What We Need to Know about Liposomes as Drug Nanocarriers: An Updated Review.

Liposomes have been attracted considerable attention as phospholipid spherical vesicles, over the past 40 years. These lipid vesicles are valued in biomedical application due to their ability to carry both hydrophobic and hydrophilic agents, high biocompatibility and biodegradability. Various methods have been used for the synthesis of liposomes, so far and numerous modifications have been performed to introduce liposomes with different characteristics like surface charge, size, number of their layers, and length of circulation in biological fluids. This article provides an overview of the significant advances in synthesis of liposomes via active or passive drug loading methods, as well as describes some strategies developed to fabricate their targeted formulations to overcome limitations of the "first-generation" liposomes.

PSSMCOOL: a comprehensive R package for generating evolutionary-based descriptors of protein sequences from PSSM profiles.

Position-specific scoring matrix (PSSM), also called profile, is broadly used for representing the evolutionary history of a given protein sequence. Several investigations reported that the PSSM-based feature descriptors can improve the prediction of various protein attributes such as interaction, function, subcellular localization, secondary structure, disorder regions, and accessible surface area. While plenty of algorithms have been suggested for extracting evolutionary features from PSSM in recent years, there is not any integrated standalone tool for providing these descriptors. Here, we introduce PSSMCOOL, a flexible comprehensive R package that generates 38 PSSM-based feature vectors. To our best knowledge, PSSMCOOL is the first PSSM-based feature extraction tool implemented in R. With the growing demand for exploiting machine-learning algorithms in computational biology, this package would be a practical tool for machine-learning predictions.

Investigation and characterization of human gut phageome in advanced liver cirrhosis of defined etiologies.

BACKGROUND: Liver cirrhosis is a major public health problem, accounting for high rates of morbidity and mortality worldwide. The cirrhosis etiology is a broad and essential step in planning a treatment strategy. Many recent studies have documented that gut microbiome alterations play a vital role in the development and progression of cirrhosis and its complications. Nevertheless, there is insufficient data on the correlation between liver cirrhosis and gut phageome alterations in patients with advanced liver diseases. This study aimed to analyze the taxonomic structure and functional attributes of the gut phageome in six different etiologies of advanced liver cirrhosis. METHODS: We first retrieved metagenomic sequencing data from three datasets of fecal samples taken from cirrhotic patients with various etiologies. Subsequently, several bioinformatics pipelines were used to analyze bacteriophage composition and determine their functionality. RESULTS: A gene catalog of 479,425 non-redundant genes was developed as a reference to measure gene prevalence. The results of the analysis revealed a few significant differences among the cohorts at the phage species level. However, the alternations were more evident as there were more in-depth analyses of the functional resolution of the gut phageome. CONCLUSIONS: Our findings suggest that the functional analysis of the gut phageome would provide meaningful markers to predict the progression of liver cirrhosis and facilitate the development of novel treatment approaches.