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Introduction: Rhegmatogenous retinal detachment (RRD) is one of the most common fundus diseases. Many rural areas of China have few ophthalmologists, and ophthalmologic ultrasound examination is of great significance for remote diagnosis of RRD. Therefore, this study aimed to develop and evaluate a deep learning (DL) model, to be used for automated RRD diagnosis based on ophthalmologic ultrasound images, in order to support timely diagnosis of RRD in rural and remote areas. Methods: A total of 6,000 ophthalmologic ultrasound images from 1,645 participants were used to train and verify the DL model. A total of 5,000 images were used for training and validating DL models, and an independent testing set of 1,000 images was used to test the performance of eight DL models trained using four different DL model architectures (fully connected neural network, LeNet5, AlexNet, and VGG16) and two preprocessing techniques (original, original image augmented). Receiver operating characteristic (ROC) curves were used to analyze their performance. Heatmaps were generated to visualize the process of the best DL model in the identification of RRD. Finally, five ophthalmologists were invited to diagnose RRD independently on the same test set of 1,000 images for performance comparison with the best DL model. Results: The best DL model for identifying RRD achieved an area under the ROC curve (AUC) of 0.998 with a sensitivity and specificity of 99.2% and 99.8%, respectively. The best preprocessing method in each model architecture was the application of original image augmentation (average AUC = 0.982). The best model architecture in each preprocessing method was VGG16 (average AUC = 0.998). Conclusion: The best DL model determined in this study has higher accuracy, sensitivity, and specificity than the ophthalmologists' diagnosis in identifying RRD based on ophthalmologic ultrasound images. This model may provide support for timely diagnosis in locations without access to ophthalmologic care. [ABSTRACT FROM AUTHOR]

Introduction: Ovarian aging is characterized by a gradual decline in quantity and quality of oocytes and lower chance of fertility. Better understanding the genetic modulation during ovarian aging can further address available treatment options for aging-related ovarian diseases and fertility preservation. Methods: A novel technique spatial transcriptomics (ST) was used to investigate the spatial transcriptome features of rat ovaries. Transcriptomes from ST spots in the young and aged ovaries were clustered using differentially expressed genes. These data were analyzed to determine the spatial organization of age-induced heterogeneity and potential mechanisms underlying ovarian aging. Results: In this study, ST technology was applied to profile the comprehensive spatial imaging in young and aged rat ovary. Fifteen ovarian cell clusters with distinct gene-expression signatures were identified. The gene expression dynamics of granulosa cell clusters revealed three sub-types with sequential developmental stages. Aged ovary showed a significant decrease in the number of granulosa cells from the antral follicle. Besides, a remarkable rearrangement of interstitial gland cells was detected in aging ovary. Further analysis of aging-associated transcriptional changes revealed that the disturbance of oxidative pathway was a crucial factor in ovarian aging. Conclusions: This study firstly described an aging-related spatial transcriptome changes in ovary and identified the potential targets for prevention of ovarian aging. These data may provide the basis for further investigations of the diagnosis and treatment of aging-related ovarian disorders. [ABSTRACT FROM AUTHOR]

Background/Aims: Hyperglycemia is an important risk factor for the most severe cardiovascular diseases in patients with diabetes. It has been demonstrated that cardiac stem cells (CSCs) play a pivotal role in the maintenance of cardiac homeostasis and regeneration. However, the mechanism underlying the influence of diabetes on CSCs remains unclear. This study demonstrated that hyperglycemia might promote adipogenesis in CSCs, which induces a decline in myocardial regeneration capability in diabetes. Methods: CSCs were isolated and cultured in high-glucose medium. The levels of β-catenin and TCF-4 in CSCs were determined by immunofluorescence staining and western blot analysis. Adipogenic transcriptional factors and CSCs markers were also examined by flow cytometry and western blot analysis after adipogenesis induction. In addition, Oil Red O staining was performed to investigate lipid droplet formation during adipogenesis induction with or without LiCl, a potent activator of TCF/β-catenin-dependent transcription. Results: High-glucose conditions inhibited nuclear translocation of β-catenin/TCF-4 and promoted adipogenesis in CSCs. After adipogenesis induction, expression of adipogenic transcriptional factors (PPARγ, ADD1, and C/EBPα) were increased (P < 0.01) and that of CSCs markers (c-Kit, Sca-1, MDR-1, and isl-1) were decreased (P< 0.01) in CSCs in the high-glucose group. Furthermore, lipid droplet formation was increased in CSCs cultured with high glucose, while LiCl attenuated lipid droplet formation in these CSCs (P < 0.01). Conclusion: These results demonstrated that hyperglycemia inhibited the β-catenin/TCF-4 pathway and promoted CSCs adipogenesis. Our findings suggest a new opportunity for future interventional strategie for abnormal myocardial regeneration and epicardial fat in patients with diabetes. [ABSTRACT FROM AUTHOR]

Background/Aims: Adhesion-regulating molecule 1 (ADRM1), a receptor located on the 26S proteasome, is upregulated in many solid cancers. However, little is known about its role in acute leukemia (AL). Methods: We determined ADRM1 expression levels in both untreated AL samples and leukemia cell lines using real-time polymerase chain reaction or Western blot analysis. Growth curves, colony formation assays, cell cycle and apoptosis analyses, cell migration and invasion assays and NF-κB p65 nuclear translocation assays via Western blotting were used to examine the biological behavior of HL60 cells and the underlying mechanism. Results: ADRM1 was upregulated in both untreated AL samples and leukemia cell lines. ADRM1 knockdown significantly suppressed HL60 cell proliferation (48.82 ± 12.58%) and colony formation and caused cell cycle arrest in the G0/G1 phase. Furthermore, we confirmed that ADRM1 knockdown suppressed p65 nuclear translocation. Conclusion: Our study revealed that ADRM1 was overexpressed in AL, especially in CD34+ leukemia stem and progenitor cells. ADRM1 may play a role in AL via the proteasome-ubiquitin pathway by potentially sustaining the activation of NF-κB signaling. © 2015 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]