Electrocardiogram identification based on data generative network and non-fiducial data processing.

Nowadays, the use of biological signals as a criterion for identity recognition has gained increasing attention from various organizations and companies. Therefore, it has become crucial to have a biometric identity recognition method that is fast and accurate. In this paper, we propose a linear electrocardiogram (ECG) data preprocessing algorithm based on Kalman filters for rapid noise data filtering (wavelet transform filtering algorithm). Additionally, we introduce a generative network model called Data Generation Strategy Network (DRCN) based on generative networks. The DRCN is employed to augment training samples for convolutional classification networks, ultimately improving the classification performance of the model. Through the final experiments, our method successfully reduced the average misidentification rate of ECG-based identity recognition to 2.5%, and achieved an average recognition rate of 98.7% for each category, significantly surpassing previous achievements. In the future, this method is expected to be widely applied in the field of ECG-based identity recognition.

Transient Receptor Potential Ankyrin 1-dependent Activation of Extracellular Signal-regulated Kinase 2 in the Cerebral Cortices Contributes to Cortical Spreading Depolarization.

Extracellular signal-regulated kinase (ERK) are serine/threonine-selective proteins and ERK1/2 can be phosphorylated in peripheral and central brain regions after cortical spreading depolarization (CSD) and calcitonin gene-related peptide; However, it remains unclear about whether and how ERK activity modulates CSD that correlates to migraine aura. Here, we determined the role of ERK in regulating CSD and explored the underlying mechanism involving transient receptor potential ankyrin 1 (TRPA1), a stress-sensing cation channel. CSD was recorded using intrinsic optical imaging in mouse brain slices, and electrophysiology in rats. Phosphorylated ERK (pERK1/2) and interleukin-1ß (IL-1ß) protein levels were detected using Western blot or enzyme-linked immunosorbent assay, respectively. IL-1ß mRNA level was detected using qPCR. The results showed that an ERK inhibitor, SCH77298, markedly prolonged CSD latency and reduced propagation rate in mouse brain slices. Corresponding to this, CSD induction increased levels of cytosolic pERK1/2 in ipsilateral cerebral cortices of rats, the elevation of which correlated to the level of IL-1ß mRNA. Mechanistic analysis showed that pre-treatment of an anti-TRPA1 antibody reduced the cytosolic pERK2 level but not pERK1 following CSD in cerebral cortices of rats and this level of pERK2 correlated with that of cerebral cortical IL-1ß protein. Furthermore, an ERK activator, AES16-2M, but not its scrambled control, reversed the prolonged CSD latency by a TRPA1 inhibitor, HC-030031, in mouse brain slices. These data revealed a crucial role of ERK activity in regulating CSD, and elevation of pERK and IL-1ß production induced by CSD is predominantly TRPA1 channel-dependent, thereby contributing to migraine pathogenesis.

System for automatically assessing the likelihood of inferior alveolar nerve injury.

Inferior alveolar nerve (IAN) injury is a severe complication associated with mandibular third molar (MM3) extraction. Consequently, the likelihood of IAN injury must be assessed before performing such an extraction. However, existing deep learning methods for classifying the likelihood of IAN injury that rely on mask images often suffer from limited accuracy and lack of interpretability. In this paper, we propose an automated system based on panoramic radiographs, featuring a novel segmentation model SS-TransUnet and classification algorithm CD-IAN injury class. Our objective was to enhance the precision of segmentation of MM3 and mandibular canal (MC) and classification accuracy of the likelihood of IAN injury, ultimately reducing the occurrence of IAN injuries and providing a certain degree of interpretable foundation for diagnosis. The proposed segmentation model demonstrated a 0.9 % and 2.6 % enhancement in dice coefficient for MM3 and MC, accompanied by a reduction in 95 % Hausdorff distance, reaching 1.619 and 1.886, respectively. Additionally, our classification algorithm achieved an accuracy of 0.846, surpassing deep learning-based models by 3.8 %, confirming the effectiveness of our system.

Synthesis and Properties of a Novel Thermally Conductive Pressure-Sensitive Adhesive with UV-Responsive Peelability.

Thermally conductive pressure-sensitive adhesive (PSA) has received a great amount of attention in recent years, but the traditional PSA hardly loses adhesion properties after UV irradiation or heating. Therefore, endowing thermally conductive adhesive with UV-responsive peelability becomes a design strategy. Herein, vinyl-functionalized graphene (AA-GMA-G) is prepared by modifying graphene with acrylic acid and subsequently reacting with glycidyl methacrylate. Then, the UV-curable acrylate copolymer is synthesized by grafting glycidyl methacrylate. Finally, the novel thermally conductivity PSA with UV-responsive peelability is obtained by blending the copolymer with AA-GMA-G and photoinitiator. The results show that the PSA at 2 wt% AA-GMA-G loading exhibits an excellent thermal conductivity (0.74 W m-1 K-1 ) and a relatively strong peel strength, increasing by 15% compared with pristine graphene/PSA. Interestingly, the peel strength of AA-GMA-G/PSA can achieve a dramatic drop after UV treatment, and the decrease rate is 96.7%. Therefore, the novel thermally conductive PSA with UV-responsive peelability has potential applications in certain electronic devices.

Src Family Kinases Facilitate the Crosstalk between CGRP and Cytokines in Sensitizing Trigeminal Ganglion via Transmitting CGRP Receptor/PKA Pathway.

The communication between calcitonin gene-related peptide (CGRP) and cytokines plays a prominent role in maintaining trigeminal ganglion (TG) and trigeminovascular sensitization. However, the underlying regulatory mechanism is elusive. In this study, we explored the hypothesis that Src family kinases (SFKs) activity facilitates the crosstalk between CGRP and cytokines in sensitizing TG. Mouse TG tissue culture was performed to study CGRP release by enzyme-linked immunosorbent assay, cytokine release by multiplex assay, cytokine gene expression by quantitative polymerase chain reaction, and phosphorylated SFKs level by western blot. The results demonstrated that a SFKs activator, pYEEI (YGRKKRRQRRREPQY(PO3H2)EEIPIYL) alone, did not alter CGRP release or the inflammatory cytokine interleukin-1ß (IL-1ß) gene expression in the mouse TG. In contrast, a SFKs inhibitor, saracatinib, restored CGRP release, the inflammatory cytokines IL-1ß, C-X-C motif ligand 1, C-C motif ligand 2 (CCL2) release, and IL-1ß, CCL2 gene expression when the mouse TG was pre-sensitized with hydrogen peroxide and CGRP respectively. Consistently with this, the phosphorylated SFKs level was increased by both hydrogen peroxide and CGRP in the mouse TG, which was reduced by a CGRP receptor inhibitor BIBN4096 and a protein kinase A (PKA) inhibitor PKI (14-22) Amide. The present study demonstrates that SFKs activity plays a pivotal role in facilitating the crosstalk between CGRP and cytokines by transmitting CGRP receptor/PKA signaling to potentiate TG sensitization and ultimately trigeminovascular sensitization.

Study on strain sensing property of fiber Bragg grating based on surface strain measurement of mechanical structure.

Strain monitoring is of great significance to identify the failure of key mechanical components and ensure the good operation of mechanical equipment. In terms of the common issue of the low sensitivity of fiber Bragg grating (FBG) strain sensor in strain measurement on the mechanical structure surface, this paper describes a flexible hinge strain sensor with the FBG as the sensitive element. A theoretical analysis of the sensitivity of the sensor is performed, a copper alloy material with a large elastic modulus is selected, the simulation analysis and optimization design for the structural parameters of the sensor are carried out by using ANSYS and Solidworks software, then the object of the sensor is developed according to the simulation results, and finally, the performance of the sensor is tested. The results show that the maximum deformation the sensor can measure is 0.5299 µÎµ, the sensitivity of the sensor is ∼1.8870 pm/µÎµ, which is approximately twice that of the bare FBG sensor, the linearity is greater than 99%, and the relative standard deviation of the repeatability is 0.9%. The results of the study provide a reference for developing the optical fiber strain sensor and further improving its sensitivity.