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To evaluate the clinical efficacy of etonogestrel subcutaneous implant (ENG-SCI) with that of the levonorgestrel-releasing intrauterine system (LNG-IUD) for adenomyosis treatment. A prospective randomized cohort study was conducted including 108 patients (50 patients in ENG-SCI group and 58 in the LNG-IUD group) with adenomyosis from January 2019 to July 2021. After 3 months of treatment, both ENG-SCI group and LNG-IUD group showed significant improvement in patients’ visual analog scale, pictorial blood loss assessment chart (PBAC), and uterine volume (P ＜ 0.05). The uterine volume of patients in LNG-IUD group decreased more significantly than that in the ENG-SCI group since 3 months of treatment. The PBAC score in the LNG-IUD group improved better than that in the ENG-SCI group since 6 months of treatment (P ＜ 0.05). No significant difference in the occurrence rate of ideal vaginal bleeding patterns and the hemoglobin levels between the two groups was observed. The ENG-SCI group had a higher probability of weight gain and progesterone-related side effects (P ＜ 0.05). Both ENG-SCI and LNG-IUD were effective in treatment of adenomyosis. However, LNG-IUD had a more significant effect in treating adenomyosis-related dysmenorrhea, excessive menstrual flow, anemia, and uterine enlargement, with relatively fewer side effects.

Endothelial-mesenchymal transition (EndMT) is a differentiation process in which endothelial cells lose their own characteristics and acquire mesenchymal-like characteristics, which contributes to the formation and development of atherosclerotic plaques. Until now, there is still a lack of effective measures to treat atherosclerosis (AS), so there is an urgent need to understand the underlying mechanisms of AS. In addition, although various studies have shown that EndMT is involved in the pathological stages of cardiovascular diseases, such as myocardial fibrosis, myocardial hypertrophy, and hypertension, the specific molecular mechanisms driving EndMT are still in the exploratory stage. In this review, we review the role of histone modifications (methylation, demethylation and acetylation, deacetylation) on EndMT in cardiovascular disease, aiming to target histone-modifying enzymes to guide cardiovascular disease therapy.

Background: Major depressive disorder (MDD) plays a crucial role in the occurrence of heart failure (HF). This investigation was undertaken to explore the possible mechanism of MDD's involvement in HF pathogenesis and identify candidate biomarkers for the diagnosis of MDD with HF. Methods: GWAS data for MDD and HF were collected, and Mendelian randomization (MR) analysis was performed to investigate the causal relationship between MDD and HF. Differential expression analysis (DEA) and WGCNA were used to detect HF key genes and MDD-associated secretory proteins. Protein–protein interaction (PPI), functional enrichment, and cMAP analysis were used to reveal potential mechanisms and drugs for MDD-related HF. Then, four machine learning (ML) algorithms (including GLM, RF, SVM, and XGB) were used to screen candidate biomarkers, construct diagnostic nomograms, and predict MDD-related HF. Furthermore, the MCPcounter algorithm was used to explore immune cell infiltration in HF, and MR analysis was performed to explore the causal effect of immunophenotypes on HF. Finally, the validation of the association of MDD with reduced left ventricular ejection fraction (LVEF) and the performance assessment of diagnostic biomarkers was accomplished based on animal models mimicking MDD. Results: The MR analysis showed that the MDD was linked to an increased risk of HF (OR = 1.129, p < 0.001). DEA combined with WGCNA and secretory protein gene set identified 315 HF key genes and 332 MDD-associated secretory proteins, respectively. Through PPI and MCODE analysis, 78 genes were pinpointed as MDD-related pathogenic genes for HF. The enrichment analysis revealed that these genes were predominantly enriched in immune and inflammatory regulation. Through four ML algorithms, two hub genes (ISLR/SFRP4) were identified as candidate HF biomarkers, and a nomogram was developed. ROC analysis showed that the AUC of the nomogram was higher than 0.90 in both the HF combined dataset and two external cohorts. In addition, an immune cell infiltration analysis revealed the immune dysregulation in HF, with ISLR/SFRP4 displaying notable associations with the infiltration of B cells, CD8 T cells, and fibroblasts. More importantly, animal experiments showed that the expression levels of ISLR (r = −0.653, p < 0.001) and SFRP4 (r = −0.476, p = 0.008) were significantly negatively correlated with LVEF. Conclusions: The MR analysis indicated that MDD is a risk factor for HF at the genetic level. Bioinformatics analysis and the ML results suggest that ISLR and SFRP4 have the potential to serve as diagnostic biomarkers for HF. Animal experiments showed a negative correlation between the serum levels of ISLR/SFRP4 and LVEF, emphasizing the need for additional clinical studies to elucidate their diagnostic value. [ABSTRACT FROM AUTHOR]

In this paper, we theoretically discuss and empirically show how IT capability spurs companies towards greener strategies. Based on the data of listed Chinese manufacturing companies from 2008 to 2018, using a panel regression model, the results show that: (1) corporate IT capability can promote green technological innovation. (2) Compared with state-owned enterprises (SOEs), the IT effect is more significant for non-state-owned enterprises (non-SOEs); compared with regions with weak environmental regulation, the IT effect is more significant in regions with strong environmental regulation. (3) Additionally, we found that the promotion of IT software capability is stronger than IT hardware capability, and they have a synergistic effect on green technological innovation. Overall, our findings offer a new point view for a deeper understanding of green technological innovation, and provide microscopic evidence for the objective evaluation of corporate IT capability. [ABSTRACT FROM AUTHOR]