This study investigates the impact of foreign direct investment (FDI), economic growth and energy consumption on carbon emissions in five selected member countries in the Association of South East Asian Nations (ASEAN-5), including Indonesia, Malaysia, the Philippines, Singapore and Thailand. This paper employs a panel quantile regression model that takes unobserved individual heterogeneity and distributional heterogeneity into consideration. Moreover, to avoid an omitted variable bias, certain related control variables are included in our model. Our empirical results show that the effect of the independent variables on carbon emissions is heterogeneous across quantiles.Specifically, the effect of FDI on carbon emissions is negative, except at the 5th quantile, and becomes significant at higher quantiles. Energy consumption increases carbon emissions, with the strongest effects occurring at higher quantiles. Among the high-emissions countries, greater economic growth and population size appear to reduce emissions. The results of the study also support the validity of the halo effect hypothesis in higher-emissions countries. However, we find little evidence in support of an inverted U-shaped curve in the ASEAN-5 countries. In addition, a higher level of trade openness can mitigate the increase in carbon emissions, especially in low-and high-emissions nations. Finally, the results of the study also provide policymakers with important policy recommendations.

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miRNAs originate from primary transcripts (pri-miRNAs) with characteristic stem-loop structures. Accurate processing of pri-miRNAs is required for functional miRNAs. Here, using pri-miR166 family as a paradigm, we report the decisive role of pri-miRNA terminal loops in miRNA biogenesis. We found that multi-branched terminal loops in pri-miR166s substantially suppressed miR166 expression in vivo. Unlike canonical processing of pri-miRNAs, terminal-loop-branched (TLBed) pri-miRNAs can be processed by Dicer-like1 (DCL1) complexes bi-directionally: from base to loop and from loop to base, resulting in productive and abortive processing of miRNAs, respectively. In either case, DCL1 complexes canonically cut pri-miRNAs at a distance of 16-17 base pairs (bp) from a reference single-stranded loop region. DCL1 also adjusts processing sites toward an internal loop through its helicase domain. Thus, these results provide new insight into the poorly understood processing mechanism of pri-miRNAs with complicated secondary structures.

Triple-negative breast cancer (TNBC) is a heterogeneous disease with poor prognosis that lacks targeted therapies, especially in patients with chemotherapy-resistant disease. Since DNA methylation-induced silencing of tumor suppressors is common in cancer, reversal of promoter DNA hypermethylation by 5-aza-2'-deoxycytidine (decitabine), an FDA-approved DNA methyltransferase (DNMT) inhibitor, has proven effective in treating hematological neoplasms. However, its antitumor effect varies in solid tumors, stressing the importance of identifying biomarkers predictive of therapeutic response. Here, we focused on the identification of biomarkers to select decitabine-sensitive TNBC through increasing our understanding of the mechanism of decitabine action. We showed that protein levels of DNMTs correlated with response to decitabine in patient-derived xenograft (PDX) organoids originating from chemotherapy-sensitive and -resistant TNBCs, suggesting DNMT levels as potential biomarkers of response. Furthermore, all 3 methytransferases, DNMT1, DNMT3A, and DNMT3B, were degraded following low-concentration, long-term decitabine treatment both in vitro and in vivo. The DNMT proteins could be ubiquitinated by the E3 ligase, TNF receptor-associated factor 6 (TRAF6), leading to lysosome-dependent protein degradation. Depletion of TRAF6 blocked decitabine-induced DNMT degradation, conferring resistance to decitabine. Our study suggests a potential mechanism of regulating DNMT protein degradation and DNMT levels as response biomarkers for DNMT inhibitors in TNBCs.

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