A series of room temperature ionic liquids (ILs), in which cholinium acts as the cation and amino acids as the anions, were prepared via a simple and green chemical route, and characterized. Most of the ILs dissolved lignin efficiently and selectively (with solubilities of 140-220 mg of lignin per g of IL). The solubility of xylan in these ILs (which ranged from <1 to 85 mg g -1 ) depended on the nature of the anion, while cellulose was scarcely soluble (<5 mg g -1 ). In addition, enzymatic hydrolysis of microcrystalline cellulose and rice straw was enhanced significantly after pretreatment using the IL [Ch][Gly].Room temperature ionic liquids (RTILs) have been attracting increasing attention as electrolyte materials, catalysts and solvents for synthesis, catalysis and extraction etc., due to their excellent properties such as low vapor pressure, nonflammability, high thermal and chemical stability, and outstanding ability to dissolve a wide range of compounds.

The development of novel green solvents has been one of the hottest subjects in green chemistry. Deep eutectic solvents (DESs) have logically and naturally emerged in the search for more biocompatible and biodegradable solvents. In this study, some basic physical properties, including viscosity, conductivity and density, of twenty DESs prepared from choline chloride and various hydrogen bond donors were investigated systematically. In addition, the biocompatibility of the tested DESs was qualitatively and quantitatively evaluated using two gram-positive (Staphylococcus aureus and Listeria monocytogenes) and two gram-negative (Escherichia coli and Salmonella enteritidis) bacteria. A Closed Bottle Test was used to assess the biodegradability of these DESs. The results demonstrated that these choline chloride-based DESs were excellent solvents with extremely low toxicity and favorable biodegradability. Finally, DESs were used to extract a flavonoid (rutin) from the flower buds of Sophora japonica. An extraction efficiency of 194.17±2.31 mg·g −1 was achieved using choline chloride/triethylene glycol containing 20% water. The excellent properties of DESs indicate their potential as promising green solvents for the extraction of rutin with favorable prospects for wide use in the field of green technology. acid, levulinic acid, malonic acid, malic acid, citric acid, tartaric acid, xylose, sucrose, fructose, glucose, and maltose (all ≥99% mass fraction purity) were all purchased from Tianjin Kermel Chemical Reagent Co., Ltd. (Tianjin, China). Rutin (≥98% mass fraction purity) was purchased from Shanghai Yuanye Biotechnology Co., Ltd. (Shanghai, China). S. japonica bud was purchased from ZhanJiang Yizhou Medicines Co., Ltd. (Guangdong, China). All other chemicals were of analytical grade.Preparation of DESs. DESs were synthesized by mixing choline chloride and HBDs at a defined molar ratio (see Table 1) and heating at 100 °C for 2-4 h at an atmospheric pressure under constant stirring until a stable homogeneous liquid was formed. 21 Sugar-based DESs were prepared using the same conditions but under a nitrogen atmosphere. All the prepared DESs were allowed to cool to room temperature and dried in a vacuum oven at 50 °C for 24 h.The solvents were stored in sealed laboratory vials and kept in a desiccator. Physical Properties. The water contents of the samples were measured using a Metrohm Karl-Fischer (model 890) titrator. The viscosities of the DESs were measured with a HAAKE RheoStress 600 at 100 Hz from 25-80 °C at a rate of 5 °C min −1 . The conductivity of all samples was measured with a conductivity meter (Shanghai Leici DDS-307A) at a preset temperature.The densities of all samples were determined using a 5 cm 3 pycnometer calibrated with deionized water at 30 °C. As for the determination of viscosities, conductivity and densities, all the DESs except sugar-based DESs were dried at 100 °C to minimize the water content. All measurements were performed at constant temperature. The relative standard deviation for all th...

We present Bisque, a tool for estimating cell type proportions in bulk expression. Bisque implements a regression-based approach that utilizes single-cell RNA-seq (scRNA-seq) or single-nucleus RNA-seq (snRNA-seq) data to generate a reference expression profile and learn gene-specific bulk expression transformations to robustly decompose RNA-seq data. These transformations significantly improve decomposition performance compared to existing methods when there is significant technical variation in the generation of the reference profile and observed bulk expression. Importantly, compared to existing methods, our approach is extremely efficient, making it suitable for the analysis of large genomic datasets that are becoming ubiquitous. When applied to subcutaneous adipose and dorsolateral prefrontal cortex expression datasets with both bulk RNA-seq and snRNA-seq data, Bisque replicates previously reported associations between cell type proportions and measured phenotypes across abundant and rare cell types. We further propose an additional mode of operation that merely requires a set of known marker genes.

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