Human serum albumin (HSA) is the most abundant protein in plasma and plays an essential physiological role in the human body. Ethanol precipitation is the most widely used way to obtain HSA, and pH and ethanol are crucial factors affecting the process. In this study, infrared (IR) spectroscopy and near-infrared (NIR) spectroscopy in combination with chemometrics were used to investigate the changes in the secondary structure and hydration of HSA at acidic pH (5.6–3.2) and isoelectric pH when ethanol concentration was varied from 0% to 40% as a perturbation. IR spectroscopy combined with the two-dimensional correlation spectroscopy (2DCOS) analysis for acid pH system proved that the secondary structure of HSA changed significantly when pH was around 4.5. What’s more, the IR spectroscopy and 2DCOS analysis showed different secondary structure forms under different ethanol concentrations at the isoelectric pH. For the hydration effect analysis, NIR spectroscopy combined with the McCabe–Fisher method and aquaphotomics showed that the free hydrogen-bonded water fluctuates dynamically, with ethanol at 0–20% enhancing the hydrogen-bonded water clusters, while weak hydrogen-bonded water clusters were formed when the ethanol concentration increased continuously from 20% to 30%. These measurements provide new insights into the structural changes and changes in the hydration behavior of HSA, revealing the dynamic process of protein purification, and providing a theoretical basis for the selection of HSA alcoholic precipitation process parameters, as well as for further studies of complex biological systems.

Background For thousands of years, Traditional Chinese Medicine (TCM) has been clinically proven, and doctors have highly valued the differences in utility between different species. Objective This study aims to replace the complex methods traditionally used for empirical identification by compensating for the information loss of a single sensor through data fusion. The research object of the study is Coptidis Rhizome (CR). Methods Using spectral optimization and data fusion technology, Near Infrared (NIR) and Mid-Infrared (MIR) spectra were collected for CR. PLS-DA (n = 134) and PLSR (n = 63) models were established to identify the medicinal materials and determine the moisture content in the medicinal materials. Results For the identification of the three species of CR, the mid-level fusion model performed better than the single-spectrum model. The sensitivity and specificity of the prediction set coefficients for NIR, MIR, and data fusion qualitative models were all higher than 0.95, with an AUC value of 1. The NIR data model was superior to the MIR data model. The results of low-level fusion were similar to those of the NIR optimization model. The RPD of the test set of NIR and low-level fusion model was 3.6420 and 3.4216, respectively, indicating good prediction ability of the model. Conclusion Data fusion technology using NIR and MIR can be applied to identify CR species and determine the moisture content of CR. It provides technical support for the rapid determination of moisture content, with fast analysis speed and without the need for complex pretreatment methods. Highlights This study is the first to introduce spectral data fusion technology to identify CR species. Data fusion technology is feasible for multivariable calibration model performance and reduces the cost of manual identification. The moisture content of CR can be quickly evaluated, reducing the difficulty of traditional methods.

The traditional Chinese herb pair of Huangqi (HQ) and Taoren (TR) for the treatment of ischemic brain injury (IBI). However, the mechanism of action of HQ and TR for treating IBI still remains unclear. Network pharmacology was adopted to detect the active components of DL and TR. The key targets and signaling pathways in the treatment of IBI were predicted, and the key ingredients and targets were screened for molecular docking. In this study, we identified 27 active components from the herb pair of DL and TR, predicted to act on IBI-associated targets by network pharmacology. PPI network demonstrated that 36 proteins might serve as the key targets of DL and HQ for the treatment of IBI. GO and KEGG pathway enrichment analyzes indicated that the effects of DL and HQ are mediated by genes related to inflammation and apoptosis as well as the HIF-1α, lipid and atherosclerosis pathways. We also had transcription factors and miRNAs analysis of hub genes. Molecular docking revealed good binding ability between the active compounds and screened targets. We comprehensively illustrated the active ingredients, potential targets, and molecular mechanism of the herb pair of HQ and TR treat IBI.