Histone methyltransferase MLL4 protects against pressure overload-induced heart failure via a THBS4-mediated protection in ER stress.

Pressure overload-induced pathological cardiac hypertrophy eventually leads to heart failure (HF). Unfortunately, lack of effective targeted therapies for HF remains a challenge in clinical management. Mixed-lineage leukemia 4 (MLL4) is a member of the SET family of histone methyltransferase enzymes, which possesses histone H3 lysine 4 (H3K4)-specific methyltransferase activity. However, whether and how MLL4 regulates cardiac function is not reported in adult HF. Here we report that MLL4 is required for endoplasmic reticulum (ER) stress homeostasis of cardiomyocytes and protective against pressure overload-induced cardiac hypertrophy and HF. We observed that MLL4 is increased in the heart tissue of HF mouse model and HF patients. The cardiomyocyte-specific deletion of Mll4 (Mll4-cKO) in mice leads to aggravated ER stress and cardiac dysfunction following pressure overloading. MLL4 knockdown neonatal rat cardiomyocytes (NRCMs) also display accelerated decompensated ER stress and hypertrophy induced by phenylephrine (PE). The combined analysis of Cleavage Under Targets and Tagmentation sequencing (CUT&Tag-seq) and RNA sequencing (RNA-seq) data reveals that, silencing of Mll4 alters the chromatin landscape for H3K4me1 modification and gene expression patterns in NRCMs. Interestingly, the deficiency of MLL4 results in a marked reduction of H3K4me1 and H3K27ac occupations on Thrombospondin-4 (Thbs4) gene loci, as well as Thbs4 gene expression. Mechanistically, MLL4 acts as a transcriptional activator of Thbs4 through mono-methylation of H3K4 and further regulates THBS4-dependent ER stress response, ultimately plays a role in HF. Our study indicates that pharmacologically targeting MLL4 and ER stress might be a valid therapeutic approach to protect against cardiac hypertrophy and HF.

CPhaMAS: An online platform for pharmacokinetic data analysis based on optimized parameter fitting algorithm.

BACKGROUND AND OBJECTIVE: Clinical pharmacological modeling and statistical analysis software is an essential basic tool for drug development and personalized drug therapy. The learning curve of current basic tools is steep and unfriendly to beginners. The curve is even more challenging in cases of significant individual differences or measurement errors in data, resulting in difficulties in accurately estimating pharmacokinetic parameters by existing fitting algorithms. Hence, this study aims to explore a new optimized parameter fitting algorithm that reduces the sensitivity of the model to initial values and integrate it into the CPhaMAS platform, a user-friendly online application for pharmacokinetic data analysis. METHODS: In this study, we proposed an optimized Nelder-Mead method that reinitializes simplex vertices when trapped in local solutions and integrated it into the CPhaMAS platform. The CPhaMAS, an online platform for pharmacokinetic data analysis, includes three modules: compartment model analysis, non-compartment analysis (NCA) and bioequivalence/bioavailability (BE/BA) analysis. Our proposed CPhaMAS platform was evaluated and compared with existing WinNonlin. RESULTS: The platform was easy to learn and did not require code programming. The accuracy investigation found that the optimized Nelder-Mead method of the CPhaMAS platform showed better accuracy (smaller mean relative error and higher R2) in two-compartment and extravascular administration models when the initial value was set to true and abnormal values (10 times larger or smaller than the true value) compared with the WinNonlin. The mean relative error of the NCA calculation parameters of CPhaMAS and WinNonlin was <0.0001 %. When calculating BE for conventional, high-variability and narrow-therapeutic drugs. The main statistical parameters of the parameters Cmax, AUCt, and AUCinf in CPhaMAS have a mean relative error of <0.01% compared to WinNonLin. CONCLUSIONS: In summary, CPhaMAS is a user-friendly platform with relatively accurate algorithms. It is a powerful tool for analysing pharmacokinetic data for new drug development and precision medicine.

Evaluation of time-dependent phenotypes of myocardial ischemia-reperfusion in mice.

BACKGROUND: A mouse model of myocardial ischemia-reperfusion (I/R) is widely used to study myocardial ischemia-reperfusion injury (I/RI). However, few studies focus on the direct comparison of the extent of pathological events resulting from variant durations of ischemia and reperfusion process. METHODS: A mouse model of I/RI was established by ligation and perfusion of the left anterior descending coronary artery (LAD), and the dynamic changes were recorded by electrocardiogram at different stages of I/R. Subsequently, reperfusion duration was used as a variable to directly compare the phenotypes of different myocardial injury degrees induced by 3 h, 6 h and 24 h reperfusion from myocardial infarct size, myocardial apoptosis, myocardial enzyme, and inflammatory cytokine levels. RESULTS: All mice subjected to myocardial I/R surgery showed obvious myocardial infarction, extensive myocardial apoptosis, dynamic changes in serum myocardial enzyme and inflammatory cytokines, at least for the first 24 h of reperfusion. The infarct size and apoptosis rates gradually increased with the extension of reperfusion time. The peaks of serum myocardial enzyme and inflammatory cytokines occurred at 6 h and 3 h of reperfusion, respectively. We also established I/R mice models with 30 and 60 mins of ischemia. After 21 days of remodeling, longer periods of ischemia increased the degree of fibrosis and reduced cardiac function. CONCLUSIONS: In summary, we conclude that reperfusion durations of 3 h, 6 h, and 24 h induces different injury phenotypes in ischemia-reperfusion mouse model. At the same time, the ischemia duration before reperfusion also affects the degree of cardiac remodeling.