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Efficient transition‐metal‐free synthesis of benzo[b]azepines and oxindoles is achieved via a radical relay cascade strategy employing halogen atom transfer (XAT) for aryl radical generation followed by intramolecular hydrogen atom transfer (HAT). Optimization yielded moderate to substantial yields under visible light irradiation. Preliminary biological assessments revealed promising anti‐tumor activity for select compounds. This study underscores the potential of XAT‐mediated radical relay cascades in medicinal chemistry and anticancer drug discovery. [ABSTRACT FROM AUTHOR]

This study presents detailed time-integrated and time-resolved spectral analysis of the Fermi Gamma-ray Burst Monitor observations of the bright GRB 231129C. The results reveal its distinct spectral characteristics, featuring a hard low-energy spectral index (α) and soft high-energy spectral index (β), similar to GRB 090902B, suggesting a possible dominance of thermal emission. Further analysis indicates that 92% of the spectral indices exceed the synchrotron "line of death," with the hardest index at α ∼ +0.44. Simultaneously, 53% of the spectra can be well fitted by the nondissipative photosphere model, supporting a potential origin from a nondissipative photosphere. Additionally, we observe strong correlations between the spectral index α and peak energy E p with flux. For the α − F relationship, we employ F = F 0 e (3.00±0.10) α to describe it, whereas the E p− F relationship requires a smoothly bending power-law function. Based on the framework proposed by Hascoët et al. and Gao & Zhang, the jet characteristics of this burst were studied, revealing that both methods support the suitability of a pure fireball model for this GRB at small initial jet radii. [ABSTRACT FROM AUTHOR]

The relationship among polycystic ovary syndrome (PCOS), endometrial cancer (EC), and glycometabolism remains unclear. We explored shared genes between PCOS and EC, using bioinformatics to unveil their pathogenic connection and influence on EC prognosis. Gene Expression Omnibus datasets GSE226146 (PCOS) and GSE196033 (EC) were used. A protein–protein interaction (PPI) network was constructed to identify the central genes. Candidate markers were screened using dataset GSE54250. Differences in marker expression were confirmed in mouse PCOS and human EC tissues using RT‐PCR and immunohistochemistry. The effect of PGD on EC proliferation and migration was explored using Ki‐67 and Transwell assays. PGD's impact on the glycometabolic pathway within carbon metabolism was assessed by quantifying glucose content and lactic acid production. R software identified 31 common genes in GSE226146 and GSE196033. Gene Ontology functional classification revealed enrichment in the "purine nucleoside triphosphate metabolism process," with key Kyoto Encyclopedia of Genes and Genomes pathways related to "carbon metabolism." The PPI network identified 15 hub genes. HK2, NDUFS8, PHGDH, PGD, and SMAD3 were confirmed as candidate markers. The RT‐PCR analysis validated distinct HK2 and PGD expression patterns in mouse PCOS ovarian tissue and human EC tissue, as well as in normal and EC cells. Transfection experiments with Ishikawa cells further confirmed PGD's influence on cell proliferation and migration. Suppression of PGD expression impeded glycometabolism within the carbon metabolism of EC cells, suggesting PGD as a significant PCOS risk factor impacting EC proliferation and migration through modulation of single carbon metabolism. These findings highlight PGD's pivotal role in EC onset and prognosis. [ABSTRACT FROM AUTHOR]

This report describes a copper-catalyzed, photoinduced N-to-alkyl radical relay Sonogashira-type reactions at benzylic sites in o-alkylbenzamides with alkynes. The process employs an N-to-alkyl radical mechanism, initiated through the copper-catalyzed reductive generation of nitrogen radicals. Radical translocation is facilitated by a 1,5-hydrogen atom transfer (1,5-HAT), leading to the formation of translocated carbon radicals. These radicals are then subjected to copper-catalyzed alkynylation. The methodology exhibits broad sub-strate scope and applicability to the synthesis of complex natural products. [ABSTRACT FROM AUTHOR]

Traditional Chinese medicine (TCM) has relied on pulse diagnosis as a cornerstone of healthcare assessment for thousands of years. Despite its long history and widespread use, TCM pulse diagnosis has faced challenges in terms of diagnostic accuracy and consistency due to its dependence on subjective interpretation and theoretical analysis. This study introduces an approach to enhance the accuracy of TCM pulse diagnosis for diabetes by leveraging the power of deep learning algorithms, specifically LeNet and ResNet models, for pulse waveform analysis. LeNet and ResNet models were applied to analyze TCM pulse waveforms using a diverse dataset comprising both healthy individuals and patients with diabetes. The integration of these advanced algorithms with modern TCM pulse measurement instruments shows great promise in reducing practitioner-dependent variability and improving the reliability of diagnoses. This research bridges the gap between ancient wisdom and cutting-edge technology in healthcare. LeNet-F, incorporating special feature extraction of a pulse based on TMC, showed improved training and test accuracies (73% and 67%, respectively, compared with LeNet's 70% and 65%). Moreover, ResNet models consistently outperformed LeNet, with ResNet18-F achieving the highest accuracy (82%) in training and 74% in testing. The advanced preprocessing techniques and additional features contribute significantly to ResNet18-F's superior performance, indicating the importance of feature engineering strategies. Furthermore, the study identifies potential avenues for future research, including optimizing preprocessing techniques to handle pulse waveform variations and noise levels, integrating additional time–frequency domain features, developing domain-specific feature selection algorithms, and expanding the scope to other diseases. These advancements aim to refine traditional Chinese medicine pulse diagnosis, enhancing its accuracy and reliability while integrating it into modern technology for more effective healthcare approaches. [ABSTRACT FROM AUTHOR]

Nanoscience is one of the fastest growing and most impactful fields in global scientific research. In order to support the continued development of nanoscience and nanotechnology, it is important that nanoscience education be a top priority to accelerate research excellence. In this Nano Focus, we discuss current approaches to nanoscience training and propose a learning design framework to promote the next generation of nanoscientists. Prominent among these are the abilities to communicate and to work across and between conventional disciplines. While the United States has played leading roles in initiating these developments, the global landscape of nanoscience calls for worldwide attention to this educational need. Recent developments in emerging nanoscience nations are also discussed. Photo credit: Jae Hyeon Park.