Fe-Ion-Catalyzed Synthesis of CdSe/Cu Core/Shell Nanowires.

CdSe/Cu core/shell nanowires (NWs) are successfully synthesized by a wet chemical method for the first time. By utilizing the solution-liquid-solid (SLS) mechanism, CdSe NWs are fabricated by Bi seeds, which act as catalysts. In the subsequent radial overcoating of the Cu shell on the CdSe NWs, Fe ions have been proven to be an indispensable and efficient catalyzer. The thickness of the Cu shell could be well controlled in the range of 3 to 6 nm by varying the growth temperature (from 300 to 360 °C). Our synthetic strategy pioneers a new possibility for the controlled synthesis of semiconductor-metal heterostructure NWs (especially for II-VI semiconductors), such as CdS/Cu, ZnS/Au, and ZnO/Ag, which had broad application prospects in photoconductors, thin-film transistors, and light-emitting diodes. Theoretically, electrons flow from a higher Fermi-level material to the bottom Fermi-level at the metal-semiconductor heterojunction interface, which aligns the Fermi level and establishes the Schottky barrier. It leads to excess negative charges in metals and excess positive charges in semiconductors. Therefore, those effective electron traps reduce the probability of photogenerated electron-hole pair recombination efficiently, which has been widely applied in solar cells, sensors, photocatalysis, and energy storage. The breakthrough and innovation of this synthesis method have opened up a new synthetic route with a mild reaction environment, low energy consumption, and convenience.

Recent progress in electrochemical C-N coupling: metal catalyst strategies and applications.

Electrochemical C-N coupling reactions hold significant importance in the fields of organic chemistry and green chemistry. Conventional methods for constructing C-N bonds typically rely on high temperatures, high pressures, and other conditions that are energy-intensive and prone to generating environmental pollutants. In contrast, the electrochemical approaches employ electrical energy as the driving force to achieve C-N bond formation under ambient conditions, representing a more environment-friendly and sustainable alternative. The notable advantages of electrochemical C-N coupling include high efficiency, good selectivity, and mild reaction conditions. Through rational design of corresponding electrocatalysts, it is possible to achieve efficient C-N bond coupling at low potentials. Moreover, the electrochemical methods allow for precise control over reaction conditions, thereby avoiding side reactions and by-products that are common for conventional methods, improving both selectivity and product purity. Despite the extensive research efforts devoted to exploring the potential of electrochemical C-N coupling, the design of efficient and stable metal catalysts remains a significant challenge. In this review, we summarize and evaluate the latest strategies developed for designing metal catalysts, and their application prospects for different nitrogen sources such as N2 and NOx. We delineate how the control over nanoscale structures, morphologies, and electronic properties of metal catalysts can optimize their performance in C-N coupling reactions, and discuss the performances and advantages of single-metal catalysts, bimetallic catalysts, and single-atom catalysts under various reaction conditions. By summarizing the latest research achievements, particularly in the development of high-efficiency catalysts, the application of novel catalyst materials, and the in-depth study of reaction mechanisms, this review aims to provide insights for future research in the field of electrochemical C-N coupling, and demonstrates that rationally designed metal catalysts could not only enhance the efficiency and selectivity of electrochemical C-N coupling reactions, but also offer conceptual frameworks for other electrochemical reactions.

A decentralized federated learning-based cancer survival prediction method with privacy protection.

Background: Survival prediction is one of the crucial goals in precision medicine, as accurate survival assessment can aid physicians in selecting appropriate treatment for individual patients. To achieve this aim, extensive data must be utilized to train the prediction model and prevent overfitting. However, the collection of patient data for disease prediction is challenging due to potential variations in data sources across institutions and concerns regarding privacy and ownership issues in data sharing. To facilitate the integration of cancer data from different institutions without violating privacy laws, we developed a federated learning-based data integration framework called AdFed, which can be used to evaluate patients' survival while considering the privacy protection problem by utilizing the decentralized federated learning technology and regularization method. Results: AdFed was tested on different cancer datasets that contain the patients' information from different institutions. The experimental results show that AdFed using distributed data can achieve better performance in cancer survival prediction (AUC = 0.605) than the compared federated-learning-based methods (average AUC = 0.554). Additionally, to assess the biological interpretability of our method, in the case study we list 10 identified genes related to liver cancer selected by AdFed, among which 5 genes have been proved by literature review. Conclusions: The results indicate that AdFed outperforms better than other federated-learning-based methods, and the interpretable algorithm can select biologically significant genes and pathways while ensuring the confidentiality and integrity of data.

Challenges and Perspectives of Single-Atom-Based Catalysts for Electrochemical Reactions.

Single-atom catalysts (SACs) are emerging as the most promising catalysts for various electrochemical reactions. The isolated dispersion of metal atoms enables high density of active sites, and the simplified structure makes them ideal model systems to study the structure-performance relationships. However, the activity of SACs is still insufficient, and the stability of SACs is usually inferior but has received little attention, hindering their practical applications in real devices. Moreover, the catalytic mechanism on a single metal site is unclear, leading the development of SACs to rely on trial-and-error experiments. How can one break the current bottleneck of active sites density? How can one further increase the activity/stability of metal sites? In this Perspective, we discuss the underlying reasons for the current challenges and identify precisely controlled synthesis involving designed precursors and innovative heat-treatment techniques as the key for the development of high-performance SACs. In addition, advanced operando characterizations and theoretical simulations are essential for uncovering the true structure and electrocatalytic mechanism of an active site. Finally, future directions that may arise breakthroughs are discussed.

Hollow structures as drug carriers: Recognition, response, and release.

Hollow structures have demonstrated great potential in drug delivery owing to their privileged structure, such as high surface-to-volume ratio, low density, large cavities, and hierarchical pores. In this review, we provide a comprehensive overview of hollow structured materials applied in targeting recognition, smart response, and drug release, and we have addressed the possible chemical factors and reactions in these three processes. The advantages of hollow nanostructures are summarized as follows: hollow cavity contributes to large loading capacity; a tailored structure helps controllable drug release; variable compounds adapt to flexible application; surface modification facilitates smart responsive release. Especially, because the multiple physical barriers and chemical interactions can be induced by multishells, hollow multishelled structure is considered as a promising material with unique loading and releasing properties. Finally, we conclude this review with some perspectives on the future research and development of the hollow structures as drug carriers.

Predictive Value of Folate Receptor-Positive Circulating Tumor Cells for the Preoperative Diagnosis of Lymph Node Metastasis in Patients with Lung Adenocarcinoma.

Noninvasive assessments of the risk of lymph node metastasis (LNM) in patients with lung adenocarcinoma (LAD) are of great value for selecting individualized treatment options. However, the diagnostic accuracies of different preoperative LN evaluation methods in routine clinical practice are not satisfactory. Here, an assessment to detect folate receptor (FR)-positive circulating tumor cells (CTCs) based on ligand-targeted enzyme-linked polymerization is established. FR-positive CTCs have the potential to improve the specificity and sensitivity of diagnosing LNM in lung cancer patients. The addition of CTC level improved the diagnostic efficiency of the initial prediction model that comprises other clinical parameters. A nomogram for predicting preoperative LNM is established, which showed good prediction and calibration capacities and achieved an average area under the curve of 0.786. Good correlations are observed between the CTC level and nodal classifications, such as the number of positive LNs and the ratio of the number of positive LNs to removed LNs (LN ratio or LNR). The ligand-targeted enzyme-linked polymerization-assisted assessment of CTCs enables noninvasive detection and has a useful predictive value for the preoperative diagnosis of LNM in patients with LAD.