Large-scale uterine myoma MRI dataset covering all FIGO types with pixel-level annotations.

Uterine myomas are the most common pelvic tumors in women, which can lead to abnormal uterine bleeding, abdominal pain, pelvic compression symptoms, infertility, or adverse pregnancy. In this article, we provide a dataset named uterine myoma MRI dataset (UMD), which can be used for clinical research on uterine myoma imaging. The UMD is the largest publicly available uterine MRI dataset to date including 300 cases of uterine myoma T2-weighted imaging (T2WI) sagittal patient images and their corresponding annotation files. The UMD covers 9 types of uterine myomas classified by the International Federation of Obstetrics and Gynecology (FIGO), which were annotated and reviewed by 11 experienced doctors to ensure the authority of the annotated data. The UMD is helpful for uterine myomas classification and uterine 3D reconstruction tasks, which has important implications for clinical research on uterine myomas.

UWV-Yolox: A Deep Learning Model for Underwater Video Object Detection.

Underwater video object detection is a challenging task due to the poor quality of underwater videos, including blurriness and low contrast. In recent years, Yolo series models have been widely applied to underwater video object detection. However, these models perform poorly for blurry and low-contrast underwater videos. Additionally, they fail to account for the contextual relationships between the frame-level results. To address these challenges, we propose a video object detection model named UWV-Yolox. First, the Contrast Limited Adaptive Histogram Equalization method is used to augment the underwater videos. Then, a new CSP_CA module is proposed by adding Coordinate Attention to the backbone of the model to augment the representations of objects of interest. Next, a new loss function is proposed, including regression and jitter loss. Finally, a frame-level optimization module is proposed to optimize the detection results by utilizing the relationship between neighboring frames in videos, improving the video detection performance. To evaluate the performance of our model, We construct experiments on the UVODD dataset built in the paper, and select mAP@0.5 as the evaluation metric. The mAP@0.5 of the UWV-Yolox model reaches 89.0%, which is 3.2% better than the original Yolox model. Furthermore, compared with other object detection models, the UWV-Yolox model has more stable predictions for objects, and our improvements can be flexibly applied to other models.

Renal cell carcinoma-derived exosomes deliver lncARSR to induce macrophage polarization and promote tumor progression via STAT3 pathway.

Tumor-derived exosomes play a pivotal role in regulating tumor progression by mediating crosstalk between tumor cells and immune cells such as macrophages within the tumor microenvironment. Macrophages can adopt two distinct polarization statuses and switch between M1 or M2 activation phenotypes in response to the different external stimuli. However, the role of tumor derived exosomes in the macrophage phenotypic switch and tumor development have not been elucidated in renal cell carcinoma (RCC). Here we found that high macrophage infiltration was associated with worse prognosis in RCC patients, therefore we propose our hypothesis that RCC derived exosomes might directly influence macrophage polarization and thus promote tumor progression. Both cell-based in vitro models and orthotopic transplantation in vivo tumor models were constructed and ELISA, flow cytometry, and macrophage functional studies were performed to investigate whether and how RCC-derived exosomes regulate macrophage polarization and tumor growth. The results found that these exosomes promote macrophage polarization, cytokine release, phagocytosis, angiogenesis, and tumor development. Further study revealed high amount of a recently discovered lncRNA called lncARSR in RCC-derived exosomes. Overexpression of lncARSR induced phenotypic and functional changes of macrophages in vitro and promoted tumor growth in vivo, while knockdown of lncARSR by siRNA disrupted the exosomes-mediated macrophage polarization. LncARSR interacts directly with miR-34/miR- 449 to increase STAT3 expression and mediate macrophage polarization in RCC cells. Together, RCC-derived exosomes facilitate the development of tumor through inducing macrophage polarization via transferring lncARSR, suggesting that RCC-derived exosomes, lncARSR and STAT3 are the potential therapeutic targets for treatment of RCC.

FAM198B promotes colorectal cancer progression by regulating the polarization of tumor-associated macrophages via the SMAD2 signaling pathway.

Colorectal cancer (CRC) is one of the most common malignant tumors. Tumor-associated macrophages (TAMs) promote the progression of CRC, but the mechanism is not completely clear. The present study aimed to reveal the expression and function of FAM198B in TAMs, and the role of FAM198B in mediating macrophage polarization in CRC. The role of FAM198B in macrophage activity, cell cycle, and angiogenesis was evaluated by CCK-8 assay, flow cytometry, and vasculogenic mimicry assay. The effects of FAM198B on macrophage polarization were determined by flow cytometry. The function of FAM198B-mediated macrophage polarization on CRC progression was evaluated by transwell assays. Bioinformatic analyses and rescue assays were performed to identify biological functions and signaling pathways involved in FAM198B regulation of macrophage polarization. Increased FAM198B expression in TAMs is negatively associated with poor CRC prognosis. Functional assays showed that FAM198B promotes M2 macrophage polarization, which leads to CRC cell proliferation, migration, and invasion. Mechanistically, FAM198B regulates the M2 polarization of macrophages by targeting SMAD2, identifying the SMAD2 pathway as a mechanism by which FAM198B promotes CRC progression through regulating macrophage polarization. These findings provide a possible molecular mechanism for FAM198B in TAMs in CRC and suggest that FAM198B may be a novel therapeutic target in CRC.

MiR-25 enhances autophagy and promotes sorafenib resistance of hepatocellular carcinoma via targeting FBXW7.

Sorafenib resistance is a major challenge in the treatment of patients with advanced hepatocellular carcinoma (HCC). MicroRNAs (miRNAs) are a large family of non-coding RNA molecules, which is an important mechanism of drug resistance. We previously found that knockdown of miR-25 increased the sensitivity of TRAIL-induced apoptosis in liver cancer stem cells. We aimed to study the effects of miR-25 on sorafenib resistance of HCC and the underlying mechanisms. In the present study, we analyzed the expression of miR-25 between HCC and normal tissues and predicted miR-25 target genes through databases. After transfecting miR-25 mimics, inhibitor or FBXW7 Plasmid, CCK-8 and flow cytometry assay was performed to determine the sorafenib resistance. We performed LC3-dual-fluorescence assay and Western blotting to detect the autophagy levels. The expression of miR-25 was upregulated in human HCC tissues and was associated with tumor pathological grade, clinic staging, and lymphatic metastasis. MiR-25 enhanced sorafenib resistance of HCC cells and autophagy. FBXW7 is the direct target of miR-25. Overexpression of FBXW7 could reverse the increase of sorafenib resistance caused by miR-25 mimics. Our results suggested that miR-25 increased the sorafenib resistance of HCC via inducing autophagy. In addition, miR-25 decreases the expression of FBXW7 protein to regulate autophagy. Therefore, miR-25 may represent a novel therapeutic target for the treatment of HCC.