate the attributes of human skin and act as a Human-Machine Interface (HMI). Recent advances in e-skin for real-time detection of medical signals such as pulse, temperature, electromyogram (EMG), electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), and other bioelectric signals laid down an intelligent foundation for early prediction and diagnosis of diseases with a motive of reducing the risk of the ailment reaching to the end stage. In particular, sweat testing has been employed in diverse applications ranging from medical diagnosis of diabetes, cystic fibrosis, tuberculosis, blood pressure, and autonomic neuropathy to evaluating fluid and electrolyte balance in athletes. Typically, sweat testing techniques are done by trained experts and require off-body measurements, which prevent individuals from de-coding health issues quickly and independently. With the onset of soft electronics, wearable sweat sensors overcome this disadvantage via in situ sweat measurements with real-time feedback, timely diagnosis, creating the potential for preventive care and treatment. Over the past few decades, wearable microfluidic-based e-skin sweat sensors have paved a new way, promising sensing interfaces that are highly compatible with arranging medical and electronic applications. The present review highlights the recent research carried out in the microfluidic-based wearable sweat sensors with a critical focus on real-time sensing of lactate, chloride, and glucose concentration; sweat rate, simultaneously with pH, and total sweat loss for preventive care, timely diagnosis, and point-of-care health and fitness monitoring.

Towards Accurate Point-of-Care Tests for Tuberculosis in Children

In childhood tuberculosis (TB), with an estimated 69% of missed cases in children under 5 years of age, the case detection gap is larger than in other age groups, mainly due to its paucibacillary nature and children’s difficulties in delivering sputum specimens. Accurate and accessible point-of-care tests (POCTs) are needed to detect TB disease in children and, in turn, reduce TB-related morbidity and mortality in this vulnerable population. In recent years, several POCTs for TB have been developed. These include new tools to improve the detection of TB in respiratory and gastric samples, such as molecular detection of Mycobacterium tuberculosis using loop-mediated isothermal amplification (LAMP) and portable polymerase chain reaction (PCR)-based GeneXpert. In addition, the urine-based detection of lipoarabinomannan (LAM), as well as imaging modalities through point-of-care ultrasonography (POCUS), are currently the POCTs in use. Further to this, artificial intelligence-based interpretation of ultrasound imaging and radiography is now integrated into computer-aided detection products. In the future, portable radiography may become more widely available, and robotics-supported ultrasound imaging is currently being trialed. Finally, novel blood-based tests evaluating the immune response using “omic-“techniques are underway. This approach, including transcriptomics, metabolomic, proteomics, lipidomics and genomics, is still distant from being translated into POCT formats, but the digital development may rapidly enhance innovation in this field. Despite these significant advances, TB-POCT development and implementation remains challenged by the lack of standard ways to access non-sputum-based samples, the need to differentiate TB infection from disease and to gain acceptance for novel testing strategies specific to the conditions and settings of use.

Combined small and large magnetic nanoparticle extraction and concentration from biofluids for non-toxic detection of biomarkers

Sketch of the concentration of small and large magnetic nanoparticles in biofluid to the area of biomarker detection for enhancing the method sensitivity.

Digital Biomarkers in Psychiatric Research: Data Protection Qualifications in a Complex Ecosystem

Psychiatric research traditionally relies on subjective observation, which is time-consuming and labor-intensive. The widespread use of digital devices, such as smartphones and wearables, enables the collection and use of vast amounts of user-generated data as "digital biomarkers." These tools may also support increased participation of psychiatric patients in research and, as a result, the production of research results that are meaningful to them. However, sharing mental health data and research results may expose patients to discrimination and stigma risks, thus discouraging participation. To earn and maintain participants' trust, the first essential requirement is to implement an appropriate data governance system with a clear and transparent allocation of data protection duties and responsibilities among the actors involved in the process. These include sponsors, investigators, operators of digital tools, as well as healthcare service providers and biobanks/databanks. While previous works have proposed practical solutions to this end, there is a lack of consideration of positive data protection law issues in the extant literature. To start filling this gap, this paper discusses the GDPR legal qualifications of controller, processor, and joint controllers in the complex ecosystem unfolded by the integration of digital biomarkers in psychiatric research, considering their implications and proposing some general practical recommendations.

A disposable, wearable, flexible, stitched textile electrochemical biosensing platform

Wearable sensors are a fast growing and exciting research area, the success of smart watches are a great example of the utility and demand for wearable sensing systems. The current state of the art routinely uses expensive and bulky equipment designed for long term use. There is a need for cheap and disposable wearable sensors to make single use measurements, primarily in the area of biomarker detection. Herein we report the ability to make cheap (0.22 USD/sensor), disposable, wearable sensors by stitching conductive gold coated threads into fabrics. These threads are easily functionalised with thiolate self-assembled monolayers which can be designed for the detection of a broad range of different biomarkers. This all textile sensing platform is ideally suited to be scaled up and has the added advantage of being stretchable with insignificant effect on the electrochemistry of the devices. As a proof of principle, the devices have been functionalised with a continuous glucose sensing system which was able to detect glucose in human sweat across the clinically relevant range (0.1-0.6 mM). The sensors have a sensitivity of 126 ± 14 nA/mM of glucose and a limit of detection of 301 ± 2 nM. This makes them ideally suited for biomarker detection in point-of-care sensing applications.

Can Wearable Sweat Lactate Sensors Contribute to Sports Physiology?

The rise of wearable sensors to measure lactate content in human sweat during sports activities has attracted the attention of physiologists given the potential of these “analytical tools” to provide real-time information. Beyond the assessment of the sensing technology per se, which, in fact, has not rigorously been validated yet in controlled conditions, there are many open questions about the true usefulness of such wearable sensors in real scenarios. On the one hand, the evidence for the origin of sweat lactate (e.g., via the sweat gland, derivation from blood, or other alternative mechanisms), its high concentration (1–25 mM or even higher) compared to levels in the blood, and the possible correlation between different biofluids (particularly blood) is rather contradictory and generates vivid debate in the field. On the other hand, it is important to point out that accurate detection of sweat lactate is highly dependent on the procedure used to collect and/or reach the fluid, and this can likely explain the large discrepancies reported in the literature. In brief, this paper provides our vision of the current state of the field and a thoughtful evaluation of the possible reasons for present controversies, together with an analysis of the impact of wearable sweat lactate sensors in the physiological context. Finally, although there is not yet overwhelming scientific evidence to provide an unequivocal answer to whether wearable sweat lactate sensors can contribute to sports physiology, we still understand the importance to bring this challenging question up-front to create awareness and guidance in the development, validation, and implementation of wearable sensors.

Body composition analysis in patients with acute heart failure: the Scale Heart Failure trial

Aims

In this study, we aimed to investigate whether body composition analysis (BCA) derived from bioelectrical impedance vector analysis (BIVA) could be used to monitor the hydration status of patients with acute heart failure (AHF) during intensified diuretic therapy.

Methods and results

This observational, single‐centre study involved a novel, validated eight‐electrode segmental body composition analyser to perform BCA derived from BIVA with an alternating current of 100 μA at frequencies of 5, 7.5, 50, and 75 kHz. The BCA‐derived and BIVA‐derived parameters were estimated and compared with daily body weight measurements in hospitalized patients with AHF. A total of 867 BCA and BIVA assessments were conducted in 142 patients (56.3% men; age 76.8 ± 10.7 years). Daily changes in total body water (TBW) and extracellular water (ECW) were significantly associated with changes in body weight in 62.2% and 89.1% of all measurements, respectively (range, ±1 kg). Repeated measures correlation coefficients between weight loss and TBW loss resulted with rho 0.43, P < 0.01, confidence interval (CI) [0.36, 0.50] and rho 0.71, P > 0.01, CI [0.67, 0.75] for ECW loss. Between the first and last assessments, the mean weight loss was −2.5 kg, compared with the −2.6 L mean TBW loss and −1.7 L mean ECW loss. BIVA revealed an increase in mean Resistance R and mean Reactance X_c across all frequencies, with the subsequent reduction in body fluid (including corresponding body weight) between the first and last assessments.

Conclusions

Body composition analysis derived from BIVA with a focus on ECW is a promising approach to detect changes in hydration status in patients undergoing intensified diuretic therapy. Defining personalized BIVA reference values using bioelectrical impedance devices is a promising approach to monitor hydration status.

State of Sweat: Emerging Wearable Systems for Real-Time, Noninvasive Sweat Sensing and Analytics

Skin-interfaced wearable systems with integrated colorimetric assays, microfluidic channels, and electrochemical sensors offer powerful capabilities for noninvasive, real-time sweat analysis. This Perspective details recent progress in the development and translation of novel wearable sensors for personalized assessment of sweat dynamics and biomarkers, with precise sampling and real-time analysis. Sensor accuracy, system ruggedness, and large-scale deployment in remote environments represent key opportunity areas, enabling broad deployment in the context of field studies, clinical trials, and recent commercialization. On-body measurements in these contexts show good agreement compared to conventional laboratory-based sweat analysis approaches. These device demonstrations highlight the utility of biochemical sensing platforms for personalized assessment of performance, wellness, and health across a broad range of applications.

Bacterial cellulose spheroids as building blocks for 3D and patterned living materials and for regeneration

Engineered living materials (ELMs) based on bacterial cellulose (BC) offer a promising avenue for cheap-to-produce materials that can be programmed with genetically encoded functionalities. Here we explore how ELMs can be fabricated in a modular fashion from millimetre-scale biofilm spheroids grown from shaking cultures of Komagataeibacter rhaeticus. Here we define a reproducible protocol to produce BC spheroids with the high yield bacterial cellulose producer K. rhaeticus and demonstrate for the first time their potential for their use as building blocks to grow ELMs in 3D shapes. Using genetically engineered K. rhaeticus, we produce functionalized BC spheroids and use these to make and grow patterned BC-based ELMs that signal within a material and can sense and report on chemical inputs. We also investigate the use of BC spheroids as a method to regenerate damaged BC materials and as a way to fuse together smaller material sections of cellulose and synthetic materials into a larger piece. This work improves our understanding of BC spheroid formation and showcases their great potential for fabricating, patterning and repairing ELMs based on the promising biomaterial of bacterial cellulose.

Bacterial cellulose is a promising cheap-to-produce programmable engineered living material. Here the authors present a method for production of spheroids for use as engineerable building blocks able to sense and respond to chemical inputs.

Next-Generation Digital Biomarkers for Tuberculosis and Antibiotic Stewardship: Perspective on Novel Molecular Digital Biomarkers in Sweat, Saliva, and Exhaled Breath

The internet of health care things enables a remote connection between health care professionals and patients wearing smart biosensors. Wearable smart devices are potentially affordable, sensitive, specific, user-friendly, rapid, robust, lab-independent, and deliverable to the end user for point-of-care testing. The datasets derived from these devices are known as digital biomarkers. They represent a novel patient-centered approach to collecting longitudinal, context-derived health insights. Adding automated, analytical smartphone applications will enable their use in high-, middle-, and low-income countries. So far, digital biomarkers have been focused primarily on accelerometer data and heart rate due to well-established sensors originating from the consumer market. Novel emerging smart biosensors will detect biomarkers (or compounds) independent of a lab and noninvasively in sweat, saliva, and exhaled breath. These molecular digital biomarkers are a promising novel approach to reduce the burden from 2 major infectious diseases with urgent unmet needs: tuberculosis and infections with multidrug resistant pathogens. Active tuberculosis (aTbc) is one of the deadliest diseases from an infectious agent. However, a simple and reliable test for its detection is still missing. Furthermore, inappropriate antimicrobial use leads to the development of antimicrobial resistance, which is associated with high mortality and health care costs. From this perspective, we discuss the innovative approach of a noninvasive and lab-independent collection of novel biomarkers to detect aTbc, which at the same time may additionally serve as a scalable therapeutic drug monitoring approach for antibiotics. These molecular digital biomarkers are next-generation digital biomarkers and have the potential to shape the future of infectious diseases.

Wearable Biosensors for Non-Invasive Sweat Diagnostics

Recent advances in microfluidics, microelectronics, and electrochemical sensing methods have steered the way for the development of novel and potential wearable biosensors for healthcare monitoring. Wearable bioelectronics has received tremendous attention worldwide due to its great a potential for predictive medical modeling and allowing for personalized point-of-care-testing (POCT). They possess many appealing characteristics, for example, lightweight, flexibility, good stretchability, conformability, and low cost. These characteristics make wearable bioelectronics a promising platform for personalized devices. In this paper, we review recent progress in flexible and wearable sensors for non-invasive biomonitoring using sweat as the bio-fluid. Real-time and molecular-level monitoring of personal health states can be achieved with sweat-based or perspiration-based wearable biosensors. The suitability of sweat and its potential in healthcare monitoring, sweat extraction, and the challenges encountered in sweat-based analysis are summarized. The paper also discusses challenges that still hinder the full-fledged development of sweat-based wearables and presents the areas of future research.

Recent Impact of Microfluidics on Skin Models for Perspiration Simulation

Skin models offer an in vitro alternative to human trials without their high costs, variability, and ethical issues. Perspiration models, in particular, have gained relevance lately due to the rise of sweat analysis and wearable technology. The predominant approach to replicate the key features of perspiration (sweat gland dimensions, sweat rates, and skin surface characteristics) is to use laser-machined membranes. Although they work effectively, they present some limitations at the time of replicating sweat gland dimensions. Alternative strategies in terms of fabrication and materials have also showed similar challenges. Additional research is necessary to implement a standardized, simple, and accurate model representing sweating for wearable sensors testing.

Skin Metabolomics

Skin retains numerous low-molecular-weight compounds (metabolites). Some of these compounds fulfill specific physiological roles, while others are by-products of metabolism. The skin surface can be sampled to detect and quantify skin metabolites related to diseases. Miniature probes have been developed to detect selected high-abundance metabolites secreted with sweat. To characterize a broad spectrum of skin metabolites, specimens are collected with one of several available methods, and the processed specimens are analyzed by chromatography, mass spectrometry (MS), or other techniques. Diseases for which skin-related biomarkers have been found include cystic fibrosis (CF), psoriasis, Parkinson's disease (PD), and lung cancer. To increase the clinical significance of skin metabolomics, it is desirable to verify correlations between metabolite levels in skin and other biological tissues/matrices.

Screening of Potential Stress Biomarkers in Sweat Associated with Sports Training

BACKGROUND

Intense and continuous physical training in sports is related with psychological and physiological stress, affecting the health and well-being of athletes. The development of non-invasive sampling methodologies is essential to consider sweat as a potential biological fluid for stress biomarker assessment. In the current work, the identification in sweat samples of potential molecules that may be used as stress biomarkers was pursued.

METHODS

A sweat pool sample from football players after a 90-min intense training game was studied.

RESULTS

An analysis method using liquid chromatography with detection by tandem mass spectrometry (LC-MSMS) to attain a screening profile of sweat composition is presented. The major focus was on neurotransmitters (e.g. monoamines and metabolites) and other biological molecules related with physical training, such as precursors of biogenic amines (phenylaniline, tyrosine, etc.).

CONCLUSIONS

This study allowed the identification of small biomolecules, neurotransmitters and other related molecules in sweat that are potentially associated with stress conditions. The developed methodology intends to contribute to the assessment and study of physical and psychological stress biomarkers related with intense sports using non-invasive methods.

A fully screen-printed potentiometric chloride ion sensor employing a hydrogel-based touchpad for simple and non-invasive daily electrolyte analysis

This is the first report demonstrating proof of concept for the passive, non-invasive extraction and in situ potentiometric detection of human sweat chloride ions (Cl^- ions) using a stable printed planar liquid-junction reference electrode-integrated hydrogel-based touch-sensor pad without activities such as exercise to induce perspiration, environmental temperature control, or requiring cholinergic drug administration. The sensor pad was composed entirely of a screen-printed bare Ag/AgCl-based chloride ion-selective electrode and a planar liquid-junction Ag/AgCl reference electrode, which were fully covered by an agarose hydrogel in phosphate-buffered saline (PBS). When human skin contacted the hydrogel pad, sweat Cl^- ions were continuously extracted into the gel, followed by in situ potentiometric detection. The planar liquid-junction Ag/AgCl reference electrode had a polymer-based KCl-saturated inner electrolyte layer to stabilize the potential of the Ag/AgCl electrode even with a substantial change in the chloride ion concentration in the hydrogel pad. We expect this fully screen-printed sensor to achieve the low-cost passive and non-invasive daily monitoring of human Cl^- ions in sweat in the future.

The Detection of Vancomycin in Sweat: A Next-Generation Digital Surrogate Marker for Antibiotic Tissue Penetration: A Pilot Study

BACKGROUND

Assuring adequate antibiotic tissue concentrations at the point of infection, especially in skin and soft tissue infections, is pivotal for an effective treatment and cure. Despite the global issue, a reliable AB monitoring test is missing. Inadequate antibiotic treatment leads to the development of antimicrobial resistances and toxic side effects. β-lactam antibiotics were already detected in sweat of patients treated with the respective antibiotics intravenously before. With the emergence of smartphone-based biosensors to analyse sweat on the spot of need, next-generation molecular digital biomarkers will be increasingly available for a non-invasive pharmacotherapy monitoring.

OBJECTIVE

Here, we investigated if the glycopeptide antibiotic vancomycin is detectable in sweat samples of in-patients treated with intravenous vancomycin.

METHODS

Eccrine sweat samples were collected using the Macroduct Sweat Collector®. Along every sweat sample, a blood sample was taken. Bio-fluid analysis was performed by Ultra-high Pressure Liquid Chromatograph-Tandem Quadrupole Mass Spectrometry coupled with tandem mass spectrometry.

RESULTS

A total of 5 patients were included. Results demonstrate that vancomycin was detected in 5 out of 5 sweat samples. Specifically, vancomycin concentrations ranged from 0.011 to 0.118 mg/L in sweat and from 4.7 to 8.5 mg/L in blood.

CONCLUSION

Our results serve as proof-of-concept that vancomycin is detectable in eccrine sweat and may serve as a surrogate marker for antibiotic tissue penetration. A targeted vancomycin treatment is crucial in patients with repetitive need for antibiotics and a variable antibiotic distribution such as in peripheral artery disease to optimize treatment effectiveness. If combined with on-skin smartphone-based biosensors and smartphone applications, the detection of antibiotic concentrations in sweat might enable a first digital, on-spot, lab-independent and non-invasive therapeutic drug monitoring in skin and soft tissue infections.

The Role of Digital Navigators in Promoting Clinical Care and Technology Integration into Practice

As the role of technology expands in healthcare, so does the need to support its implementation and integration into the clinic. The concept of a new team member, the digital navigator, able to assume this role is introduced as a solution. With a digital navigator, any clinic today can take advantage of digital health and smartphone tools to augment and expand existing telehealth and face to face care. The role of a digital navigator is suitable as an entry level healthcare role, additional training for an experienced clinician, and well suited to peer specialists. To facilitate the training of digital navigators, we draw upon our experience in creating the role and across health education to introduce a 10-h curriculum designed to train digital navigators across 5 domains: (1) core smartphone skills, (2) basic technology troubleshooting, (3) app evaluation, (4) clinical terminology and data, and (5) engagement techniques. This paper outlines the curricular content, skills, and modules for this training and features a rich online supplementary Appendix with step by step instructions and resources.

Device- and Analytics-Agnostic Infrastructure for Continuous Inpatient Monitoring: A Technical Note

The internet of healthcare things aims at connecting biosensors, clinical information systems and electronic health dossiers. The resulting data expands traditionally available diagnostics with digital biomarkers. In this technical note, we report the implementation and pilot operation of a device- and analytics-agnostic automated monitoring platform for in-house patients at hospitals. Any available sensor, as well as any analytics tool can be integrated if the application programming interface is made available. The platform consists of a network of Bluetooth gateways communicating via the hospital's secure Wi-Fi network, a server application (Device Hub) and associated databases. Already existing access points or low-cost hardware can be used to run the gateway software. The platform can be extended to a remote patient monitoring solution to close the gap between in-house treatments and follow-up patient monitoring.

More Data, Please: Machine Learning to Advance the Multidisciplinary Science of Human Sociochemistry

Communication constitutes the core of human life. A large portion of our everyday social interactions is non-verbal. Of the sensory modalities we use for non-verbal communication, olfaction (i.e., the sense of smell) is often considered the most enigmatic medium. Outside of our awareness, smells provide information about our identity, emotions, gender, mate compatibility, illness, and potentially more. Yet, body odors are astonishingly complex, with their composition being influenced by various factors. Is there a chemical basis of olfactory communication? Can we identify molecules predictive of psychological states and traits? We propose that answering these questions requires integrating two disciplines: psychology and chemistry. This new field, coined sociochemistry, faces new challenges emerging from the sheer amount of factors causing variability in chemical composition of body odorants on the one hand (e.g., diet, hygiene, skin bacteria, hormones, genes), and variability in psychological states and traits on the other (e.g., genes, culture, hormones, internal state, context). In past research, the reality of these high-dimensional data has been reduced in an attempt to isolate unidimensional factors in small, homogenous samples under tightly controlled settings. Here, we propose big data approaches to establish novel links between chemical and psychological data on a large scale from heterogeneous samples in ecologically valid settings. This approach would increase our grip on the way chemical signals non-verbally and subconsciously affect our social lives across contexts.

Non-invasive Drug Monitoring of β-Lactam Antibiotics Using Sweat Analysis-A Pilot Study

Background: Antimicrobial resistance is a major challenge in treating infectious diseases. Therapeutic drug monitoring (TDM) can optimize and personalize antibiotic treatment. Previously, antibiotic concentrations in tissues were extrapolated from skin blister studies, but sweat analyses for TDM have not been conducted. Objective: To investigate the potential of sweat analysis as a non-invasive, rapid, and potential bedside TDM method. Methods: We analyzed sweat and blood samples from 13 in-house patients treated with intravenous cefepime, imipenem, or flucloxacillin. For cefepime treatment, full pharmacokinetic sampling was performed (five subsequent sweat samples every 2 h) using ultra-high-performance liquid chromatography coupled with triple quadrupole mass spectrometry. The ClinicalTrials.gov registration number is NCT03678142. Results: In this study, we demonstrated for the first time that flucloxacillin, imipenem, and cefepime are detectable in sweat. Antibiotic concentration changes over time demonstrated comparable (age-adjusted) dynamics in the blood and sweat of patients treated with cefepime. Patients treated with standard flucloxacillin dosage showed the highest mean antibiotic concentration in sweat. Conclusions: Our results provide a proof-of-concept that sweat analysis could potentially serve as a non-invasive, rapid, and reliable method to measure antibiotic concentration and as a surrogate marker for tissue penetration. If combined with smart biosensors, sweat analysis may potentially serve as the first lab-independent, non-invasive antibiotic TDM method.

Weaving Off-The-Shelf Yarns into Textile Micro Total Analysis Systems (μTAS)

Textile based biosensors have garnered much interest in recent years. Devices woven out of yarns have the ability to be incorporated into clothing and bandages. Most woven devices reported in the literature require yarns that are not available on an industrial scale or that require modifications which are not possible in large scale manufacturing. In this work, commercially produced yarns are taken without any modification or cleaning, and developed woven textile diagnostic devices out of them. The yarn properties that are important to their function within the device have been characterised and discussed. The wicking ability and analyte retention of Coolmax yarns, developed to wick sweat in mass produced sportswear, are determined. The electrochemistry and functionalizability of Au coated multifilament yarns are investigated with no cleaning or treatment and are found to have as good a thiolate self-assembled monolayer (SAM) coverage as cleaned Au disk electrodes. The feasibility of using these yarns is established off the shelf, with no cleaning, to make woven capillary force driven microfluidic devices and three electrode sensing devices. A proof of principle three electrode system capable of detecting clinically relevant concentrations of glucose in human sweat is reported.