Abstract: Adverse drug events are common in critically ill children and often result from systemic or target organ drug exposure. Methods of drug dosing and titration that consider pharmacokinetic alterations may improve our ability to optimally dose critically ill patients and reduce the risk for drug-related adverse events. To demonstrate this possibility, we explored the exposure-response relationship between midazolam and delirium in critically ill children. We retrospectively examined electronic health records (EHRs) of critically ill children <18 years of age hospitalized in the pediatric intensive care unit at Duke University; these children were administered midazolam during mechanical ventilation and had >/=1 Cornell Assessment of Pediatric Delirium (CAPD) score. We used individual-level data extracted from the EHR and a previously published population pharmacokinetic (PK) model developed in critically ill children to simulate plasma concentrations at the time of CAPD scores in 1,000 representative datasets. We used multilevel repeated measures models, with clustering at patient and simulation levels, to evaluate the associations between measures of drug exposure (e.g., concentration and area under concentration time curve) and delirium scores. We included 61 children, median age 1.5 years (range = 0.1-16.3), with 181 CAPD assessments. We identified similarities between simulated Empirical Bayesian parameter estimates from the EHR cohort and those from the PK model population. We identified a stronger association between drug concentration at the time of score and CAPD scores (coefficient 1.78; 95% confidence interval: 1.66-1.90) compared with cumulative dose per kilogram and CAPD scores (coefficient -0.01; 95% confidence interval: -0.01 to -0.01). EHR and PK models can be leveraged to investigate exposure-response relationships in critically ill children.

Abstract: BACKGROUND: Cancer is a second leading cause of death in the world, killing approximately 3500 per million people each year. Therefore, the drugs with multitarget pharmacology based on biological networks are crucial to investigate the molecular mechanisms of cancer drugs and repurpose the existing drugs to reduce adverse effects. Clerodendrum is a diversified genus with a wide range of economic and pharmacological properties. Limited studies were conducted on the genus's putative anticancer properties and the mechanisms of action based on biological networks remains unknown. This study was aimed to construct the possible compound/target/pathway biological networks for anticancer effect of Clerodendrum sp. using docking weighted network pharmacological approach and to investigate its potential mechanism of action. METHODS: A total of 194 natural Clerodendrum sp. Compounds were retrieved from public databases and screened using eight molecular descriptors. The cancer-associated gene targets were retrieved from databases and the function of the target genes with related pathways were examined. Cytoscape v3.7.2 was used to build three major networks: compound-target network, target-target pathway network, and compound-target-pathway network. RESULTS: Our finding indicates that the anticancer activity of Clerodendrum sp. involves 6 compounds, 9 targets, and 63 signaling pathways, resulting in multicompounds, multitargets, and multipathways networks. Additionally, molecular dynamics (MD) simulations were used to estimate the binding affinity of the best hit protein-ligand complexes. Conclusion. This study suggests the potential anticancer activity of Clerodendrum sp. which could further contribute to scavenger novel compounds for the development of new alternative anticancer drugs.

Abstract: Protein tyrosine phosphatases function in dephosphorylating target proteins to regulate signaling pathways that control a broad spectrum of fundamental physiological and pathological processes. Detailed knowledge concerning the roles of classical PTPs in human cancer merits in-depth investigation. We comprehensively analyzed the regulatory mechanisms and clinical relevance of classical PTPs in more than 9000 tumor patients across 33 types of cancer. The independent datasets and functional experiments were employed to validate our findings. We exhibited the extensive dysregulation of classical PTPs and constructed the gene regulatory network in human cancer. Moreover, we characterized the correlation of classical PTPs with both drug-resistant and drug-sensitive responses to anti-cancer drugs. To evaluate the PTP activity in cancer prognosis, we generated a PTPscore based on the expression and hazard ratio of classical PTPs. Our study highlights the notable role of classical PTPs in cancer biology and provides novel intelligence to improve potential therapeutic strategies based on pTyr regulation.

Abstract: Overview: In treating pulmonary fibrosis (PF), traditional Chinese medicine (TCM) has received much attention, but its mechanism is unclear. The pharmacological mechanisms of TCM can be explored through network pharmacology. However, due to its virtual screening properties, it still needs to be verified by in vitro or in vivo experiments. Therefore, we investigated the anti-PF mechanism of Yiqi Huayu Decoction (YHD) by combining network pharmacology with in vivo experiments. Methods: Firstly, we used classical bleomycin (BLM)-induced rat model of PF and administrated fibrotic rats with YHD (low-, medium-, and high-dose). We comprehensively assessed the treatment effect of YHD according to body weight, lung coefficient, lung function, and histopathologic examination. Second, we predict the potential targets by ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) combined with network pharmacology. In brief, we obtained the chemical ingredients of YHD based on the UHPLC-MS/MS and TCMSP database. We collected drug targets from TCMSP, HERB, and Swiss target prediction databases based on active ingredients. Disease targets were acquired from drug libraries, Genecards, HERB, and TTD databases. The intersecting targets of drugs and disease were screened out. The STRING database can obtain protein-protein interaction (PPI) networks and hub target proteins. Molecular Complex Detection (MCODE) clustering analysis combined with enrichment analysis can explore the possible biological mechanisms of YHD. Enrichment analyses were conducted through the R package and the David database, including the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Reactome. Then, we further validated the target genes and target proteins predicted by network pharmacology. Protein and gene expression detection by immunohistochemistry, Western blot (WB), and real-time quantitative PCR (rt-qPCR). Results: The results showed that high-dose YHD effectively attenuated BLM-induced lung injury and fibrosis in rats, as evidenced by improved lung function, relief of inflammatory response, and reduced collagen deposition. We screened nine core targets and cellular senescence pathways by UHPLC-MS/MS analysis and network pharmacology. We subsequently validated key targets of cellular senescence signaling pathways. WB and rt-qPCR indicated that high-dose YHD decreased protein and gene expression of senescence-related markers, including p53 (TP53), p21 (CDKN1A), and p16 (CDKN2A). Increased reactive oxygen species (ROS) are upstream triggers of the senescence program. The senescence-associated secretory phenotypes (SASPs), containing interleukin 6 (IL-6), tumor necrosis factor-alpha (TNF-alpha), and transforming growth factor-beta1 (TGF-beta1), can further exacerbate the progression of senescence. High-dose YHD inhibited ROS production in lung tissue and consistently reduced the SASPs expression in serum. Conclusion: Our study suggests that YHD improves lung pathological injury and lung function in PF rats. This protective effect may be related to the ability of YHD to inhibit cellular senescence.

Abstract: INTRODUCTION: Approximately 15%~30% of breast cancers have gene amplification or overexpression of the human epidermal growth factor receptor 2 (HER2), resulting in the chemotherapy resistance, a more-aggressive phenotype and poor prognosis. METHODS: We propose a strategy of nanocarriers co-loaded with docetaxel (DTX) and pictilisib (PIC) at a synergistic ratio and non-covalently bound with dual anti-HER2 epitopes bispecific antibodies (BsAbs: anti-HER2-IV/methoxy-polyethylene glycol (mPEG) and anti-HER2-II/methoxy-PEG) for synergistic targeting to overcome the therapeutic dilemmas of the resistance for HER2-targetable chemodrugs. DTX/PIC-loaded nanocarriers (D/P_NCs) were prepared with single emulsion methods and characterized using dynamic light scattering analysis, and the drug content was assayed by high-performance liquid chromatographic method. The integrity and function of BsABs were evaluated using sodium dodecylsulfate polyacrylamide gel electrophoresis (SDS-PAGE) and enzyme-linked immunosorbent assay (ELISA). The in vitro cell studies and in vivo breast tumor-bearing mice model were used to evaluate the anti-cancer effect and biosafety of formulations. RESULTS: D/P_NCs optimally prepared exhibited a spherical morphology with small particle sizes (~140 nm), high drug loading (~5.5%), and good colloidal stability. The synergistic tumor cytotoxicity of loading DTX and PIC at 2:1 ratio in D/P_NCs was discovered. The BsAbs are successfully decorated on mPEGylated DTX/PIC-loaded nanocarriers via anti-mPEG moiety. In vitro studies revealed that non-covalent decoration with dual BsAbs on D_P-NCs significantly and synergistically increased cellular uptake, while with loading DTX and PIC at a synergistic ratio of 2:1 in D/P_NCs further resulted in synergistic cytotoxicity. In vivo tumor inhibition studies showed the comparable results for synergistic antitumor efficacy while minimizing systemic toxicity of chemodrugs. CONCLUSION: Non-covalent modification with dual distinct epitopes BsAbs on the nanocarriers loaded with dual chemodrugs at a synergistic ratio was expected to be a promising therapeutic platform to overcome the chemoresistance of various cancers and warrants further development for future therapy in the clinical.

Abstract: Background: Glucocorticoid-induced osteoporosis (GIOP) is a common form of secondary osteoporosis caused by the protracted or a large dosage of glucocorticoids (GCs). Total flavonoids of Drynariae rhizoma (TFDR) have been widely used in treating postmenopausal osteoporosis (POP). However, their therapeutic effects and potential mechanism against GIOP have not been fully elucidated. Methods: Ultra-high-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESIQ-TOF-MS) experiments were performed for qualitative analysis. We performed hematoxylin-eosin (HE) staining and microcomputed tomography (micro-CT) analysis to detect the changes in bone microstructure. The changes in biochemical parameters in the serum samples were determined by performing an enzyme-linked immunosorbent assay (ELISA). The prediction results of network pharmacology were verified via quantitative real-time polymerase chain reaction (qRT-PCR) to elucidate the potential mechanism of TFDR against GIOP. Results: A total of 191 ingredients were identified in vitro and 48 ingredients in vivo. In the in-vivo experiment, the levels of the serum total cholesterol (TC), the serum triglyceride (TG), Leptin (LEP), osteocalcin (OC), osteoprotegerin (OPG), bone morphogenetic protein-2 (BMP-2), propeptide of type I procollagen (PINP), tartrate-resistant acid phosphatase (TRACP) and type-I collagen carboxy-terminal peptide (CTX-1) in the TFDR group significantly changed compared with those in the GIOP group. Moreover, the TFDR group showed an improvement in bone mineral density and bone microstructure. Based on the results of network pharmacology analysis, 67 core targets were selected to construct the network and perform PPI analysis as well as biological enrichment analysis. Five of the targets with high "degree value" had differential gene expression between groups using qRT-PCR. Conclusion: TFDR, which may play a crucial role between adipose metabolism and bone metabolism, may be a novel remedy for the prevention and clinical treatment of GIOP.

Abstract: The rapid and accurate evaluation of chemical toxicity is of great significance for estimation of chemical safety. In the past decades, a great number of excellent computational models have been developed for chemical toxicity prediction. But most machine learning models tend to be "black box", which bring about poor interpretability. In the present study, we focused on the identification and collection of structural alerts (SAs) responsible for a series of important toxicity endpoints. Then, we carried out effective storage of these structural alerts and developed a web-server named SApredictor (www.sapredictor.cn) for screening chemicals against structural alerts. People can quickly estimate the toxicity of chemicals with SApredictor, and the specific key substructures which cause the chemical toxicity will be intuitively displayed to provide valuable information for the structural optimization by medicinal chemists.

Abstract: Background: Danhong injection (DHI) is widely used in the treatment of cardiovascular and cerebrovascular diseases, and its safety and effectiveness have been widely recognized and applied in China. However, the potential molecular mechanism of action for the treatment of arrhythmia is not fully understood. Aim: In this study, through network pharmacology and in vitro cell experiments, we explored the active compounds of DHI for the treatment of arrhythmia and predicted the potential targets of the drug to investigate its mechanism of action. Materials and Methods: First, the potential therapeutic effect of DHI on arrhythmia was investigated in an in vitro arrhythmia model using human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), in which calcium transients were recorded to evaluate the status of arrhythmia. Next, the active compounds and key targets in the treatment of arrhythmia were identified through network pharmacology and molecular docking, and the key signaling pathways related to the treatment of arrhythmia were analyzed. Furthermore, we used real-time quantitative reverse transcription PCR (qRT-PCR) to verify the expression levels of key genes. Results: Early afterdepolarizations (EADs) were observed during aconitine treatment in hiPSC-CMs, and the proarrhythmic effect of aconitine was partially rescued by DHI, indicating that the antiarrhythmic role of DHI was verified in an in vitro human cardiomyocyte model. To further dissect the underlying molecular basis of this observation, network pharmacology analysis was performed, and the results showed that there were 108 crosstargets between DHI and arrhythmia. Moreover, 30 of these targets, such as AKT1 and HMOX1, were key genes. In addition, the mRNA expression of AKT1 and HMOX1 could be regulated by DHI. Conclusion: DHI can alleviate aconitine-induced arrhythmia in an in vitro model, presumably because of its multitarget regulatory mechanism. Key genes, such as AKT1 and HMOX1, may contribute to the antiarrhythmic role of DHI in the heart.

Abstract: Biofilm synthesizing multi-drug resistant Staphylococcus pseudintermedius bacteria has been recognized as the human infectious agent. It has been detected in the diseases of skin, ear, and postoperative infections. Its infections are becoming a major health problem due to its multi-drug resistance capabilities. However, no commercial vaccine for the treatment of its infections is currently available in the market. Here we employed the subtractive proteomics and reverse vaccinology approach to determine the potential novel drug and vaccine targets against S. pseudintermedius infections in humans. After screening the core-proteome of the 39 complete genomes of S. pseudintermedius, 2 metabolic pathways dependent and 34 independent proteins were determined as novel potential drug targets. Two proteins were found and used as potential candidates for designing the chimeric vaccine constructs. Depending on the properties such as antigenicity, toxicity and solubility, multi-epitope based vaccines constructs were designed. For immunogenicity enhancement, different specific sequences like linkers, PADRE sequences and molecular adjuvants were added. Molecular docking and molecular dynamic simulation analyses were performed to evaluate the prioritized vaccine construct's interactions with human immune cells HLA and TLR4. Finally, the cloning and expression ability of the vaccine construct was determined in the bacterial cloning system and human body immune response was predicted through immune simulation analysis. In conclusion, this study proposed the potential drug and vaccine targets and also designed a chimera vaccine to be tested and validated against infectious S. pseudintermedius species.

Abstract: Colitis-associated colorectal cancer (CAC) is a specific type of colorectal cancer (CRC) with high mortality and morbidity, the chronic inflammation in the intestinal mucosal is the characteristic of CAC. Chang Qing formula (CQF) is a Chinese herbal formula used clinically for the treatment of CAC with remarkable clinical efficacy, but its mechanism remains unclear. In the present work, Combined network pharmacology and transcriptomics were used to analyze the potential active ingredients and elucidate molecular mechanism of CQF in treating CAC. Firstly, the constituents migrating to blood of CQF were analyzed and identified by UPLC-Q-TOF-MS/MS, and core genes and pathways were screened by network pharmacology analysis. Encyclopedia of Genes and Genomes (KEGG) analysis showed that the IL-17 signaling pathway involved in CAC may be closely associated with the potential mechanismof action of CQF. Subsequently, the results from animal studies indicated that CQF profoundly reduced tumor numbers and tumor size in AOM/DSS mice. The RNA-seq data was analysed utilizing Ingenuity Pathway Analysis (IPA), and the results supported the idea that CQF exerts a tumour-suppressive effect via the IL-17 signalling pathway. Further studies demonstrated that CQF significantly reduced IL-17A levels, which in turn inhibited NF-kappaB/IL-6/STAT3 signaling cascade, suppressed MMP9 expression and promoted tumor cell apoptosis. In conclusion, the current study demonstrated that CQF remarkably improved inflammatory tumor microenvironment, and hindered the transformation of inflammation into cancer. These findings may help to design future strategies for the treatment of CAC.