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Objective:To investigate the clinical application of multi-oil fat emulsion (SMOF) in preterm infants with necrotizing enterocolitis (NEC).Methods:Preterm infants with NEC admitted to the Neonatal Intensive Care Unit in our hospital between January 2017 and December 2022 were retrospectively included. According to the type of fat emulsion used, they were divided into SMOF group and medium and long chain triglycerides (MCT/LCT) group. The data of two groups were compared and analyzed.Results:A total of 69 preterm infants were included, 34 in the SMOF group and 35 in the MCT/LCT group. There were no significant differences between the two groups in the levels of total bilirubin, indirect bilirubin, direct bilirubin, bile acid and γ-glutamyl transferase ( P>0.05). There were no significant differences between the two groups in triglyceride, low density lipoprotein and total cholesterol ( P>0.05). There were no significant differences between the two groups in the C reactive protein level, procalcitonin level, and the time to normal C reactive protein ( P>0.05). There were no significant differences in incidence of complications between the two groups, including parenteral nutrition-related cholestasis, bronchopulmonary dysplasia, retinopathy of prematurity, and brain injury ( P>0.05). Conclusions:Compared with MCT/LCT, the application of SMOF did not show significant effect on liver function, inflammation, or incidence of complications (parenteral nutrition-related cholestasis, bronchopulmonary dysplasia and retinopathy of prematurity) in preterm infants with NEC. Multi-center studies with larger sample size are needed for further investigation.
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BackgroundCOVID-19 has been deeply affecting peoples lives all over the world. It is significant for prevention and control to model the evolution effectively and efficiently. MethodsWe first propose the multi-chain Fudan-CCDC model which is based on the original Fudan-CCDC model to describe the revival of COVID-19 in some countries. Multi-chains are considered as the superposition of distinctive single chains. Parameter identification is carried out by minimizing the penalty function. ResultsFrom results of numerical simulations, the multi-chain model performs well on data fitting and reasonably interprets the revival phenomena. The band of {+/-}25% fluctuation of simulation results could contain most seemly unsteady increments. ConclusionThe multi-chain model has better performance on data fitting in revival situations compared with the single-chain model. It is predicted by the three-chain model with data by Apr 21 that the epidemic curve of Iran would level off on round May 10, and the final cumulative confirmed cases would be around 88820. The upper bound of the 95% confidence interval would be around 96000.
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BackgroundCOVID-19 has been impacting on the whole world critically and constantly since late December 2019. Rapidly increasing infections has raised intense world-wide attention. How to model the evolution of COVID-19 effectively and efficiently is of great significance for prevention and control. MethodsWe propose the multi-chain Fudan-CCDC model based on the original single-chain model in [8] to describe the evolution of COVID-19 in Singapore. Multi-chains can be considered as the superposition of several single chains with different characteristics. We identify parameters of models by minimizing the penalty function. ResultsThe numerical simulation results exhibit the multichain model performs well on data fitting. Though unsteady the increments are, they could still fall within the range of {+/-}25% fluctuation from simulation results. It is predicted by multi-chain models that Singapore are experiencing a nonnegligible risk of explosive outbreak, thus stronger measures are urgently needed to contain the epidemic. ConclusionThe multi-chain Fudan-CCDC model provides an effective way to early detect the appearance of imported infectors and super spreaders and forecast a second outbreak. It can also explain the data in those countries where the single-chain model shows deviation from the data.
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COVID-19 has been impacting on the whole world critically and constantly Since December 2019. We have independently developed a novel statistical time delay dynamic model on the basis of the distribution models from CCDC. Based only on the numbers of confirmed cases in different regions in China, the model can clearly reveal that the containment of the epidemic highly depends on early and effective isolation. We apply the model on the epidemic in Japan and conclude that there could be a rapid outbreak in Japan if no effective quarantine measures are carried out immediately.
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As one of the main members of the Rho GDI dissociation inhibitory factors,D4-GDI inhibits the dissociation of Rho protein and GDP,which is also involved in a wide range of celluar functions,such as cell contraction,adhesion,migration,proliferation and apoptosis.Recently,accumulating evidence has been suggested that D4-GDI is involved in the pathogenesis of several pulmonary diseases,such as lung cancer.Intervention of D4-GDI expression may improve the pathological changes and prognosis of these diseases.
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Objective Collecting the loosening periprosthetic interface-membrane, to discuss the mechanism of hip arthroplasty loosening. Methods The periprosthetic interface tissues of 29 hip arthroplasty revision cases from February 1995 to December 2003 were collected. The retrieved periprosthetic interface tissues were detected by immunohistochemistry. Some of them were studied by electronic microscope. Results (1)Transmission electronic microscope examination: the mitochondria swell. There were some substantia like lipid in the plasm of macrophages. Wear particles could be seen under scaning electronic microscope.(2)Immunohistochemistry: there were 22 IL-1? positive cases in cells of interface membrane. There were 29 IL-6 positive cases in cells of interface membrane. There were no positive results in TNF-? test. Conclusion (1)The wear particles of arthroplasty are important factors which cause biological reaction.(2)The interface membranes contain cytokine IL-1? and IL-6, which may play an important role in periprosthetic osteolysis and arthroplasty loosening.