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Despite the fast development of various energy harvesting and storage devices, their judicious integration into efficient, autonomous, and sustainable wearable systems has not been widely explored. Here, we introduce the concept and design principles of e-textile microgrids by demonstrating a multi-module bioenergy microgrid system. Unlike earlier hybrid wearable systems, the presented e-textile microgrid relies solely on human activity to work synergistically, harvesting biochemical and biomechanical energy using sweat-based biofuel cells and triboelectric generators, and regulating the harvested energy via supercapacitors for high-power output. Through energy budgeting, the e-textile system can efficiently power liquid crystal displays continuously or a sweat sensor-electrochromic display system in pulsed sessions, with half the booting time and triple the runtime in a 10-min exercise session. Implementing “compatible form factors, commensurate performance, and complementary functionality” design principles, the flexible, textile-based bioenergy microgrid offers attractive prospects for the design and operation of efficient, sustainable, and autonomous wearable systems. Though energy-harvesting wearable systems have been reported in the literature, their system design imposes limitations that hinder their overall performance. Here, the authors report a system-level wearable e-textile microgrid system that relies solely on human activity for energy harvesting.

Implementations of wearable microneedle-based arrays of sensors for the monitoring of multiple biomarkers in interstitial fluid have lacked system integration and evidence of robust analytical performance. Here we report the development and testing of a fully integrated wearable array of microneedles for the wireless and continuous real-time sensing of two metabolites (lactate and glucose, or alcohol and glucose) in the interstitial fluid of volunteers performing common daily activities. The device works with a custom smartphone app for data capture and visualization, comprises reusable electronics and a disposable microneedle array, and is optimized for system integration, cost-effective fabrication via advanced micromachining, easier assembly, biocompatibility, pain-free skin penetration and enhanced sensitivity. Single-analyte and dual-analyte measurements correlated well with the corresponding gold-standard measurements in blood or breath. Further validation of the technology in large populations with concurrent validation of sensor readouts through centralized laboratory tests should determine the robustness and utility of real-time simultaneous monitoring of several biomarkers in interstitial fluid. A wearable array of microneedle-based sensors can be used to wirelessly measure the levels of glucose simultaneously with those of alcohol or lactate in the interstitial fluid of volunteers performing common daily activities.

Rapid and precise analytical tools are essential for monitoring food safety and screening of any undesirable contaminants, allergens, or pathogens, which may cause significant health risks upon consumption. Substantial developments in analytical techniques have empowered the analyses and quantitation of these contaminants. However, conventional techniques are limited by delayed analysis times, expensive and laborious sample preparation, and the necessity for highly-trained workers. Therefore, prompt advances in electrochemical biosensors have supported significant gains in quantitative detection and screening of food contaminants and showed incredible potential as a means of defying such limitations. Apart from indicating high specificity towards the target analytes, these biosensors have also addressed the challenge of food industry by providing high analytical accuracy within complex food matrices. Here, we discuss some of the recent advances in this area and analyze the role and contributions made by electrochemical biosensors in the food industry. This article also reviews the key challenges we believe biosensors need to overcome to become the industry standard.

A rapid prototyping of an inexpensive, disposable graphene and copper nanocomposite sensor strip using polymeric flexible substrate for highly sensitive and selective nonenzymatic glucose detection has been developed and tested for direct oxidization of glucose. The CuNPs were electrochemically deposited on to the graphene sheets to improve electron transfer rates and to enhance electrocatalytic activity toward glucose. The graphene based electrode with CuNPs demonstrated a high degree of sensitivity (1101.3 ± 56 μA/mM.cm2), excellent selectivity (without an interference with Ascorbic Acid, Uric Acid, Dopamine, and Acetaminophen), good stability with a linear response to glucose ranging from 0.1 mM to 0.6 mM concentration, and detection limits of 0.025 mM to 0.9 mM. Characterization of the electrodes was performed by scanning electron microscopy (FESEM and SEM). The electrochemical properties of the modified graphene electrodes were inspected by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and amperometry.

A novel and highly sensitive disposable glucose sensor strip was developed using direct laser engraved graphene (DLEG) decorated with pulse deposited copper nanocubes (CuNCs). The high reproducibility (96.8%), stability (97.4%) and low cost demonstrated by this 3-step fabrication method indicates that it could be used for high volume manufacturing of disposable glucose strips. The fabrication method also allows for a high degree of flexibility, allowing for control of the electrode size, design, and functionalization method. Additionally, the excellent selectivity and sensitivity (4,532.2 μA/mM.cm 2 ), low detection limit (250 nM), and suitable linear range of 25 μM–4 mM, suggests that these sensors may be a great potential platform for glucose detection within the physiological range for tear, saliva, and/or sweat.

As wearable healthcare monitoring systems advance, there is immense potential for biological sensing to enhance the management of type 1 diabetes (T1D). The aim of this work is to describe the ongoing development of biomarker analytes in the context of T1D. Technological advances in transdermal biosensing offer remarkable opportunities to move from research laboratories to clinical point‐of‐care applications. In this review, a range of analytes, including glucose, insulin, glucagon, cortisol, lactate, epinephrine, and alcohol, as well as ketones such as beta‐hydroxybutyrate, will be evaluated to determine the current status and research direction of those analytes specifically relevant to T1D management, using both in‐vitro and on‐body detection. Understanding state‐of‐the‐art developments in biosensing technologies will aid in bridging the gap from bench‐to‐clinic T1D analyte measurement advancement.

Although levodopa remains the most efficacious symptomatic therapy for Parkinson disease (PD), management of levodopa treatment during the advanced stages of the disease is extremely challenging. This difficulty is a result of levodopa’s short half-life, a progressive narrowing of the therapeutic window, and major inter-patient and intra-patient variations in the dose–response relationship. Therefore, a suitable alternative to repeated oral administration of levodopa is being sought. Recent research efforts have focused on the development of novel levodopa delivery strategies and wearable physical sensors that track symptoms and disease progression. However, the need for methods to monitor the levels of levodopa present in the body in real time has been overlooked. Advances in chemical sensor technology mean that the development of wearable and mobile biosensors for continuous or frequent levodopa measurements is now possible. Such levodopa monitoring could help to deliver personalized and timely medication dosing to alleviate treatment-related fluctuations in the symptoms of PD. Therefore, with the aim of optimizing therapeutic management of PD and improving the quality of life of patients, we share our vision of a future closed-loop autonomous wearable ‘sense-and-act’ system. This system consists of a network of physical and chemical sensors coupled with a levodopa delivery device and is guided by effective big data fusion algorithms and machine learning methods.In this Perspective, the authors present their vision for a closed-loop system for automatic symptom monitoring and levodopa administration in individuals with Parkinson disease. The system would capitalize on the ongoing advances in wearable sensor technology, drug delivery systems and machine learning.

Lab-Under-The-Skin based on a microneedle platform opens a new realm of possibilities that can shape the future of healthcare worldwide. From continuous monitoring to multiplexed measurements of numerous biochemical biomarkers, real-time measurements, remote monitoring/care, and actionable feedback to the wearer are parts of the possibilities to be realized in this realm. A microneedle-based wearable sensing platform is the closest system to realizing such a possibility in a pragmatically viable fashion. The pain-free, blood-free, minimally invasive microneedle tips gently access the revitalizing interstitial fluid (ISF) to initiate electrochemical transduction of the biochemical molecule of interest. Almost identically, ISF mimics the composition of the gold-standard blood, both chemically and temporally. ISF is considered the most reliable and clinically valid biosensing medium, especially in comparison to sweat, saliva, tear, urine, and stimulated ISF, and has a highly matured commercial and research track record. The present thesis first, introduces the historical development of microneedle-based biosensors. Next, for the first time, it unravels the engineering and scientific fundamentals that make the idea of the \"Lab-Under-The-Skin\" a practical reality. The writing then elaborates on additional biochemical biomarkers of interest and their sensing mechanism when used in a microneedle-based form factor. Lastly, the thesis portrays the future of the microneedle-based wearable sensing field with an example from the cutting-edge electrochemical aptamer-based microneedle biosensing.

In this study, the prevalence and spatial distribution of Newcastle disease, infectious bronchitis, and avian influenza have been evaluated in commercial broiler farms in 31 provinces in Iran. In this survey, a total of 233 affected broiler chicken farms were sampled. The infectious bronchitis virus (alone) was detected with highest frequency in 60 farms, and separately or combined with other agents, in 110 farms; Newcastle disease virus, separately, was detected in 28 farms, and in 63 farms separately or combined with other infectious agents; and avian influenza H9N2 was detected in 22 farms separately and in 51 farms separately or concomitant with other infectious agents. The sample tested negative for all H5 serotypes. The results of the present study show that the most prevalent avian viral infectious disease contributing to respiratory syndromes in broiler farms in Iran was infectious bronchitis due to infectious bronchitis virus serotypes variant 2 and 793/B. On the other hand, combined with the alternation of dominant viruses and circulating strains, flocks are exposed to unremitting anamorphic viral infections. Thus, the permanent monitoring of cases that have occurred and the review of vaccination plans of affected flocks every year are some of the necessary measures needed for strategic control of respiratory syndrome in broilers. It is noteworthy that execution of epidemiologic examinations on the cogent factors of prevalence of this syndrome and defeat of vaccination strategy in the flocks is urgent and has to be fulfilled on the definite causes of time.

In 2010, H5N8 highly pathogenic avian influenza (HPAI) viruses of the A/Goose/Guangdong/1/1996 lineage dramatically affected poultry and wild birds in Asia, Europe, and North America. In November 2016, HPAI H5N8 was detected in a commercial layer farm in Tehran province. The diagnosis was based on real-time reverse transcriptase PCR (RRT-PCR) and sequencing of haemaglutinin (HA) and neuraminidase (NA) genes from suspected samples. Genetic and phylogenetic analysis of the HA gene demonstrated that the Iranian HPAI H5N8 viruses belong to the HPAI H5 virus clade 2.3.4.4 and cluster within group B (Gochang-like). In particular, the highest similarity was found with the sequences of the HPAI H5N8 identified in Russia in 2016. To our knowledge, this clade has not been previously detected in Iran. Previous HPAI A (H5) epidemic in Iran occurred in 2015 and involved exclusively viruses of clade 2.3.2.1c. These findings indicate that Iran is at high risk of introduction of HPAI H5 of the A/Goose/Guangdong/1/1996 lineage from East Asia and highlight the need to maintain adequate monitoring activities in target wild and domestic bird species for HPAI early detection. This study is useful for better understanding the genetic and antigenic evolution of H5 HPAI viruses in the region and the world.