Effect of botanical drugs in improving symptoms of hypertensive nephropathy: Analysis of real-world data, retrospective cohort, network, and experimental assessment.

Background/aim: Hypertensive nephropathy (HN) is a common complication of hypertension. Traditional Chinese medicine has long been used in the clinical treatment of Hypertensive nephropathy. However, botanical drug prescriptions have not been summarized. The purpose of this study is to develop a prescription for improving hypertensive nephropathy, explore the evidence related to clinical application of the prescription, and verify its molecular mechanism of action. Methods: In this study, based on the electronic medical record data on Hypertensive nephropathy, the core botanical drugs and patients' symptoms were mined using the hierarchical network extraction and fast unfolding algorithm, and the protein interaction network between botanical drugs and Hypertensive nephropathy was established. The K-nearest neighbors (KNN) model was used to analyze the clinical and biological characteristics of botanical drug compounds to determine the effective compounds. Hierarchical clustering was used to screen for effective botanical drugs. The clinical efficacy of botanical drugs was verified by a retrospective cohort. Animal experiments were performed at the target and pathway levels to analyze the mechanism. Results: A total of 14 botanical drugs and five symptom communities were obtained from real-world clinical data. In total, 76 effective compounds were obtained using the K-nearest neighbors model, and seven botanical drugs were identified as Gao Shen Formula by hierarchical clustering. Compared with the classical model, the Area under the curve (AUC) value of the K-nearest neighbors model was the best; retrospective cohort verification showed that Gao Shen Formula reduced serum creatinine levels and Chronic kidney disease (CKD) stage [OR = 2.561, 95% CI (1.025-6.406), p < 0.05]. With respect to target and pathway enrichment, Gao Shen Formula acts on inflammatory factors such as TNF-α, IL-1ß, and IL-6 and regulates the NF-κB signaling pathway and downstream glucose and lipid metabolic pathways. Conclusion: In the retrospective cohort, we observed that the clinical application of Gao Shen Formula alleviates the decrease in renal function in patients with hypertensive nephropathy. It is speculated that Gao Shen Formula acts by reducing inflammatory reactions, inhibiting renal damage caused by excessive activation of the renin-angiotensin-aldosterone system, and regulating energy metabolism.

Application of molecular markers in the research of genetic diversity in medical helminths / 中国热带医学

@#Human-animal parasitic diseases caused by medical helminths are hazardous to human health. Genetic polymorphism studies on medical helminth populations can not only understand the biological characteristics and genetic structure of their populations, but also help reveal how they adapt to their parasitic environment, thus contributing to deepen our understanding of the epidemiological patterns of parasitic diseases and improve our understanding of accurate prevention and control of parasitic diseases. With the development of molecular biology, molecular markers such as DNA barcodes, simple sequence repeats, and single nucleotide polymorphism markers have been widely used to study the genetic relationships among parasite populations and individuals, and to reveal the genetic variation of parasite populations and the evolution of species origins. In this paper, we systematically review the application of three molecular markers commonly used in the study of genetic polymorphism in medical helminths, with a view to laying the foundation for related research.

Transcriptome profiling of plerocercoid and adult developmental stages of the neglected medical tapeworm Spirometra erinaceieuropaei.

The plerocercoid larvae of the tapeworm Spirometra erinaceieuropaei can parasitize humans and animals and cause serious parasitic zoonosis. However, our knowledge of the developmental process of S. erinaceieuropaei is still inadequate. To better characterize differential and specific genes and pathways associated with parasite development, a comparative transcriptomic analysis of the plerocercoid stage and the adult stage was performed using RNA-seq and de novo analysis. Approximately 13,659 differentially expressed genes (DEGs) were identified in plerocercoids versus adults, of which 6455 DEGs were upregulated and 7204 were downregulated. DEGs involved in parasite immunoevasion were more active in plerocercoid larvae than in adults, while DEGs associated with metabolic activity were upregulated in adults. Gene Ontology (GO) and Kyoto Encyclopedia of Genes (KEGG) analyses revealed that most DEGs involved in protein phosphorylation/dephosphorylation and the Wnt signalling pathway were much more active in plerocercoid larvae. The molecular functions of upregulated unigenes in adults were mainly enriched for metabolic activities. qPCR validated that the expression levels of 10 selected DEGs were consistent with those in RNA-seq, confirming the accuracy of the RNA-seq results. Our results contributed to increasing the knowledge on the S. erinaceieuropaei gene repertoire and expression profile and also provide valuable resources for functional studies on the molecular mechanisms of S. erinaceieuropaei.

Predicting Coupled Herbs for the Treatment of Hypertension Complicated with Coronary Heart Disease in Real-World Data Based on a Complex Network and Machine Learning.

Hypertension and coronary heart disease are the most common cardiovascular diseases, and traditional Chinese medicine is applied as an auxiliary treatment for common cardiovascular diseases. This study is based on 3 years of electronic medical record data from the Affiliated Hospital of Shandong University of Traditional Chinese Medicine. A complex network and machine learning algorithm were used to establish a screening model of coupled herbs for the treatment of hypertension complicated with coronary heart disease. A total of 5688 electronic medical records were collected to establish the prescription network and symptom database. The hierarchical network extraction algorithm was used to obtain core herbs. Biological features of herbs were collected from public databases. At the same time, five supervised machine learning models were established based on the biological features of the coupled herbs. Finally, the K-nearest neighbor model was established as a screening model with an AUROC of 91.0%. Seventy coupled herbs for adjuvant treatment of hypertension complicated with coronary heart disease were obtained. It was found that the coupled herbs achieved the purpose of adjuvant therapy mainly by interfering with cytokines and regulating inflammatory and metabolic pathways. These results show that this model can integrate the molecular biological characteristics of herbs, preliminarily screen combinations of herbs, and provide ideas for explaining the value in clinical applications.

Classifying and Predicting Salinization Level in Arid Area Soil Using a Combination of Chua's Circuit and Fractional Order Sprott Chaotic System.

Soil salinization is very complex and its evolution is affected by numerous interacting factors produce strong non-linear characteristics. This is the first time fractional order chaos theory has been applied to soil salinization-level classification to decrease uncertainty in salinization assessment, solve fuzzy problems, and analyze the spectrum chaotic features in soil with different levels of salinization. In this study, typical saline soil spectrum data from different human interference areas in Fukang City (Xinjiang) and salt index test data from an indoor chemical analysis laboratory are used as the base information source. First, we explored the correlation between the spectrum reflectance features of soil with different levels of salinization and chaotic dynamic error and chaotic attractor. We discovered that the chaotic status error in the 0.6 order has the greatest change. The 0.6 order chaotic attractors are used to establish the extension matter-element model. The determination equation is built according to the correspondence between section domain and classic domain range to salinization level. Finally, the salt content from the chemical analysis is substituted into the discriminant equation in the extension matter-element model. Analysis found that the accuracy of the discriminant equation is higher. For areas with no human interference, the extension classification can successfully identify nine out of 10 prediction data, which is a 90% identification accuracy rate. For areas with human interference, the extension classification can successfully identify 10 out of 10 prediction data, which is a success rate of 100%. The innovation in this study is the building of a smart classification model that uses a fractional order chaotic system to inversely calculate soil salinization level. This model can accurately classify salinization level and its predictive results can be used to rapidly calculate the temporal and spatial distribution of salinization in arid area/desert soil.