A practical method for the 1,3-azidoheteroarylation of[1.1.1]propellane with cyclic aldimines and azidotrimethylsilane(TMSN_(3))is presented.A broad spectrum of 1-azido-3-heteroaryl bicyclo[1.1.1]pentanes(BCPs)can be ...A practical method for the 1,3-azidoheteroarylation of[1.1.1]propellane with cyclic aldimines and azidotrimethylsilane(TMSN_(3))is presented.A broad spectrum of 1-azido-3-heteroaryl bicyclo[1.1.1]pentanes(BCPs)can be synthesized in moderate-to-good yields under standard conditions.The versatility of this method is further confirmed by its applicability to large-scale synthesis,product derivatizations,and late-stage functionalization of pharmaceutically relevant molecules.Mechanistic studies reveal that a radical relay mechanism initiated by a single-electron transfer(SET)process is operational.展开更多
Two dimensional(2D) materials based on boron and carbon have attracted wide attention due to their unique properties. BC compounds have rich active sites and diverse chemical coordination, showing great potential in o...Two dimensional(2D) materials based on boron and carbon have attracted wide attention due to their unique properties. BC compounds have rich active sites and diverse chemical coordination, showing great potential in optoelectronic applications. However, due to the limitation of calculation and experimental conditions, it is still a challenging task to predict new 2D BC monolayer materials. Specifically, we utilized Crystal Diffusion Variational Autoencoder(CDVAE) and pre-trained Materials Graph Neural Network with 3-Body Interactions(M3GNet) model to generate novel and stable BCP materials. Each crystal structure was treated as a high-dimensional vector, where the encoder extracted lattice information and element coordinates, mapping the high-dimensional data into a low-dimensional latent space. The decoder then reconstructed the latent representation back into the original data space. Additionally, our designed attribute predictor network combined the advantages of dilated convolutions and residual connections,effectively increasing the model's receptive field and learning capacity while maintaining relatively low parameter count and computational complexity. By progressively increasing the dilation rate, the model can capture features at different scales. We used the DFT data set of about 1600 BCP monolayer materials to train the diffusion model, and combined with the pre-trained M3GNet model to screen the best candidate structure. Finally, we used DFT calculations to confirm the stability of the candidate structure.The results show that the combination of generative deep learning model and attribute prediction model can help accelerate the discovery and research of new 2D materials, and provide effective methods for exploring the inverse design of new two-dimensional materials.展开更多
[Objectives]To explore the impact of bone collagen peptide(BCP)on patients with knee osteoarthritis(KOA).[Methods]A total of 100 patients diagnosed with KOA were admitted to the study and randomly assigned to either a...[Objectives]To explore the impact of bone collagen peptide(BCP)on patients with knee osteoarthritis(KOA).[Methods]A total of 100 patients diagnosed with KOA were admitted to the study and randomly assigned to either a control group or a treatment group,with each group comprising 50 participants.The control group received health education along with standard daily treatment protocols.In contrast,the treatment group was administered an additional dosage of 20 g of BCP twice daily,in conjunction with the treatment regimen provided to the control group.Both groups received continuous treatment for 3 months.The WOMAC scores and the WHOQOL-BREF scores of the participants in both groups were assessed both prior to and following treatment.[Results]Following treatment,the WOMAC scores of patients in the treatment group demonstrated a significant improvement compared to those in the control group(13.39±2.19 vs.15.46±1.30,P<0.05).Additionally,the WHOQOL-BREF scores for patients in both groups showed improvement,with the treatment group exhibiting superior WHOQOL-BREF scores relative to the control group(P<0.05).[Conclusions]For patients diagnosed with KOA,the supplementation of BCP alongside conventional treatment has been shown to significantly enhance knee joint function and improve the overall quality of life for these individuals.展开更多
Block copolymer(BCP) nanolithography offers potential beyond traditional photolithographic limits, yet reliably producing low-defect, perpendicular domains remains challenging. We introduce a microenvironmentdriven is...Block copolymer(BCP) nanolithography offers potential beyond traditional photolithographic limits, yet reliably producing low-defect, perpendicular domains remains challenging. We introduce a microenvironmentdriven isothermal annealing method for directed self-assembly of BCP thin films. By annealing films at stable temperature in a quasi-sealed, inert-gas chamber, our approach promotes highly uniform perpendicular lamellar nanopatterns over large areas, effectively mitigating environmental fluctuations and emulating solvent-vapor annealing without solvent exposure. Resulting BCP structures demonstrate enhanced spatial coherence and notably low defect density. Furthermore, we successfully transfer these nanopatterns into precise metal nano-line arrays,confirming the method's capability for high-fidelity pattern replication. This scalable, solvent-free technique provides a robust, reliable route for high-resolution nanopatterning in advanced semiconductor manufacturing.展开更多
基金Project supported by the Natural Science Foundation of Zhejiang Province(No.LMS25B060007)。
文摘A practical method for the 1,3-azidoheteroarylation of[1.1.1]propellane with cyclic aldimines and azidotrimethylsilane(TMSN_(3))is presented.A broad spectrum of 1-azido-3-heteroaryl bicyclo[1.1.1]pentanes(BCPs)can be synthesized in moderate-to-good yields under standard conditions.The versatility of this method is further confirmed by its applicability to large-scale synthesis,product derivatizations,and late-stage functionalization of pharmaceutically relevant molecules.Mechanistic studies reveal that a radical relay mechanism initiated by a single-electron transfer(SET)process is operational.
基金supported by the National Nature Science Foundation of China (Nos. 61671362 and 62071366)。
文摘Two dimensional(2D) materials based on boron and carbon have attracted wide attention due to their unique properties. BC compounds have rich active sites and diverse chemical coordination, showing great potential in optoelectronic applications. However, due to the limitation of calculation and experimental conditions, it is still a challenging task to predict new 2D BC monolayer materials. Specifically, we utilized Crystal Diffusion Variational Autoencoder(CDVAE) and pre-trained Materials Graph Neural Network with 3-Body Interactions(M3GNet) model to generate novel and stable BCP materials. Each crystal structure was treated as a high-dimensional vector, where the encoder extracted lattice information and element coordinates, mapping the high-dimensional data into a low-dimensional latent space. The decoder then reconstructed the latent representation back into the original data space. Additionally, our designed attribute predictor network combined the advantages of dilated convolutions and residual connections,effectively increasing the model's receptive field and learning capacity while maintaining relatively low parameter count and computational complexity. By progressively increasing the dilation rate, the model can capture features at different scales. We used the DFT data set of about 1600 BCP monolayer materials to train the diffusion model, and combined with the pre-trained M3GNet model to screen the best candidate structure. Finally, we used DFT calculations to confirm the stability of the candidate structure.The results show that the combination of generative deep learning model and attribute prediction model can help accelerate the discovery and research of new 2D materials, and provide effective methods for exploring the inverse design of new two-dimensional materials.
基金Supported by the Horizontal Research Program"Observational Study on the Therapeutic Effects of Collagen Protein Peptides in Knee Osteoarthritis"(KY202208-1-119).
文摘[Objectives]To explore the impact of bone collagen peptide(BCP)on patients with knee osteoarthritis(KOA).[Methods]A total of 100 patients diagnosed with KOA were admitted to the study and randomly assigned to either a control group or a treatment group,with each group comprising 50 participants.The control group received health education along with standard daily treatment protocols.In contrast,the treatment group was administered an additional dosage of 20 g of BCP twice daily,in conjunction with the treatment regimen provided to the control group.Both groups received continuous treatment for 3 months.The WOMAC scores and the WHOQOL-BREF scores of the participants in both groups were assessed both prior to and following treatment.[Results]Following treatment,the WOMAC scores of patients in the treatment group demonstrated a significant improvement compared to those in the control group(13.39±2.19 vs.15.46±1.30,P<0.05).Additionally,the WHOQOL-BREF scores for patients in both groups showed improvement,with the treatment group exhibiting superior WHOQOL-BREF scores relative to the control group(P<0.05).[Conclusions]For patients diagnosed with KOA,the supplementation of BCP alongside conventional treatment has been shown to significantly enhance knee joint function and improve the overall quality of life for these individuals.
基金supported by the National Natural Science Foundation of China (Grant Nos.U20A20168 and 62404120)the National Key R&D Program (Grant No.2022YFB3204100)+2 种基金the Postdoctoral Fellowship Program of CPSF (Grant Nos.GZB20240335 and GZC20231216)the China Postdoctoral Science Foundation (Grant No.2025T180151)the Initiative Scientific Research Program of the School of Integrated Circuits,Tsinghua University。
文摘Block copolymer(BCP) nanolithography offers potential beyond traditional photolithographic limits, yet reliably producing low-defect, perpendicular domains remains challenging. We introduce a microenvironmentdriven isothermal annealing method for directed self-assembly of BCP thin films. By annealing films at stable temperature in a quasi-sealed, inert-gas chamber, our approach promotes highly uniform perpendicular lamellar nanopatterns over large areas, effectively mitigating environmental fluctuations and emulating solvent-vapor annealing without solvent exposure. Resulting BCP structures demonstrate enhanced spatial coherence and notably low defect density. Furthermore, we successfully transfer these nanopatterns into precise metal nano-line arrays,confirming the method's capability for high-fidelity pattern replication. This scalable, solvent-free technique provides a robust, reliable route for high-resolution nanopatterning in advanced semiconductor manufacturing.
