Yiqi Shexue formula (YQSX) is traditionally used to treat primary immune thrombocytopenia (ITP) in clinical practice of traditional Chinese medicine. However, its mechanisms of action and molecular targets for treatment of ITP are not clear. The active compounds of YQSX were collected and their targets were identified. ITP-related targets were obtained by analyzing the differential expressed genes between ITP patients and healthy individuals. Protein–protein interaction (PPI) data were then obtained and PPI networks of YQSX putative targets and ITP-related targets were visualized and merged to identify the candidate targets for YQSX against ITP. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis were carried out. The gene-pathway network was constructed to screen the key target genes. In total, 177 active compounds and 251 targets of YQSX were identified. Two hundred and thirty differential expressed genes with an P value < 0.005 and |log2(fold change)| > 1 were identified between ITP patient and control groups. One hundred and eighty-three target genes associated with ITP were finally identified. The functional annotations of target genes were found to be related to transcription, cytosol, protein binding, and so on. Twenty-four pathways including cell cycle, estrogen signaling pathway, and MAPK signaling pathway were significantly enriched. MDM2 was the core gene and other several genes including TP53, MAPK1, CDKN1A, MYC, and DDX5 were the key gens in the gene-pathway network of YQSX for treatment of ITP. The results indicated that YQSX’s effects against ITP may relate to regulation of immunological function through the specific biological processes and the related pathways. This study demonstrates the application of network pharmacology in evaluating mechanisms of action and molecular targets of complex herbal formulations.

The aim of this study was to develop a model that could be used to forecast the bleeding risk of ITP based on proinflammatory and anti-inflammatory factors. One hundred ITP patients were recruited to build a new predictive nomogram, another eighty-eight ITP patients were enrolled as validation cohort, and data were collected from January 2016 to January 2019. Four demographic characteristics and fifteen clinical characteristics were taken into account. Eleven cytokines (IFN-γ, IL-1, IL-4, IL-6, IL-8, IL-10, IL-17A, IL-22, IL-23, TNF-α and TGF-β) were used to study and the levels of them were detected by using a cytometric bead array (CBA) human inflammation kit. The least absolute shrinkage and selection operator regression model was used to optimize feature selection. Multivariate logistic regression analysis was applied to build a new predictive nomogram based on the results of the least absolute shrinkage and selection operator regress ion model. The application of C-index, ROC curve, calibration plot, and decision curve analyses were used to assess the discrimination, calibration, and clinical practicability of the predictive model. Bootstrapping validation was used for testing and verifying the predictive model. After feature selection, cytokines IL-1, IL-6, IL-8, IL-23 and TGF-β were excluded, cytokines IFN-γ, IL-4, IL-10, IL-17A, IL-22, TGF-β, the count of PLT and the length of time of ITP were used as predictive factors in the predictive nomogram. The model showed good discrimination with a C-index of 0.82 (95% confidence interval 0.73376–0.90 624) in training cohortn and 0.89 (95% CI 0.868, 0.902) in validation cohort, an AUC of 0.795 in training cohort, 0.94 in validation cohort and good calibration. A high C-index value of 0.66 was reached in the interval validation assessment. Decision curve analysis showed that the bleeding risk nomogram was clinically useful when intervention was decided at the possibility threshold of 16–84%. The bleeding risk model based on IFN-γ, IL-4, IL-10, IL-17A, IL-22, TGF-β, the count of PLT and the length of time of ITP could be conveniently used to predict the bleeding risk of ITP.

No abstract

Objective To establish the clinical safe and effective methods of arsenic-containing compound-Qinghuang Powder (compound-QHP) in the treatment of myelodysplastic syndrome (MDS). Methods 200 patients with MDS were treated with compound-QHP (daily dose of 0.1 g realgar). The blood arsenic concentrations (BACs) were detected by atomic fluorescence spectrophotometry (HF-AFS). After treatment for 1 month, the patients were randomly divided into group A and group B when the BACs were less than 20 μg/L. Daily dose of realgar was maintained in group A and it was increased to that when the BACs were more than 20 μg/L in group B. The BAC and clinical efficacy and safety in two groups were compared at the end of the treatment with compound-QHP. Results The average BAC of group B was significantly higher than that of group A (P < 0.01). The rates of hematology improvement and reduced transfusion were significantly higher in group B than in group A (P < 0.05). The HGB, ANC, and PLT significantly increased in group B after treatment (P > 0.05). Conclusions Monitoring the BAC and adjusting the daily dose of realgar to increase the effective BAC and then improving efficacy without increasing the clinical toxicity are the clinical safe and effective methods in the treatment of MDS.

Ruxolitinib is a targeted drug to treat myelofibrosis (MF). Ruxolitinib has significant advantages in spleen reduction and increasing 5-year overall survival (OS), and ruxolitinib-based combinations might provide more benefits than ruxolitinib monotherapy. In this review, we focus on the data of ruxolitinib-based combinations therapies and treatment-related adverse events (AEs) and safety. We analyzed and summarized the data of ruxolitinib-based combinations. Ruxolitinib combined with prednisone + thalidomide + danazol (TPD), panobinostat, pracinostat, azacytidine, or hydroxyurea has well reduced spleen. Ruxolitinib combined with danazol or TPD had well therapies in improvement of hemoglobin (Hgb) and platelets (PLT). Most ruxolitinibbased combinations therapies showed a superior benefit on reduced treatment-related AEs than ruxolitinib monotherapy. Treatment-related AEs and dose modification affect the safety and tolerability of ruxolitinib-based combinations. Genetic testing before treatment is recommended. To provide better clinical guidance, comparisons of these randomized controlled trials with the trials of ruxolitinib alone are necessary. This review suggests that the clinical application of ruxolitinib-based combinations is worth waiting for.

No abstract

Background: LongChaiJiangXue formula (LCJX) has the effect of not only clearing up excessive erythrocytes but also relieving clinical symptoms of Polycythemia vera (PV). Material/Methods: The chemical constitution of LCJX was identified from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP). Seven hundred and fifty-nine targets were identified and a total of 248 targets were screened out after discarding duplication and genes without any ID in databases. GeneCards database, OMIM database, and GEO database were searched for differential expression genes. The network was built by Cytoscape (3.7.2) software and the protein-protein interaction (PPI) networks of PV and LCJX were merged by https://string-db.org . Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment was processed by the R platform. The molecular docking technology was used to further analyze the intense of the assosiation of the compounds and targets. Results: 73 compounds of LCJX were chosen as the candidate active compounds. The compound-targets network contained 105 nods and 216 edges that presented the interaction of agents and targets. The PPI network of LCJX targets involved 59 nodes and 168 edges. The network showed that the key nodes were concentrated in signal transducer and activator of transcription-3(STAT-3), interleukin-6(IL-6), Janus kinase 2(JAK2), and vascular endothelial growth factor-A(VEGFA). The most enriched terms in the GO analysis in the GO biological processes(BP) were reactive oxygen species metabolic process, response to lipopolysaccharide, and response to oxidative stress. According to GO molecular functions(MF), the central nodes were generally enriched in cytokine receptor binding, cytokine activity, and heme binding. Regarding the GO cell components(CC), the terms included vesicle lumen, cytoplasmic vesicle lumen, and secretory granule lumen. In light of the KEGG enrichment analysis, the Hepatitis B, AGE-RAGE signaling pathway in diabetic complications, Kaposi sarcoma-associated herpesvirus infection, measles, Human cytomegalovirus infection, and JAK-STAT signaling pathway were significantly enriched. The molecular docking technology found that puerarin and saikosaponin A had relative stronger affinity with VEGFA, HIF-1A, JAK2 and STAT3 than other compounds in terms of the binding free energy. Conclusions: The effect of LCJX on PV is achieved through a series of complex mechanisms. Network pharmacology and molecular docking are powerful tools to reveal the effect of compound Chinese medicine on the disease.