Methylation synthetic lethality: Exploiting selective drug targets for cancer therapy.

In cancer, synthetic lethality refers to the drug-induced inactivation of one gene and the inhibition of another in cancer cells by a drug, resulting in the death of only cancer cells; however, this effect is not present in normal cells, leading to targeted killing of cancer cells. Recent intensive epigenetic research has revealed that aberrant epigenetic changes are more frequently observed than gene mutations in certain cancers. Recently, numerous studies have reported various methylation synthetic lethal combinations involving DNA damage repair genes, metabolic pathway genes, and paralogs with significant results in cellular models, some of which have already entered clinical trials with promising results. This review systematically introduces the advantages of methylation synthetic lethality and describes the lethal mechanisms of methylation synthetic lethal combinations that have recently demonstrated success in cellular models. Furthermore, we discuss the future opportunities and challenges of methylation synthetic lethality in targeted anticancer therapies.

Clinical utility of a model-based amoxicillin dosage regimen in neonates with early-onset sepsis.

Early-onset sepsis (EOS) is one of the most significant causes of morbidity and mortality in neonates. Currently, amoxicillin is empirically used to treat neonates with EOS. However, data on its effectiveness in neonates with EOS are still limited. Therefore, we aimed to evaluate the pharmacodynamics (PD) target attainment and effectiveness of a model-based amoxicillin dosage regimen in these neonates. We used a previously developed model and collected additional clinical data from the EOS neonates who used the model-based dosage regimen (25 mg/kg every 12 h). The primary outcomes were PD target attainment (free drug concentration above minimum inhibitory concentration during 70% of the dosing interval) and treatment failure rate. The secondary endpoints were length of amoxicillin treatment, duration of hospitalization etc. Seventy-five neonates (postmenstrual age 28.4-41.6 wk) were enrolled. A total of 70 (93.3%) neonates reached their PD target using 1 mg/L as the minimum inhibitory concentration breakpoint. The treatment failure rate was 10.7%.

Population Pharmacokinetics and Dosing Optimization of Amoxicillin in Chinese Infants.

Amoxicillin is used to treat various bacterial infections (eg, pneumonia, sepsis, meningitis) in infants. Despite its frequent use, there is a lack of population pharmacokinetic studies in infants, resulting in a substantial variability in dosing regimens used in clinical practice. Therefore, the objective of this study was to evaluate the population pharmacokinetics of intravenous amoxicillin in infants and suggest an optimal dosage regimen. Blood samples were collected for the determination of amoxicillin concentrations using an opportunistic sampling strategy. The amoxicillin plasma concentrations were determined using high-performance liquid chromatography. Population pharmacokinetic analysis was performed using NONMEM. A total of 62 pharmacokinetic samples from 47 infants (age range, 0.09 to 2.0 years) were available for analysis. A 2-compartment model with first-order elimination was most suitable to describe the population pharmacokinetics of amoxicillin, and covariate analysis showed that only current body weight was a significant covariate. Monte Carlo simulation demonstrated that the currently used dosage regimen (25 mg/kg twice daily) resulted in only 22.4% of infants reaching their pharmacodynamic target, using a minimum inhibitory concentration (MIC) break point of 2 mg/L, whereas a dosage regimen (60 mg/kg thrice daily), as supported by the British National Formulary for Children, resulted in 80.9% of infants achieving their pharmacodynamic target. It is recommended to change antibiotics for infections caused by Escherichia coli (MIC = 8.0 mg/L) because only 27.9% of infants reached target using 60 mg/kg thrice daily.

[Lightning-caused fire, its affecting factors and prediction: a review].

Lightning-caused fire is the most important natural fire source. Its induced forest fire brings enormous losses to human beings and ecological environment. Many countries have paid great attention to the prediction of lightning-caused fire. From the viewpoint of the main factors affecting the formation of lightning-caused fire, this paper emphatically analyzed the effects and action mechanisms of cloud-to-ground lightning, fuel, meteorology, and terrain on the formation and development process of lightning-caused fire, and, on the basis of this, summarized and reviewed the logistic model, K-function, and other mathematical methods widely used in prediction research of lightning-caused fire. The prediction methods and processes of lightning-caused fire in America and Canada were also introduced. The insufficiencies and their possible solutions for the present researches as well as the directions of further studies were proposed, aimed to provide necessary theoretical basis and literature reference for the prediction of lightning-caused fire in China.