ABSTRACT Antimicrobial‐resistant bacteria, a growing worldwide concern, reduce the effectiveness of antibiotics against a wide range of microbial infections. Various bacterial species have quickly developed antibiotic resistance since the first mention of penicillin resistance in 1947. A rise in mortality, more extended hospital stays, more healthcare expenditures, and morbidity are all brought about by these bacteria that are resistant to antibiotics. To develop resistance, bacteria may undergo genetic changes, engage in horizontal gene transfer, produce β‐lactamase, activate efflux pumps, form biofilms, and alter their metabolism to become less susceptible to drugs. Environmental factors and sublethal antibiotic exposure exacerbate resistance, particularly in cases of persistent infections caused by biofilms. This tendency is prompted by the overuse of antibiotics in both human and veterinary medicine, as well as inadequate infection control measures and environmental pollution. This review presents an extensive survey of antimicrobial resistance across bacterial taxa, with a focus on the physiological and genetic processes underlying this phenomenon. It delves into the current therapeutic landscape and showcases cutting‐edge methods—such as artificial intelligence‐driven antibiotic discovery and resistance prediction—to inform the development of next‐generation antibiotics and containment systems.
Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)
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AbstractMotivationNext generation sequencing technologies have enabled the study of the human microbiome through direct sequencing of microbial DNA, resulting in an enormous amount of microbiome sequencing data. One unique characteristic of microbiome data is the phylogenetic tree that relates all the bacterial species. Closely related bacterial species have a tendency to exhibit a similar relationship with the environment or disease. Thus, incorporating the phylogenetic tree information can potentially improve the detection power for microbiome-wide association studies, where hundreds or thousands of tests are conducted simultaneously to identify bacterial species associated with a phenotype of interest. Despite much progress in multiple testing procedures such as false discovery rate (FDR) control, methods that take into account the phylogenetic tree are largely limited.ResultsWe propose a new FDR control procedure that incorporates the prior structure information and apply it to microbiome data. The proposed procedure is based on a hierarchical model, where a structure-based prior distribution is designed to utilize the phylogenetic tree. By borrowing information from neighboring bacterial species, we are able to improve the statistical power of detecting associated bacterial species while controlling the FDR at desired levels. When the phylogenetic tree is mis-specified or non-informative, our procedure achieves a similar power as traditional procedures that do not take into account the tree structure. We demonstrate the performance of our method through extensive simulations and real microbiome datasets. We identified far more alcohol-drinking associated bacterial species than traditional methods.Availability and implementationR package StructFDR is available from CRAN.Supplementary informationSupplementary data are available at Bioinformatics online.
Short-Term Monotherapy with IDX184, a Liver-Targeted Nucleotide Polymerase Inhibitor, in Patients with Chronic Hepatitis C Virus Infection
ABSTRACT IDX184 is a liver-targeted prodrug of 2′-methylguanosine (2′-MeG) monophosphate. This study investigated the safety, tolerability, antiviral activity, and pharmacokinetics of IDX184 as a single agent in treatment-naïve patients with genotype-1 chronic hepatitis C virus (HCV) infection. Forty-one patients with baseline HCV RNA ≥ 5 log 10 IU/ml, alanine aminotransferase (ALT) ≤ 2.5× the upper limit of normal, and compensated liver disease were dosed. Sequential cohorts of 10 patients, randomized 8:2 (active:placebo), received 25, 50, 75, and 100 mg of IDX184 once daily for 3 days, with a 14-day follow-up. There were no safety-related treatment discontinuations or serious adverse events. The adverse events and laboratory abnormalities observed for IDX184- and placebo-treated patients were similar. At the end of the 3-day treatment period, changes from baseline in HCV RNA levels (means ± standard deviations) were −0.5 ± 0.6, −0.7 ± 0.2, −0.6 ± 0.3, and −0.7 ± 0.5 log 10 for the 25-, 50-, 75-, and 100-mg doses, respectively, while viral load remained unchanged for the pooled placebo patients (−0.05 ± 0.3 log 10 ). Patients with genotype-1a and patients with genotype-1b responded similarly. Serum ALT levels decreased, especially at daily doses ≥ 75 mg. During the posttreatment period, plasma viremia and serum aminotransferase levels returned to near pretreatment levels. No resistance mutations associated with IDX184 were detected. Plasma exposure of IDX184 and its nucleoside metabolite 2′-MeG was dose related and low. Changes in plasma viral load correlated with plasma exposure of 2′-MeG. In conclusion, the results from this proof-of-concept study show that small doses of the liver-targeted prodrug IDX184 were able to deliver significant antiviral activity and support further clinical evaluation of the drug candidate.