Annealing temperature effects on monolayer WS2-veiled Ag nanoparticle array for surface catalytic reaction.

Plasmonic-WS2 hybrids have attracted widespread interest for plasmon driven catalytic reactions. In this work, a Ag nanoparticles (NPs)/WS2 hybrid was fabricated by utilizing a one-step anodized Al template-assisted vacuum thermal evaporation technique and wet transfer method. To optimize the catalytic performance, the morphological evolution and corresponding changes in the catalytic properties of the Ag NPs/WS2 hybrid at different thermal annealing temperatures were investigated. It was found that the surface-enhanced Raman scattering (SERS) and catalytic activity of the hybrid were optimized by tuning the annealing temperature, with the optimal SERS and catalytic properties observed at 290 °C. These results may open new avenues for improving the efficiency and expanding the research field of plasmon-driven reactions.

Machine learning approach to screen new diagnostic features of adamantinomatous craniopharyngioma and explore personalised treatment strategies.

Background: Adamantinoma craniopharyngioma (ACP) is a non-malignant tumour of unknown pathogenesis that frequently occurs in children and has malignant potential. The main treatment options are currently surgical resection and radiotherapy. These treatments can lead to serious complications that greatly affect the overall survival and quality of life of patients. It is therefore important to use bioinformatics to explore the mechanisms of ACP development and progression and to identify new molecules. Methods: Sequencing data of ACP was downloaded from the comprehensive gene expression database for differentially expressed gene identification and visualized by Gene Ontology, Kyoto Gene, and gene set enrichment analyses (GSEAs). Weighted correlation network analysis was used to identify the genes most strongly associated with ACP. GSE94349 was used as the training set and five diagnostic markers were screened using machine learning algorithms to assess diagnostic accuracy using receiver operating characteristic (ROC) curves, while GSE68015 was used as the validation set for verification. Results: Type I cytoskeletal 15 (KRT15), Follicular dendritic cell secreted peptide (FDCSP), Rho-related GTP-binding protein RhoC (RHOC), Modulates negatively TGFB1 signaling in keratinocytes (CD109), and type II cytoskeletal 6A (KRT6A) (area under their receiver operating characteristic curves is 1 for both the training and validation sets), Nomograms constructed using these five markers can predict progression of ACP patients. Whereas ACP tissues with activated T-cell surface glycoprotein CD4, Gamma delta T cells, eosinophils and regulatory T cells were expressed at higher levels than in normal tissues, which may contribute to the pathogenesis of ACP. According to the analysis of the CellMiner database (Tumor cell and drug related database tools), high CD109 levels showed significant drug sensitivity to Dexrazoxane, which has the potential to be a therapeutic agent for ACP. Conclusions: Our findings extend understandings of the molecular immune mechanisms of ACP and suggest possible biomarkers for the targeted and precise treatment of ACP.

Novel prognostic features and personalized treatment strategies for mitochondria-related genes in glioma patients.

Background: Gliomas are the most common intracranial nervous system tumours that are highly malignant and aggressive, and mitochondria are an important marker of metabolic reprogramming of tumour cells, the prognosis of which cannot be accurately predicted by current histopathology. Therefore, Identify a mitochondrial gene with immune-related features that could be used to predict the prognosis of glioma patients. Methods: Gliomas data were downloaded from the TCGA database and mitochondrial-associated genes were obtained from the MITOCARTA 3.0 dataset. The CGGA, kamoun and gravendeel databases were used as external datasets. LASSO(Least absolute shrinkage and selection operator) regression was applied to identify prognostic features, and area and nomograms under the ROC(Receiver Operating Characteristic) curve were used to assess the robustness of the model. Single sample genomic enrichment analysis (ssGSEA) was employed to explore the relationship between model genes and immune infiltration, and drug sensitivity was used to identify targeting drugs. Cellular studies were then performed to demonstrate drug killing against tumours. Results: COX assembly mitochondrial protein homolog (CMC1), Cytochrome c oxidase protein 20 homolog (COX20) and Cytochrome b-c1 complex subunit 7 (UQCRB) were identified as prognostic key genes in glioma, with UQCRB, CMC1 progressively increasing and COX20 progressively decreasing with decreasing risk scores. ROC curve analysis of the TCGA training set model yielded AUC (Area Under The Curve) values >0.8 for 1-, 2- and 3-year survival, and the model was associated with both CD8+ T cells and immune checkpoints. Finally, using cellMiner database and molecular docking, it was confirmed that UQCRB binds covalently to Amonafide via lysine at position 78 and threonine at position 82, while cellular assays showed that Amonafide inhibits glioma migration and invasion. Conclusion: Our three mitochondrial genomic composition-related features accurately predict Survival in glioma patients, and we also provide glioma chemotherapeutic agents that may be mitochondria-related targets.

Annealing Temperature-Dependent Surface-Enhanced Raman spectroscopy on MoS2-Covered silver nanoparticle array.

Surface-enhanced Raman spectroscopy (SERS) is an ultra-sensitive analytical tool that can effectively detect and identify molecules by their unique vibrational fingerprints. Development of SERS substrates with good stability, high sensitivity and reproducibility is still a big challenge in practical applications. Recently, 2D materials/metallic hybrid SERS substrates provide a new prospect to improve the SERS performance. Here, we obtain a monolayer MoS2 covered silver nanoparticle (AgNP) array as a high-performance SERS substrate. Annealing temperature-dependent SERS signals on the hybrid substrate have been explored. The optimum SERS performance was obtained at 290 ℃ (the detection limit of 10-13 M for Rhodamine 6G and the corresponding SERS enhancement factor of 8.3 × 109), which is attributed to the better contact between AgNPs and MoS2 and the uniform AgNPs with appropriate particle sizes. The prepared MoS2/AgNPs hybrid substrates also have been utilized to detect various molecules, which demonstrates a great potential for applications in food safety and biochemical environmental detection.

A temporal stability approach to position and attention-shift-invariant recognition.

Incorporation of visual-related self-action signals can help neural networks learn invariance. We describe a method that can produce a network with invariance to changes in visual input caused by eye movements and covert attention shifts. Training of the network is controlled by signals associated with eye movements and covert attention shifting. A temporal perceptual stability constraint is used to drive the output of the network toward remaining constant across temporal sequences of saccadic motions and covert attention shifts. We use a four-layer neural network model to perform the position-invariant extraction of local features and temporal integration of invariant presentations of local features in a bottom-up structure. We present results on both simulated data and real images to demonstrate that our network can acquire both position and attention shift invariance.