CK1α protects cardiomyocytes in sepsis-induced myocardial depression by repressing the interaction of ATG5 with myD88/NF-kappaB signaling

Purpose: To explore the effects of casein kinase 1α (CK1α) on cardiomyocytes in sepsis-induced myocardial depression.Methods: Colorectal ligation puncture (CLP) surgery was performed for the establishment of the mouse model. Total RNAs of the lungs, kidneys, liver tissues and alveolar macrophages were extracted using TRIzol™ reagent, while gene expression analysis was performed by quantitative polymerase chain reaction (qPCR) following reverse transcription. Western blot was employed to evaluate protein expression, and echocardiography was conducted to assess cardiac function. Immunofluorescent assay was performed to determine the expression of p-FOXO3a in primary cardiomyocytes.Results: Inhibition of CK1α impaired autophagy influx, and significantly increased inflammatory cytokines in H9C2 cells after lipopolysaccharide (LPS) treatment (p < 0.05). Moreover, aberrant activation of the Toll-like receptor 4(TLR4)/myD88/NF-kappaB pathway was observed in the H9C2 cell line after LPS treatment (p < 0.05). Immunoprecipitation analysis revealed an interaction between MyD88 and autophagy-related gene 5 (Atg5), and cardiac dysfunction in mice intravenously injectedwith an adenoviral vector containing shRNA (casein kinase 1 α) CSNK1A1 was suppressed (p < 0.05). In contrast, overexpression of CK1α remarkably improved cardiac systolic function (p < 0.05), the expression of inflammatory cytokines was repressed, and autophagy was enhanced in the hearts of mice with the specific overexpression of CSNK1A1 in cardiomyocytes (p < 0.05). In Atg5-deficient mice pretreated with DC661, the protective effect of adenoviral vector containing CK1α overexpression was eliminated.Conclusion: CK1α protects cardiomyocytes during sepsis after the inhibition of TLR/MyD88/NF-kappaBpathway via interaction of Atg5 with MyD88. The results of the current study may provide new insights into the treatment of sepsis-induced myocardial depression

Microbial community analysis in biocathode microbial fuel cells packed with different materials

Biocathode MFCs using microorganisms as catalysts have important advantages in lowering cost and improving sustainability. Electrode materials and microbial synergy determines biocathode MFCs performance. In this study, four materials, granular activated carbon (GAC), granular semicoke (GS), granular graphite (GG) and carbon felt cube (CFC) were used as packed cathodic materials. The microbial composition on each material and its correlation with the electricity generation performance of MFCs were investigated. Results showed that different biocathode materials had an important effect on the type of microbial species in biocathode MFCs. The microbes belonging to Bacteroidetes and Proteobacteria were the dominant phyla in the four materials packed biocathode MFCs. Comamonas of Betaproteobacteria might play significant roles in electron transfer process of GAC, GS and CFC packed biocathode MFCs, while in GG packed MFC Acidovorax may be correlated with power generation. The biocathode materials also had influence on the microbial diversity and evenness, but the differences in them were not positively related to the power production

The adverse effect of gestational diabetes mellitus and hypertensive disorders of pregnancy on maternal–perinatal outcomes among singleton and twin pregnancies:A retrospective cohort study (2011–2019)

Background: Gestational diabetes mellitus (GDM) and hypertensive disorders of pregnancy (HDP) are the predominant pregnancy complications among singleton and twin pregnancies worldwide. Our primary objective was to explore the adverse effect of GDM and HDP on maternal–perinatal outcomes compared with non-GDM and non-HDP in singleton and twin pregnancies. The secondary objective was to find the risk of adverse maternal–perinatal outcomes in twin pregnancies compared with singleton pregnancies complicated with GDM and HDP in Hubei, China. Methods: A tertiary hospital-based retrospective study was conducted at Wuhan University Renmin Hospital, Hubei Province, China, from 2011 to 2019. A chi-square test was used to determine the difference in adverse maternal–perinatal outcomes between singleton and twin pregnancies. A multiple binary logistic regression model and a joinpoint regression model were used to determine the association of GDM and HDP with adverse maternal–perinatal outcomes and GDM and HDP temporal trend among singleton and twin pregnancies. Results: The trend of HDP [average annual percentage change (AAPC) 15.1% (95% confidence interval (95%CI): 5.3, 25.7)] among singleton pregnancies and GDM [AAPC 50.4% (95%CI: 19.9, 88.7)] among twin pregnancies significantly increased from 2011 to 2019. After adjusting for confounding factors, GDM is associated with an increased risk of C-section (adjusted odds ratio (aOR), 1.5; 95%CI: 1.3, 1.6) and macrosomia (aOR, 1.3; 95%CI: 1.1, 1.6) in singleton and preterm birth (PTB) (aOR, 2.1; 95%CI: 1.2, 3.3) in twin pregnancies compared with non-GDM. HDP was associated with a higher risk of C-section, PTB, perinatal mortality, and low birth weight (LBW) in both singleton and twin pregnancies compared with the non-HDP. Compared with singleton pregnancies complicated with GDM and HDP, twin pregnancies showed higher odds of C-section [(aOR, 1.7; 95%CI: 1.1, 2.7), (aOR, 4.6; 95%CI: 2.5, 8.7), respectively], PTB [(aOR, 22.9; 95%CI: 14.1, 37.3), (aOR, 8.1; 95%CI: 5.3, 12.3), respectively], LBW [(aOR, 12.1; 95%CI: 8.2, 18.1), (aOR, 5.1; 95%CI: 3.6, 7.4), respectively], and low Apgar score [(aOR, 8.2; 95%CI: 4.4, 15.1), (aOR, 3.8; 95%CI: 2.4, 5.8), respectively] complicated with GDM and HDP. Conclusion: In conclusion, GDM showed an increased risk of a few adverse maternal–perinatal outcomes and HDP is associated with a higher risk of several adverse maternal–perinatal outcomes in singleton and twin pregnancies compared to non-GDM and non-HDP. Moreover, twin pregnancies complicated with GDM and HDP showed higher odds of adverse maternal–neonatal outcomes compared with singleton pregnancies complicated with GDM and HDP.</p

The adverse effect of gestational diabetes mellitus and hypertensive disorders of pregnancy on maternal–perinatal outcomes among singleton and twin pregnancies:A retrospective cohort study (2011–2019)

Background: Gestational diabetes mellitus (GDM) and hypertensive disorders of pregnancy (HDP) are the predominant pregnancy complications among singleton and twin pregnancies worldwide. Our primary objective was to explore the adverse effect of GDM and HDP on maternal–perinatal outcomes compared with non-GDM and non-HDP in singleton and twin pregnancies. The secondary objective was to find the risk of adverse maternal–perinatal outcomes in twin pregnancies compared with singleton pregnancies complicated with GDM and HDP in Hubei, China. Methods: A tertiary hospital-based retrospective study was conducted at Wuhan University Renmin Hospital, Hubei Province, China, from 2011 to 2019. A chi-square test was used to determine the difference in adverse maternal–perinatal outcomes between singleton and twin pregnancies. A multiple binary logistic regression model and a joinpoint regression model were used to determine the association of GDM and HDP with adverse maternal–perinatal outcomes and GDM and HDP temporal trend among singleton and twin pregnancies. Results: The trend of HDP [average annual percentage change (AAPC) 15.1% (95% confidence interval (95%CI): 5.3, 25.7)] among singleton pregnancies and GDM [AAPC 50.4% (95%CI: 19.9, 88.7)] among twin pregnancies significantly increased from 2011 to 2019. After adjusting for confounding factors, GDM is associated with an increased risk of C-section (adjusted odds ratio (aOR), 1.5; 95%CI: 1.3, 1.6) and macrosomia (aOR, 1.3; 95%CI: 1.1, 1.6) in singleton and preterm birth (PTB) (aOR, 2.1; 95%CI: 1.2, 3.3) in twin pregnancies compared with non-GDM. HDP was associated with a higher risk of C-section, PTB, perinatal mortality, and low birth weight (LBW) in both singleton and twin pregnancies compared with the non-HDP. Compared with singleton pregnancies complicated with GDM and HDP, twin pregnancies showed higher odds of C-section [(aOR, 1.7; 95%CI: 1.1, 2.7), (aOR, 4.6; 95%CI: 2.5, 8.7), respectively], PTB [(aOR, 22.9; 95%CI: 14.1, 37.3), (aOR, 8.1; 95%CI: 5.3, 12.3), respectively], LBW [(aOR, 12.1; 95%CI: 8.2, 18.1), (aOR, 5.1; 95%CI: 3.6, 7.4), respectively], and low Apgar score [(aOR, 8.2; 95%CI: 4.4, 15.1), (aOR, 3.8; 95%CI: 2.4, 5.8), respectively] complicated with GDM and HDP. Conclusion: In conclusion, GDM showed an increased risk of a few adverse maternal–perinatal outcomes and HDP is associated with a higher risk of several adverse maternal–perinatal outcomes in singleton and twin pregnancies compared to non-GDM and non-HDP. Moreover, twin pregnancies complicated with GDM and HDP showed higher odds of adverse maternal–neonatal outcomes compared with singleton pregnancies complicated with GDM and HDP.</p

The adverse effect of gestational diabetes mellitus and hypertensive disorders of pregnancy on maternal–perinatal outcomes among singleton and twin pregnancies:A retrospective cohort study (2011–2019)

Background: Gestational diabetes mellitus (GDM) and hypertensive disorders of pregnancy (HDP) are the predominant pregnancy complications among singleton and twin pregnancies worldwide. Our primary objective was to explore the adverse effect of GDM and HDP on maternal–perinatal outcomes compared with non-GDM and non-HDP in singleton and twin pregnancies. The secondary objective was to find the risk of adverse maternal–perinatal outcomes in twin pregnancies compared with singleton pregnancies complicated with GDM and HDP in Hubei, China. Methods: A tertiary hospital-based retrospective study was conducted at Wuhan University Renmin Hospital, Hubei Province, China, from 2011 to 2019. A chi-square test was used to determine the difference in adverse maternal–perinatal outcomes between singleton and twin pregnancies. A multiple binary logistic regression model and a joinpoint regression model were used to determine the association of GDM and HDP with adverse maternal–perinatal outcomes and GDM and HDP temporal trend among singleton and twin pregnancies. Results: The trend of HDP [average annual percentage change (AAPC) 15.1% (95% confidence interval (95%CI): 5.3, 25.7)] among singleton pregnancies and GDM [AAPC 50.4% (95%CI: 19.9, 88.7)] among twin pregnancies significantly increased from 2011 to 2019. After adjusting for confounding factors, GDM is associated with an increased risk of C-section (adjusted odds ratio (aOR), 1.5; 95%CI: 1.3, 1.6) and macrosomia (aOR, 1.3; 95%CI: 1.1, 1.6) in singleton and preterm birth (PTB) (aOR, 2.1; 95%CI: 1.2, 3.3) in twin pregnancies compared with non-GDM. HDP was associated with a higher risk of C-section, PTB, perinatal mortality, and low birth weight (LBW) in both singleton and twin pregnancies compared with the non-HDP. Compared with singleton pregnancies complicated with GDM and HDP, twin pregnancies showed higher odds of C-section [(aOR, 1.7; 95%CI: 1.1, 2.7), (aOR, 4.6; 95%CI: 2.5, 8.7), respectively], PTB [(aOR, 22.9; 95%CI: 14.1, 37.3), (aOR, 8.1; 95%CI: 5.3, 12.3), respectively], LBW [(aOR, 12.1; 95%CI: 8.2, 18.1), (aOR, 5.1; 95%CI: 3.6, 7.4), respectively], and low Apgar score [(aOR, 8.2; 95%CI: 4.4, 15.1), (aOR, 3.8; 95%CI: 2.4, 5.8), respectively] complicated with GDM and HDP. Conclusion: In conclusion, GDM showed an increased risk of a few adverse maternal–perinatal outcomes and HDP is associated with a higher risk of several adverse maternal–perinatal outcomes in singleton and twin pregnancies compared to non-GDM and non-HDP. Moreover, twin pregnancies complicated with GDM and HDP showed higher odds of adverse maternal–neonatal outcomes compared with singleton pregnancies complicated with GDM and HDP.</p

The adverse effect of gestational diabetes mellitus and hypertensive disorders of pregnancy on maternal–perinatal outcomes among singleton and twin pregnancies:A retrospective cohort study (2011–2019)

Background: Gestational diabetes mellitus (GDM) and hypertensive disorders of pregnancy (HDP) are the predominant pregnancy complications among singleton and twin pregnancies worldwide. Our primary objective was to explore the adverse effect of GDM and HDP on maternal–perinatal outcomes compared with non-GDM and non-HDP in singleton and twin pregnancies. The secondary objective was to find the risk of adverse maternal–perinatal outcomes in twin pregnancies compared with singleton pregnancies complicated with GDM and HDP in Hubei, China. Methods: A tertiary hospital-based retrospective study was conducted at Wuhan University Renmin Hospital, Hubei Province, China, from 2011 to 2019. A chi-square test was used to determine the difference in adverse maternal–perinatal outcomes between singleton and twin pregnancies. A multiple binary logistic regression model and a joinpoint regression model were used to determine the association of GDM and HDP with adverse maternal–perinatal outcomes and GDM and HDP temporal trend among singleton and twin pregnancies. Results: The trend of HDP [average annual percentage change (AAPC) 15.1% (95% confidence interval (95%CI): 5.3, 25.7)] among singleton pregnancies and GDM [AAPC 50.4% (95%CI: 19.9, 88.7)] among twin pregnancies significantly increased from 2011 to 2019. After adjusting for confounding factors, GDM is associated with an increased risk of C-section (adjusted odds ratio (aOR), 1.5; 95%CI: 1.3, 1.6) and macrosomia (aOR, 1.3; 95%CI: 1.1, 1.6) in singleton and preterm birth (PTB) (aOR, 2.1; 95%CI: 1.2, 3.3) in twin pregnancies compared with non-GDM. HDP was associated with a higher risk of C-section, PTB, perinatal mortality, and low birth weight (LBW) in both singleton and twin pregnancies compared with the non-HDP. Compared with singleton pregnancies complicated with GDM and HDP, twin pregnancies showed higher odds of C-section [(aOR, 1.7; 95%CI: 1.1, 2.7), (aOR, 4.6; 95%CI: 2.5, 8.7), respectively], PTB [(aOR, 22.9; 95%CI: 14.1, 37.3), (aOR, 8.1; 95%CI: 5.3, 12.3), respectively], LBW [(aOR, 12.1; 95%CI: 8.2, 18.1), (aOR, 5.1; 95%CI: 3.6, 7.4), respectively], and low Apgar score [(aOR, 8.2; 95%CI: 4.4, 15.1), (aOR, 3.8; 95%CI: 2.4, 5.8), respectively] complicated with GDM and HDP. Conclusion: In conclusion, GDM showed an increased risk of a few adverse maternal–perinatal outcomes and HDP is associated with a higher risk of several adverse maternal–perinatal outcomes in singleton and twin pregnancies compared to non-GDM and non-HDP. Moreover, twin pregnancies complicated with GDM and HDP showed higher odds of adverse maternal–neonatal outcomes compared with singleton pregnancies complicated with GDM and HDP.</p

The adverse effect of gestational diabetes mellitus and hypertensive disorders of pregnancy on maternal–perinatal outcomes among singleton and twin pregnancies:A retrospective cohort study (2011–2019)

Background: Gestational diabetes mellitus (GDM) and hypertensive disorders of pregnancy (HDP) are the predominant pregnancy complications among singleton and twin pregnancies worldwide. Our primary objective was to explore the adverse effect of GDM and HDP on maternal–perinatal outcomes compared with non-GDM and non-HDP in singleton and twin pregnancies. The secondary objective was to find the risk of adverse maternal–perinatal outcomes in twin pregnancies compared with singleton pregnancies complicated with GDM and HDP in Hubei, China. Methods: A tertiary hospital-based retrospective study was conducted at Wuhan University Renmin Hospital, Hubei Province, China, from 2011 to 2019. A chi-square test was used to determine the difference in adverse maternal–perinatal outcomes between singleton and twin pregnancies. A multiple binary logistic regression model and a joinpoint regression model were used to determine the association of GDM and HDP with adverse maternal–perinatal outcomes and GDM and HDP temporal trend among singleton and twin pregnancies. Results: The trend of HDP [average annual percentage change (AAPC) 15.1% (95% confidence interval (95%CI): 5.3, 25.7)] among singleton pregnancies and GDM [AAPC 50.4% (95%CI: 19.9, 88.7)] among twin pregnancies significantly increased from 2011 to 2019. After adjusting for confounding factors, GDM is associated with an increased risk of C-section (adjusted odds ratio (aOR), 1.5; 95%CI: 1.3, 1.6) and macrosomia (aOR, 1.3; 95%CI: 1.1, 1.6) in singleton and preterm birth (PTB) (aOR, 2.1; 95%CI: 1.2, 3.3) in twin pregnancies compared with non-GDM. HDP was associated with a higher risk of C-section, PTB, perinatal mortality, and low birth weight (LBW) in both singleton and twin pregnancies compared with the non-HDP. Compared with singleton pregnancies complicated with GDM and HDP, twin pregnancies showed higher odds of C-section [(aOR, 1.7; 95%CI: 1.1, 2.7), (aOR, 4.6; 95%CI: 2.5, 8.7), respectively], PTB [(aOR, 22.9; 95%CI: 14.1, 37.3), (aOR, 8.1; 95%CI: 5.3, 12.3), respectively], LBW [(aOR, 12.1; 95%CI: 8.2, 18.1), (aOR, 5.1; 95%CI: 3.6, 7.4), respectively], and low Apgar score [(aOR, 8.2; 95%CI: 4.4, 15.1), (aOR, 3.8; 95%CI: 2.4, 5.8), respectively] complicated with GDM and HDP. Conclusion: In conclusion, GDM showed an increased risk of a few adverse maternal–perinatal outcomes and HDP is associated with a higher risk of several adverse maternal–perinatal outcomes in singleton and twin pregnancies compared to non-GDM and non-HDP. Moreover, twin pregnancies complicated with GDM and HDP showed higher odds of adverse maternal–neonatal outcomes compared with singleton pregnancies complicated with GDM and HDP.</p

Deep Learning based 3D Segmentation: A Survey

3D object segmentation is a fundamental and challenging problem in computer vision with applications in autonomous driving, robotics, augmented reality and medical image analysis. It has received significant attention from the computer vision, graphics and machine learning communities. Traditionally, 3D segmentation was performed with hand-crafted features and engineered methods which failed to achieve acceptable accuracy and could not generalize to large-scale data. Driven by their great success in 2D computer vision, deep learning techniques have recently become the tool of choice for 3D segmentation tasks as well. This has led to an influx of a large number of methods in the literature that have been evaluated on different benchmark datasets. This paper provides a comprehensive survey of recent progress in deep learning based 3D segmentation covering over 150 papers. It summarizes the most commonly used pipelines, discusses their highlights and shortcomings, and analyzes the competitive results of these segmentation methods. Based on the analysis, it also provides promising research directions for the future.Comment: Under review of ACM Computing Surveys, 36 pages, 10 tables, 9 figure