Hollow MXene Sphere-Based Flexible E-Skin for Multiplex Tactile Detection.

Skin-like electronics that can provide comprehensively tactile sensing is required for applications such as soft robotics, health monitoring, medical treatment, and human-machine interfaces. In particular, the capacity to monitor the contact parameters such as the magnitude, direction, and contact location of external forces is crucial for skin-like tactile sensing devices. Herein, a flexible electronic skin which can measure and discriminate the contact parameters in real time is designed. It is fabricated by integrating the three-dimensional (3D) hollow MXene spheres/Ag NW hybrid nanocomposite-based embedded stretchable electrodes and T-ZnOw/PDMS film-based capacitive pressure sensors. To the best of our knowledge, it is the first stretchable electrode to utilize the 3D hollow MXene spheres with the essential characteristic, which can effectively avoid the drawbacks of stress concentration and shedding of the conductive layer. The strain-resistance module and the pressure-capacitance module show the excellent sensing performance in stability and response time, respectively. Moreover, a 6 × 6 sensor array is used as a demonstration to prove that it can realize the multiplex detection of random external force stimuli without mutual interference, illustrating its potential applications in biomimetic soft wearable devices, object recognition, and robotic manipulation.

Spider Web-like Flexible Tactile Sensor for Pressure-Strain Simultaneous Detection.

Multiparameter integrated sensors are required for the next generation of flexible wearable electronics. However, mutual interference between detected signals is a technical bottleneck for a flexible tactile sensor to realize pressure-strain monitoring simultaneously and sensitively. Herein, a flexible dual-parameter pressure-strain sensor based on the three-dimensional (3D) tubular graphene sponge (TGS) and spider web-like stretchable electrodes is designed and fabricated. As the pressure-sensitive module, the unique 3D-TGS with an uninterrupted network of tubular graphene and high graphitic degree demonstrates great robust compressibility, supporting compression to ∼20% without shape collapse. The spider web-like stretchable electrodes as the strain-sensitive module are fabricated by a spray-embedded process based on the hierarchical multiscale hybrid nanocomposite of Ag nanowires (NWs) and carbon nanotubes (CNTs) with an optimal mass ratio. By comparing the output signals of spider web-like flexible electrodes, the magnitude and direction of the applied force can be effectively monitored simultaneously. Moreover, the potential applications of the flexible dual-parameter pressure-strain device in human-machine interaction are also explored, showing great promise in artificial intelligence and wearable systems.

Serum caspase-cleaved cytokeratin-18 levels and outcomes after aneurysmal subarachnoid hemorrhage.

OBJECTIVE: Cell apoptosis is involved in acute brain injury after aneurysmal subarachnoid hemorrhage (aSAH). The protein cytokeratin-18 (CK-18) is cleaved by the action of caspases during apoptosis, and the resulting fragments are released into the blood as caspase-cleaved CK (CCCK)-18. Our study examined the relationship between circulating CCCK-18 levels and long-term clinical outcomes among aSAH patients. METHODS: We recruited 128 aSAH patients and 128 controls (matched on age and sex). Serum was collected at admission to the emergency department. Unfavorable outcome was defined as the Glasgow Outcome Score scores of 1-3. After a 6-month follow-up period, outcomes were assessed using a logistic regression analyses. The prognostic predictive values were evaluated according to receiver operating curves analysis. RESULTS: aSAH patients had higher plasma CCCK-18 levels compared to controls (235.1 ± 86.8 U/L vs. 25.6 ± 23.4 U/L, P<0.001). CCCK-18 was independently associated with World Federation of Neurological Surgeons (WFNS) scores (t=4.460, P<0.001) and modified Fisher scores (t=3.781, P<0.001). Furthermore, CCCK-18 levels were markedly higher among patients with an unfavorable outcome and among non-survivors. CCCK-18 was yet identified as an independent prognostic predictor for mortality (odds ratio, 5.769; 95% confidence interval, 1.196-27.832; P=0.029) and unfavorable outcome (odds ratio, 4.909; 95% confidence interval, 1.521-15.838; P=0.008), as well as had similar predictive values for them compared with WFNS scores and modified Fisher scores. CONCLUSIONS: High circulating CCCK-18 levels were associated with injury severity and a poor clinical outcome after aSAH and CCCK-18 had the potential to be a good prognostic biomarker for aSAH.

[Establishment of diagnostic model of cerebrospinal protein fingerprint pattern for glioma and its clinical application].

OBJECTIVE: To establish the diagnostic model of cerebrospinal protein profile for gliomas by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) and bioinformatics. METHODS: Seventy-five samples of cerebrospinal fluid from patients with gliomas, benign brain tumors and mild brain traumas were collected. A total of 50 samples from gliomas and non-brain-tumors were divided into training sets (33 cases including 17 gliomas and 16 non-brain-tumors) and testing sets (17 cases including 5 gliomas and 12 non-brain-tumors). The cerebrospinal proteins bound to H4 chip were detected by SELDI-TOF MS, the profiles of cerebrospinal protein were gained and then analyzed with artificial neural network algorithm (ANN); and the diagnostic model of cerebrospinal protein profiles for differentiating gliomas from non-brain-tumors was established. Forty-seven of cerebrospinal samples of gliomas and benign brain tumors were divided into training sets (31 cases including 13 gliomas and 18 benign brain tumors) and testing sets (16 cases including 9 gliomas and 7 benign brain tumors), the diagnostic model of cerebrospinal protein profiles for differentiating gliomas from benign brain tumors was established based on the same method. The support vector machine (SVM) algorithm was also used for evaluation, both results were very similar, but the result derived from ANN was more stable than that from SVM. RESULT: The diagnostic model of cerebrospinal protein profiles for differentiating gliomas from non-brain-tumors was established and was challenged with the test set randomly, the sensitivity and specificity were 100% and 91.7%, respectively. The cerebrospinal protein profiling model for differentiating gliomas from benign brain tumors was also developed and was challenged with the test set randomly, the sensitivity and specificity were 88.9%, and 100%, respectively. CONCLUSION: The technology of SELDI-TOF MS which combined with analysis tools of bioinformatics is a novel effective method for screening and identifying tumor biomarkers of gliomas and it may provide a new approach for the clinical diagnosis of glioma.