Graphene based nanomaterials have attracted significant attention for their potentials in biomedical and biotechnology applications in recent years, owing to the outstanding physical and chemical ...properties. However, the interaction mechanism and impact on biological activity of macro and micro biomolecules still require more concerns and further research in order to enhance their applicability in biosensors, etc. Herein, an integrated method has been developed to predict the protein bioactivity performance when interacting with nanomaterials for protein based biosensor. Molecular dynamics simulation and molecular docking technique were consolidated to investigate several nanomaterials C60 fullerene, single walled carbon nanotube, pristine graphene and graphene oxide, and their effect when interacting with protein. The adsorption behavior, secondary structure changes and protein bioactivity changes were simulated, and the results of protein activity simulation were verified in combination with atomic force spectrum, circular dichroism spectrum fluorescence and electrochemical experiments. The best quantification alignment between bioactivity obtained by simulation and experiment measurements was further explored. The two proteins, RNase A and Exonuclease III, were regarded as analysis model for the proof of concept, and the prediction accuracy of protein bioactivty could reach up to 0.98.
To investigate the composition of potassium channels in normal rat coronary smooth muscle cells (CASMCs) and the activation effects of docosahexaenoic acid (DHA).
CASMCs were isolated by enzyme ...digestion.Effects of different types of potassium channel blockers and/or DHA on potassium channels currents were studied by whole-cell patch clamp technique.
Potassium currents were significantly increased with 5 μmol/L DHA perfusion (P<0.05). The current density was increased from (52.80±6.68) pA/pF to (110.09±13.39) pA/pF (P<0.05) after DHA perfusion when the stimulation voltage was 100 mV.Compared with baseline, potassium currents were significantly decreased by various inhibitor perfusion (tetraethylammonium: (49.63±5.75) pA/pF vs. (13.96±2.18) pA/pF; ibritoxin: (50.67±7.89) pA/pF vs. (26.53±4.68) pA/pF; TRAM-34: (52.60±7.02) pA/pF vs. (46.05±7.60) pA/pF; apamin: (51.97±3.83) pA/pF vs. (44.89±5.04) pA/pF; 4-aminopyridine: (51.19±3.44) pA/pF vs. (29.92±2.81) pA/pF; glyburide: (49.67±1.77) pA/pF vs. (49.61±1.87) pA/
Action potential induces membrane depolarization and triggers intracellular free Ca
concentration (Ca
)-dependent secretion (CDS) via Ca
influx through voltage-gated Ca
channels. We report a new type ...of somatic exocytosis triggered by the action potential per se-Ca
-independent but voltage-dependent secretion (CiVDS)-in dorsal root ganglion neurons. Here we uncovered the molecular mechanism of CiVDS, comprising a voltage sensor, fusion machinery, and their linker. Specifically, the voltage-gated N-type Ca
channel (Ca
2.2) is the voltage sensor triggering CiVDS, the SNARE complex functions as the vesicle fusion machinery, the "synprint" of Ca
2.2 serves as a linker between the voltage sensor and the fusion machinery, and ATP is a cargo of CiVDS vesicles. Thus, CiVDS releases ATP from the soma while CDS releases glutamate from presynaptic terminals, establishing the Ca
2.2-SNARE "voltage-gating fusion pore" as a novel pathway co-existing with the canonical "Ca
-gating fusion pore" pathway for neurotransmitter release following action potentials in primary sensory neurons.
Data imbalance in skin lesions datasets are common problems of skin cancer classification tasks based on deep learning. This study proposes a two-stage classification strategy based on an advanced ...benchmark multi-classification model, which transforms the "multi-category" task into a "main class and non-main class binary" task and a "multi-category within non-main classes" task to smooth the class distribution of skin cancer datasets. This strategy can significantly improve the final classification performance compared to the direct multi-classification task, and can provide a reference for solving similar data imbalance problems.
Global place recognition is a crucial ability for unmanned ground vehicles since it is the premise of localization in a prior map. However, global place recognition using only 3D LIDAR is still a ...challenging problem. In this paper, a LIDAR-based place recognition method within a 3D Point cloud map is proposed. The global descriptor Scan Context (SC) is adopted and improved by building a local reference frame so that it's more robust to viewpoint changes. Accordingly, a three-stage matching algorithm is proposed to efficiently perform place recognition. The proposed method is verified on the KITTI dataset. The experimental results show that the proposed method can perform precise place recognition in about 200ms and the success rate is around 98%, which is 16% higher than SC.
At present, the failure disposal process for the CBTC system relies heavily on the personal experience of practitioners, and the level of intelligence is at a low level. At the same time, the ...valuable information in the failure log text is not effectively exploited. Aiming at these problems, this paper proposes a decision-making method for CBTC system operation and maintenance(O&M) based on knowledge graph. First, the knowledge graph construction process is built by combining top-down and bottom-up methods, and the schema layer of the whole failure O&M process is designed by combining expert knowledge. Then, the BERT pre-training model is applied to extract failure entities from the labeled dataset, and the experiment is used to prove the good performance of this model. Next, the extracted entities and their relationships are in the form of nodes and edges for failure knowledge graph is populated and visualized using Neo4j. Finally, the CBTC system O&M knowledge graph is applied to give the failure cause tracing and maintenance suggestion generation method, and the usability of the proposed method is verified with examples, which can effectively assist practitioners to make the O&M decision.
Transcorneal electrical stimulation (TES) has been proved to be able to provide neuroprotection effect to delay retinal degenerative diseases. However, the diffuse electric field and subthreshold ...stimulation current delivered by the conventional TES cannot accurately stimulate retinal neurons. A more recently developed temporal interference (TI) stimulation approach has demonstrated the capability of generating a more localized electrical field near the target neurons, suggesting its promising performance in localized retinal stimulation. The characteristics of retinal ganglion cell (RGC) activation are not only related to the electric field distribution, but also related to the morphological and electrophysiological characteristics of RGCs itself. This study investigated the effect of multiple RGC morphological and electrophysiological properties on the RGC activation threshold under TI stimulation. Our simulation suggested that RGC activation threshold was most affected by sodium channel conductance distributed in high sodium channel band (SOCB) and less affected by dendritic field size, dendritic field depth, and SOCB length. RGC activation threshold decreased with the increment of SOCB conductance and slightly decreased with the increment of dendritic field depth and SOCB length, while slightly increased with the increment of dendritic field size. This study provides new knowledge about the spatial responsive characteristics of RGC activation under TI stimulation.
Transcorneal electrical stimulation (TES) used in a therapeutic device has been demonstrated significant neuroprotective effect for rescuing retinal function. However, the diffuse electric field ...induced by conventional TES devices reduced their spatial resolution and selectivity, limiting their capability of actively stimulating a severely diseased retina. A cutting-edge neuromodulation approach named temporal interference stimulation (TIS) was reported to induce electric fields focalizing on local neuronal targets. Despite the competent feasibility of application in retinal TIS, the interpretation of characteristics of spatial resolution and selectivity under TIS remains rudimentary. In this study, we conduct in silico investigations to understand the characteristics of spatial selectivity and resolution using a finite element model of a multi-layered eyeball and multiple electrode configuration. By simulating different metrics of electric potentials envelope modulated by TIS, our model supports the possibility of achieving mini-invasive and spatially selective electrical stimulation using retinal TIS. These simulations provide theoretical evidence on the basis of which sophisticated devices for improved spatial selectivity can be designed.Clinical Relevance- This study provides a theoretical basis for understanding how the design of electrode configuration impacts transcorneal TIS performance. This model can guide future development of transcorneal TIS configurations and stimulation strategies that may benefit patients with inherited retinal diseases.
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