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Abstract Eco-friendly Sn-based perovskites show significant potential for high-performance second near-infrared window light-emitting diodes (900 nm – 1700 nm). Nevertheless, achieving efficient and stable Sn-based perovskite second near-infrared window light-emitting diodes remains challenging due to the propensity of Sn2+ to oxidize, resulting in detrimental Sn4+-induced defects and compromised device performance. Here, we present a targeted strategy to eliminate Sn4+-induced defects through moisture-triggered hydrolysis of tin tetrahalide, without degrading Sn2+ in the CsSnI3 film. During the moisture treatment, tin tetrahalide is selectively hydrolyzed to Sn(OH)4, which provides sustained protection. As a result, we successfully fabricate second near-infrared window light-emitting diodes emitting at 945 nm, achieving a performance breakthrough with an external quantum efficiency of 7.6% and an operational lifetime reaching 82.6 h.

Accurately predicting Drug-Drug Interaction (DDI) is a critical and challenging aspect of the drug discovery process, particularly in preventing adverse reactions in patients undergoing combination therapy. However, current DDI prediction methods often overlook the interaction information between chemical substructures of drugs, focusing solely on the interaction information between drugs and failing to capture sufficient chemical substructure details. To address this limitation, we introduce a novel DDI prediction method: Multi-layer Adaptive Soft Mask Graph Neural Network (MASMDDI). Specifically, we first design a multi-layer adaptive soft mask graph neural network to extract substructures from molecular graphs. Second, we employ an attention mechanism to mine substructure feature information and update latent features. In this process, to optimize the final feature representation, we decompose drug-drug interactions into pairwise interaction correlations between the core substructures of each drug. Third, we use these features to predict the interaction probabilities of DDI tuples and evaluate the model using real-world datasets. Experimental results demonstrate that the proposed model outperforms state-of-the-art methods in DDI prediction. Furthermore, MASMDDI exhibits excellent performance in predicting DDIs of unknown drugs in two tasks that are more aligned with real-world scenarios. In particular, in the transductive scenario using the DrugBank dataset, the ACC and AUROC and AUPRC scores of MASMDDI are 0.9596, 0.9903, and 0.9894, which are 2% higher than the best performing baseline.

Abstract Due to their unique photoelectric properties, nontoxic tin‐based perovskites are emerging candidates for efficient near‐infrared LEDs. However, the facile oxidation of Sn2+ and the rapid crystallization rate of tin‐based perovskites result in suboptimal film quality, leading to inferior efficiencies of tin‐based perovskite light‐emitting diodes (Pero‐LEDs). In this study, we investigate the influence of commonly used solvents on the quality of the CsSnI3 films. Remarkably, DMSO exhibits a stronger interaction with SnI2, forming a stable intermediate phase of SnI2·3DMSO. This intermediate effectively inhibits the oxidation of Sn2+ and slows down the crystallization rate, bringing in lower defect state density and higher photoluminescence quantum yield of the prepared perovskite films. Consequently, the corresponding Pero‐LEDs achieve a maximum external quantum efficiency (EQE) of 5.6%, among the most efficient near‐infrared Pero‐LEDs. In addition, the device processes ultra‐low efficiency roll‐off and high reproducibility. Our research underscores the crucial role of solvent‐perovskite coordination in determining film quality. These findings offer valuable guidance for screening solvents to prepare highly efficient and stable tin‐based perovskites.

Hemerocallis citrina Baroni (H. citrina) has been commonly utilized in diet and conventional medicine. In this study, 21 compounds were obtained from the flower buds of H. citrina. Compounds 1, 2 and 3 were three novel compounds isolated from Hemerocallis genus. Compounds 4, 6, 7, 9, 10, 13–19 were isolated from Hemerocallis genus for the first time. It indicated that compounds 1, 2, 3, 4, 5, 7 and 13 exhibited a significant NO inhibitory effect in the LPS induced BV2 cells. The analysis result of PPI and molecular docking showed that compound 1 may play an anti-neuroinflammatory role through MAPK signaling pathway. The result of pharmacological experiments proved that compound 1 effectively inhibited the generation of NO and inflammatory cytokines by inhibiting the activation of MAPK and NF-κB pathway. This research provided a basis for further study and utilization of H. citrina in anti-neuroinflammatory effect.

Taihang Mountains are situated between Shanxi Province and the North China Plain, spanning Beijing, Hebei, Shanxi, and Henan provinces and cities. The mountains extend from northeast to southwest for over 400 km, naturally deviding the second step from the third one in China. The southeastern area of Taihang Mountains specifically refers to Changzhi City and Jincheng Administrative Region of Shanxi Province. Given Shanxi Province’s robust development plans for the southeast area of Taihang Mountains, the medicinal plant resources in this area will be affected. Therefore, it is imperative and urgent to conduct a comprehensive investigation and study on the medicinal plant resources in the southeast area of Taihang Mountains. By means of field investigation, literature review, and specimen identification, the plant resources and diversity of two counties in the southeast of Taihang Mountains were evaluated. The findings revealed 234 plants species across 172 genera in 70 families, primarily comprising angiosperms. The families with more species included Compositae, Leguminosae, Rosaceae, Labiatae, Ranunculaceae. Among the genera, those with more species were Cynanchum, Selaginella, Clematis, Thalictrum, and Rhamnus. A total of 114 medicinal plants were identified, constituting 48.72% of the total. Regarding medicinal parts, the concentration is in roots and rhizomes, followed by whole plants and fruits. On the basis of investigation and study, some suggestions on the development, utilization, and protection of medicinal plant resources in southeast Taihang Mountains were made. These suggestions provide valuable insights for the study on medicinal plant resources and vegetation in the southeast of Taihang Mountains, serving as a scientific basis for the protection and sustainable utilization of wild medicinal plant resources. [ABSTRACT FROM AUTHOR]