Palladium-Catalyzed Cyanation of Aryl Bromides Promoted by Low-Level Organotin Compounds

A novel method for palladium-catalyzed cyanation of aryl bromides promoted by low-level tri-n-butyltin chloride or cyanide is described. The method features low catalyst loading and mild reaction conditions. KCN is used as the cyanide source. Only trace levels of the tri-n-butyltin compound are required to achieve high conversion and yield in the cyanation of aryl bromides, iodides, and triflates

Palladium-Catalyzed Cyanation of Aryl Bromides Promoted by Low-Level Organotin Compounds

A novel method for palladium-catalyzed cyanation of aryl bromides promoted by low-level tri-n-butyltin chloride or cyanide is described. The method features low catalyst loading and mild reaction conditions. KCN is used as the cyanide source. Only trace levels of the tri-n-butyltin compound are required to achieve high conversion and yield in the cyanation of aryl bromides, iodides, and triflates

sj-xlsx-3-wso-10.1177_17474930241246955 – Supplemental material for Global, regional, and national burden of stroke from 1990 to 2019: A temporal trend analysis based on the Global Burden of Disease Study 2019

Supplemental material, sj-xlsx-3-wso-10.1177_17474930241246955 for Global, regional, and national burden of stroke from 1990 to 2019: A temporal trend analysis based on the Global Burden of Disease Study 2019 by Liwei Zhang, Hao Lu and Chunhua Yang in International Journal of Stroke</p

sj-xlsx-4-wso-10.1177_17474930241246955 – Supplemental material for Global, regional, and national burden of stroke from 1990 to 2019: A temporal trend analysis based on the Global Burden of Disease Study 2019

Supplemental material, sj-xlsx-4-wso-10.1177_17474930241246955 for Global, regional, and national burden of stroke from 1990 to 2019: A temporal trend analysis based on the Global Burden of Disease Study 2019 by Liwei Zhang, Hao Lu and Chunhua Yang in International Journal of Stroke</p

sj-xlsx-2-wso-10.1177_17474930241246955 – Supplemental material for Global, regional, and national burden of stroke from 1990 to 2019: A temporal trend analysis based on the Global Burden of Disease Study 2019

Supplemental material, sj-xlsx-2-wso-10.1177_17474930241246955 for Global, regional, and national burden of stroke from 1990 to 2019: A temporal trend analysis based on the Global Burden of Disease Study 2019 by Liwei Zhang, Hao Lu and Chunhua Yang in International Journal of Stroke</p

sj-pdf-1-wso-10.1177_17474930241246955 – Supplemental material for Global, regional, and national burden of stroke from 1990 to 2019: A temporal trend analysis based on the Global Burden of Disease Study 2019

Supplemental material, sj-pdf-1-wso-10.1177_17474930241246955 for Global, regional, and national burden of stroke from 1990 to 2019: A temporal trend analysis based on the Global Burden of Disease Study 2019 by Liwei Zhang, Hao Lu and Chunhua Yang in International Journal of Stroke</p

Oral administration of M13-loaded nanoliposomes is safe and effective to treat colitis-associated cancer in mice

Colitis-associated cancer (CAC) treatment lacks effective small-molecule drugs and efficient targeted delivery systems. Here, we loaded M13 (an anti-cancer drug candidate) to colon-targeting ginger-derived nanoliposomes (NL) and investigated if orally administered M13-NL could enhance the anticancer effects of M13 in CAC mouse models. The biopharmaceutical properties of M13 were assessed by physicochemical characterizations. The in vitro immunotoxicity of M13 was assessed against PBMCs using FACS and the mutagenic potential of M13 was evaluated by the Ames assay. The in vitro efficacy of M13 was tested in 2D- and 3D-cultured cancerous intestinal cells. AOM/DSS-induced CAC mice were used to evaluate the therapeutic effects of free M13 or M13-NL on CAC in vivo. M13 has beneficial physiochemical properties, including high stability, and no apparent immunotoxicity or mutagenic potential in vitro. M13 is effective against the growth of 2D- and 3D-cultured cancerous intestinal cells in vitro. The in vivo safety and efficacy of M13 were significantly improved by using NL for drug delivery (p  M13-NL is a promising oral drug formulation for CAC treatment.</p

Preparation of C-3,5-Acyl Furanoses via Highly Selective Intramolecular Acyl Migration

A practical synthesis of C-3,5-acyl furanose via a base-catalyzed, highly selective intramolecular acyl migration in alcohol solvents is reported

Preparation of C-3,5-Acyl Furanoses via Highly Selective Intramolecular Acyl Migration

A practical synthesis of C-3,5-acyl furanose via a base-catalyzed, highly selective intramolecular acyl migration in alcohol solvents is reported

Semi-Supervised Deep Learning-Based Multi-component Spectral Calibration Modeling for UV–vis and Near-Infrared Spectroscopy without Information Loss

Spectral analysis is an important method for characterizing and identifying chemical species. However, quantitative spectral analysis of multiple chemical properties in the real world has always been a challenging problem due to the strong correlation, massive noise, and serious information overlapping of the spectral features. Here, we present a new semi-supervised spectral calibration method based on information lossless decoupling of spectral features named NICEM. To realize the separation and extraction of key latent features, the method uses the flow-based model non-linear independent component estimation (NICE) to learn the sample distribution. The spectral data information is transformed into independent latent variables obeying Gaussian distribution by the reversible structure of deep network without information loss, so as to find the essential properties and realize the feature nonlinear decomposition. Moreover, the association between the input latent feature variables and attributes is evaluated by the maximum mutual information coefficient to eliminate the adverse effects of irrelevant information in the latent variable space and mine key information. Since the latent variables are independent in each dimension, the NICEM method is easier to establish an accurate semi-supervised multi-component calibration model even for high overlapping and complex spectral data. The applicability of the proposed spectral modeling method is demonstrated by using three ultraviolet–visible and near-infrared spectral data sets with 15 physical and chemical properties including diesel fuels, corn, and multi-metal ions solution. Results show that the proposed NICEM method has the highest determination coefficient (R2) and significantly improves extrapolation compared with the seven state-of-the-art methods. The proposed method is intuitive because it obviates complex feature engineering and prior knowledge and is a promising spectral calibration tool for quantitative analysis in other spectroscopy applications