The hydrogel sensor composited with MXene presents high stretchability, high sensitivity and high durability.
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The flourishing development in flexible electronics has provoked ...intensive research in flexible strain sensors to realize accurate perception acquisition under different external stimuli. However, building hydrogel-based strain sensors with high stretchability and sensitivity remains a great challenge. Herein, MXene nanosheets were composited into polyacrylamide-sodium alginate matrix to construct mechanical robust and sensitive double networked hydrogel strain sensor. The hydrophilic MXene nanosheets formed strong interactions with the polymer matrix and endowed the hydrogel with excellent tensile properties (3150%), compliant mechanical strength (2.03 kPa−1 in Young’s Module) and long-lasting stability and fatigue resistance (1000 dynamic cycles under 1,600% strain). Due to the highly oriented MXene-based three dimensional conductive networks, the hydrogel sensor achieved extremely high tensile sensitivity (18.15 in gauge factor) and compression sensitivity (0.38 kPa−1 below 3 kPa). MXene hydrogel-based strain sensors also displayed negligible hysteresis in electromechanical performance, typical frequent-independent feature and rapid response time to external stimuli. Moreover, the sensor exhibited accurate response to different scales of human movements, providing potential application in speech recognition, expression recognition and handwriting verification.
Electronic skin is driving the next generation of cutting-edge wearable electronic products due to its good wearability and high accuracy of information acquisition. However, it remains a challenge ...to fulfill the requirements on detecting full-range human activities with existing flexible strain sensors. Herein, highly stretchable, sensitive, and multifunctional flexible strain sensors based on MXene- (Ti
C
T
-) composited poly(vinyl alcohol)/polyvinyl pyrrolidone double-network hydrogels were prepared. The uniformly distributed hydrophilic MXene nanosheets formed a three-dimensional conductive network throughout the hydrogel, endowing the flexible sensor with high sensitivity. The strong interaction between the double-network hydrogel matrix and MXene greatly improved the mechanical properties of the hydrogels. The resulting nanocomposited hydrogels featured great tensile performance (2400%), toughness, and resilience. Particularly, the as-prepared flexible pressure sensor revealed ultrahigh sensitivity (10.75 kPa
) with a wide response range (0-61.5 kPa), fast response (33.5 ms), and low limit of detection (0.87 Pa). Moreover, the hydrogel-based flexible sensors, with high sensitivity and durability, could be employed to monitor full-range human motions and assembled into some aligned devices for subtle pressure detection, providing enormous potential in facial expression and phonation recognition, handwriting verification, healthy diagnosis, and wearable electronics.
Head and neck cancer (HNC) is a fatal and debilitating disease that is characterized by steady, poor survival rates despite advances in treatment. There is an urgent and unmet need to improve our ...understanding of what drives this insidious cancer and causes poor outcomes. Extracellular vesicles (EVs) are small vesicles that originate from tumor cells, immune cells, and other cell types and are secreted into plasma, saliva, and other bio-fluids. EVs represent dynamic, real-time changes of cells and offer an exciting opportunity to improve our understanding of HNC biology that may translate to improved clinical practice. Considering the amplified interest in EVs, we have sought to provide a contemporary review of the most recent and salient literature that is shaping the field. Herein, we discuss the functionality of EVs in HNCs and their clinical potential with regards to biomarker and therapeutic capabilities.
Road traffic safety issues pose a serious threat to urban health, and how the built environment affects traffic crashes has been hotly discussed. However, there are limitations in the selection of ...built environment factors according to the classic 5Ds system in most previous studies. Few studies have considered the influence exerted by visibility factors in intersection level and road diversity at the community level on traffic crashes, and the multi-level structure of crash data may be ignored. Therefore, the proposed visibility analysis method considering visible triangles and visual sensitivity is used to quantify the visual environment features of the intersections. Based on the proposed six-dimensional factors (6Ds) of the built environment (considering the intersection visibility degree and road diversity) and the hierarchical linear model (HLM), this paper proposes the 6Ds-HLM framework to analyze how road traffic crashes are influenced by the built environment factors. The results show that (1) the full model of the proposed 6Ds-HLM which contained the variables of intersection level and community level considering road diversity and the cross-level interactive effect performed best. (2) Interactive effects between intersection visibility and community built environment are founded, and significant 6Ds variables are identified using HLM: a) There was a positive cross-effect between intervisibility and road diversity. The viewshed area of the middle visual sensitive region also presented significant positive cross effects with traffic congestion speed, entertainment venue density, and road diversity. b) There was a significant negative cross-effect between the viewshed area of the middle visual sensitive region and school density.
Background
The mechanism underlying cervical carcinogenesis that is mediated by persistent human papillomavirus (HPV) infection remains elusive.
Aims
Here, for the first time, we deciphered both the ...temporal transition and spatial distribution of cellular subsets during disease progression from normal cervix tissues to precursor lesions to cervical cancer.
Materials & Methods
We generated scRNA‐seq profiles and spatial transcriptomics data from nine patient samples, including two HPV‐negative normal, two HPV‐positive normal, two HPV‐positive HSIL and three HPV‐positive cancer samples.
Results
We not only identified three ‘HPV‐related epithelial clusters’ that are unique to normal, high‐grade squamous intraepithelial lesions (HSIL) and cervical cancer tissues but also discovered node genes that potentially regulate disease progression. Moreover, we observed the gradual transition of multiple immune cells that exhibited positive immune responses, followed by dysregulation and exhaustion, and ultimately established an immune‐suppressive microenvironment during the malignant program. In addition, analysis of cellular interactions further verified that a ‘homeostasis‐balance‐malignancy’ change occurred within the cervical microenvironment during disease progression.
Discussion
We for the first time presented a spatiotemporal atlas that systematically described the cellular heterogeneity and spatial map along the four developmental steps of HPV‐related cervical oncogenesis, including normal, HPV‐positive normal, HSIL and cancer. We identified three unique HPV‐related clusters, discovered critical node genes that determined the cell fate and uncovered the immune remodeling during disease escalation.
Conclusion
Together, these findings provided novel possibilities for accurate diagnosis, precise treatment and prognosis evaluation of patients with precancer and cervical cancer.
Three HPV‐related epithelial clusters unique to HPV infection, HSIL and cervical cancer were identified.
We discovered several critical node genes that potentially determined disease progression.
We observed a gradual transition of multiple immune cells from a positive immune response to dysregulation and exhaustion, leading to an immune‐suppressive microenvironment of cervical cancer.
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•The skin-inspired bilayer hydrogel displays distinguishable property in each layer.•The hierarchical structure endows strain sensor excellent electromechanical property.•The ...biocompatible hydrogel achieves bacteria inhibition and wound healing promotion.
To accurately monitor human physiological activities and promote wound healing, flexible electronics with excellent electromechanical and biotherapeutic properties are demanding. Herein, skin-inspired highly stretchable, tough, and adhesive bilayer composite hydrogels for strain sensing and wound dressing were fabricated through a layer-by-layer polymerization process. Among them, the highly stretchable upper tough layer ensures the composite hydrogel's excellent mechanical and sensing properties, and the lower adhesion layer can be conformal to human skin to enhance sensing sensitivity and stability. Benefiting from the synergistic effect of the bilayer structure, the composite hydrogel presents high stretchability (over 3600%), high toughness (over 200 kPa), and excellent adhesion. In addition, the adhesion layer hydrogel, containing biological macromolecules of tannins and proline, is highly biocompatible to inhibit bacterial growth and promote wound healing. The bilayer composite hydrogel can not only accurately detect human physiological activities as a strain sensor, but also promote rapid wound recovery as wound dressing, showing great potential in health monitoring and wound treatment.
Head and neck squamous cell carcinomas (HNSCCs) arising from different anatomical sites present with different incidences and characteristics, which requires a personalized treatment strategy. ...Despite the extensive research that has conducted on this malignancy, HNSCC still has a poor overall survival rate. Many attempts have been made to improve the outcomes, but one of the bottlenecks is thought to be the lack of an effective biomarker with high sensitivity and specificity. Extracellular vesicles (EVs) are secreted by various cells and participate in a great number of intercellular communications. Based on liquid biopsy, EV detection in several biofluids, such as blood, saliva, and urine, has been applied to identify the existence and progression of a variety of cancers. In HNSCC, tumor-derived EVs exhibit many functionalities by transporting diverse cargoes, which highlights their importance in tumor screening, the determination of multidisciplinary therapy, prediction of prognosis, and evaluation of therapeutic effects. This review illustrates the classification and formation of EV subtypes, the cargoes conveyed by these vesicles, and their respective functions in HNSCC cancer biology, and discloses their potential as biomarkers during the whole process of tumor diagnosis, treatment, and follow-up.
Magnetic induction (MI) has been proven to be an efficient wireless communication technique for overcoming the transmission challenges in some very harsh propagation environments, such as ...underground, underwater, etc. For a random distributed MI ad hoc network in a 3-D space composed of uniform medium, we propose a method for determining the required node density and transmitting power that creates an almost surely fully connected network. For which we involve an MI path-loss model and consider the effect of eddy currents, the effective coverage space and the expected node degree of an MI node are then calculated by a Lambert W-function-based integration. Finally, we propose optimized frequency selection methods for improving the connectivity of MI networks. In addition to an ideal frequency-switching optimization method, we provide for engineering applications a practical frequency-fixed optimization method, which is based on the gradient descent algorithm, where an improved initialization is used to reduce iterations.
•Machine learning models might be a better analytic approach in cervical cancer prognostic prediction than traditional methods.•Our models can provide multitask predictions, which can estimate the ...individual probability of overall survival, overall recurrence, and site-specific recurrence as well as RFS and OS times at the same time.•A web-based calculator was developed and externally validated to predict prognosis for cervical cancer.
Machine learning (ML) has been gradually integrated into oncologic research but seldom applied to predict cervical cancer (CC), and no model has been reported to predict survival and site-specific recurrence simultaneously. Thus, we aimed to develop ML models to predict survival and site-specific recurrence in CC and to guide individual surveillance.
We retrospectively collected data on CC patients from 2006 to 2017 in four hospitals. The survival or recurrence predictive value of the variables was analyzed using multivariate Cox, principal component, and K-means clustering analyses. The predictive performances of eight ML models were compared with logistic or Cox models. A novel web-based predictive calculator was developed based on the ML algorithms.
This study included 5112 women for analysis (268 deaths, 343 recurrences): (1) For site-specific recurrence, larger tumor size was associated with local recurrence, while positive lymph nodes were associated with distant recurrence. (2) The ML models exhibited better prognostic predictive performance than traditional models. (3) The ML models were superior to traditional models when multiple variables were used. (4) A novel predictive web-based calculator was developed and externally validated to predict survival and site-specific recurrence.
ML models might be a better analytic approach in CC prognostic prediction than traditional models as they can predict survival and site-specific recurrence simultaneously, especially when using multiple variables. Moreover, our novel web-based calculator may provide clinicians with useful information and help them make individual postoperative follow-up plans and further treatment strategies.
To meet critical requirements on flexible electronic devices, multifunctionalized flexible sensors with excellent electromechanical performance and temperature perception are required. Herein, ...lignin-reinforced thermoresponsive poly(ionic liquid) hydrogel is prepared through an ultrasound-assisted synthesized method. Benefitting from the electrostatic interaction between lignin and ionic liquid, the hydrogel displays high stretchability (over 1425%), excellent toughness (over 132 kPa), and impressive stress loading-unloading cyclic stability. The hydrogel strain sensor presents excellent electromechanical performance with a high gauge factor (1.37) and rapid response rate (198 ms), which lays the foundation for human body movement detection and smart input. Moreover, owing to the thermal-sensitive feature of poly(ionic liquid), the as-prepared hydrogel displays remarkable thermal response sensitivity (0.217°C
) in body temperature range and low limit of detection, which can be applied as a body shell temperature indicator. Particularly, the hydrogel can detect dual stimuli of strain and temperature and identify each signal individually, showing the specific application in human-machine interaction and artificial intelligence. By integrating the hydrogel strain sensor into a wireless sensation system, remote motion capture and gesture identification is realized in real-time.
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