Extracellular Vesicles from Adipose-Derived Stem Cells Promote Diabetic Wound Healing via the PI3K-AKT-mTOR-HIF-1α Signaling Pathway

Liu Wenjian,Yuan Yu,Liu Dewu 한국조직공학과 재생의학회 2021 조직공학과 재생의학 Vol.18 No.6

Background: Impaired potential of hypoxia-mediated angiogenesis lead poor healing of diabetic wounds. Previous studies have shown that extracellular vesicles from adipose derived stem cells (ADSC-EVs) accelerate wound healing with unelucidated mechanism. However, it is not yet clear about the underlying mechanism of ADSC-EVs in regulating the hypoxia-related PI3K/AKT/mTOR signaling pathway of vascular endothelial cells in diabetic wounds. Therefore, in this study, human derived ADSC-EVs (hADSC-EVs) isolated from adipose tissue were co-cultured with advanced glycosylation end product (AGE) treated human umbilical vein endothelial cells (HUVECs) in vitro and local injected into the wounds of diabetic rats. Methods: In vitro, the therapeutic potential of hADSC-EVs on AGE-treated HUVECs was evaluated by cell counting kit-8, scratching, and tube formation assay. Subsequently, the effects of hADSC-EVs on the PI3K/AKT/mTOR/HIF-1α signaling pathway were also assayed by qRT-PCR and western blot. In vivo, the effect of hADSC-EVs on diabetic wound healing in rats were also assayed by closure kinetics, Masson staining and HIF-1α-CD31 immunofluorescence. Results: hADSC-EVs were spherical in shape with an average particle size of 198.1 ± 91.5 nm, and were positive for CD63, CD9 and TSG101. hADSC-EVs promoted the expression of PI3K-AKT-mTOR-HIF-1α signaling pathway of AGEs treated HUVECs with improved the potential of proliferation, migration and tube formation, and improve the healing and angiogenesis of diabetic wound in rats. However, the effect of hADSC-EVs described above can be blocked by PI3K-AKT inhibitor both in vitro and vivo. Conclusion: Our findings indicated that hADSC-EVs accolated the healing of diabetic wounds by promoting HIF-1α-mediated angiogenesis in the PI3K-AKT-mTOR depend manner. Background: Impaired potential of hypoxia-mediated angiogenesis lead poor healing of diabetic wounds. Previous studies have shown that extracellular vesicles from adipose derived stem cells (ADSC-EVs) accelerate wound healing with unelucidated mechanism. However, it is not yet clear about the underlying mechanism of ADSC-EVs in regulating the hypoxia-related PI3K/AKT/mTOR signaling pathway of vascular endothelial cells in diabetic wounds. Therefore, in this study, human derived ADSC-EVs (hADSC-EVs) isolated from adipose tissue were co-cultured with advanced glycosylation end product (AGE) treated human umbilical vein endothelial cells (HUVECs) in vitro and local injected into the wounds of diabetic rats. Methods: In vitro, the therapeutic potential of hADSC-EVs on AGE-treated HUVECs was evaluated by cell counting kit-8, scratching, and tube formation assay. Subsequently, the effects of hADSC-EVs on the PI3K/AKT/mTOR/HIF-1α signaling pathway were also assayed by qRT-PCR and western blot. In vivo, the effect of hADSC-EVs on diabetic wound healing in rats were also assayed by closure kinetics, Masson staining and HIF-1α-CD31 immunofluorescence. Results: hADSC-EVs were spherical in shape with an average particle size of 198.1 ± 91.5 nm, and were positive for CD63, CD9 and TSG101. hADSC-EVs promoted the expression of PI3K-AKT-mTOR-HIF-1α signaling pathway of AGEs treated HUVECs with improved the potential of proliferation, migration and tube formation, and improve the healing and angiogenesis of diabetic wound in rats. However, the effect of hADSC-EVs described above can be blocked by PI3K-AKT inhibitor both in vitro and vivo. Conclusion: Our findings indicated that hADSC-EVs accolated the healing of diabetic wounds by promoting HIF-1α-mediated angiogenesis in the PI3K-AKT-mTOR depend manner.

Use of deep learning in nano image processing through the CNN model

Xing, Lumin,Liu, Wenjian,Liu, Xiaoliang,Li, Xin,Wang, Han Techno-Press 2022 Advances in nano research Vol.12 No.2

Deep learning is another field of artificial intelligence (AI) utilized for computer aided diagnosis (CAD) and image processing in scientific research. Considering numerous mechanical repetitive tasks, reading image slices need time and improper with geographical limits, so the counting of image information is hard due to its strong subjectivity that raise the error ratio in misdiagnosis. Regarding the highest mortality rate of Lung cancer, there is a need for biopsy for determining its class for additional treatment. Deep learning has recently given strong tools in diagnose of lung cancer and making therapeutic regimen. However, identifying the pathological lung cancer's class by CT images in beginning phase because of the absence of powerful AI models and public training data set is difficult. Convolutional Neural Network (CNN) was proposed with its essential function in recognizing the pathological CT images. 472 patients subjected to staging FDG-PET/CT were selected in 2 months prior to surgery or biopsy. CNN was developed and showed the accuracy of 87%, 69%, and 69% in training, validation, and test sets, respectively, for T1-T2 and T3-T4 lung cancer classification. Subsequently, CNN (or deep learning) could improve the CT images' data set, indicating that the application of classifiers is adequate to accomplish better exactness in distinguishing pathological CT images that performs better than few deep learning models, such as ResNet-34, Alex Net, and Dense Net with or without Soft max weights.

Application of machine learning and deep neural network for wave propagation in lung cancer cell

Xing, Lumin,Liu, Wenjian,Li, Xin,Wang, Han,Jiang, Zhiming,Wang, Lingling Techno-Press 2022 Advances in nano research Vol.13 No.3

Coughing and breath shortness are common symptoms of nano (small) cell lung cancer. Smoking is main factor in causing such cancers. The cancer cells form on the soft tissues of lung. Deformation behavior and wave vibration of lung affected when cancer cells exist. Therefore, in the current work, phase velocity behavior of the small cell lung cancer as a main part of the body via an exact size-dependent theory is presented. Regarding this problem, displacement fields of small cell lung cancer are obtained using first-order shear deformation theory with five parameters. Besides, the size-dependent small cell lung cancer is modeled via nonlocal stress/strain gradient theory (NSGT). An analytical method is applied for solving the governing equations of the small cell lung cancer structure. The novelty of the current study is the consideration of the five-parameter of displacement for curved panel, and porosity as well as NSGT are employed and solved using the analytical method. For more verification, the outcomes of this reports are compared with the predictions of deep neural network (DNN) with adaptive optimization method. A thorough parametric investigation is conducted on the effect of NSGT parameters, porosity and geometry on the phase velocity behavior of the small cell lung cancer structure.

Screening of Antagonistic Bacillus against Brown Rot in Dendrocalamus latiflorus and Preparation of Applying Bacterial Suspension

Fengying Luo,Hang Chen,Wenjian Wei,Han Liu,Youzhong Chen,Shujiang Li 한국식물병리학회 2024 Plant Pathology Journal Vol.40 No.1

The aim of this study was to isolate biocontrol bacteria that could antagonize brown rot of <i>Dendrocalamus latiflorus</i>, optimize the culture conditions, and develop an effective biocontrol preparation for brown rot of <i>D. latiflorus</i>. This study isolated a bacterium with an antagonistic effect on bamboo brown rot from healthy <i>D. latiflorus</i> rhizosphere soil. Morphology, molecular biology, and physiological biochemistry methods identified it as <i>Bacillus siamensis</i>. The following culturing media and conditions improved the inhibition effect of <i>B. siamensis</i>: the best culturing media were 2% sucrose, 1.5% yeast extract, and 0.7% potassium chloride; the optimal culturing time, temperature, pH, and inoculation amount were 48 h, 30℃, 6, and 20%. The optimum formula of the applying bacterial suspension was 14% sodium dodecyl benzene sulfonate emulsifier, 4% Na₂HPO₄·2H₂O, 0.3% hydroxypropyl methylcellulose thickener, and 20% <i>B. siamensis</i>. The pot experiment results showed the control effect of applying bacterial suspension, diluted 1,000 times is still better than that of 24% fenbuconazole suspension. The applying bacterial suspension enables reliable control of brown rot in <i>D. latiflorus</i>.