1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results

The 1$^{\text{st}}$ Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritime Object Detection, (ii) UAV-based Maritime Object Tracking, (iii) USV-based Maritime Obstacle Segmentation and (iv) USV-based Maritime Obstacle Detection. The subchallenges were based on the SeaDronesSee and MODS benchmarks. This report summarizes the main findings of the individual subchallenges and introduces a new benchmark, called SeaDronesSee Object Detection v2, which extends the previous benchmark by including more classes and footage. We provide statistical and qualitative analyses, and assess trends in the best-performing methodologies of over 130 submissions. The methods are summarized in the appendix. The datasets, evaluation code and the leaderboard are publicly available at https://seadronessee.cs.uni-tuebingen.de/macvi.Comment: MaCVi 2023 was part of WACV 2023. This report (38 pages) discusses the competition as part of MaCV

The HPV E6 oncoprotein targets histone methyltransferases for modulating specific gene transcription

Expression of viral proteins causes important epigenetic changes leading to abnormal cell growth. Whether viral proteins directly target histone methyltransferases (HMTs), a key family enzyme for epigenetic regulation, and modulate their enzymatic activities remains elusive. Here we show that the E6 proteins of both low-risk and high-risk human papillomavirus (HPV) interact with three coactivator HMTs, CARM1, PRMT1 and SET7, and downregulate their enzymatic activities in vitro and in HPV-transformed HeLa cells. Furthermore, these three HMTs are required for E6 to attenuate p53 transactivation function. Mechanistically, E6 hampers CARM1- and PRMT1-catalyzed histone methylation at p53-responsive promoters, and suppresses the binding of p53 to chromatinized DNA independently of E6-mediated p53 degradation. p53 pre-methylated at lysine-372 (p53K372 mono-methylation) by SET7 protects p53 from E6-induced degradation. Consistently, E6 downregulates p53K372 mono-methylation and thus reduces p53 protein stability. As a result of the E6-mediated inhibition of HMT activity, expression of p53 downstream genes is suppressed. Together, our results not only reveal a clever approach for the virus to interfere with p53 function, but also demonstrate the modulation of HMT activity as a novel mechanism of epigenetic regulation by a viral oncoprotein

Protocatechuic acid-mediated DJ-1/PARK7 activation followed by PI3K/mTOR signaling pathway activation as a novel mechanism for protection against ketoprofen-induced oxidative damage in the gastrointestinal mucosa

Oxidative stress contributes to the progression of non-steroidal anti-inflammatory drug (NSAID)-induced gastrointestinal (GI) cell apoptosis. In our previous study, we reported that nuclear factor erythroid 2-related factor 2 (Nrf2) plays a protective role against ketoprofen-induced GI mucosal oxidative injury. Recent reports suggest that Nrf2 could exhibit antioxidative and antiapoptosis responses through up-regulation of DJ-1 (PARK7). In the current study, we proposed that induction of DJ-1 expression by protocatechuic acid (PCA) might provide a potential therapeutic approach for treating oxidative stress-associated GI ulcer diseases. The results indicated that PCA increased mRNA expression of glutathione peroxidase and heme oxygenase-1 through up-regulation of DJ-1 followed by Nrf2 translocation. Furthermore, PCA protected Int-407 cells against ketoprofen-induced oxidative stress by regulating the DJ-1, PI3K, and mTOR pathways. Pretreatment with PCA inhibited mitochondrial ROS generation, up-regulated the mitochondrial membrane potential, and down-regulated pro-apoptotic Bax as well as downstream caspase-8, caspase-9, and caspase-3 activity, and reversed impaired DJ-1 and anti-apoptotic Bcl-2 protein expression in Int-407 cells induced by ketoprofen. Similar to the in vitro results, SD rats treated with PCA before administration of ketoprofen exhibited decreased caspase-3 protein expression as well as oxidative damage, and impairment of the antioxidant system and DJ-1 protein expression in the GI mucosa were reversed. The administration of lansoprazole, a type of proton pump inhibitor (PPI), strongly inhibited ketoprofen-induced GI mucosal injuries via up-regulation of DJ-1, indicating that DJ-1 is essential for the dietary antioxidant- and PPI drug-mediated mechanism of ulcer therapy. These results suggest that DJ-1 could be a novel target for protection against ketoprofen-induced GI ulcers due to its antioxidant and anti-apoptosis characteristics

Modification effect of sex and obesity on the correlation of LEP polymorphisms with leptin levels in Taiwanese obese women

Abstract Background Obesity has become the main health issue in developed countries as it impacts life expectancy and increases mortality of cerebrovascular or cardiovascular diseases. The leptin is one of the adipokines which presents in the serum in proportion to the amount of adipose tissue and is translated from LEP gene. It involves in energy homeostasis, lipid and glucose metabolisms, modulation of immune systems, and thermogenesis. Many previous studies have revealed controversial results between LEP polymorphisms and leptin levels in different ages and ethnicities. Herein, we investigated the impacts of LEP polymorphism against leptin levels in Taiwanese subjects. Methods In 599 Taiwanese subjects, excluding clinically overt systemic disease, age below 18 years old, and C‐reactive protein (CRP) level of above 10 mg/L, few of LEP polymorphisms were genotyped with TaqMan SNP genotyping assays, were further analyzed for association with leptin level in univariate and multivariate linear regression analyses with Bonferroni correction for multiple tests in stratified groups. The univariate and stepwise multivariate linear regression analyses were performed to determine the coefficient of determinant of LEP polymorphisms over leptin level. Results Significant associations were found between LEP polymorphisms and leptin levels in obese women. Circulating leptin level was positively correlated with inflammatory, insulin resistance markers, and visceral obesity markers in all subjects. Furthermore, stratified and interaction analyses revealed that LEP polymorphisms, rs7799039 and rs2167270, were significantly associated with leptin levels in obese women—8%–10% of which could be explained by LEP polymorphisms. Conclusion The LEP polymorphisms are independently associated with leptin levels in Taiwanese obese women. Further, the genetic determinants for leptin levels may be different between obese and nonobese, and in different sex individuals. The obesity status and female sex may exert modification effect on transcription of LEP, particularly in obese women

Photothermolysis of glioblastoma stem-like cells targeted by carbon nanotubes conjugated with CD133 monoclonal antibody

CD133+ cells in glioblastoma (GBM) display cancer stem cell-like properties and have been considered as the culprit of tumor recurrence, justifying exploration of potential therapeutic modalities targeting CD133+ cancer stem-like cells (CSCs). For photothermolysis studies, GBM-CD133+ and GBM-CD133- cells mixed with various ratios were challenged with single-walled carbon nanotubes (SWNTs) conjugated with CD133 monoclonal antibody (anti-CD133) and then irradiated with near-infrared laser light. Results show that GBM-CD133+ cells were selectively targeted and eradicated, whereas GBM-CD133- cells remained viable. In addition, in vitro tumorigenic and self-renewal capability of GBM-CD133+ treated with localized hyperthermia was significantly blocked. Furthermore, GBM-CD133+ cells pretreated with anti-CD133-SWNTs and irradiated by near-infrared laser 2 days after xenotransplantation in nude mice did not exhibit sustainability of CSC features for tumor growth. Taken altogether, our studies demonstrated that anti-CD133-SWNTs have the potential to be utilized as a thermal-coupling agent to effectively target and destroy GBM CSCs in vitro and in vivo. From the Clinical Editor: Glioblastoma remains one of the most notorious cancer from the standpoint of recurrence and overall resistance to therapy. CD133+ stem cells occur among GBM cells, and may be responsible for the huge recurrence risk. This paper discusses a targeted elimination method of these cells, which may enable more efficient therapy in an effort to minimize or prevent recurrence. © 2011 Elsevier Inc

Piceatannol Exerts Anti-Obesity Effects in C57BL/6 Mice through Modulating Adipogenic Proteins and Gut Microbiota

Obesity is a global health concern. Piceatannol (Pic), an analog of resveratrol (Res), has many reported biological activities. In this study, we investigated the anti-obesity effect of Pic in a high-fat diet (HFD)-induced obese animal model. The results showed that Pic significantly reduced mouse body weight in a dose-dependent manner without affecting food intake. Serum total cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL) levels, and blood glucose (GLU) were significantly lowered in Pic-treated groups. Pic significantly decreased the weight of liver, spleen, perigonadal and retroperitoneal fat compared with the HFD group. Pic significantly reduced the adipocyte cell size of perigonadal fat and decreased the weight of liver. Pic-treated mice showed higher phosphorylated adenosine 5′-monophosphate-activated protein kinase (pAMPK) and phosphorylated acetyl-CoA carboxylase (pACC) protein levels and decreased protein levels of CCAAT/enhancer-binding protein C/EBPα, peroxisome proliferator-activated receptor PPARγ and fatty acid synthase (FAS), resulting in decreased lipid accumulation in adipocytes and the liver. Pic altered the composition of the gut microbiota by increasing Firmicutes and Lactobacillus and decreasing Bacteroidetes compared with the HFD group. Collectively, these results suggest that Pic may be a candidate for obesity treatment

Effective Invasiveness Recognition of Imbalanced Data by Semi-Automated Segmentations of Lung Nodules

Over the past few decades, recognition of early lung cancers was researched for effective treatments. In early lung cancers, the invasiveness is an important factor for expected survival rates. Hence, how to effectively identify the invasiveness by computed tomography (CT) images became a hot topic in the field of biomedical science. Although a number of previous works were shown to be effective on this topic, there remain some problems unsettled still. First, it needs a large amount of marked data for a better prediction, but the manual cost is high. Second, the accuracy is always limited in imbalance data. To alleviate these problems, in this paper, we propose an effective CT invasiveness recognizer by semi-automated segmentation. In terms of semi-automated segmentation, it is easy for doctors to mark the nodules. Just based on one clicked pixel, a nodule object in a CT image can be marked by fusing two proposed segmentation methods, including thresholding-based morphology and deep learning-based mask region-based convolutional neural network (Mask-RCNN). For thresholding-based morphology, an initial segmentation is derived by adaptive pixel connections. Then, a mathematical morphology is performed to achieve a better segmentation. For deep learning-based mask-RCNN, the anchor is fixed by the clicked pixel to reduce the computational complexity. To incorporate advantages of both, the segmentation is switched between these two sub-methods. After segmenting the nodules, a boosting ensemble classification model with feature selection is executed to identify the invasiveness by equalized down-sampling. The extensive experimental results on a real dataset reveal that the proposed segmentation method performs better than the traditional segmentation ones, which can reach an average dice improvement of 392.3%. Additionally, the proposed ensemble classification model infers better performances than the compared method, which can reach an area under curve (AUC) improvement of 5.3% and a specificity improvement of 14.3%. Moreover, in comparison with the models with imbalance data, the improvements of AUC and specificity can reach 10.4% and 33.3%, respectively