1.Participation of GATA-3 in regulation of bone healing through transcriptional upregulation of bcl-x(L) expression.
Mei Hsiu LIAO ; Pei I LIN ; Wei Pin HO ; Wing P CHAN ; Ta Liang CHEN ; Ruei Ming CHEN
Experimental & Molecular Medicine 2017;49(11):e398-
We have previously demonstrated the expression of GATA-DNA-binding protein (GATA)-3, a transcription factor, in osteoblasts and have verified its function in transducing cell survival signaling. This translational study was further designed to evaluate the roles of GATA-3 in regulating bone healing and to explore its possible mechanisms. A metaphyseal bone defect was created in the left femurs of male ICR mice. Analysis by micro-computed topography showed that the bone volume, trabecular bone number and trabecular thickness were augmented and that the trabecular pattern factor decreased. Interestingly, immunohistological analyses showed specific expression of GATA-3 in the defect area. In addition, colocalized expression of GATA-3 and alkaline phosphatase was observed at the wound site. As the fracture healed, the amounts of phosphorylated and non-phosphorylated GATA-3 concurrently increased. Separately, GATA-3 mRNA was induced during bone healing, and, levels of Runx2 mRNA and protein were also increased. The results of confocal microscopy and co-immunoprecipitation showed an association between nuclear GATA-3 and Runx2 in the area of insult. In parallel with fracture healing, Bcl-XL mRNA was significantly triggered. A bioinformatic search revealed the existence of a GATA-3-specific DNA-binding element in the promoter region of the bcl-x(L) gene. Analysis by chromatin immunoprecipitation assays further demonstrated transactivation activity by which GATA-3 regulated bcl-x(L) gene expression. Therefore, this study shows that GATA-3 participates in the healing of bone fractures via regulating bcl-xL gene expression, owing to its association with Runx2. In the clinic, GATA-3 may be used as a biomarker for diagnoses/prognoses or as a therapeutic target for bone diseases, such as bone fractures.
Alkaline Phosphatase
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Animals
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Bone Diseases
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Cell Survival
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Chromatin Immunoprecipitation
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Computational Biology
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Femur
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Fracture Healing
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Fractures, Bone
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Gene Expression
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Humans
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Immunoprecipitation
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Male
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Mice
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Mice, Inbred ICR
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Microscopy, Confocal
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Osteoblasts
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Promoter Regions, Genetic
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RNA, Messenger
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Transcription Factors
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Transcriptional Activation
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Up-Regulation*
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Wounds and Injuries
2.Sepsis, cardiovascular events and short-term mortality risk in critically ill patients.
Sharlene HO ; Hwee Pin PHUA ; Wei Yen LIM ; Niranjana MAHALINGAM ; Guan Hao Chester TAN ; Ser Hon PUAH ; Jin Wen Sennen LEW
Annals of the Academy of Medicine, Singapore 2022;51(5):272-282
INTRODUCTION:
There is paucity of data on the occurrence of cardiovascular events (CVEs) in critically ill patients with sepsis. We aimed to describe the incidence, risk factors and impact on mortality of CVEs in these patients.
METHODS:
This was a retrospective cohort study of critically ill patients admitted to the medical intensive care unit (ICU) between July 2015 and October 2016. The primary outcome was intra-hospital CVEs, while the secondary outcomes were in-hospital mortality, ICU and hospital length of stay.
RESULTS:
Patients with sepsis (n=662) had significantly more CVEs compared to those without (52.9% versus 23.0%, P<0.001). Among sepsis patients, 350 (52.9%) had 1 or more CVEs: 59 (8.9%) acute coronary syndrome; 198 (29.9%) type 2 myocardial infarction; 124 (18.7%) incident atrial fibrillation; 76 (11.5%) new or worsening heart failure; 32 (4.8%) cerebrovascular accident; and 33 (5.0%) cardiovascular death. Factors associated with an increased risk of CVEs (adjusted relative risk [95% confidence interval]) included age (1.013 [1.007-1.019]); ethnicity-Malay (1.214 [1.005-1.465]) and Indian (1.240 [1.030-1.494]) when compared to Chinese; and comorbidity of ischaemic heart disease (1.317 [1.137-1.527]). There were 278 patients (79.4%) who developed CVEs within the first week of hospitalisation. Sepsis patients with CVEs had a longer median (interquartile range [IQR]) length of stay in the ICU (6 [3-12] vs 4 [2-9] days, P<0.001), and hospital (21 [10-42] vs 15 [7-30] days, P<0.001) compared to sepsis patients without CVEs. There was no difference in in-hospital mortality between the 2 groups (46.9% vs 45.8%, P=0.792).
CONCLUSION
CVEs complicate half of the critically ill patients with sepsis, with 79.4% of patients developing CVEs within the first week of hospitalisation, resulting in longer ICU and hospital length of stay.
Cardiovascular Diseases/epidemiology*
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Critical Illness/epidemiology*
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Hospital Mortality
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Humans
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Intensive Care Units
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Length of Stay
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Retrospective Studies
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Risk Factors
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Sepsis/epidemiology*
3.Metformin and statins reduce hepatocellular carcinoma risk in chronic hepatitis C patients with failed antiviral therapy
Pei-Chien TSAI ; Chung-Feng HUANG ; Ming-Lun YEH ; Meng-Hsuan HSIEH ; Hsing-Tao KUO ; Chao-Hung HUNG ; Kuo-Chih TSENG ; Hsueh-Chou LAI ; Cheng-Yuan PENG ; Jing-Houng WANG ; Jyh-Jou CHEN ; Pei-Lun LEE ; Rong-Nan CHIEN ; Chi-Chieh YANG ; Gin-Ho LO ; Jia-Horng KAO ; Chun-Jen LIU ; Chen-Hua LIU ; Sheng-Lei YAN ; Chun-Yen LIN ; Wei-Wen SU ; Cheng-Hsin CHU ; Chih-Jen CHEN ; Shui-Yi TUNG ; Chi‐Ming TAI ; Chih-Wen LIN ; Ching-Chu LO ; Pin-Nan CHENG ; Yen-Cheng CHIU ; Chia-Chi WANG ; Jin-Shiung CHENG ; Wei-Lun TSAI ; Han-Chieh LIN ; Yi-Hsiang HUANG ; Chi-Yi CHEN ; Jee-Fu HUANG ; Chia-Yen DAI ; Wan-Long CHUNG ; Ming-Jong BAIR ; Ming-Lung YU ;
Clinical and Molecular Hepatology 2024;30(3):468-486
Background/Aims:
Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients.
Methods:
We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development.
Results:
Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients.
Conclusions
Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.