Antibacterial sensitizers from natural plants: A powerful weapon against methicillin-resistant Staphylococcus aureus

Methicillin-resistant Staphylococcus aureus (MRSA) is a drug-resistant bacterium that can cause a range of infections with high morbidity and mortality, including pneumonia, etc. Therefore, development of new drugs or therapeutic strategies against MRSA is urgently needed. Increasing evidence has shown that combining antibiotics with “antibacterial sensitizers” which itself has no effect on MRSA, is highly effective against MRSA. Many studies showed the development of antibacterial sensitizers from natural plants may be a promising strategy against MRSA because of their low side effects, low toxicity and multi-acting target. In our paper, we first reviewed the resistance mechanisms of MRSA including “Resistance to Beta-Lactams”, “Resistance to Glycopeptide antibiotics”, “Resistance to Macrolides, Aminoglycosides, and Oxazolidinones” etc. Moreover, we summarized the possible targets for antibacterial sensitizers against MRSA. Furthermore, we reviewed the synergy effects of active monomeric compounds from natural plants combined with antibiotics against MRSA and their corresponding mechanisms over the last two decades. This review provides a novel approach to overcome antibiotic resistance in MRSA

Effects of cadmium on the growth, muscle composition, digestion, gene expression of antioxidant and lipid metabolism in juvenile tilapia (Oreochromis niloticus)

Cadmium could induce various degrees of harm to aquatic organisms. A 30-day feeding trial was conducted to investigate the effects of cadmium on growth, muscle composition, digestive enzyme activity, gene expression of antioxidants and lipid metabolism in juvenile genetic improvement of farmed tilapia (GIFT, Oreochromis niloticus, Initial weight: 21.36 ± 0.24 g). Four cadmium concentrations of aquaculture water were designed: 0, 0.2, 0.4, and 0.6 mg/L Cd2+. The main results are as follows: Compared with the control group (0 mg/L Cd2+), the weight gain rate (WGR), specific growth rate (SGR), daily growth index (DGI), and spleen index (SI) of juvenile GIFT under cadmium stress were significantly decreased (p< 0.05). The contents of crude protein and crude lipid in muscle were significantly decreased (p< 0.05), and the ash was significantly increased (p< 0.05). The activities of trypsin, lipase, and α-amylase in the intestinal were significantly decreased (p< 0.05). The relative expression levels of carnitine palmityl transferase 1 (cpt-1), peroxisome proliferator-activated receptor α (pparα), pparγ, hormone-sensitive lipase (hsl), lipoprotein lipase (lpl), malate dehydrogenase (mdh), leptin (lep), fatty acid synthetase (fas), cholesterol response element binding protein 1 (srebp1), squalene cyclooxygenase (sqle), and stearoyl-CoA desaturase (scd) genes in liver were significantly decreased (p< 0.05). The relative expression levels of catalase (cat), superoxide dismutase (sod), glutathione S-transferase (gst), and glutathione peroxidase (gsh-px) genes in the liver were significantly decreased (p< 0.05). In conclusion, exposure to cadmium stress could impact growth, muscle composition, digestive enzyme activity, gene expression of antioxidant and lipid metabolism in juvenile GIFT

Identification of pivotal genes and regulatory networks associated with atherosclerotic carotid artery stenosis based on comprehensive bioinformatics analysis and machine learning

Objective:Bioinformatics methods were applied to investigate the pivotal genes and regulatory networks associated with atherosclerotic carotid artery stenosis (ACAS) and provide new insights for the treatment of this disease.Methods:The study utilized five ACAS datasets (GSE100927, GSE11782, GESE28829, GSE41571, and GSE43292) downloaded from the NCBI GEO database. The first four datasets were combined as the training set (n = 99), while GSE43292 (n = 64) was used as the validation set. Difference analysis and functional enrichment analysis were then performed on the training set. The pathogenic targets of ACAS were screened by protein-protein interaction networks and MCODE analyses, combined with three machine learning algorithms. The results were next verified by analysis of inter-group differences and ROC curve analysis. Next, immune-related function and immune cell correlation analyses were performed, and plaques of human ACAS were applied to verify the results via immunohistochemistry (IH) and immunofluorescence (IF). Finally, the competing endogenous RNAs (ceRNA) and transcription factors (TFs) regulatory networks of the characterized genes were constructed.Results:A total of 177 differentially expressed genes were identified, including 67 genes downregulated and 110 genes upregulated. Gene set enrichment analysis revealed that five pathways were active in the experimental group, including xenograft rejection, autoimmune thyroid disease, graft-versus-host disease, leishmaniasis infection, and lysosomes. Four key genes were identified, with C3AR1 being upregulated and FBLN5, PPP1R12A, and TPM1 being downregulated. The analysis of inter-group differences demonstrated that the four characterized genes were differentially expressed in both the control and experimental groups. The ROC analysis showed that they had high AUC values in both the training and validation sets. Therefore, a predictive ACAS patient nomogram model based on the screened genes was established. Correlation analysis revealed a positive correlation between C3AR1 expression and neutrophils, which was further validated in IH and IF. One or multiple lncRNAs may compete with the characterized genes for binding miRNAs. Additionally, each characterized gene interacts with multiple TFs.Conclusion:Four pivotal genes were screened, and relevant ceRNA and TFs were predicted. These molecules may exert a crucial role in ACAS and serve as potential biomarkers and therapeutic targets

Crataegus pinnatifida: Chemical Constituents, Pharmacology, and Potential Applications

Crataegus pinnatifida (Hawthorn) is widely distributed in China and has a long history of use as a traditional medicine. The fruit of C. pinnatifida has been used for the treatment of cardiodynia, hernia, dyspepsia, postpartum blood stasis, and hemafecia and thus increasing interest in this plant has emerged in recent years. Between 1966 and 2013, numerous articles have been published on the chemical constituents, pharmacology or pharmacologic effects and toxicology of C. pinnatifida. To review the pharmacologic advances and to discuss the potential perspective for future investigation, we have summarized the main literature findings of these publications. So far, over 150 compounds including flavonoids, triterpenoids, steroids, monoterpenoids, sesquiterpenoids, lignans, hydroxycinnamic acids, organic acids and nitrogen-containing compounds have been isolated and identified from C. pinnatifida. It has been found that these constituents and extracts of C. pinnatifida have broad pharmacological effects with low toxicity on, for example, the cardiovascular, digestive, and endocrine systems, and pathogenic microorganisms, supporting the view that C. pinnatifida has favorable therapeutic effects. Thus, although C. pinnatifida has already been widely used as pharmacological therapy, due to its various active compounds, further research is warranted to develop new drugs

Prediction of Compressive Strength Loss of Normal Concrete after Exposure to High Temperature

In recent years, there has been an increasing number of fires in buildings. The methods for detecting residual properties of buildings after fires are commonly destructive and subjective. In this context, property prediction based on mathematical modeling has exhibited its potential. Backpropagation (BP), particle swarm algorithms optimized-BP (PSO-BP) and random forest (RF) models were established in this paper using 1803 sets of data from the literature. Material and relevant heating parameters, as well as compressive strength loss percentage, were used as input and output parameters, respectively. Experimental work was also carried out to evaluate the feasibility of the models for prediction. The accuracy of all the models was sufficiently high, and they were also much more feasible for prediction. Moreover, based on the RF model, the importance of the inputting parameters was ranked as well. Such prediction has provided a new perspective to non-destructively and objectively assess the post-fire properties of concrete. Additionally, this model could be used to guide performance-based design for fire-resistant concrete

Prediction of Compressive Strength Loss of Normal Concrete after Exposure to High Temperature

In recent years, there has been an increasing number of fires in buildings. The methods for detecting residual properties of buildings after fires are commonly destructive and subjective. In this context, property prediction based on mathematical modeling has exhibited its potential. Backpropagation (BP), particle swarm algorithms optimized-BP (PSO-BP) and random forest (RF) models were established in this paper using 1803 sets of data from the literature. Material and relevant heating parameters, as well as compressive strength loss percentage, were used as input and output parameters, respectively. Experimental work was also carried out to evaluate the feasibility of the models for prediction. The accuracy of all the models was sufficiently high, and they were also much more feasible for prediction. Moreover, based on the RF model, the importance of the inputting parameters was ranked as well. Such prediction has provided a new perspective to non-destructively and objectively assess the post-fire properties of concrete. Additionally, this model could be used to guide performance-based design for fire-resistant concrete

A new gamboge derivative compound 2 inhibits cancer stem-like cells via suppressing EGFR tyrosine phosphorylation in head and neck squamous cell carcinoma

Cancer stem-like cells represent a population of tumour-initiating cells that lead to the relapse and metastasis of cancer. Conventional anti-cancer therapeutic drugs are usually ineffective in eliminating the cancer stem-like cells. Therefore, new drugs or therapeutic methods effectively targeting cancer stem-like cells are in urgent need to successfully cure cancer. Gamboge is a natural anti-cancer medicine whose pharmacological effects are different from those of conventional chemotherapeutical drugs and they can kill some kinds of cancer cells selectively. In this study, we identified a new gamboge derivative, Compound 2 (C2), which presents eminent suppression effects on cancer cells. Interestingly, when compared with cisplatin (CDDP), C2 effectively suppresses the growth of both cancer stem-like cells and non-cancer stem-like cells derived from head and neck squamous cell carcinoma (HNSCC), inhibiting the formation of tumour spheres and colony in vitro, resulting in the loss of expression of multiple cancer stem cell (CSC)-related molecules in HNSCC. Treating with C2 effectively inhibited the growth of HNSCC in BALB/C nude mice. Further investigation found that C2 notably inhibits the activation of epithelial growth factor receptor and the phosphorylation of its downstream protein kinase homo sapiens v-akt murine thymoma viral oncogene homolog (AKT) in HNSCC, resulting in down-regulation of multiple CSC-related molecules in HNSCC. Our study has demonstrated that C2 effectively inhibits the stem-like property of cancer stem-like cells in HNSCC and may be a hopeful targeting drug in cancer therapy

Compressive Strength Prediction of Alkali-Activated Slag Concretes by Using Artificial Neural Network (ANN) and Alternating Conditional Expectation (ACE)

Compressive strength of alkali-activated slag (AAS) concrete is influenced by multi-factors in a nonlinear way. Both artificial neural network (ANN) and alternating conditional expectation (ACE) models of 3-day (3 d) and 28-day (28 d) compressive strength of AAS were established in this study by using the data reported in related literature, where alkali concentration of activator (Na2O%), modulus of activator (Ms), water/binder ratio (W/B), surface area of slag (SA), and basicity index of slag (Kb) were taken as input parameters. The models were employed later to predict 3 d and 28 d compressive strength of AAS concretes, respectively, and the results were validated by experimental work. The results show that both the ANN and the ACE models had adequate accuracy, no matter 3 d or 28 d compressive strength was considered. Compared to the 3 d compressive strength, due to data scattering that increased with the increase of data size, both the models did not yield a higher accuracy in the case of 28 d strength. However, also due to the increase in data size, both the models were more feasible to implement 28 d strength prediction as a result of sufficient learning and training during modeling. In addition, based on ACE analysis, the weight-influencing compressive strength of AAS decreased in a sequence of Na2O% > Ms > W/B > Kb > SA. If data size was sufficiently large, it was more suitable to establish an ANN model for compressive strength prediction of AAS concretes. Otherwise, ACE could be considered as an alternative to yield an acceptable result

Design of New Antibacterial Enhancers Based on AcrB’s Structure and the Evaluation of Their Antibacterial Enhancement Activity

Previously, artesunate (AS) and dihydroartemisinine 7 (DHA7) were found to have antibacterial enhancement activity against Escherichia coli via inhibition of the efflux pump AcrB. However, they were only effective against E. coli standard strains. This study aimed to develop effective antibacterial enhancers based on the previous work. Our results demonstrate that 86 new antibacterial enhancers were designed via 3D-SAR and molecular docking. Among them, DHA27 had the best antibacterial enhancement activity. It could potentiate the antibacterial effects of ampicillin against not only E. coli standard strain but also clinical strains, and of β-lactam antibiotics, not non-β-lactamantibiotics. DHA27 could increase the accumulation of daunomycin and nile red within E. coli ATCC 35218, but did not increase the bacterial membrane permeability. DHA27 reduced acrB’s mRNA expression of E. coli ATCC 35218 in a dose-dependent manner, and its antibacterial enhancement activity is related to the degree of acrB mRNA expression in E. coli clinical strains. The polypeptides from AcrB were obtained via molecular docking assay; the pre-incubated polypeptides could inhibit the activity of DHA27. Importantly, DHA27 had no cytotoxicity on cell proliferation. In conclusion, among newly designed antibacterial enhancers, DHA27 had favorable physical and pharmacological properties with no significant cytotoxicity at effective concentrations, and might serve as a potential efflux pump inhibitor in the future