Construction and evaluation of a nanosystem that combines acidification promoted chemodynamic therapy and intracellular drug release monitoring.

Triple-negative breast cancer (TNBC) is a highly invasive subtype of breast cancer that seriously affects women's physical and mental health. Chemodynamic therapy (CDT) induces cell death by specifically generating Fenton/Fenton-like reactions within tumor cells. However, the weak acidity of the tumor microenvironment (TME) greatly weakens the effectiveness of CDT. This work constructed a kind of P-CAIDF/PT nanoparticles (NPs), composed of two Pluronic F127 (PF127) based polymers: one was PF127-CAI (P-CAI), composed by connecting PF127 with the carbonic anhydrase IX (CA IX) inhibitor (CAI); the other was PF127-SS-TPE (PT), composed of PF127 and the aggregation-induced emission molecule, tetraphenylethylene (TPE), via the linkage of disulfide bonds. The two polymers were employed to construct the doxorubicin (DOX) and ferrocene (Fc) co-loaded P-CAIDF/PT NPs through the film dispersion method. After being administrated via i.v., P-CAIDF/PT could be accumulated in the TME by the enhanced permeability and retention (EPR) effect and engulfed by tumor cells. P-CAI induced intracellular acidification by inhibiting the overexpressed CA IX, thus promoting CDT by enhancing the Fc-mediated Fenton reaction. The acidification-enhanced CDT combined with the DOX-mediated chemotherapy could improve the therapeutic effect on TNBC. Moreover, P-CAIDF/PT also monitored the intracellular drug release processes through the fluorescence resonance energy transfer (FRET) effect depending on the inherent DOX/TPE pair. In conclusion, the P-CAIDF/PT nanosystem can achieve the combination therapy of acidification-enhanced CDT and chemotherapy as well as therapy monitoring, thus providing new ideas for the design and development of TNBC therapeutic agents.

CCL2 promotes proliferation, migration and angiogenesis through the MAPK/ERK1/2/MMP9, PI3K/AKT, Wnt/ß­catenin signaling pathways in HUVECs.

Severe bone trauma can lead to poor or delayed bone healing and nonunion. Bone regeneration is based on the interaction between osteogenesis and angiogenesis. Angiogenesis serves a unique role in the repair and remodeling of bone defects. Monocyte chemoattractant protein-1, also known as CC motif ligand 2 (CCL2), is a member of the CC motif chemokine family and was the first human chemokine to be revealed to be an effective chemokine of monocytes. However, its underlying mechanism in angiogenesis of bone defect repair remains to be elucidated. Therefore, the present study investigated the detailed mechanism by which CCL2 promoted angiogenesis in bone defects based on cell and animal model experiments. In the present study, CCL2 promoted proliferation, migration and tube formation in human umbilical vein endothelial cells (HUVECs) in a concentration-dependent manner. Western blot analysis revealed that treatment of HUVECs with CCL2 upregulated the protein expression levels of rho-associated coiled-coil-containing protein kinase (Rock)1, Rock2, N-cadherin, c-Myc and VEGFR2. Furthermore, CCL2 promoted the expression of MAPK/ERK1/2/MMP9, PI3K/AKT and Wnt/ß-catenin signaling pathway-related proteins, which also demonstrated that CCL2 promoted these functions in HUVECs. Immunohistochemical staining of Sprague Dawley rat femurs following bone defects revealed that VEGF expression was positive in the newly formed bone area in each group, while the expression area of VEGF in the CCL2 addition group was markedly increased. Therefore, CCL2 is a potential therapeutic approach for bone defect repair and reconstruction through the mechanism of angiogenesis-osteogenesis coupling.

Efficacy of a Deep Learning System for Screening Myopic Maculopathy Based on Color Fundus Photographs.

INTRODUCTION: The maculopathy in highly myopic eyes is complex. Its clinical diagnosis is a huge workload and subjective. To simply and quickly classify pathologic myopia (PM), a deep learning algorithm was developed and assessed to screen myopic maculopathy lesions based on color fundus photographs. METHODS: This study included 10,347 ocular fundus photographs from 7606 participants. Of these photographs, 8210 were used for training and validation, and 2137 for external testing. A deep learning algorithm was trained, validated, and externally tested to screen myopic maculopathy which was classified into four categories: normal or mild tessellated fundus, severe tessellated fundus, early-stage PM, and advanced-stage PM. The area under the precision-recall curve, the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, and Cohen's kappa were calculated and compared with those of retina specialists. RESULTS: In the validation data set, the model detected normal or mild tessellated fundus, severe tessellated fundus, early-stage PM, and advanced-stage PM with AUCs of 0.98, 0.95, 0.99, and 1.00, respectively; while in the external-testing data set of 2137 photographs, the model had AUCs of 0.99, 0.96, 0.98, and 1.00, respectively. CONCLUSIONS: We developed a deep learning model for detection and classification of myopic maculopathy based on fundus photographs. Our model achieved high sensitivities, specificities, and reliable Cohen's kappa, compared with those of attending ophthalmologists.

Baicalin induces apoptosis and autophagy in human osteosarcoma cells by increasing ROS to inhibit PI3K/Akt/mTOR, ERK1/2 and ß-catenin signaling pathways.

Baicalin, a flavonoid derivative, exerts antitumor activity in a variety of neoplasms. However, whether baicalin exerts antitumor effects on osteosarcoma cells remains to be elucidated. In this study, treatment with baicalin reduced the proliferation and invasive potential of osteosarcoma cells and reduced the mitochondrial membrane potential, which eventually caused mitochondrial apoptosis. In addition, baicalin increased intercellular Ca2+ and ROS concentrations. Baicalin-induced apoptosis was confirmed by enhanced Bax, cleaved caspase-3, and cleaved PARP levels and decreased Bcl-2 levels. The increase in LC3-II and p62 suggested that baicalin induced autophagosome formation but ultimately inhibited downstream autophagy. Moreover, apoptosis induced by baicalin was attenuated by the addition of 3-MA. Furthermore, we found that baicalin inhibited the PI3K/Akt/mTOR, ERK1/2 and ß-catenin signaling pathways. Chelation of free Ca2+ by BAPTA-AM also inhibited both apoptosis induction and ROS concentration changes. Finally, NAC pretreatment reversed baicalin treatment outcomes, including the increase in Ca2+ concentration, induction of apoptosis and autophagy, and inhibition of the pathways. Molecular docking results indicated that baicalin might interact with the structural domain of PI3Kγ. Thus, baicalin may be considered a potential candidate for osteosarcoma treatment.