Alloying-Induced Synthesis of Amorphous PdZnS Hollow Spheres as Enhanced Oxygen Reduction Catalysts.

Amorphous alloys have multiple advantages in electrocatalysis, yet the isotropic nature makes their syntheses a great obstacle in application. In this work, it is shown that the Zn2+ can interfere with the crystallization of Pd-base structures to form amorphous alloy materials. By simply adjusting the Zn2+ content, unique PdZnS amorphous hollow spheres (AHS) with various compositions and degrees of crystallinity can be obtained through a facile one-pot wet chemical method. Owing to both the amorphous nature and hollow morphologies, the PdZnS AHSs possess appealing activities and stabilities as oxygen reduction catalysts. Typically, the Pd20 ZnS10 AHSs exhibit the highest half-wave potential (E1/2 ) of 0.940 V (vs reversible hydrogen electrode), and such E1/2 only negatively shifts 25 mV after 60 000 cycles.

Coalescence of Au-Pd Nanoropes and their Application as Enhanced Electrocatalysts for the Oxygen Reduction Reaction.

Lattice distortions and defects can lead to a strain effect that greatly affects the electronic structure of the noble metal surface and the chemical adsorption of ligands on the surfaces. Introducing defects is an efficient strategy to improve the activity of noble metal catalysts. Herein, a fusion approach is developed to fine-tune the defects and lattice strain in Au-Pd nanowires. Specifically, braided strands in Au-Pd nanoropes gradually coalesce to form solid nanowires upon H2 O2 treatment and heating, leading to a series of Au-Pd nanowires with various amounts of defects. Owing to the 1D morphology, as well as the optimized lattice strain and surface electronic structure, the intermediate Au-Pd nanowire obtained after 60 min heating (denoted as Au-Pd NW60 ) exhibits excellent catalytic activity and stability toward the oxygen reduction reaction, with the half-wave potential at 0.918 V, 45 mV higher than that of the commercial Pt/C; and specific activity reaches up to 1.7 mA cm-2 , 7.3 times higher than that of the Pt/C.

Ultrasound images-based deep learning radiomics nomogram for preoperative prediction of RET rearrangement in papillary thyroid carcinoma.

Purpose: To create an ultrasound -based deep learning radiomics nomogram (DLRN) for preoperatively predicting the presence of RET rearrangement among patients with papillary thyroid carcinoma (PTC). Methods: We retrospectively enrolled 650 patients with PTC. Patients were divided into the RET/PTC rearrangement group (n = 103) and the non-RET/PTC rearrangement group (n = 547). Radiomics features were extracted based on hand-crafted features from the ultrasound images, and deep learning networks were used to extract deep transfer learning features. The least absolute shrinkage and selection operator regression was applied to select the features of nonzero coefficients from radiomics and deep transfer learning features; then, we established the deep learning radiomics signature. DLRN was constructed using a logistic regression algorithm by combining clinical and deep learning radiomics signatures. The prediction performance was evaluated using the receiver operating characteristic curve, calibration curve, and decision curve analysis. Results: Comparing the effectiveness of the models by linking the area under the receiver operating characteristic curve of each model, we found that the area under the curve of DLRN could reach 0.9545 (95% confidence interval: 0.9133-0.9558) in the test cohort and 0.9396 (95% confidence interval: 0.9185-0.9607) in the training cohort, indicating that the model has an excellent performance in predicting RET rearrangement in PTC. The decision curve analysis demonstrated that the combined model was clinically useful. Conclusion: The novel ultrasonic-based DLRN has an important clinical value for predicting RET rearrangement in PTC. It can provide physicians with a preoperative non-invasive primary screening method for RET rearrangement diagnosis, thus facilitating targeted patients with purposeful molecular sequencing to avoid unnecessary medical investment and improve treatment outcomes.

Synthesis of substrate-bound seaweed-like Au nanowires with amino silane coupling agents.

A seedless method has been developed to synthesize seaweed-like Au nanowires on a Au substrate. The amino silane coupling agent 3-aminopropyltriethoxysilane was employed to form the active surfaces that facilitate the one dimensional growth. The growth mechanism and controlling parameters were investigated. Furthermore, the compatibility of this synthesis with a colloidal Au substrate was also demonstrated.

Isocitrate Dehydrogenase Mutations in Glioma: From Basic Discovery to Therapeutics Development.

Isocitrate dehydrogenase (IDH) is a key rate-limiting enzyme in the Krebs cycle that plays an important role in energy metabolism. In recent years, it has been found that IDH mutations are closely related to the occurrence and development of glioma, and it is a notable potential therapeutic target. First, IDH mutations can produce high levels of 2-hydroxyglutaric acid (2-HG), thereby inhibiting glioma stem cell differentiation. At the same time, IDH mutations can upregulate vascular endothelial growth factor (VEGF) to promote the formation of the tumor microenvironment. In addition, IDH mutations can also induce high levels of hypoxia-inducible factor-1α (HIF-1α) to promote glioma invasion. Ultimately, these changes will lead to the development of glioma. Currently, a large number of IDH inhibitors and vaccines have entered clinical trials, representing progress in the treatment of glioma patients.