1.Mitochondria derived from human embryonic stem cell-derived mesenchymal stem cells alleviate the inflammatory response in human gingival fibroblasts.
Bicong GAO ; Chenlu SHEN ; Kejia LV ; Xuehui LI ; Yongting ZHANG ; Fan SHI ; Hongyan DIAO ; Hua YAO
Journal of Zhejiang University. Science. B 2025;26(8):778-788
Periodontitis is a common oral disease caused by bacteria coupled with an excessive host immune response. Stem cell therapy can be a promising treatment strategy for periodontitis, but the relevant mechanism is complicated. This study aimed to explore the therapeutic potential of mitochondria from human embryonic stem cell-derived mesenchymal stem cells (hESC-MSCs) for the treatment of periodontitis. The gingival tissues of periodontitis patients are characterized by abnormal mitochondrial structure. Human gingival fibroblasts (HGFs) were exposed to 5 μg/mL lipopolysaccharide (LPS) for 24 h to establish a cell injury model. When treated with hESC-MSCs or mitochondria derived from hESC-MSCs, HGFs showed reduced expression of inflammatory genes, increased adenosine triphosphate (ATP) level, decreased reactive oxygen species (ROS) production, and enhanced mitochondrial function compared to the control. The average efficiency of isolated mitochondrial transfer by hESC-MSCs was determined to be 8.93%. Besides, a therapy of local mitochondrial injection in mice with LPS-induced periodontitis showed a reduction in inflammatory gene expression, as well as an increase in both the mitochondrial number and the aspect ratio in gingival tissues. In conclusion, our results indicate that mitochondria derived from hESC-MSCs can reduce the inflammatory response and improve mitochondrial function in HGFs, suggesting that the transfer of mitochondria between hESC-MSCs and HGFs serves as a potential mechanism underlying the therapeutic effect of stem cells.
Humans
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Gingiva/cytology*
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Fibroblasts/metabolism*
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Mitochondria/physiology*
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Mesenchymal Stem Cells/cytology*
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Animals
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Periodontitis/therapy*
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Mice
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Reactive Oxygen Species/metabolism*
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Inflammation
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Lipopolysaccharides
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Human Embryonic Stem Cells/cytology*
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Cells, Cultured
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Adenosine Triphosphate/metabolism*
;
Male
2.pH-sensitive and bubble-generating mesoporous silica-based nanoparticles for enhanced tumor combination therapy.
Zhiming ZHANG ; Chenlu HUANG ; Li ZHANG ; Qing GUO ; Yu QIN ; Fan FAN ; Boxuan LI ; Bao XIAO ; Dunwan ZHU ; Linhua ZHANG
Acta Pharmaceutica Sinica B 2021;11(2):520-533
Chemotherapy has been a major option in clinic treatment of malignant tumors. However, single chemotherapy faces some drawbacks, such as multidrug resistance, severe side effects, which hinder its clinic application in tumor treatment. Multifunctional nanoparticles loading with chemotherapeutic agent and photosensitizer could be a promising way to efficiently conduct tumor combination therapy. In the current study, a novel pH-sensitive and bubble-generating mesoporous silica-based drug delivery system (denoted as M(a)D@PI-PEG-RGD) was constructed. Ammonium bicarbonate (NH
3.Analysis of urinary arsenic metabolism model and influencing factors of people chronic exposed to arsenic through drinking water
Jian WANG ; Chenlu FAN ; Qun LOU ; Meichen ZHANG ; Fanshuo YIN ; Zaihong ZHANG ; Xin ZHANG ; Yanmei YANG ; Yanhui GAO
Chinese Journal of Endemiology 2021;40(4):268-272
Objective:Through determination of urinary arsenic metabolites in high water arsenic exposed areas of Jilin and Shanxi provinces, to explore the mode and possible influencing factors of arsenic metabolism in different populations.Methods:From October 2018 to August 2019, a cluster sampling was carried out in villages (arsenic in drinking water ≥0.05 mg/L) of some townships (towns) in Lyuliang City, Shanxi Province and Baicheng City, Jilin Province for epidemiological investigation and general health examination. The residents over 35 years old drinking water from local centralized water supply and small well water sources were selected as arsenic exposure group, and people (nearby low-arsenic water source areas) with the same diet and living habits and similar economic conditions were selected as control group. Urine samples were collected. Liquid chromatography-atomic fluorescence spectrometry(LC-AFS) technology was used to separate and detect 4 species of arsenic compounds, including trivalent inorganic arsenic (iAs Ⅲ), pentavalent inorganic arsenic (iAs Ⅴ), methylated arsine (MMA), and dimethylated arsine (DMA). Total arsenic (tAs), inorganic arsenic percentage (iAs%), MMA percentage (MMA%), DMA percentage (DMA%), primary methylation index (PMI) and the secondary methylation index (SMI) were calculated. The influencing factors of arsenic metabolism were analyzed by multiple linear regression. Results:A total of 1 415 villagers were investigated, including 1 256 in arsenic exposure group and 159 in control group. Compared with the control group, there were no significant differences in age, gender ratio and occupation distribution between arsenic exposure group and control group ( P > 0.05), but there were significant differences in smoking, drinking, body mass index (BMI) and education level distribution ( P < 0.05). The median of urinary tAs, iAs%, MMA%, DMA%, PMI and SMI in control group and arsenic exposure group were 12.86 μg/L, 15.03, 5.23, 76.35, 84.97, 93.68 and 69.68 μg/L, 10.24, 8.37, 79.31, 89.76, 90.65, respectively, the levels of urinary tAs, DMA% and PMI in arsenic exposed group were higher than those in control group, while iAs% and SMI were lower than those in control group, the differences were statistically significant ( U=- 13.87, - 4.30, - 6.64, - 6.64, - 1.99, P < 0.05). After analysis of the factors influencing urinary arsenic metabolism in the population, we found that age and BMI had an impact on iAs% ( β=- 0.08, - 0.08, P < 0.05); gender, drinking, BMI and education level were influencing factors of MMA% ( β =- 0.11, - 0.09, - 0.07, 0.08, P < 0.05); DMA% was mainly affected by age, gender, BMI and education level ( β = 0.06, 0.09, 0.10, - 0.09, P < 0.05); PMI was mainly affected by age and BMI ( β = 0.08, 0.08, P < 0.05); while SMI was affected by gender, drinking, BMI and education level ( β=0.09, 0.08, 0.08, - 0.09, P < 0.05). Conclusions:The urinary arsenic metabolism models of different arsenic exposed groups are different. Age, gender, smoking, drinking, BMI and education level may be influencing factors of different arsenic metabolism models.

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