No abstract

Imaging techniques are widely used for medical diagnostics. In some cases, a lack of medical practitioners who can manually analyze the images can lead to a bottleneck. Consequently, we developed a custom-made convolutional neural network (RiFNet = Rib Fracture Network) that can detect rib fractures in postmortem computed tomography. In a retrospective cohort study, we retrieved PMCT data from 195 postmortem cases with rib fractures from July 2017 to April 2018 from our database. The computed tomography data were prepared using a plugin in the commercial imaging software Syngo.via whereby the rib cage was unfolded on a single-in-plane image reformation. Out of the 195 cases, a total of 585 images were extracted and divided into two groups labeled “with” and “without” fractures. These two groups were subsequently divided into training, validation, and test datasets to assess the performance of RiFNet. In addition, we explored the possibility of applying transfer learning techniques on our dataset by choosing two independent noncommercial off-the-shelf convolutional neural network architectures (ResNet50 V2 and Inception V3) and compared the performances of those two with RiFNet. When using pre-trained convolutional neural networks, we achieved an F1 score of 0.64 with Inception V3 and an F1 score of 0.61 with ResNet50 V2. We obtained an average F1 score of 0.91 ± 0.04 with RiFNet. RiFNet is efficient in detecting rib fractures on postmortem computed tomography. Transfer learning techniques are not necessarily well adapted to make classifications in postmortem computed tomography.

Objectives: We investigated changes in adherence to physical activity (PA) and screen time (ST) recommendations of children and adolescents throughout the pandemic, and their association with health-related quality of life (HRQOL).Methods: 1,769 primary (PS, grades 1–6) and secondary (SS, 7–9) school children from Ciao Corona, a school-based cohort study in Zurich, Switzerland, with five questionnaires 2020–2022. HRQOL was assessed using the KINDL questionnaire. PA (≥60 min/day moderate-to-vigorous PA) and ST (≤2 h/day ST) recommendations followed WHO guidelines.Results: Adherence to PA recommendations dropped in 2020 (83%–59% PS, 77%–52% SS), but returned to pre-pandemic levels by 2022 (79%, 66%). Fewer children met ST recommendations in 2020 (74% PS, 29% SS) and 2021 (82%, 37%) than pre-pandemic (95%, 68%). HRQOL decreased 3 points between 2020 and 2022, and was 9.7 points higher (95% CI 3.0–16.3) in March 2021 in children who met both versus no recommendations.Conclusion: Adherence to WHO guidelines on PA and ST during the pandemic had a consistent association with HRQOL despite longitudinal changes in behavior.

Objectives: Both lifestyle and health-related quality of life (HRQOL) were compromised during the COVID-19 pandemic. Our aim was to investigate changes in adherence to physical activity and screen time recommendations of children and adolescents throughout the pandemic, and their association with HRQOL over time. Methods: Longitudinal data in 1769 primary (grades 1-6) and secondary (7-9) school children ages 6-17 years was taken from the Ciao Corona study, a school-based prospective cohort study in Zurich, Switzerland, with 5 online questionnaires between June 2020 and July 2022. HRQOL was assessed using the KINDL questionnaire. Meeting physical activity and screen time recommendations was defined according to criteria of the world health organization. Results: Adherence to physical activity recommendations dropped in 2020, but had returned to approximately pre-pandemic levels by 2022. Fewer children met screen time recommendations in 2020 and 2021 than pre-pandemic. HRQOL reduced approximately 3 points between 2020 and 2022, and was on average 9.7 points higher (95% CI 3.0 - 16.3) in March 2021 in children who met both recommendations. Conclusions: Adherence to WHO guidelines on physical activity and screen time during the pandemic had a consistent association with HRQOL despite longitudinal changes in behavior.

Adrenocortical carcinoma (ACC) is a rare cancer of the adrenal gland with generally very unfavourable outcome. Two molecular subgroups, C1A and C1B, have been previously identified with a significant association with patient survival. In this work, we study chromatin state organization characterized by histone modifications using ChIP-sequencing in adult ACC. We describe the super-enhancer landscape of ACC, characterized by H3K27ac, and identify super-enhancer regulated genes that play a significant role in tumorigenesis. We show that the super-enhancer landscape reflects differences between the molecular sub- groups C1A and C1B and identify networks of master transcription factors mirroring these differences. Additionally, we study the effects of molecules THZ1 and JQ1 previously reported to affect super-enhancer-driven gene expression in ACC cell lines. Our results reveal that the landscape of histone modifications in ACC is linked to its molecular subgroups and thus provide the groundwork for future analysis of epigenetic reprogramming in ACC.