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Since the first proposal by Seeman in 1982, DNA nanostructures have been gradually improved, and have been widely developed and applied to the field of biomedical fields. In recent years, as a representative of 3D DNA nanostructures, tetrahedral framework nucleic acids (tFNA) has made certain research progress and has good application prospects in frontier fields such as biosensors, tumor therapy, antigen detection, regenerative medicine, with the advantages of their good biocompatibility, editability, high stability and easy preparation. This paper briefly describes the concepts of tFNA, and summarizes the applications and research progress of tFNA in the following fields from the perspective of therapeutic applications: ① Building novel self-assembled complexes to improve the efficacy of free drugs, carrying small RNA molecules to slow down tumor progression, and self-assembled complexes for targeted therapy, etc, as biological vectors and tumor drug delivery. ② Regulating inflammation and immune response, such as reducing the level of inflammatory factors, treating inflammatory diseases, preventing diabetes, and acting as immunomodulators, etc. ③ Enhancing tissue regeneration, such as promoting stem cell proliferation and differentiation, stimulating peripheral nerve regeneration, and facilitating wound repair through angiogenesis. This review summarizes the research progress of tFNA, and looks forward to its application prospects based on the analysis of the shortcomings of existing research, in order to provide reference for further research.

The construction industry is a significant contributor to carbon emissions in China. To effectively meet the "dual carbon" targets, several provincial regions within the country started to implement policies promoting prefabricated buildings. This study examines data from 18 provinces in China over the period from 2012 to 2021, treating the introduction of prefabricated building policies as a quasi-natural experiment. Utilizing the difference-in-differences methodology, this research assesses the impact of these policies on the carbon emission performance of China's construction sector and evaluates the robustness of the findings. The results indicate that the prefabricated building policies positively influenced the carbon emission efficiency of the construction industry. Specifically, these policies enhance carbon emission efficiency by increasing labor productivity, optimizing the allocation of mechanical resources, and improving the utilization rate of building materials. Additionally, the effectiveness of these policies is positively correlated with the level of regional technological innovation, environmental protection efforts, and the advancement of energy structure optimization. The study concludes with several policy recommendations aimed at further enhancing the effectiveness of prefabricated building policies. [ABSTRACT FROM AUTHOR]

Objectives The efficacy of artificial intelligence (AI)-driven chatbots like ChatGPT4 in specialized medical consultations, particularly in rheumatology, remains underexplored. This study compares the proficiency of ChatGPT4' responses with practicing rheumatologists to inquiries from patients with SLE. Methods In this cross-sectional study, we curated 95 frequently asked questions (FAQs), including 55 in Chinese and 40 in English. Responses for FAQs from ChatGPT4 and five rheumatologists were scored separately by a panel of rheumatologists and a group of patients with SLE across six domains (scientific validity, logical consistency, comprehensibility, completeness, satisfaction level and empathy) on a 0–10 scale (a score of 0 indicates entirely incorrect responses, while 10 indicates accurate and comprehensive answers). Results Rheumatologists' scoring revealed that ChatGPT4-generated responses outperformed those from rheumatologists in satisfaction level and empathy, with mean differences of 0.537 (95% CI, 0.252–0.823; P   <  0.01) and 0.460 (95% CI, 0.227–0.693; P   <  0.01), respectively. From the SLE patients' perspective, ChatGPT4-generated responses were comparable to the rheumatologist-provided answers in all six domains. Subgroup analysis revealed ChatGPT4 responses were more logically consistent and complete regardless of language and exhibited greater comprehensibility, satisfaction and empathy in Chinese. However, ChatGPT4 responses were inferior in comprehensibility for English FAQs. Conclusion ChatGPT4 demonstrated comparable, possibly better in certain domains, to address FAQs from patients with SLE, when compared with the answers provided by specialists. This study showed the potential of applying ChatGPT4 to improve consultation in SLE patients. [ABSTRACT FROM AUTHOR]

Boronate rearrangements, such as the Matteson and Petasis reactions, are valuable metal‐free reactions for the transfer of the carbo group on boron to intramolecular electrophilic sites. However, only highly reactive electrophiles are suitable, and ketones are too inactive for those boronate rearrangements due to the high energy barriers. We disclose here the 1,3‐boronate rearrangement to ketones, for which a high energy barrier (44.9 kcal/mol) is prohibitory for thermal reactions in the ground state. The reaction is enabled by the key keto‐enol‐boronate bidentate complex formation in situ, which absorbs visible light to reach the excited state for the chemoselective 1,3‐boronate rearrangement to ketones. Experimental and computational investigations exclude free radical intermediates from organoboronates. The aryl, alkenyl, and alkyl boronic acids react with various 1,3‐diketones driven by visible light irradiation to construct structurally diverse β‐keto tertiary alcohols under metal‐free conditions. The reaction demonstrates substrate diversity with 58 examples, yields up to 98 %, and it is suitable for gram‐scale synthesis. [ABSTRACT FROM AUTHOR]

Dispersing metal‐organic framework (MOF) solids in stable colloids is crucial for their availability and processibility. Herein, we report a crown ether surface coordination approach for functionalizing the surface‐exposed metal sites of MOF particles with amphiphilic carboxylated crown ether (CEC). The surface‐bound crown ethers significantly improve MOF solvation without compromising the accessible voids. We demonstrate that CEC‐coated MOFs exhibit exceptional colloidal dispersibility and stability in 11 distinct solvents and six polymer matrices with a wide range of polarities. The MOF‐CEC can be instantaneously suspended in immiscible two‐phase solvents as an effective phase‐transfer catalyst and can form various uniform membranes with enhanced adsorption and separation performance, which highlights the effectiveness of crown ether coating. [ABSTRACT FROM AUTHOR]

Background: It has been reported that patients with early breast cancer with 1–2 positive sentinel lymph nodes have a lower risk of non-sentinel lymph node (NSLN) metastasis and cannot benefit from axillary lymph node dissection. Purpose: To develop the potential of machine learning based on multiparametric magnetic resonance imaging (MRI) and clinical factors for predicting the risk of NSLN metastasis in breast cancer. Material and Methods: This retrospective study included 144 patients with 1–2 positive sentinel lymph node breast cancer. Multiparametric MRI morphologic findings and the detailed demographical characteristics of the primary tumor and axillary lymph node were extracted. The logistic regression, support vector classification, extreme gradient boosting, and random forest algorithm models were established to predict the risk of NSLN metastasis. The prediction efficiency of a machine-learning–based model was evaluated. Finally, the relative importance of each input variable was analyzed for the best model. Results: Of the 144 patients, 80 (55.6%) developed NSLN metastasis. A total of 24 imaging features and 14 clinicopathological features were analyzed. The extreme gradient boosting algorithm had the strongest prediction efficiency with an area under curve of 0.881 and 0.781 in the training set and test set, respectively. Five main factors for the metastasis of NSLN were found, including histological grade, cortical thickness, fatty hilum, short axis of lymph node, and age. Conclusion: The machine-learning model incorporating multiparametric MRI features and clinical factors can predict NSLN metastasis with high accuracy for breast cancer and provide predictive information for clinical protocol. [ABSTRACT FROM AUTHOR]

Tungsten (W) can be used in plasma-facing components in a fusion reactor because of its excellent radiation resistance. Some studies have found that nanocrystalline metals with a high density of grain boundary show a higher ability to resist radiation damage compared to conventional coarse-grained materials. However, the interaction mechanism between grain boundary and defect is still unclear. In the present study, molecular dynamics simulations were carried out to explore the difference of defect evolution in single-crystal and bicrystal W, while the effects of temperature and the energy of the primary knocked atom (PKA) were taken into account. The irradiation process was simulated at the temperature range of 300 to 1500 K, and the PKA energy varied from 1 to 15 keV. The results show that the generation of defects is more sensitive to the energy of PKA than temperature; the number of defects increases at the thermal spike stage with the increase of the PKA energy, but the correlation with temperature is not strong. The presence of the grain boundary prevented the recombination of interstitial atoms and vacancies during the collision cascades, and the vacancies were more likely to form large clusters than interstitial atoms in the bicrystal models. This can be ascribed to the strong segregation tendency of the interstitial atoms to grain boundaries. The simulations provide useful information for understanding the role of grain boundaries in the evolution of irradiated structural defects. [ABSTRACT FROM AUTHOR]

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Copyright of Journal of Shanghai Jiaotong University (Medical Science) is the property of Journal of Shanghai Jiaotong University (Medical Science) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)