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Colorectal cancer is one of the most common cancers in the world. While colonoscopy is an effective screening technique, navigating an endoscope through the colon to detect polyps is challenging. A 3D map of the observed surfaces could enhance the identification of unscreened colon tissue and serve as a training platform. However, reconstructing the colon from video footage remains difficult. Learning-based approaches hold promise as robust alternatives, but necessitate extensive datasets. Establishing a benchmark dataset, the 2022 EndoVis sub-challenge SimCol3D aimed to facilitate data-driven depth and pose prediction during colonoscopy. The challenge was hosted as part of MICCAI 2022 in Singapore. Six teams from around the world and representatives from academia and industry participated in the three sub-challenges: synthetic depth prediction, synthetic pose prediction, and real pose prediction. This paper describes the challenge, the submitted methods, and their results. We show that depth prediction from synthetic colonoscopy images is robustly solvable, while pose estimation remains an open research question., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Danail Stoyanov reports financial support was provided by Medtronic plc. Danail Stoyanov reports a relationship with Odin Medical Ltd. that includes: equity or stocks. Laurence Lovat and Rawen Kader report a relationship with Olympus Corporation that includes: consulting or advisory., (Copyright © 2024. Published by Elsevier B.V.)

Colonoscopy is the gold standard for early diagnosis and pre-emptive treatment of colorectal cancer by detecting and removing colonic polyps. Deep learning approaches to polyp detection have shown potential for enhancing polyp detection rates. However, the majority of these systems are developed and evaluated on static images from colonoscopies, whilst in clinical practice the treatment is performed on a real-time video feed. Non-curated video data remains a challenge, as it contains low-quality frames when compared to still, selected images often obtained from diagnostic records. Nevertheless, it also embeds temporal information that can be exploited to increase predictions stability. A hybrid 2D/3D convolutional neural network architecture for polyp segmentation is presented in this paper. The network is used to improve polyp detection by encompassing spatial and temporal correlation of the predictions while preserving real-time detections. Extensive experiments show that the hybrid method outperforms a 2D baseline. The proposed architecture is validated on videos from 46 patients and on the publicly available SUN polyp database. A higher performance and increased generalisability indicate that real-world clinical implementations of automated polyp detection can benefit from the hybrid algorithm and the inclusion of temporal information., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: D.S, L.B.L and are involved with Odin Vision Ltd. D.S is involved with Digital Surgery Ltd, (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

A large body of data emphasizes the central role of mitochondrial dysfunction during aging and as an early event in neurodegenerative diseases. In this study we used PC12 cells and dissociated mice brain cells, as well as isolated mitochondria to investigate the effects of EGb 761 on mitochondrial functions. We mimicked mitochondrial abnormalities during aging by using external factors (nitrosative stress, serum deprivation and complexes inhibitors) consequently altering mitochondrial processes, such as energy metabolism. As markers for the function of mitochondria, ATP levels and mitochondrial membrane potential were measured. EGb 761 alleviated mitochondrial functions in vitro at concentrations as low as 0.01 mg/ml. Treating two different age groups of mice with EGb 761 (100mg/kg body weight for 14 days) showed beneficial effects on complexes I, IV and V of the mitochondrial respiratory chain and against nitrosative stress. Interestingly, these effects were only observed in the aged mice group, proving higher efficacy of EGb 761 during aging. The single components of EGb 761 showed in both cell models protection of the mitochondrial membrane potential indicating that a complementary action of the components is responsible for the versatile actions of EGb 761.