Rapid Sample Pretreatment Facilitating SERS Detection of Trace Weak Organic Acids/Bases in Simple Matrices.

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for highly sensitive qualitative and quantitative analyses of trace targets. However, sensitive SERS detection can only be facilitated with a suitable sample pretreatment in fields related to trace amounts for food safety and clinical diagnosis. Currently, the sample pretreatment for SERS detection is normally borrowed and improved from the ones in the lab, which yields a high recovery but is tedious and time-consuming. Rapid detection of trace targets in a complex environment is still a considerable issue for SERS detection. Herein, we proposed a liquid-liquid extraction method coupled with a back-extraction method for sample pretreatment based on the pH-sensitive reversible phase transition of the weak organic acids and bases, where the lowest detectable concentrations were identical before and after the pretreatment process. The sensitive (µg L-1 level) and rapid (within 5 min) SERS detection of either koumine, a weak base, or celastrol, a weak acid, was demonstrated in different drinking water samples and beverages. Furthermore, target generality was demonstrated for a variety of weak acids and bases (2 < pKa < 12), and the hydrophilicity/hydrophobicity of the target determines the pretreatment efficiency. Therefore, the LLE-BE coupled SERS was developed as an easy, rapid, and low-cost tool for the trace detection of the two types of targets in simple matrices, which paved the way toward trace targets in complex matrices.

Signal2signal: Pushing the Spatiotemporal Resolution to the Limit by Single Chemical Hyperspectral Imaging.

There is growing interest in developing a high-performance self-supervised denoising algorithm for real-time chemical hyperspectral imaging. With a good understanding of the working function of the zero-shot Noise2Noise-based denoising algorithm, we developed a self-supervised Signal2Signal (S2S) algorithm for real-time denoising with a single chemical hyperspectral image. Owing to the accurate distinction and capture of the weak signal from the random fluctuating noise, S2S displays excellent denoising performance, even for the hyperspectral image with a spectral signal-to-noise ratio (SNR) as low as 1.12. Under this condition, both the image clarity and the spatial resolution could be significantly improved and present an almost identical pattern with a spectral SNR of 7.87. The feasibility of real-time denoising during imaging was well demonstrated, and S2S was applied to monitor the photoinduced exfoliation of transition metal dichalcogenide, which is hard to accomplish by confocal Raman spectroscopy. In general, the real-time denoising capability of S2S offers an easy way toward in situ/in vivo/operando research with much improved spatial and temporal resolution. S2S is open-source at https://github.com/3331822w/Signal2signal and will be accessible online at https://ramancloud.xmu.edu.cn/tutorial.

Positively Charged Silver and Gold Nanoparticles with Controllable Size Distribution for SERS Detection of Negatively Charged Molecules.

Surface-enhanced Raman spectroscopy (SERS) has been demonstrated as an ultrasensitive tool for various molecules. However, for the negatively charged molecules, the widely used SERS substrate [negatively charged Ag and Au nanoparticles (Ag or Au NPs (-)] showed either low sensitivity or poor stability. The best solution is to synthesize positively charged silver or gold nanoparticles [Ag or Au NPs (+)] with high stability and excellent SERS performance, which are currently unavailable. To this end, we revitalized the strategy of "charge reversal and seed growth". By selection of ascorbic acid as the reductant and surfactant, the surface charge of Ag or Au NP (-) seeds is adjusted to a balanced state, where the surface charge is negative enough to satisfy the stabilization of the NPs (-) but does not hinder the subsequent charge reversal. By optimization of the chain length and electric charge of polyamine molecules, the highly stable and size-controllable uniform Ag NPs (+) and Au NPs (+) were seed-growth synthesized with high reproducibility. More importantly, the SERS performance of both Ag NPs (+) and Au NPs (+) achieved the trace detection of negatively charged molecules at the level of 1 µg/L, demonstrating an improved SERS sensitivity of up to 3 orders of magnitude compared to the previously reported sensitivity. Promisingly, the introduction of polyamine-capped Ag NPs (+) and Au NPs (+) as SERS substrates with high stability (1 year shelf life) will significantly broaden the application of SERS.

Revealing Trace Nanoplastics in Food Packages─An Electrochemical Approach Facilitated by Synergistic Attraction of Electrostatics and Hydrophobicity.

Most food packages are made of plastics, nanoplastics released from which can be directly ingested and induce serious damage to organisms. Therefore, it is urgent to develop an effective and convenient method for nanoplastic determinations in food packages. In this work, we present a sandwich-based electrochemical strategy for nanoplastic determination. Positively charged Au nanoparticles were coated onto a Au electrode to selectively capture negatively charged nanoplastics in an aqueous environment. Subsequently, the nanoplastics were recognized by the signal molecule ferrocene via the hydrophobic interaction and determined by differential pulse voltammetry. Our sandwich-type detection depends on both electronegativity and hydrophobicity of nanoplastics, which make the method applicable for the assays of packages made of widely commercialized polystyrene (PS), polypropylene (PP), polyethylene (PE), and polyamide (PA). The method displays different sensitivities to above four nanoplastics but the same dynamic range from 1 to 100 µg·L-1. Based on it, the nanoplastics released from several typical food packages were assayed. Teabags were revealed with significant nanoplastic release, while instant noodle boxes, paper cups, and take-out boxes release slightly. The good recoveries in nanoplastic-spiked samples confirm the accuracy and applicability of this method. This work provides a sensitive, low-cost, and simple method without complicated instruments and pretreatment, which is of great significance for the determination of nanoplastics released from food packages.

Wireless closed-loop optogenetics across the entire dorsoventral spinal cord in mice.

Optoelectronic systems can exert precise control over targeted neurons and pathways throughout the brain in untethered animals, but similar technologies for the spinal cord are not well established. In the present study, we describe a system for ultrafast, wireless, closed-loop manipulation of targeted neurons and pathways across the entire dorsoventral spinal cord in untethered mice. We developed a soft stretchable carrier, integrating microscale light-emitting diodes (micro-LEDs), that conforms to the dura mater of the spinal cord. A coating of silicone-phosphor matrix over the micro-LEDs provides mechanical protection and light conversion for compatibility with a large library of opsins. A lightweight, head-mounted, wireless platform powers the micro-LEDs and performs low-latency, on-chip processing of sensed physiological signals to control photostimulation in a closed loop. We use the device to reveal the role of various neuronal subtypes, sensory pathways and supraspinal projections in the control of locomotion in healthy and spinal-cord injured mice.

Epineural optogenetic activation of nociceptors initiates and amplifies inflammation.

Activation of nociceptor sensory neurons by noxious stimuli both triggers pain and increases capillary permeability and blood flow to produce neurogenic inflammation1,2, but whether nociceptors also interact with the immune system remains poorly understood. Here we report a neurotechnology for selective epineural optogenetic neuromodulation of nociceptors and demonstrate that nociceptor activation drives both protective pain behavior and inflammation. The wireless optoelectronic system consists of sub-millimeter-scale light-emitting diodes embedded in a soft, circumneural sciatic nerve implant, powered and driven by a miniaturized head-mounted control unit. Photostimulation of axons in freely moving mice that express channelrhodopsin only in nociceptors resulted in behaviors characteristic of pain, reflecting orthodromic input to the spinal cord. It also led to immune reactions in the skin in the absence of inflammation and potentiation of established inflammation, a consequence of the antidromic activation of nociceptor peripheral terminals. These results reveal a link between nociceptors and immune cells, which might have implications for the treatment of inflammation.

Automatic Resonance Frequency Retuning of Stretchable Liquid Metal Receive Coil for Magnetic Resonance Imaging.

Stretchable magnetic resonance (MR) receive coils show shifts in their resonance frequency when stretched. An in-field receiver measures the frequency response of a stretchable coil. The receiver and coil are designed to operate at 128 MHz for a 3T MR scanner. Based on the measured frequency response, we are able to detect the changes of the resonance frequency of the coil. We show a proportional-integral-derivative controller that tracks the changes in resonance frequency and retunes the stretchable coil. The settling time of the control loop is less than 3.8ms. The retuning system reduces the loss in signal-to-noise ratio of phantom images from 1.6 dB to 0.3 dB, when the coil is stretched by 40% and the coil is retuned to 128 MHz.

A Fully Integrated Dual-Channel On-Coil CMOS Receiver for Array Coils in 1.5-10.5 T MRI.

Magnetic resonance imaging (MRI) is among the most important medical imaging modalities. Coil arrays and receivers with high channel counts (16 and more) have to be deployed to obtain the image quality and acquisition speed required by modern clinical protocols. In this paper, we report the theoretical analysis, the system-level design, and the circuit implementation of the first receiver IC (RXIC) for clinical MRI fully integrated in a modern CMOS technology. The dual-channel RXIC sits directly on the sensor coil, thus eliminating any RF cable otherwise required to transport the information out of the magnetic field. The first stage LNA was implemented using a noise-canceling architecture providing a highly reflective input used to decouple the individual channels of the array. Digitization is performed directly on-chip at base-band by means of a delta-sigma modulator, allowing the subsequent optical transmission of data. The presented receiver, implemented in a CMOS technology, is compatible with MRI scanners up to . It reaches sub- noise figure for MRI units and features a dynamic range up to at a power consumption below per channel, with an area occupation of . Mounted on a small-sized printed circuit board (PCB), the receiver IC has been employed in a commercial MRI scanner to acquire in-vivo images matching the quality of traditional systems, demonstrating the first step toward multichannel wearable MRI array coils.

A Versatile Embedded Platform for EMG Acquisition and Gesture Recognition.

Wearable devices offer interesting features, such as low cost and user friendliness, but their use for medical applications is an open research topic, given the limited hardware resources they provide. In this paper, we present an embedded solution for real-time EMG-based hand gesture recognition. The work focuses on the multi-level design of the system, integrating the hardware and software components to develop a wearable device capable of acquiring and processing EMG signals for real-time gesture recognition. The system combines the accuracy of a custom analog front end with the flexibility of a low power and high performance microcontroller for on-board processing. Our system achieves the same accuracy of high-end and more expensive active EMG sensors used in applications with strict requirements on signal quality. At the same time, due to its flexible configuration, it can be compared to the few wearable platforms designed for EMG gesture recognition available on market. We demonstrate that we reach similar or better performance while embedding the gesture recognition on board, with the benefit of cost reduction. To validate this approach, we collected a dataset of 7 gestures from 4 users, which were used to evaluate the impact of the number of EMG channels, the number of recognized gestures and the data rate on the recognition accuracy and on the computational demand of the classifier. As a result, we implemented a SVM recognition algorithm capable of real-time performance on the proposed wearable platform, achieving a classification rate of 90%, which is aligned with the state-of-the-art off-line results and a 29.7 mW power consumption, guaranteeing 44 hours of continuous operation with a 400 mAh battery.