No abstract

In times where only a few novel antibiotics are to be expected, antimicrobial resistance remains an expanding global health threat. In case of chronic infections caused by therapy-resistant pathogens, physicians have limited therapeutic options, which are often associated with detrimental consequences for the patient. This has resulted in a renewed interest in alternative strategies, such as bacteriophage (phage) therapy. However, there are still important hurdles that currently impede the more widespread implementation of phage therapy in clinical practice. First, the limited number of good-quality case series and clinical trials have failed to show the optimal application protocol in terms of route of administration, frequency of administration, treatment duration and phage titer. Second, there is limited information on the systemic effects of phage therapy. Finally, in the past, phage therapy has been applied intuitively in terms of the selection of phages and their combination as parts of phage cocktails. This has led to an enormous heterogeneity in previously published studies, resulting in a lack of reliable safety and efficacy data for phage therapy. We hereby present a study protocol that addresses these scientific hurdles using a multidisciplinary approach, bringing together the experience of clinical, pharmaceutical and molecular microbiology experts.

Background: Topical hemostatic agents are commonly used for reducing perioperative blood loss and transfusion requirement in primary total knee arthroplasty (TKA), although the optimal option has yet to be defined. This study aimed to evaluate the efficacy and safety of topical hemostatic agents and rank the best intervention using the network meta-analysis (NMA) method. Methods: We searched Web of science, PubMed, and Cochrane Library database up to April 2020, for randomized controlled trials (RCTs) on topical hemostatic agents in primary TKA. The quality of included studies was assessed using the Cochrane “risk of bias” tool. Direct and indirect comparisons were performed for the result of network meta-analysis followed by consistency test. Results: Thirty seven RCTs with 3792 patients were included in this NMA and the pooled results indicated that tranexamic acid plus diluted epinephrine (TXA+DEP) displayed the highest efficacy in reducing total blood loss, hemoglobin drop and transfusion requirement. None of the included treatments was found to increase risk of thromboembolic events compared to placebo. According to the results of ranking probabilities, TXA+DEP had the highest possibility to be the best topical hemostatic agent with regard to the greatest comparative efficacy and a relatively high safety level. Conclusion: Current evidence supports that administration of TXA+DEP may be the optimal topical hemostatic agent to decrease blood loss and transfusion requirement in primary TKA. More direct studies that focused on the topical application of TXA+DEP versus other treatments are needed in the future.

Objectives Smoking is a significant independent risk factor for postmenopausal osteoporosis, leading to genome variations in postmenopausal smokers. This study investigates potential biomarkers and molecular mechanisms of smoking-related postmenopausal osteoporosis (SRPO). Materials and methods The GSE13850 microarray dataset was downloaded from Gene Expression Omnibus (GEO). Gene modules associated with SRPO were identified using weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) analysis, and pathway and functional enrichment analyses. Feature genes were selected using two machine learning methods: support vector machine-recursive feature elimination (SVM-RFE) and random forest (RF). The diagnostic efficiency of the selected genes was assessed by gene expression analysis and receiver operating characteristic curve. Results Eight highly conserved modules were detected in the WGCNA network, and the genes in the module that was strongly correlated with SRPO were used for constructing the PPI network. A total of 113 hub genes were identified in the core network using topological network analysis. Enrichment analysis results showed that hub genes were closely associated with the regulation of RNA transcription and translation, ATPase activity, and immune-related signaling. Six genes (HNRNPC, PFDN2, PSMC5, RPS16, TCEB2, and UBE2V2) were selected as genetic biomarkers for SRPO by integrating the feature selection of SVM-RFE and RF. Conclusion The present study identified potential genetic biomarkers and provided a novel insight into the underlying molecular mechanism of SRPO.