Pulmonary fibrosis is a chronic progressive interstitial lung disease caused by a variety of etiologies. The disease can eventually lead to irreversible damage to the lung tissue structure, severely affecting respiratory function and posing a serious threat to human health. Currently, glucocorticoids and immunosuppressants are the main drugs used in the clinical treatment of pulmonary fibrosis, but their efficacy is limited and they can cause serious adverse effects. Traditional Chinese medicines have important research value and potential for clinical application in anti-pulmonary fibrosis. In recent years, more and more scientific researches have been conducted on the use of traditional Chinese medicine to improve or reduce pulmonary fibrosis, and some important breakthroughs have been made. This review paper systematically summarized the research progress of pharmacological mechanism of traditional Chinese medicines and their active compounds in improving or reducing pulmonary fibrosis. We conducted a systematic search in several main scientific databases, including PubMed, Web of Science, and Google Scholar, using keywords such as idiopathic pulmonary fibrosis, pulmonary fibrosis, interstitial pneumonia, natural products, herbal medicine, and therapeutic methods. Ultimately, 252 articles were included and systematically evaluated in this analysis. The anti-fibrotic mechanisms of these traditional Chinese medicine studies can be roughly categorized into 5 main aspects, including inhibition of epithelial-mesenchymal transition, anti-inflammatory and antioxidant effects, improvement of extracellular matrix deposition, mediation of apoptosis and autophagy, and inhibition of endoplasmic reticulum stress. The purpose of this article is to provide pharmaceutical researchers with information on the progress of scientific research on improving or reducing Pulmonary fibrosis with traditional Chinese medicine, and to provide reference for further pharmacological research.

Introduction: Chronic kidney disease-mineral and bone disorder (CKD-MBD) is characterized by bone abnormalities, vascular calcification, and some other complications. Although there are diagnostic criteria for CKD-MBD, in situations when conducting target feature examining are unavailable, there is a need to investigate and discover alternative biochemical criteria that are easy to obtain. Moreover, studying the correlations between the newly discovered biomarkers and the existing ones may provide insights into the underlying molecular mechanisms of CKD-MBD. Methods: We collected a cohort of 116 individuals, consisting of three subtypes of CKD-MBD: calcium abnormality, phosphorus abnormality, and PTH abnormality. To identify the best biomarker panel for discrimination, we conducted six machine learning prediction methods and employed a sequential forward feature selection approach for each subtype. Additionally, we collected a separate prospective cohort of 114 samples to validate the discriminative power of the trained prediction models. Results: Using machine learning under cross validation setting, the feature selection method selected a concise biomarker panel for each CKD-MBD subtype as well as for the general one. Using the consensus of these features, best area under ROC curve reached up to 0.95 for the training dataset and 0.74 for the perspective dataset, respectively. Discussion/Conclusion: For the first time, we utilized machine learning methods to analyze biochemical criteria associated with CKD-MBD. Our aim was to identify alternative biomarkers that could serve not only as early detection indicators for CKD-MBD, but also as potential candidates for studying the underlying molecular mechanisms of the condition.

In this research, a very practical QuEChERS-GC-MS/MS analytical approach for 74 pesticide residues in herb based on retention index was established. This novel analytical approach has two important technical advantages. One advantage is to quickly screen pesticide compounds in herbs without having to use a large number of pesticide standard substances at the beginning of the experiment. The other advantage is to assist in identifying the target pesticide compound accurately. A total of 74 kinds of pesticides were quickly prescreened in all chuanxiong rhizoma samples. The results showed that three kinds of pesticides were screened out in all the samples, including chlorpyrifos, fipronil, and procymidone, and the three pesticides were qualitatively and quantitatively determined. The RSD values for interday and intraday variation were acquired to evaluate the precision of the analytical approach, and the overall interday and intraday variations are not more than 1.97 and 3.82, respectively. The variations of concentrations of the analyzed three pesticide compounds in sample CX16 are 0.744.15, indicating that the three pesticides in the sample solutions were stable in 48h. The spiked recoveries of the three pesticides are 95.22, 93.03, and 94.31, and the RSDs are less than ±6.0. The methodological verification results indicated the good reliability and accuracy of the new analytical method. This research work is a new application of retention index, and it will be a valuable tool to assist quickly and accurately in the qualitative and quantitative analysis of multipesticide residues in herbs.

Sennoside A and sennoside B are the major bioactive components in laxative herbs like rhubarb, senna, etc. The previously reported techniques for the quantitative analysis of sennoside A and sennoside B have the disadvantages of defective peak purity and stability. This study investigates the influence of analytical parameters on the efficiency of separation of sennoside A and sennoside B in rhubarb by ultra-high-performance liquid chromatography (UHPLC). The chromatographic parameters of column temperature and flow rate have a non-linear relationship with the theoretical plate number and symmetry factor; the optimal column temperature was 30 °C and the optimal flow rate was 0.20 mL min⁻¹. A new UHPLC analytical method was developed based on these optimal parameters. The chromatographic peak purity of sennoside A and sennoside B in rhubarb was satisfactory. This UHPLC-based analytical method was successfully applied for the quantitative determination of sennoside A and sennoside B in two sources of rhubarbs, Cassia angustifolia Vahl. and Paidu Yangyan capsule. There are remarkable content differences between sennoside A (more than 19 times) and sennoside B (more than 18 times) in the two species of rhubarb tested. In order to make the analytical method widely applicable, the analytical parameters of UHPLC have been converted into those of HPLC. In conclusion, the devised technique is suitable for the quality control of laxative herbs and diet drugs containing sennoside A and sennoside B.

There are still some difficulties in accurately quantifying pesticide residues in herbal medicines. One difficulty is the rapid screening of the existing unknown pesticide species in samples. Another difficulty is the accurate identification of the target pesticide under the severe interference of complex components in herbs. In this study, we have developed a very novel and practical analytical method for 130 pesticide residues based on the retention index principle, and an exemplary study was performed using Panacis quinquefolii radix. This newly developed method has two significant advantages for pesticide residue analysis. One of the advantages is the ability to quickly pre-screen pesticides in samples without necessarily requiring a large amount of standard solution. This means that the efficiency of the pesticide analysis can be improved and the cost of testing can be greatly reduced. Another advantage is that this method can help researchers accurately identify target pesticides, which means that the accuracy of pesticide analysis can be improved. In summary, this study is a new utilization of the Kovats retention index, and this method will be a very promising tool for pesticide residue analysis in herbal medicines.

Two previously undescribed phenylpropanoid derivatives, including a terpenylated coumarin (1) and a ferulic acid analogue (2), were isolated from the roots of Notopterygium incisum (Umbelliferae). Their structures were successfully established using spectroscopic techniques, including mass spectrometry (MS), nuclear magnetic resonance (NMR), and electronic circular dichroism (ECD) spectroscopy. In vitro anti-inflammatory assay using a lipopolysaccharide-stimulated RAW264.7 macrophages indicated compounds 1 and 2 showed anti-inflammatory potential by inhibiting the secretion of NO at the concentra-tion of 7.5 μM.