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1.
EMBO J ; 37(22)2018 11 15.
Article in English | MEDLINE | ID: mdl-30389664

ABSTRACT

The endoplasmic reticulum-associated protein degradation (ERAD) is responsible for recognizing and retro-translocating protein substrates, misfolded or not, from the ER for cytosolic proteasomal degradation. HMG-CoA Reductase (HMGCR) Degradation protein-HRD1-was initially identified as an E3 ligase critical for ERAD. However, its physiological functions remain largely undefined. Herein, we discovered that hepatic HRD1 expression is induced in the postprandial condition upon mouse refeeding. Mice with liver-specific HRD1 deletion failed to repress FGF21 production in serum and liver even in the refeeding condition and phenocopy the FGF21 gain-of-function mice showing growth retardation, female infertility, and diurnal circadian behavior disruption. HRD1-ERAD facilitates the degradation of the liver-specific ER-tethered transcription factor CREBH to downregulate FGF21 expression. HRD1-ERAD catalyzes polyubiquitin conjugation onto CREBH at lysine 294 for its proteasomal degradation, bridging a multi-organ crosstalk in regulating growth, circadian behavior, and female fertility through regulating the CREBH-FGF21 regulatory axis.


Subject(s)
Cyclic AMP Response Element-Binding Protein/metabolism , Endoplasmic Reticulum-Associated Degradation , Fibroblast Growth Factors/biosynthesis , Liver/metabolism , Ubiquitin-Protein Ligases/metabolism , Ubiquitination , Animals , Cyclic AMP Response Element-Binding Protein/genetics , Female , Fertility/genetics , Fibroblast Growth Factors/genetics , Gene Expression Regulation , HEK293 Cells , Humans , Liver/pathology , Male , Mice , Mice, Transgenic , Polyubiquitin/genetics , Polyubiquitin/metabolism , Proteasome Endopeptidase Complex/genetics , Proteasome Endopeptidase Complex/metabolism , Proteolysis , Ubiquitin-Protein Ligases/genetics
2.
Environ Dev Sustain ; 24(4): 4623-4640, 2022.
Article in English | MEDLINE | ID: mdl-34230806

ABSTRACT

The current decade has witnessed the rise of empirical research in the domain of ecological footprint which has become a major scholarly area among environmental researchers. However, many key factors determining ecological footprint have been inadequately dealt within the existing body of knowledge. The current research aims to explore the association between economic complexity, human capital, renewable energy generation, urbanization, economic growth, export quality, trade and ecological footprint for the top ten economic complex countries. This study applied panel data estimators, for instance, fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS) and the system-GMM long-run estimators from 1980 to 2017. The long-run estimates reveal that economic complexity, economic growth, export quality, trade and urbanization increase ecological footprint. Human capital and renewable energy generation help to mitigate ecological footprint. We conclude that investment in more renewable energy generation and its consumption and efficient use of human capital will improve economic complexity, export quality, and environment in developed and developing countries.

3.
Waste Manag Res ; 40(6): 609-624, 2022 Jun.
Article in English | MEDLINE | ID: mdl-34269157

ABSTRACT

Population growth and the acceleration of urbanization have led to a sharp increase in municipal solid waste production, and researchers have sought to use advanced technology to solve this problem. Machine learning (ML) algorithms are good at modeling complex nonlinear processes and have been gradually adopted to promote municipal solid waste management (MSWM) and help the sustainable development of the environment in the past few years. In this study, more than 200 publications published over the last two decades (2000-2020) were reviewed and analyzed. This paper summarizes the application of ML algorithms in the whole process of MSWM, from waste generation to collection and transportation, to final disposal. Through this comprehensive review, the gaps and future directions of ML application in MSWM are discussed, providing theoretical and practical guidance for follow-up related research.


Subject(s)
Refuse Disposal , Waste Management , Algorithms , Cities , Machine Learning , Solid Waste
4.
Bull Environ Contam Toxicol ; 107(4): 585-596, 2021 Oct.
Article in English | MEDLINE | ID: mdl-33779775

ABSTRACT

Microplastics are abundant in the environment and have been proven to affect ecosystems and human health. Microorganisms play essential roles in the ecological fate of microplastics pollution, potentially yielding positive and negative effects. This study reviews the research progress of interaction between microplastics and microorganisms based on a bibliometric and visualized analysis. Publication numbers, subjects, countries, institutions, highly cited papers, and keywords were investigated by statistical analysis. VOSviewer software was applied to visualize the co-occurrence and aggregation of national collaboration, subjects, and keywords. Results revealed trends of rapidly increasing publication output that involved multiple disciplines. Contributing countries and their institutions were also identified in this study. Keywords, co-occurrence network visualization, highly cited papers analysis, and knowledge-based mining were all used to give insight into microorganisms or microbiota related to microplastics pollution, and the potential impacts that microplastics biodegradation may cause. In the future, research efforts need to focus on the following areas: microbial degradation processes and mechanisms, assessment of ecological microplastics risks, and potential effects of microplastics bioaccumulation and human exposure. This study provides a holistic view of ongoing microplastics and related microbial research, which may be useful for future microplastics biodegradation studies.


Subject(s)
Microbiota , Microplastics , Bibliometrics , Biodegradation, Environmental , Humans , Plastics
5.
Biochem Biophys Res Commun ; 463(4): 1115-21, 2015 Aug 07.
Article in English | MEDLINE | ID: mdl-26093295

ABSTRACT

miRNAs, sorting as non-coding RNAs, are differentially expressed in breast tumor and act as tumor promoters or suppressors. miR-206 could suppress the progression of breast cancer, the mechanism of which remains unclear. The study here was aimed to investigate the effect of miR-206 on human breast cancers. We found that miR-206 was down-regulated while one of its predicted targets, 6-Phosphofructo-2-kinase (PFKFB3) was up-regulated in human breast carcinomas. 17ß-estradiol dose-dependently decreased miR-206 expression as well as enhanced PFKFB3 mRNA and protein expression in estrogen receptor α (ERα) positive breast cancer cells. Furthermore, we identified that miR-206 directly interacted with 3'-untranslated region (UTR) of PFKFB3 mRNA. miR-206 modulated PFKFB3 expression in MCF-7, T47D and SUM159 cells, which was influenced by 17ß-estradiol depending on ERα expression. In addition, miR-206 overexpression impeded fructose-2,6-bisphosphate (F2,6BP) production, diminished lactate generation and reduced cell proliferation and migration in breast cancer cells. In conclusion, our study demonstrated that miR-206 regulated PFKFB3 expression in breast cancer cells, thereby stunting glycolysis, cell proliferation and migration.


Subject(s)
Cell Proliferation , Glycolysis , MicroRNAs/genetics , Neoplasm Metastasis , Phosphofructokinase-2/metabolism , Triple Negative Breast Neoplasms/pathology , Cell Line, Tumor , HEK293 Cells , Humans , Triple Negative Breast Neoplasms/metabolism
6.
Growth Horm IGF Res ; 55: 101341, 2020 12.
Article in English | MEDLINE | ID: mdl-32890915

ABSTRACT

OBJECTIVE: Insulin-like growth factor 1 (IGFI) is one of several growth factors which is induced by growth hormone (GH), which activates the Janus kinase 2 (JAK2)-signal transducer and activator of transcription 5 (STAT5) pathway, and plays crucial roles in normal human growth, metabolism, and systemic energy homeostasis. However, little is known about the negative regulation of IGF-I production under different physiological or pathological conditions. Herein, we explore whether activation of endoplasmic reticulum (ER) stress regulates IGF-I production and normal body growth. MATERIALS AND METHODS: C57BL/6 J mice were challenged with tunicamycin (Tm) to induce ER stress activation. 24 h after stimulation, hepatic mRNA expression was analyzed by RNA-Seq and validated by qPCR. Enzyme-linked immunosorbent assay (ELISA) was performed 24 h after Tm stimulation. Body growth was determined 16 days after Tm stimulation. Animals were then sacrificed and liver tissues were collected for further analysis. RESULTS: Mice challenged with Tm displayed a retardation of growth. Molecularly, we found that ER stress inhibited phosphorylation of STAT5. IGF-I transcription and circulating IGF-I were also dramatically decreased under ER stress activation. Moreover, our results demonstrate that IGF-I administration ameliorates Tm-induced growth retardation. CONCLUSIONS: ER stress induces growth retardation. ER stress inhibits hepatic GH-JAK2 signaling activation and its downstream target gene expression. These results warrant further research to explore the crosstalk between ER stress and growth hormone signaling in improving body growth.


Subject(s)
Endoplasmic Reticulum Stress , Growth Disorders/pathology , Growth Hormone/antagonists & inhibitors , Insulin-Like Growth Factor I/antagonists & inhibitors , Animals , Growth Disorders/etiology , Growth Disorders/metabolism , Male , Mice , Mice, Inbred C57BL
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