BR regulates wheat root salt tolerance by maintaining ROS homeostasis.

MAIN CONCLUSION: Trace amounts of epibrassinolide (EpiBL) could partially rescue wheat root length inhibition in salt-stressed situation by scavenging ROS, and ectopic expression of TaDWF4 or TaBAK1 enhances root salt tolerance in Arabidopsis by balancing ROS level. Salt stress often leads to ion toxicity and oxidative stress, causing cell structure damage and root development inhibition in plants. While prior research indicated the involvement of exogenous brassinosteroid (BR) in plant responses to salt stress, the precise cytological role and the function of BR in wheat root development under salt stress remain elusive. Our study demonstrates that 100 mM NaCl solution inhibits wheat root development, but 5 nM EpiBL partially rescues root length inhibition by decreasing H2O2 content, oxygen free radical (OFR) content, along with increasing the peroxidase (POD) and catalase (CAT) activities in salt-stressed roots. The qRT-PCR experiment also shows that expression of the ROS-scavenging genes (GPX2 and CAT2) increased in roots after applying BR, especially during salt stress situation. Transcriptional analysis reveals decreased expression of BR synthesis and root meristem development genes under salt stress in wheat roots. Differential expression gene (DEG) enrichment analysis highlights the significant impact of salt stress on various biological processes, particularly "hydrogen peroxide catabolic process" and "response to oxidative stress". Additionally, the BR biosynthesis pathway is enriched under salt stress conditions. Therefore, we investigated the involvement of wheat BR synthesis gene TaDWF4 and BR signaling gene TaBAK1 in salt stress responses in roots. Our results demonstrate that ectopic expression of TaDWF4 or TaBAK1 enhances salt tolerance in Arabidopsis by balancing ROS (Reactive oxygen species) levels in roots.

Deep Learning-Assisted Colorimetric/Electrical Dual-Sensing System for Ultrafast Detection of Hydrogen Sulfide.

This study presents a colorimetric/electrical dual-sensing system (CEDS) for low-power, high-precision, adaptable, and real-time detection of hydrogen sulfide (H2S) gas. The lead acetate/poly(vinyl alcohol) (Pb(Ac)2/PVA) nanofiber film was transferred onto a polyethylene terephthalate (PET) flexible substrate by electrospinning to obtain colorimetric/electrical sensors. The CEDS was constructed to simultaneously record both the visual and electrical response of the sensor, and the improved Manhattan segmentation algorithm and deep neural network (DNN) were used as its intelligent algorithmic aids to achieve quantitative exposure to H2S. By exploring the mechanism of color change and resistance response of the sensor, a dual-sensitivity mechanism explanation model was proposed to verify that the system, as a dual-mode parallel system, can adequately solve the sensor redundancy problem. The results show that the CEDS can achieve a wide detection range of H2S from 0.1-100 ppm and identify the H2S concentration in 4 s at the fastest. The sensor can be stabilized for 180 days with excellent selectivity and a low limit of detection (LOD) to 0.1 ppm of H2S. In addition, the feasibility of the CEDS for measuring H2S levels in underground waterways was validated. This work provides a new method for adaptable, wide range of applications and low-power, high-precision H2S gas detection.

A Room Temperature Trimethylamine Gas Sensor Based on Electrospinned Molybdenum Oxide Nanofibers/Ti3C2Tx MXene Heterojunction.

The combination of two-dimensional material MXene and one-dimensional metal oxide semiconductor can improve the carrier transmission rate, which can effectively improve sensing performance. We prepared a trimethylamine gas sensor based on MoO3 nanofibers and layered Ti3C2Tx MXene. Using electrospinning and chemical etching methods, one-dimensional MoO3 nanofibers and two-dimensional Ti3C2Tx MXene nanosheets were prepared, respectively, and the composites were characterized via XPS, SEM, and TEM. The Ti3C2Tx MXene-MoO3 composite material exhibits excellent room-temperature response characteristics to trimethylamine gas, showing high response (up to four for 2 ppm trimethylamine gas) and rapid response-recovery time (10 s/7 s). Further, we have studied the possible sensitivity mechanism of the sensor. The Ti3C2Tx MXene-MoO3 composite material has a larger specific surface area and more abundant active sites, combined with p-n heterojunction, which effectively improves the sensitivity of the sensor. Because of its low detection limit and high stability, it has the potential to be applied in the detection system of trimethylamine as a biomarker in exhaled air.

Expression of lncRNAs in glioma: A lighthouse for patients with glioma.

Glioma is the most common malignant tumour in the central nervous system, accounting for approximately 30 % of the primary tumours of this system. The World Health Organization grades for glioma include: Grade I (pilocytic astrocytoma), Grade II (astrocytoma, oligodastoma, etc.), Grade III (anaplastic astrocytoma, anaplastic oligodastoma, etc.) and Grade IV (glioblastoma). With grade increases, the proliferation, invasion and other malignant biological properties of the glioma are enhanced, and the treatment results are less satisfactory. The overall survival of patients with glioblastoma is less than 15 months. Recent research has focused on the roles of long non-coding RNAs, previously regarded as "transcriptional noise", in diseases, leading to a new understanding of these roles. Therefore, we conducted this review to explore the progress of research regarding the expression and mechanism of long non-coding RNAs in glioma.

PDMS Film-Based Flexible Pressure Sensor Array with Surface Protruding Structure for Human Motion Detection and Wrist Posture Recognition.

Flexible pressure sensors have been widely concerned because of their great application potential in the fields of electronic skin, human-computer interaction, health detection, and so on. In this paper, a flexible pressure sensor is designed, with polydimethylsiloxane (PDMS) films with protruding structure as elastic substrate and poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate) (PEDOT:PSS)/cellulose nanocrystals (CNC) as conductive-sensitive material. The flexible pressure sensor has a wide linear detection range (0-100 kPa), outstanding sensitivity (2.32 kPa-1), and stability of more than 2000 cycles. The sensor has been proven to be able to detect a wide range of human movements (finger bending, elbow bending, etc.) and small movements (breathing, pulse, etc.). In addition, the pressure sensor array can detect the pressure distribution and judge the shape of the object. A smart wristband equipped with four flexible pressure sensors is designed. Among them, the k-nearest neighbor (KNN) algorithm is used to classify sensor data to achieve high accuracy (99.52%) recognition of seven kinds of wrist posture. This work provides a new opportunity to fabricate simple, flexible pressure sensors with potential applications in the next-generation electronic skin, health detection, and intelligent robotics.

A Comprehensive Pan-cancer Analysis of the Biological Immunomodulatory Function and Clinical Value of CD27.

Background: CD27 is an immunological checkpoint gene, plays a critical function inInhibition or activation of cancer immunity. The CD27/CD27L axis is its pathway of action. Therefore, our goal was to examine the predictive role of CD27 in the clinical prognosis of 33 cancer types and its functions in cancer progression, as well as explore the link between pan-cancer CD27 gene expression and immune infiltration. Methods: By comprehensive use of datasets and methods from TCGA, cBioPortal, GTEx, HPA, KM-plotter, Spearman, CellMinerTM, R packages and RT-qPCR, we delved deeper into the potential impact of the CD27 on cancer development. These include expression differences, immune infiltration, matrix infiltration, gene mutations, DNA methylation, signaling pathways, TMB, MSI, and prognosis. Also, we explored CD27 interactions with different drugs. Results: The results showed that, mutated CD27 was highly expressed in most cancers. The CD27 showed strong diagnostic value in 4 cancers and marked a positive prognosis for CESC, intracervical adenocarcinoma, HNSC, and endometrial cancer, and a poor prognosis for UVM. In addition, CD27 affects multiple immune and inflammatory signaling pathways and is positively correlated with immune cell infiltration, T cell differentiation, macrophage M1 polarization, stromal infiltration, and drug sensitivity. DNA methylation is involved in CD27 expression in cancer. Conclusion: CD27, which is mutated in cancers and appears widely highly expressed and altered tumor immune invasion and stromal invasion by affecting multiple immune-related and inflammation signaling pathways, plays a significant role in CESC, HNSC, UCEC and UVM, and may be used as a therapeutic target for related cancers.

MXene/PPy@PDMS sponge-based flexible pressure sensor for human posture recognition with the assistance of a convolutional neural network in deep learning.

The combination of flexible sensors and deep learning has attracted much attention as an efficient method for the recognition of human postures. In this paper, an in situ polymerized MXene/polypyrrole (PPy) composite is dip-coated on a polydimethylsiloxane (PDMS) sponge to fabricate an MXene/PPy@PDMS (MPP) piezoresistive sensor. The sponge sensor achieves ultrahigh sensitivity (6.8925 kPa-1) at 0-15 kPa, a short response/recovery time (100/110 ms), excellent stability (5000 cycles) and wash resistance. The synergistic effect of PPy and MXene improves the performance of the composite materials and facilitates the transfer of electrons, making the MPP sponge at least five times more sensitive than sponges based on each of the individual single materials. The large-area conductive network allows the MPP sensor to maintain excellent electrical performance over a large-scale pressure range. The MPP sensor can detect a variety of human body activity signals, such as radial artery pulse and different joint movements. The detection and analysis of human motion data, which is assisted by convolutional neural network (CNN) deep learning algorithms, enable the recognition and judgment of 16 types of human postures. The MXene/PPy flexible pressure sensor based on a PDMS sponge has broad application prospects in human motion detection, intelligent sensing and wearable devices.

Multifunctional, Self-Adhesive MXene-Based Hydrogel Flexible Strain Sensors for Hand-Written Digit Recognition with Assistance of Deep Learning.

The conductive hydrogel as a flexible sensor not only has certain mechanical flexibility but also can be used in the field of human health detection and human-computer interaction. Herein, by introduction of tannic acid (TA) with MXene into the polyacrylamide (PAM)/carboxymethyl chitosan (CMC) double-network hydrogel, a hydrogel with high stretchability, self-adhesion, and high sensitivity was prepared. CMC and PAM form a semi-interpenetrating double-network of high toughness and durability through electrostatic interactions and multiple hydrogen bonding networks. The abundant hydrophilic functional groups on TA and MXene form multiple hydrogen bonds simultaneously with the polymer network, ensuring high stretchability and sensitivity of the hydrogel. The hydrogel can display an accurate response to a variety of stimulus signals and can monitor both human joint movements and small physiological signal changes. It can also be combined with deep learning algorithms to classify handwritten digits with an accuracy rate of 98%. This work can promote the application of hydrogel sensors with durability and high sensitivity. The combination of algorithms and flexible sensors provides important ideas for the further development of flexible devices.

RPL34-Divergent Transcript, a Novel Long NonCoding Ribonucleic Acid, Promotes Migration by Activating Epithelial-Mesenchymal Transition in Glioma.

OBJECTIVE: Glioma is one of the leading causes of death in patients with intracranial tumours. RPL34 divergent transcript (RPL34-DT) is a long non-coding ribonucleic acid that is significantly upregulated in glioma tissues. However, the role of RPL34-DT in glioma behavior remains to be elucidated. Therefore, in this study, we focused on the effect of RPL34-DT on the epithelial-mesenchymal transition in gliomas. METHODS: Real-time quantitative reverse transcription polymerase chain reaction was used to detect the levels of RPL34-DT in glioma tissue and cell lines. We further used the LN229 and U251 glioma cell lines to assess the role of RPL34-DT. Wound healing and invasion assays were performed to determine the role of RPL34-DT in migration. Changes in protein levels were assessed by western blotting. RESULTS: We found that RPL34-DT was upregulated in glioma tissues and glioma cell lines. Knockdown of RPL34-AS1 blocked migration of glioma cell. This effect occurred through a decrease of epithelial-mesenchymal transition and ß-catenin. CONCLUSIONS: This study suggests that RPL34-DT affects cell migration in glioma and therefore may serve as a valuable therapeutic target in patients with glioma.

ACVRL1 drives resistance to multitarget tyrosine kinase inhibitors in colorectal cancer by promoting USP15-mediated GPX2 stabilization.

BACKGROUND: Multitarget tyrosine kinase inhibitors (mTKIs) such as Regorafenib and Sorafenib have already been approved for the treatment of many solid tumours. However, the efficacy of mTKIs in colorectal cancer (CRC) is limited; the underlined mechanism remains largely elusive. Our study was aimed to find out the resistance mechanism of mTKIs in CRC. METHODS: RNA sequencing was used to identify the expression of Activin A receptor-like type 1 (ACVRL1) under the treatment of mTKIs. Gain/loss-of-function experiments were performed to assess the biological function of ACVRL1 in resistance to mTKIs. The underlying mechanisms of ACVRL1-mediated mTKI resistance were investigated by using liquid chromatography-mass spectrometry assays (LC-MS), co-immunoprecipitation assays (Co-IP), chromatin immunoprecipitation assays, ubiquitination assays, dual luciferase reporter assays, etc. RESULTS: RNA sequencing identified the activation of ACVRL1 under the treatment of mTKIs in CRC cells. ACVRL1 knockdown and overexpression significantly affects the sensitivity of CRC cells to mTKIs both in vitro and vivo. Mechanistically, we found the ß-catenin/TCF-1-KCNQ1OT1/miR-7-5p axis mediated the activation of ACVRL1. Furthermore, LC-MS assays indicated the interaction between ACVRL1 and glutathione peroxidase 2(GPX2) protein. IP assay defined ACVRL1 truncation (282-503aa) could be responsible for interacting with GPX2, and rescue experiments with ACVRL1 truncations confirmed the importance of this interaction in driving mTKI resistance. Co-IP assays confirmed that ACVRL1 associates with ubiquitin-specific peptidase 15(USP15) which directly deubiquinates GPX2 at the K187(K, lysine) site, leading to the accumulation of GPX2 protein. Rescue experiments performed with the lysine mutants in GPX2 CRISPR knockout cell model confirmed the importance of GPX2 K187 mutant. As a result, the increased ROS clearance and decreased cell apoptosis eventually lead to mTKI resistance in CRC. CONCLUSIONS: Our results demonstrate that the Wnt/ß-catenin/KCNQ1OT1/miR-7-5p/ACVRL1/GPX2 biological axis plays a vital role in CRC, targeting which may be an effective approach for overcoming mTKI resistance.

Constructing a novel signature and predicting the immune landscape of colon cancer using N6-methylandenosine-related lncRNAs.

Background: Colon cancer (CC) is a prevalent malignant tumor that affects people all around the world. In this study, N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) in 473 colon cancers and 41 adjacent tissues of CC patients from The Cancer Genome Atlas (TCGA) were investigated. Method: The Pearson correlation analysis was conducted to examine the m6A-related lncRNAs, and the univariate Cox regression analysis was performed to screen 38 prognostic m6A-related lncRNAs. The least absolute shrinkage and selection operator (LASSO) regression analysis were carried out on 38 prognostic lncRNAs to develop a 14 m6A-related lncRNAs prognostic signature (m6A-LPS) in CC. The availability of the m6A-LPS was evaluated using the Kaplan-Meier and Receiver Operating Characteristic (ROC) curves. Results: Three m6A modification patterns with significantly different N stages, survival time, and immune landscapes were identified. It has been discovered that the m6A-LPS, which is based on 14 m6A-related lncRNAs (TNFRSF10A-AS1, AC245041.1, AL513550.1, UTAT33, SNHG26, AC092944.1, ITGB1-DT, AL138921.1, AC099850.3, NCBP2-AS1, AL137782.1, AC073896.3, AP006621.2, AC147651.1), may represent a new, promising biomarker with great potential. It was re-evaluated in terms of survival rate, clinical features, tumor infiltration immune cells, biomarkers related to Immune Checkpoint Inhibitors (ICIs), and chemotherapeutic drug efficacy. The m6A-LPS has been revealed to be a novel potential and promising predictor for evaluating the prognosis of CC patients. Conclusion: This study revealed that the risk signature is a promising predictive indicator that may provide more accurate clinical applications in CC therapeutics and enable effective therapy strategies for clinicians.

Efficient Fabrication of TPU/MXene/Tungsten Disulfide Fibers with Ultra-Fast Response for Human Respiratory Pattern Recognition and Disease Diagnosis via Deep Learning.

Flexible wearable pressure sensors have received increasing attention as the potential application of flexible wearable devices in human health monitoring and artificial intelligence. However, the complex and expensive process of the conductive filler has limited its practical production and application on a large scale to a certain extent. This study presents a kind of piezoresistive sensor by sinking nonwoven fabrics (NWFs) into tungsten disulfide (WS2) and Ti3C2Tx MXene solutions. With the advantages of a simple production process and practicality, it is conducive to the realization of large-scale production. The assembled flexible pressure sensor exhibits high sensitivity (45.81 kPa-1), wide detection range (0-410 kPa), fast response/recovery time (18/36 ms), and excellent stability and long-term durability (up to 5000 test cycles). Because of the high elastic modulus of MXene and the synergistic effect between WS2 and MXene, the detection range and sensitivity of the piezoresistive pressure sensor are greatly improved, realizing the stable detection of human motion status in all directions. Meanwhile, its high sensitivity at low pressure allows the sensor to accurately detect weak signals such as weak airflow and wrist pulses. In addition, combining the sensor with deep-learning makes it easy to recognize human respiratory patterns with high accuracy, demonstrating its potential impact in the fields of ergonomics and low-cost flexible electronics.

Waterproof Flexible Pressure Sensors Based on Electrostatic Self-Assembled MXene/NH2-CNTs for Motion Monitoring and Electronic Skin.

Flexible wearable sensors to monitor human movement and for electronic skins must exhibit high sensitivity, a wide detection range, and waterproof characteristics. This work reports a flexible, highly sensitive, and waterproof sponge pressure sensor (SMCM). The sensor is made by assembling SiO2 (S), MXene (M), and NH2-CNTs (C) on the backbone of melamine sponge (M). The SMCM sensor exhibits excellent sensitivity (10.8 kPa-1), an ultra-short response/recovery time (40 ms/60 ms), a wide detection range (30 kPa), and an extremely low detection limit (4.6 Pa). Benefiting from layer-by-layer self-assembly, the sensor still exhibits excellent stability after 5000 cycles. In addition, the SMCM sensor also has excellent waterproof performance (a water contact angle of 142°), enabling it to operate unaffectedly under wet conditions. The SMCM sensor can accurately detect small body movements such as pulse and swallowing while also accurately detecting finger and elbow movements. In addition, the sensor can be designed as an array to construct an electronic skin for detecting the magnitude and distribution of external pressure. This work holds great application potential in next-generation electronic skin, fitness detection, and flexible pressure sensors.

Self-Adhesive, Anti-Freezing MXene-Based Hydrogel Strain Sensor for Motion Monitoring and Handwriting Recognition with Deep Learning.

Flexible strain sensors based on self-adhesive, high-tensile, super-sensitive conductive hydrogels have promising application in human-computer interaction and motion monitoring. Traditional strain sensors have difficulty in balancing mechanical strength, detection function, and sensitivity, which brings challenges to their practical applications. In this work, the double network hydrogel composed of polyacrylamide (PAM) and sodium alginate (SA) was prepared, and MXene and sucrose were used as conductive materials and network reinforcing materials, respectively. Sucrose can effectively enhance the mechanical performance of the hydrogels and improve the ability to withstand harsh conditions. The hydrogel strain sensor has excellent tensile properties (strain >2500%), high sensitivity with a gauge factor of 3.76 at 1400% strain, reliable repeatability, self-adhesion, and anti-freezing ability. Highly sensitive hydrogels can be assembled into motion detection sensors that can distinguish between various strong or subtle movements of the human body, such as joint flexion and throat vibration. In addition, the sensor can be applied in handwriting recognition of English letters by using the fully convolutional network (FCN) algorithm and achieved the high accuracy of 98.1% for handwriting recognition. The as-prepared hydrogel strain sensor has broad prospect in motion detection and human-machine interaction, which provides great potential application of flexible wearable devices.

Triboelectric Nanogenerators Based on Super-Stretchable Conductive Hydrogels with the Assistance of Deep-Learning for Handwriting Recognition.

Nowadays, wearable electronic devices are developing rapidly with the internet of things and human-computer interactions. However, there are problems such as low power, short power supply time, and difficulty in charging, leading to a limited range of practical applications. In this paper, a composite hydrogel composed of polyacrylamide, hydroxypropyl methylcellulose, and MXene (Ti3C2Tx) nanosheets was developed, which formed a stable double-chain structure by hydrogen bonding. The configuration endows the hydrogel with excellent properties, such as high strength, strong stretchability, excellent electrical conductivity, and high strain sensitivity. Based on these characteristics, a flexible multifunctional triboelectric nanogenerator (PHM-TENG) was prepared using the hydrogel as a functional electrode. The nanogenerator can collect biomechanical energy and convert it to 183 V with a maximum power density of 78.3 mW/m2. It is worth noting that PHM-TENG can be applied as a green power source for driving miniature electronics. Also, it can be used as an auto-powered strain sensor that distinguishes letters, enabling monitoring under small strain conditions. This work is anticipated to provide an avenue for the development of new intelligent systems for handwriting recognition.

Application of small extracellular vesicles in the diagnosis and prognosis of nasopharyngeal carcinoma.

Nasopharyngeal carcinoma (NPC) is a malignant tumor originating from the epithelium of the nasopharynx. The disease is insidious, and most patients are diagnosed at the advanced stage, resulting in poor prognosis. Early diagnosis is important to reduce NPC mortality. Small extracellular vesicles (sEVs) are rich in a variety of bioactive molecules, such as proteins, nucleic acids, and lipids, which can participate in the physiological and pathological regulation of the body by affecting the function of target cells. Numerous studies have shown that some RNAs and proteins in sEVs of tumor origin have a key role in the development of NPC and are potential candidates for malignancy detection. Studying the relationship between the cargoes of these sEVs and NPC may help in the diagnosis of the disease. Here in this review, we summarize the application of sEVs as biomarkers in the diagnosis of NPC and their role in NPC metastasis and prognosis. In addition, we discuss possible future applications and limitations of sEVs as biomarkers.

Nifuroxazide inhibits the growth of glioblastoma and promotes the infiltration of CD8 T cells to enhance antitumour immunity.

INTRODUCTION: Glioblastoma is a primary intracranial tumour with extremely high disability and fatality rates among adults. Existing diagnosis and treatment methods have not significantly improved the overall poor prognosis of patients. Nifuroxazide, an oral antibiotic, has been reported to act as a tumour suppressor in a variety of tumours and to participate in the process of antitumour immunity. However, whether it can inhibit the growth of glioma is still unclear. METHODS: We explored the potential mechanism of nifuroxazide inhibiting the growth of glioblastoma cells through in vitro and in vivo experiments. RESULTS: nifuroxazide can inhibit the proliferation of glioblastoma cells, promote G2 phase arrest, induce apoptosis, and inhibit epithelial-mesenchymal transition through the MAP3K1/JAK2/STAT3 pathway. Similarly, clinical sample analysis confirmed that MAP3K1 combined with STAT3 can affect the prognostic characteristics of patients with glioma. In addition, nifuroxazide can drive the M1 polarization of microglioma cells, inhibit the expression of CTLA4 and PD-L1 in tumour cells, and promote the infiltration of CD8 T cells to exert antitumour effects. Combination treatment with PD-L1 inhibitors can significantly prolong the survival time of mice. CONCLUSION: we found that nifuroxazide can inhibit the growth of glioblastoma and enhance antitumour immunity. Thus, nifuroxazide is an effective drug for the treatment of glioblastoma and has great potential for clinical application.

In Situ Polymerized MXene/Polypyrrole/Hydroxyethyl Cellulose-Based Flexible Strain Sensor Enabled by Machine Learning for Handwriting Recognition.

Flexible strain sensors have significant progress in the fields of human-computer interaction, medical monitoring, and handwriting recognition, but they also face many challenges such as the capture of weak signals, comprehensive acquisition of the information, and accurate recognition. Flexible strain sensors can sense externally applied deformations, accurately measure human motion and physiological signals, and record signal characteristics of handwritten text. Herein, we prepare a sandwich-structured flexible strain sensor based on an MXene/polypyrrole/hydroxyethyl cellulose (MXene/PPy/HEC) conductive material and a PDMS flexible substrate. The sensor features a wide linear strain detection range (0-94%), high sensitivity (gauge factor 357.5), reliable repeatability (>1300 cycles), ultrafast response-recovery time (300 ms), and other excellent sensing properties. The MXene/PPy/HEC sensor can detect human physiological activities, exhibiting excellent performance in measuring external strain changes and real-time motion detection. In addition, the signals of English words, Arabic numerals, and Chinese characters handwritten by volunteers measured by the MXene/PPy/HEC sensor have unique characteristics. Through machine learning technology, different handwritten characters are successfully identified, and the recognition accuracy is higher than 96%. The results show that the MXene/PPy/HEC sensor has a significant impact in the fields of human motion detection, medical and health monitoring, and handwriting recognition.

Rapid simultaneous SERS detection of dual myocardial biomarkers on single-track finger-pump microfluidic chip.

Acute myocardial infarction (AMI) is a serious disease with high mortality that afflicts many people around the world. The main cause of death from AMI was the inaccurate early diagnosis, which resulted from the medical treatment might be a delay. Therefore, it is crucial to achieve the rapid detection of AMI. The cardiac troponin I (cTnI) level in human serum may significantly increase as the myocardial membrane ruptured, and the creatine kinase-MB (CK-MB) was also associated with the AMI recurrence and the infarct size of myocardial infarction. Both of them are regarded as important cardiac biomarkers for the early diagnosis of AMI. Therefore, we chose these two cardiac biomarkers as indicators for simultaneous detection. We proposed a single-track finger-pump microfluidic chip for simultaneous surface-enhanced Raman scattering (SERS) detection of cTnI and CK-MB. The entire detection process takes only 5 min without the cumbersome syringe pump. Meanwhile, it enables multiple reagent additions and removals of the unbonded reactants. This microfluidic sensor employed "sandwich" immunoassays based on SERS nanoprobes, AMI biomarkers, and magnetic beads. It is possible to detect two cardiac biomarkers simultaneously in a single measurement, greatly simplifying the detection process and reducing the detection time. Magnetic beads with SERS nanoprobes were separated and captured in the microchamber by a round magnet integrated into the chip. Our results showed that the detection limits of cTnI and CK-MB could reach to 0.01 ng mL-1, respectively. The limit of detections (LODs) match with the clinical threshold values for AMI biomarkers. It is believed that the proposed single-track finger-pump microfluidic chip can be used as an effective tool for determining early AMI.

Ultrastretchable, Self-Healing Conductive Hydrogel-Based Triboelectric Nanogenerators for Human-Computer Interaction.

The rapid development of wearable electronic devices and virtual reality technology has revived interest in flexible sensing and control devices. Here, we report an ionic hydrogel (PTSM) prepared from polypropylene amine (PAM), tannic acid (TA), sodium alginate (SA), and MXene. Based on the multiple weak H-bonds, this hydrogel exhibits excellent stretchability (strain >4600%), adhesion, and self-healing. The introduction of MXene nanosheets endows the hydrogel sensor with a high gauge factor (GF) of 6.6. Meanwhile, it also enables triboelectric nanogenerators (PTSM-TENGs) fabricated from silicone rubber-encapsulated hydrogels to have excellent energy harvesting efficiency, with an instantaneous output power density of 54.24 mW/m2. We build a glove-based human-computer interaction (HMI) system using PTSM-TENGs. The multidimensional signal features of PTSM-TENG are extracted and analyzed by the HMI system, and the functions of gesture visualization and robot hand control are realized. In addition, triboelectric signals can be used for object recognition with the help of machine learning techniques. The glove based on PTSM-TENG achieves the classification and recognition of five objects through contact, with an accuracy rate of 98.7%. Therefore, strain sensors and triboelectric nanogenerators based on hydrogels have broad application prospects in man-machine interface, intelligent recognition systems, auxiliary control systems, and other fields due to their excellent stretchable and high self-healing performance.