A wearable microfluidic system for efficient sweat collection and real-time detection.

Sweat is an important biofluid with rich physiological information that can evaluate human health condition. Wearable sweat sensors have received widespread attention in recent years due to the benefits of non-invasive, continuous, and real-time monitoring. Currently, an efficient device integrating sweat collection and detection is still needed. Here, a wearable sweat microfluidic system was fabricated for real-time collection and analysis of sweat. The fabricated microfluidic system consisted of four layers, including a skin adhesive layer, a microfluidic layer, an electrode layer, and a capping layer. The sweat collection rate was around 0.79 µL/min, which demonstrated efficient sweat sampling, storage, and refreshing capabilities. Simultaneous detection of multiple sweat biomarkers was achieved with a screen-printed sweat sensing array, which could realize high-precision detection of Na+, K+, and glucose. Moreover, the sensing array also showed good repeatability and stability, with a relative standard deviation of sensitivity of less than 5%. Additionally, human testing was conducted to demonstrate that this microfluidic system can continuously monitor Na+, K+, and glucose in subjects' sweat during exercise, which showed high potential for non-invasive human health monitoring.

A nanonewton-scale biomimetic mechanosensor.

Biomimetic mechanosensors have profound implications for various areas, including health care, prosthetics, human‒machine interfaces, and robotics. As one of the most important parameters, the sensitivity of mechanosensors is intrinsically determined by the detection resolution to mechanical force. In this manuscript, we expand the force detection resolution of current biomimetic mechanosensors from the micronewton to nanonewton scale. We develop a nanocrack-based electronic whisker-type mechanosensor that has a detection resolution of 72.2 nN. We achieve the perception of subtle mechanical stimuli, such as tiny objects and airflow, and the recognition of surface morphology down to a 30 nm height, which is the finest resolution ever reported in biomimetic mechanosensors. More importantly, we explore the use of this mechanosensor in wearable devices for sensing gravity field orientation with respect to the body, which has not been previously achieved by these types of sensors. We develop a wearable smart system for sensing the body's posture and movements, which can be used for remote monitoring of falls in elderly people. In summary, the proposed device offers great advantages for not only improving sensing ability but also expanding functions and thus can be used in many fields not currently served by mechanosensors.

Exhaled metabolic markers and relevant dysregulated pathways of lung cancer: a pilot study.

INTRODUCTION: The clinical application of lung cancer detection based on breath test is still challenging due to lack of predictive molecular markers in exhaled breath. This study explored potential lung cancer biomarkers and their related pathways using a typical process for metabolomics investigation. MATERIAL AND METHODS: Breath samples from 60 lung cancer patients and 176 healthy people were analyzed by GC-MS. The original data were GC-MS peak intensity removing background signal. Differential metabolites were selected after univariate statistical analysis and multivariate statistical analysis based on OPLS-DA and Spearman rank correlation analysis. A multivariate PLS-DA model was established based on differential metabolites for pattern recognition. Subsequently, pathway enrichment analysis was performed on differential metabolites. RESULTS: The discriminant capability was assessed by ROC curve of whom the average AUC and average accuracy in 100-fold cross validations were 0.871 and 0.787, respectively. Eight potential biomarkers were involved in a total of 18 metabolic pathways. Among them, 11 metabolic pathways have p-value smaller than .1. DISCUSSION: Some pathways among them are related to risk factors or therapies of lung cancer. However, more of them are dysregulated pathways of lung cancer reported in studies based on genome or transcriptome data. CONCLUSION: We believe that it opens the possibility of using metabolomics methods to analyze data of exhaled breath and promotes involvement of knowledge dataset to cover more volatile metabolites. CLINICAL SIGNIFICANCE: Although a series of related research reported diagnostic models with highly sensitive and specific prediction, the clinical application of lung cancer detection based on breath test is still challenging due to disease heterogeneity and lack of predictive molecular markers in exhaled breath. This study may promote the clinical application of this technique which is suitable for large-scale screening thanks to its low-cost and non-invasiveness. As a result, the mortality of lung cancer may be decreased in future.Key messagesIn the present study, 11 pathways involving 8 potential biomarkers were discovered to be dysregulated pathways of lung cancer.We found that it is possible to apply metabolomics methods in analysis of data from breath test, which is meaningful to discover convinced volatile markers with definite pathological and histological significance.

[Development of sensitive-micro RF coils in desktop MRI systems].

A RF coil (or probe) is one of the key components in NMR spectrometers and MRI systems, and designing a quality RF coil is a cheaper way to improves the signal-to-noise ratio (SNR) of systems and image quality. According to different applications there are a variety of RF coils. This article describes high-sensitive micro RF coils used in NMR spectrometers specially for test-tube samples. Their performance has been verified on the desktop MRI systems.