Real-time Activity Monitoring Research Articles

Soft Electrodes for Electrochemical and Electrophysiological Monitoring of Beating Cardiomyocytes.

Many cells in vivo have their inherent motions, which involve numerous biochemical and biophysical signals synergistically regulating cell behavior and function. However, existing methods offer little information about the concurrently chemical and physical responses of dynamically pulsing cells. Here, we report a soft electrode with an electrospun poly(3,4-ethylenedioxythiophene) (PEDOT)-based nanomesh to fully comply with spontaneous motions of cells. Moreover, this electrode demonstrated excellent electrical conductivity, electrochemical performance and cellular biocompatibility. Cardiomyocytes cultured thereon exhibited autonomous and rhythmic contractility, and synchronously induced mechanical deformation of the underlying electrode, which allowed real-time monitoring of nitric oxide release and electrophysiological activity of cardiomyocytes. This work provides a promising way toward recording chemical and electrical signals of biological systems with their natural motions.

Modulating the Biomimetic and Fluorescence Quenching Activities of Metal-Organic Framework/Platinum Nanoparticle Composites and Their Applications in Molecular Biosensing.

Nanoscale metal-organic frameworks (nMOFs) have gained considerable attention with significant potential applications. Although great efforts have been devoted to designing and fabricating nanoscaffold structures, approaches of deliberately regulating the intrinsic functionality of nMOFs have been poorly explored. Herein, we report a simple and novel strategy to regulate the catalytic and fluorescence quenching behaviors of nMOFs through coordination-driven self-assembly. As a proof-of-concept, we synthesized a synergistic and stable MOF-metal nanocomposite by loading platinum nanoparticles (PtNPs) on a commonly used Fe-MOF, i.e., MIL-88B-NH2/Pt, as a MOF composite model for exploration. On one hand, the complexation with ATP effectively broke the pH limitation of the peroxidase-mimicking MIL-88B-NH2/Pt nanozyme, bringing a 10-fold increased catalytic activity under alkaline condition. Based on the distinct catalytic enhancement between ATP and other nucleotides, real-time monitoring of apyrase activity as well as colorimetric detection of alkaline phosphatase (ALP) was performed. On the other hand, interactions of MIL-88B-NH2/Pt with fluorescent DNA were tolerant of different nucleic acids and, more importantly, were further manipulated by inorganic molecules. As a result, H2O2 could only trigger the release of a G-rich sequence, while phosphates could readily induce desorption of various DNA molecules with varying lengths, sequences, and fluorescent dyes. Accordingly, fluorescent DNA and MIL-88B-NH2/Pt as functional probe-quencher pairs were proposed, allowing the establishment of a fluorescence bioassay for ALP and PPase detection and Boolean logic calculations. This work offers a means to tune the intrinsic activities of nMOFs by surface engineering, benefiting design of functional nanomaterials and development of advanced biosensing systems.

Monitoring Methionine Decarboxylase by a Supramolecular Tandem Assay.

Methionine is an essential amino acid involved in many physiological and pathological processes. Methionine starvation caused by methionine decarboxylase (MetDC) degradation becomes a promising strategy for cancer treatment. Multistep colorimetric method, the present approach to monitor the MetDC activity, possesses drawbacks of the complicated process, low accuracy, and poor anti-interference due to indirect detection. Herein, we report a facile and easy-to-use supramolecular tandem assay (STA) with the cucurbit[7]uril and acridine orange reporter pair for the direct and real-time monitoring of MetDC activity. This strategy not only provides a feasible method for enzymatic activity detection but also establishes the capability of inhibitor screening.

The use of real-time passive cavitation imaging for monitoring boiling histotripsy treatments

Boiling histotripsy (BH) is a high intensity focused ultrasound method that induces mechanical tissue liquefaction and relies on the formation of a mm-sized vapor bubble at the focus. One challenge of transcutaneous BH is to confirm the presence of such bubble and to differentiate it from prefocal cavitation. Strong prefocal cavitation can shield the focus, prevent initiation of boiling, and lead to unsuccessful treatment, although an echogenic region would still be present on B-mode ultrasound images. Here, a methodology for real-time monitoring of different bubble activity during BH treatment is proposed. Custom BH systems of 1 and 1.5 MHz with inline ultrasound imaging probes connected to a Verasonics V1 system were used for BH treatments in pigs in vivo and in ex vivo tissues. Backscattered signals arriving to the imaging probe were recorded during the 10 ms BH pulses delivered at 1 Hz and passive cavitation imaging (PCI) reconstruction was performed and displayed on top of the B-mode images to identify and classify the regions of bubble activity. Spectral analysis of the PCI signals promoting prefocal cavitation and lack thereof was performed to identify the spectral features corresponding to prefocal cavitation and vapor bubble formation. [Work supported by NIH R01EB007643, R01GM122859, and R01EB25187.]

Ultrasensitive Pressure Sensor Sponge Using Liquid Metal Modulated Nitrogen-Doped Graphene Nanosheets.

Wearable pressure sensors are crucial for real-time monitoring of human activities and biomimetic robot status. Here, the ultrasensitive pressure sensor sponge is prepared by a facile method, realizing ultrasensitive pressure sensing for wearable health monitoring. Since the liquid metal in the sponge-skeleton structure under pressure is conducive to adjust the contact area with nitrogen-doped graphene nanosheets and thus facilitates the charge transfer at the interface, such sensors exhibit a fast response and recovery speed with the response/recovery time 0.41/0.12 s and a comprehensive response range with a sensitivity of up to 476 KPa-1. Notably, the liquid metal-based spongy pressure sensor can accurately monitor the human body's pulse, the pressure on the skin, throat swallowing, and other activities in real time, demonstrating a broad application prospect. Those results provide a convenient and low-cost way to fabricate easily perceptible pressure sensors, expanded the application potential of liquid metal-based composites for future electronic skin development.

Tannic acid-Fe3+ activated rapid polymerization of ionic conductive hydrogels with high mechanical properties, self-healing, and self-adhesion for flexible wearable sensors

Wearable sensors based on hydrogels have been rapidly developed in many fields such as electronic skin, health detection, and human-machine interface. Wearable sensors for real-time monitoring of human activities require hydrogels with desirable mechanical strength, self-healing ability, sensing stability, and self-adhesion. However, to meet all these mentioned requirements, the preparation process of hydrogels is always complicated and time-consuming. Herein, rapid polymerization hydrogels (PATG-B-Fe) for wearable sensors were designed from bacterial cellulose nanowhisker (BCW), tannic acid (TA), polyacrylic acid (PAA), Fe3+ and glycerol/water (Gly/H2O). The dual catalysis system of TA-Fe3+ and Gly remarkably shortened the reaction time to 4 s at ambient temperature. With multiple hydrogen bonds and coordination among BCW-TA, PAA, and Fe3+, hydrogels exhibited an excellent trade-off between mechanical (stress of 203 kPa, elongation at break of 1950%) and self-healing property (91% of efficiency). Strain sensors based on PATG-B-Fe hydrogels had good sensitivity (Gauge factor, maximum GF = 5.2 in 1200–1900% strain) and stable sensing properties at a wide temperature range (−20–60 °C). Furthermore, strain sensors were adhered directly to skin to monitor large and subtle human movements. We believe PATG-B-Fe sensors may be a new horizon for the development of wearable and flexible electronic devices in the future.

Development of a novel latent electrochemical molecular substrate for the real-time monitoring of the tumor marker aminopeptidase N in live cells, whole blood and urine

Aminopeptidase N (APN/CD13) plays an important role in the growth and metastasis, of tumor, and is a potential biomarker for the post-treatment surveillance of cancer reoccurrence and progression of various malignancies. Thus, we have designed and prepared a convenient and ultrasensitive APN-targeting activity-based ratiometric electrochemical molecular substrate (Ala-AFC) for direct real-time monitoring of APN activity in biosamples. The APN in our experiment was used to hydrolyze the alanine moiety of the Ala-AFC probe and, as a result of this hydrolysis, realize concomitantly a cascade reaction to unmask the electrochemical reporter N-alkylated amino ferrocene (AAF). The Ala-AFC probe exhibited high sensitivity with a wide detection range of 0.05–110 ng mL-1 and a low limit of detection of 23.18 pg mL-1. The electrochemical signals were found to be distinctly specific for APN and free of interference from other electroactive biological species. Furthermore, the Ala-AFC probe was employed to monitor and quantify, in real-time, the activity of APN in tumor cells, whole blood, and urine. In addition, the results of our direct electrochemical quantifications of the amount of APN in whole blood and urine were found to be consistent with the results of the use of commercially available fluorometric assay kits to sense APN in serum and urine. Thus our approach shows promise as a point-of-care tool for cancer diagnostics and post-treatment surveillance of cancer reoccurrence.

Simultaneous Biomechanical and Biochemical Monitoring for Self-Powered Breath Analysis.

The high moisture level of exhaled gases unavoidably limits the sensitivity of breath analysis via wearable bioelectronics. Inspired by pulmonary lobe expansion/contraction observed during respiration, a respiration-driven triboelectric sensor (RTS) was devised for simultaneous respiratory biomechanical monitoring and exhaled acetone concentration analysis. A tin oxide-doped polyethyleneimine membrane was devised to play a dual role as both a triboelectric layer and an acetone sensing material. The prepared RTS exhibited excellent ability in measuring respiratory flow rate (2-8 L/min) and breath frequency (0.33-0.8 Hz). Furthermore, the RTS presented good performance in biochemical acetone sensing (2-10 ppm range at high moisture levels), which was validated via finite element analysis. This work has led to the development of a novel real-time active respiratory monitoring system and strengthened triboelectric-chemisorption coupling sensing mechanism.

High-throughput assay of tyrosine phenol-lyase activity using a cascade of enzymatic reactions

Tyrosine phenol-lyase (TPL) exhibits great potential in industrial biosynthesis of l-tyrosine and its derivates. To uncover and screen TPLs with excellent catalytic properties, there is unmet demand for development of facile and reliable screening system for TPL. Here we presented a novel assay format for the detection of TPL activity based on catechol 2,3-dioxygenase (C23O)-catalyzed reaction. Catechol released from TPL-catalyzed cleavage of 3,4-dihydroxy-l-phenylalanine (l-DOPA) was further oxidized by C23O to form 2-hydroxymuconate semialdehyde, which could be readily detected by spectrophotometric measurements at 375 nm. The assay achieved a unique balance between the ease of operation and superiority of analytical performances including linearity, sensitivity and accuracy. In addition, this assay enabled real-time monitoring of TPL activity with high efficiency and reliability. As C23O is highly specific towards catechol, a non-natural product of microorganism, the assay was therefore accessible to both crude cell extracts and the whole-cell system without elaborate purification steps of enzymes, which could greatly expedite discovery and engineering of TPLs. This study provided fundamental principle for high-throughput screening of other enzymes consuming or producing catechol derivatives.

A Model for Research of Transitions among Different Care Settings in Smart Lifetime Neighbourhoods

Neighbourhoods in EU member states are ageing, increasingly becoming the subjects of geo-gerontology and supply network analyses. Geo-gerontological aspects of the care and supply networks are becoming essential in the processes of deinstitutionalisation of long-term care and services and are crucial for the successful development and implementation of Ambient Assisted Living technologies (AAL_T). A growing number of older adults suffer from declining functional capacities and, thereby, experience decreased mobility and increasing frailty, which can lead to difficulties in carrying out essential activities of daily living as well as increased exposure to the risk of falls. Aid in managing one's daily life needs to be provided on time and in a properly built environment. Ambient intelligence for real-time monitoring of daily activities and supporting older residents with AAL_T will become essential means by which ageing cities will be able to maintain and improve the quality of life for older adults with declining functional capacities. This development will further influence the delineation of service areas and the timing of services. AAL_T and ambient intelligence will enable older adults to live longer in their dwellings and specialised facilities in the community and postpone or even avoid relocation to a nursing home altogether. Development in AAL_T has raised the possibility of developing more efficient services if the functional area of service networks is optimised. Based on these developments, we propose the adaptation of a multi-state competing risk model based on time to failure as modelled in reliability engineering to model and control the trajectories of declining functional capacities and related events that lead to the ill-health and disabilities. In this model, the built environment and timing in service networks are supposed to be embedded. The final goal of such a model is to support decision making that would extend the physically and mentally active life of seniors and enable them to live autonomously and be engaged with their communities. This paper aims to review the development of condition monitoring systems in ambient technologies, shape the model and propose a future research agenda.

Epileptic Seizure Detection Using Brain-Rhythmic Recurrence Biomarkers and ONASNet-Based Transfer Learning.

The electroencephalogram (EEG) tool has great potential for real-time monitoring of abnormal brain activities, such as preictal and ictal seizures. Developing an EEG-based detection system for patients with epilepsy is vital for clinical management and targeted therapy. This paper proposes a single-channel seizure detection system using brain-rhythmic recurrence biomarkers (BRRM) and an optimized model (ONASNet). BRRM is a direct mapping of the recurrence morphology of brain rhythms in phase space; it reflects the nonlinear dynamics of original EEG signals. The architecture of ONASNet is determined through a modified neural network searching strategy. Then, we exploited transfer learning to apply ONASNet to our EEG data. The combination of BRRM and ONASNet leverages the multiple channels of a neural network to extract features from different brain rhythms simultaneously. We evaluated the efficiency of BRRM-ONASNet on the real EEG recordings derived from Bonn University. In the experiments, different transfer-learning models (TLMs) are respectively constructed using ONASNet and seven well-known neural network structures (VGG16/VGG19/ResNet50/InceptionV3/DenseNet121/Xception/NASNet). Moreover, we compared those TLMs by model size, computing complexity, learning capability, and prediction latency. ONASNet outperforms other structures by strong learning capability, high stability, small model size, short latency, and less requirement of computing resources. Comparing BRRM-ONASNet with other existing methods, our work performs better than others with 100% accuracy under the identical dataset and same detection task. Contributions: The proposed method in this study, analyzing nonlinear features from phase-space representations using a deep neural network, provides new insights for EEG decoding. The successful application of this method in epileptic-seizure detection contributes to computationally medical assistance for epilepsy.

All-fiber-transmission photometry for simultaneous optogenetic stimulation and multi-color neuronal activity recording

Manipulating and real-time monitoring of neuronal activities with cell-type specificity and precise spatiotemporal resolution during animal behavior are fundamental technologies for exploring the functional connectivity, information transmission, and physiological functions of neural circuits<italic>in vivo</italic>. However, current techniques for optogenetic stimulation and neuronal activity recording mostly operate independently. Here, we report an all-fiber-transmission photometry system for simultaneous optogenetic manipulation and multi-color recording of neuronal activities and the neurotransmitter release in a freely moving animal. We have designed and manufactured a wavelength-independent multi-branch fiber bundle to enable simultaneous optogenetic manipulation and multi-color recording at different wavelengths. Further, we combine a laser of narrow linewidth with the lock-in amplification method to suppress the optogenetic stimulation-induced artifacts and channel crosstalk. We show that the collection efficiency of our system outperforms a traditional epi-fluorescence system. Further, we demonstrate successful recording of dynamic dopamine (DA) responses to unexpected rewards in the nucleus accumbens (NAc) in a freely moving mouse. We also show simultaneous dual-color recording of neuronal Ca²⁺ signals and DA dynamics in the NAc upon delivering an unexpected reward and the simultaneous optogenetic activating at dopaminergic terminals in the same location. Thus, our multi-function fiber photometry system provides a compatible, efficient, and flexible solution for neuroscientists to study neural circuits and neurological diseases.

Activity Detection for the Wellbeing of Dogs Using Wearable Sensors Based on Deep Learning

Among pets, dogs are very famous in the whole world. The owners of dogs are very cautious about the well-being of dogs. The well-being of dogs can be ensured by continuous monitoring of their activities. Studies related to activity detection have gained much popularity due to the significant progress in sensor technology during the last few years. Automatic monitoring of pet applications includes real-time monitoring systems and surveillance which detect the pets with high accuracy using the latest pet activity classification techniques. The revolution in the domain of technology has allowed us to obtain better results using conventional techniques. Convolutional neural networks (CNNs) 1D recently become a cutting-edge approach for signal processing-based systems such as patient-individual ECG categorization, sensor-based health monitoring systems, and anomaly identification in manufacturing areas. Adaptive and compact 1D models have several advantages over their conventional 2D counterparts. A limited dataset is sufficient to train a 1D CNN efficiently while 2D CNNs require a plethora of data for training. Its architecture is not very complicated, so it is suitable for real-time detection of activities. The main goal of this study is to develop a state-of-the-art system that can detect and classify the activities based on sensors’ data (accelerometer, and gyroscope. We proposed a 1D CNN-based system for pet activity detection. The objective of this study was to recognize ten pet activities such as walking, sitting, down, staying, eating, sideway, jumping, running, shaking, and nose work respectively, using wearable sensor devices based on deep learning technique. The data collection procedure for this study was conducted with 10 dogs of different breeds, sex (male=7, female = 3), age (age = 4±3), and sizes (small, medium, large) in a healthy environment. After collecting the data, the following steps, namely data synchronization, and data preprocessing were considered to remove the irrelevant data from the dataset. To overcome imbalanced problems in the dataset we used the class-weight technique. Subsequently, we applied 1D CNN algorithm using the class-weight technique. The model with the class-weight technique showed 99.70% training accuracy and 96.85% validation accuracy. The 1D CNN approach will be helpful for real-time monitoring of activities and for tracing the behavior of dogs.

Real-time monitoring of occupancy activities and window opening within buildings using an integrated deep learning-based approach for reducing energy demand

Occupancy behaviour in buildings can impact the energy performance and operation of heating, ventilation and air-conditioning (HVAC) systems. HVAC, which uses conventional control strategies or “fixed” setpoint schedules, could not adjust to the conditioned spaces' actual requirements, resulting in building spaces being over or under-conditioned. While the unintended opening of windows can lead to substantial heat loss and consequently raises energy consumption. To optimise building operations, it is necessary to employ solutions such as demand-driven controls, which can monitor the utilisation of indoor spaces and provide the actual thermal comfort requirements of occupants. This study presents a novel vision-based deep learning framework for occupancy activity detection and recognition including the manual window operations in buildings. A region-based Convolutional Neural Network (R-CNN) model was trained and deployed to a camera for real-time detection and recognition. Based on the field experiments conducted within a case study University building, overall accuracy of 85.63% was achieved for occupancy activity detection and 92.20% for window operation detection. Building energy simulation and various scenario-based cases were used to assess the impact of such an approach on the building energy demand and provide insights into how the proposed detection method can enable HVAC systems to respond to dynamic changes within indoor spaces. Results showed that the proposed approach could reduce the over-or under-estimation of occupancy heat gains compared with the use of “fixed” or static profiles. In addition, the approach can help alert building users or managers about windows left open unintentionally, which can reduce unnecessary ventilation heat losses. Furthermore, the approach can also predict the room CO2 concentration and advise occupants about a suitable natural ventilation strategy. The study highlighted the potential of the multi-purpose detection approach, but further development is necessary, including optimisation of the deep learning model, full integration with HVAC controls and further model training and field testing.

The Basolateral Amygdala Mediates the Role of Rapid Eye Movement Sleep in Integrating Fear Memory Responses.

The basolateral amygdala (BLA) mediates the effects of stress and fear on rapid eye movement sleep (REM) and on REM-related theta (θ) oscillatory activity in the electroencephalograph (EEG), which is implicated in fear memory consolidation. We used optogenetics to assess the potential role of BLA glutamate neurons (BLAGlu) in regulating behavioral, stress and sleep indices of fear memory, and their relationship to altered θ. An excitatory optogenetic construct targeting glutamatergic cells (AAV-CaMKIIα-hChR2-eYFP) was injected into the BLA of mice. Telemetry was used for real-time monitoring of EEG, activity, and body temperature to determine sleep states and stress-induced hyperthermia (SIH). For 3 h following shock training (ST: 20 footshocks, 0.5 mA, 0.5 s, 1 min interval), BLA was optogenetically stimulated only during REM (REM + L) or NREM (NREM + L). Mice were then re-exposed to the fear context at 24 h, 48 h, and 1 week after ST and assessed for behavior, SIH, sleep and θ activity. Control mice were infected with a construct without ChR2 (eYFP) and studied under the same conditions. REM + L significantly reduced freezing and facilitated immediate recovery of REM tested at 24 h and 48 h post-ST during contextual re-exposures, whereas NREM + L had no significant effect. REM + L significantly reduced post-ST REM-θ, but attenuated REM-θ reductions at 24 h compared to those found in NREM + L and control mice. Fear-conditioned SIH persisted regardless of treatment. The results demonstrate that BLAGlu activity during post-ST REM mediates the integration of behavioral and sleep indices of fear memory by processes that are associated with θ oscillations within the amygdalo-hippocampal pathway. They also demonstrate that fear memories can remain stressful (as indicated by SIH) even when fear conditioned behavior (freezing) and changes in sleep are attenuated.

Preliminary Analysis of a Wireless and Wearable Electronic-Textile EASI-Based Electrocardiogram

Background: With cardiovascular disease continuing to be the leading cause of death and the primary reason for hospitalization worldwide, there is an increased burden on healthcare facilities. Electronic-textile (e-textile)-based cardiac monitoring offers a viable option to allow cardiac rehabilitation programs to be conducted outside of the hospital.Objectives: This study aimed to determine whether signals produced by an e-textile ECG monitor with textile electrodes in an EASI configuration are of sufficient quality to be used for cardiac monitoring. Specific objectives were to investigate the effect of the textile electrode characteristics, placement, and condition on signal quality, and finally to compare results to a reference ECG obtained from a current clinical standard the Holter monitor.Methods: ECGs during different body movements (yawning, deep-breathing, coughing, sideways, and up movement) and activities of daily living (sitting, sitting/standing from a chair, and climbing stairs) were collected from a baseline standard of normal healthy adult male using a novel e-textile ECG and a reference Holter monitor. Each movement or activity was recorded for 5 min with 2-min intervals between each recording. Three different textile area electrodes (40, 60, and 70 mm2) and electrode thicknesses (3, 5, and 10 mm) were considered in the experiment. The effect of electrode placement within the EASI configuration was also studied. Different signal quality parameters, including signal to noise ratio, approximate entropy, baseline power signal quality index, and QRS duration and QT intervals, were used to evaluate the accuracy and reliability of the textile-based ECG monitor.Results: The overall signal quality from the 70 mm2 textile electrodes was higher compared to the smaller area electrodes. Results showed that the ECGs from 3 and 5 mm textile electrodes showed good quality. Regarding location, placing the “A” and “I” electrodes on the left and right anterior axillary points, respectively, showed higher signal quality compared to the standard EASI electrode placement. Wet textile electrodes showed better signal quality compared to their dry counterparts. When compared to the traditional Holter monitor, there was no significant difference in signal quality, which indicated textile monitoring was as good as current clinical standards (non-inferior).Conclusion: The e-textile EASI ECG monitor could be a viable option for real-time monitoring of cardiac activities. A clinical trial in a larger sample is recommended to validate the results in a clinical population.

Remote Monitoring of the Performance Status and Burden of Symptoms of Patients With Gastrointestinal Cancer Via a Consumer-Based Activity Tracker: Quantitative Cohort Study.

BackgroundThe number of older patients with gastrointestinal cancer is increasing due to an aging global population. Minimizing reliance on an in-clinic patient performance status test to determine a patient’s prognosis and course of treatment can improve resource utilization. Further, current performance status measurements cannot capture patients' constant changes. These measurements also rely on self-reports, which are subjective and subject to bias. Real-time monitoring of patients' activities may allow for a more accurate assessment of patients’ performance status while minimizing resource utilization.ObjectiveThis study investigates the validity of consumer-based activity trackers for monitoring the performance status of patients with gastrointestinal cancer.MethodsA total of 27 consenting patients (63% male, median age 58 years) wore a consumer-based activity tracker 7 days before chemotherapy and 14 days after receiving their first treatment. The provider assessed patients using the Eastern Cooperative Oncology Group Performance Status (ECOG-PS) scale and Memorial Symptom Assessment Scale-Short Form (MSAS-SF) before and after chemotherapy visits. The statistical correlations between ECOG-PS and MSAS-SF scores and patients’ daily step counts were assessed.ResultsThe daily step counts yielded the highest correlation with the patients' ECOG-PS scores after chemotherapy (P<.001). The patients with higher ECOG-PS scores experienced a higher fluctuation in their step counts. The patients who walked more prechemotherapy (mean 6071 steps per day) and postchemotherapy (mean 5930 steps per day) had a lower MSAS-SF score (lower burden of symptoms) compared to patients who walked less prechemotherapy (mean 5205 steps per day) and postchemotherapy (mean 4437 steps per day).ConclusionsThis study demonstrates the feasibility of using inexpensive, consumer-based activity trackers for the remote monitoring of performance status in the gastrointestinal cancer population. The findings need to be validated in a larger population for generalizability.

A tough hydrogel with fast self-healing and adhesive performance for wearable sensors

The purpose of this work is to address the two existing challenges. One is to achieve the balance of mechanical properties, adhesion, and self-healing ability in hydrogel used in wearable devices. The other is to use mature products as raw materials and simplify the preparation process of adhesive hydrogels, so as to make it possible for large-scale industrial production. A novel PAA/Fe/PVP hydrogel has been prepared by a simple one-step radical polymerization to meet the above requirements. As the main component of adhesives in daily life, PVP is used to improve the adhesion of the hydrogel. The adhesion as high as 64 kPa is achieved in the hydrogel. The adhesion can also withstand multiple uses due to the good mechanical properties of the hydrogel. Furthermore, the hydrogel displays outstanding self-healing ability in terms of both mechanical properties and conductivity. Because of the good mechanical properties, robust adhesion and rapid self-healing ability, the hydrogel-based sensors have demonstrated stability, accuracy and reliability in real-time monitoring of subtle facial micro-expressions and large human activities. In addition, the method uses mature products as raw materials, and the preparation process is simple, so it has the potential for large-area and low-cost production.

Ethylenediamine derivatives efficiently react with oxidized RNA 3' ends providing access to mono and dually labelled RNA probes for enzymatic assays and in vivo translation.

Development of RNA-based technologies relies on the ability to detect, manipulate, and modify RNA. Efficient, selective and scalable covalent modification of long RNA molecules remains a challenge. We report a chemical method for modification of RNA 3′-end based on previously unrecognized superior reactivity of N-substituted ethylenediamines in reductive amination of periodate-oxidized RNA. Using this method, we obtained fluorescently labelled or biotinylated RNAs varying in length (from 3 to 2000 nt) and carrying different 5′ ends (including m7G cap) in high yields (70–100% by HPLC). The method is scalable (up to sub-milligrams of mRNA) and combined with label-facilitated HPLC purification yields highly homogeneous products. The combination of 3′-end labelling with 5′-end labelling by strain-promoted azide-alkyne cycloaddition (SPAAC) afforded a one-pot protocol for site-specific RNA bifunctionalization, providing access to two-colour fluorescent RNA probes. These probes exhibited fluorescence resonance energy transfer (FRET), which enabled real-time monitoring of several RNA hydrolase activities (RNase A, RNase T1, RNase R, Dcp1/2, and RNase H). Dually labelled mRNAs were efficiently translated in cultured cells and in zebrafish embryos, which combined with their detectability by fluorescent methods and scalability of the synthesis, opens new avenues for the investigation of mRNA metabolism and the fate of mRNA-based therapeutics.

An In Situ Fluorescence Assay for Cholesterol Transporter Activity of the Patched.

We recently developed a simultaneous in situ quantitative imaging technique for cholesterol in both leaflets of the plasma membrane of mammalian cells. This ratiometric fluorescence technique allows real-time monitoring of the cholesterol transporter activity of plasma membrane-resident proteins in living cells. When applied to the hedgehog signaling system, it enables direct quantitative measurement of the cholesterol transporter activity of Patched1 and the effect of the hedgehog ligand on this activity.