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Background: Limited evidence supports the effects of short-interval high-intensity interval training (HIIT) for improving cardiorespiratory fitness (V̇O 2 peak) after stroke. We aimed to compare the effects of 12 weeks of short-interval HIIT versus moderate-intensity continuous training (MICT) on V̇O 2 peak, cardiovascular risk factors, and mobility outcomes among individuals ≥6 months poststroke., Methods: This study was a multi-site, 12-week randomized controlled trial (NCT03614585) with an 8-week follow-up. Participants were randomized into 3 d/wk of HIIT (10×1 minute 80%-100% heart rate reserve interspersed with 1 minute 30% heart rate reserve [19 minutes]) or MICT (20-30 minutes 40%-60% heart rate reserve). Secondary outcomes of the trial, including V̇O 2 peak, cardiovascular risk factors (carotid-femoral pulse wave velocity, blood pressure, and waist-hip ratio), and mobility (6-minute walk test, 10 m gait speed), were reported. Linear mixed model analyses with a group×study time point interaction evaluated between-group differences., Results: Of the 305 potential participants, 82 consented (mean [SD] age 64.9 [9.3] years, 32 females [39%], 1.8 [1.2] years poststroke) and were randomized to HIIT (n=42, mean [SD] baseline V̇O 2 peak 17.3 [5.9] mL/kg·min) or MICT (n=40, mean [SD] baseline V̇O 2 peak 17.2 [6.0] mL/kg·min). Participants attended 82% of visits (n=2417/2952). No adverse events occurred during the study period. A significant group×study time point interaction was found (χ 2 =8.46; P =0.015) for V̇O 2 peak at 12 weeks (mean difference, 1.81 [95% CI, 0.58-3.04]; P =0.004) whereby the HIIT group had greater gains in V̇O 2 peak (∆3.52 mL/kg·min [95% CI, 2.47-4.57]; P <0.001) compared with the MICT group (∆1.71 mL/kg·min [95% CI, 0.55-2.86]; P =0.001). There was no between-group difference in V̇O 2 peak (mean difference, 1.08 [95% CI, -0.26 to 2.42]; P =0.11) at 8-week follow-up. No group×study time point interactions were found for cardiovascular risk factors or mobility outcomes., Conclusions: Short-interval HIIT may be an effective alternative to MICT for improving V̇O 2 peak at 12 weeks postintervention., Registration: URL: https://clinicaltrials.gov; Unique identifier: NCT03614585., Competing Interests: Dr Moncion and K.S. Noguchi are supported by an Ontario Graduate Scholarship. L. Rodrigues is supported by a Doctoral Scholarship from the Fonds Recherche Santé Québec. Dr Eng is supported by the Canada Research Chairs program. Dr Roig is supported by a Salary Award (Junior II) from Fonds de Recherche Santé Québec. This study is funded by an operating grant from the Canadian Institutes of Health Research (388320). Dr Tang reports grants from Canadian Institutes of Health Research; grants from Physiotherapy Foundation of Canada; and grants from Heart and Stroke Foundation of Canada.

Purpose To evaluate the reproducibility of radiomics features extracted from T2-weighted MR images in patients with neuroblastoma. Materials and Methods A retrospective study included 419 patients (mean age, 29 months ± 34 [SD]; 220 male, 199 female) with neuroblastic tumors diagnosed between 2002 and 2023, within the scope of the PRedictive In-silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers (ie, PRIMAGE) project, involving 746 T2/T2*-weighted MRI sequences at diagnosis and/or after initial chemotherapy. Images underwent processing steps (denoising, inhomogeneity bias field correction, normalization, and resampling). Tumors were automatically segmented, and 107 shape, first-order, and second-order radiomics features were extracted, considered as the reference standard. Subsequently, the previous image processing settings were modified, and volumetric masks were applied. New radiomics features were extracted and compared with the reference standard. Reproducibility was assessed using the concordance correlation coefficient (CCC); intrasubject repeatability was measured using the coefficient of variation (CoV). Results When normalization was omitted, only 5% of the radiomics features demonstrated high reproducibility. Statistical analysis revealed significant changes in the normalization and resampling processes ( P < .001). Inhomogeneities removal had the least impact on radiomics (83% of parameters remained stable). Shape features remained stable after mask modifications, with a CCC greater than 0.90. Mask modifications were the most favorable changes for achieving high CCC values, with a radiomics features stability of 70%. Only 7% of second-order radiomics features showed an excellent CoV of less than 0.10. Conclusion Modifications in the T2-weighted MRI preparation process in patients with neuroblastoma resulted in changes in radiomics features, with normalization identified as the most influential factor for reproducibility. Inhomogeneities removal had the least impact on radiomics features. Keywords: Pediatrics, MR Imaging, Oncology, Radiomics, Reproducibility, Repeatability, Neuroblastic Tumors Supplemental material is available for this article. © RSNA, 2024 See also the commentary by Safdar and Galaria in this issue.

This review paper presents the practical development of imaging biomarkers in the scope of the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project, as a noninvasive and reliable way to improve the diagnosis and prognosis in pediatric oncology. The PRIMAGE project is a European multi-center research initiative that focuses on developing medical imaging-derived artificial intelligence (AI) solutions designed to enhance overall management and decision-making for two types of pediatric cancer: neuroblastoma and diffuse intrinsic pontine glioma. To allow this, the PRIMAGE project has created an open-cloud platform that combines imaging, clinical, and molecular data together with AI models developed from this data, creating a comprehensive decision support environment for clinicians managing patients with these two cancers. In order to achieve this, a standardized data processing and analysis workflow was implemented to generate robust and reliable predictions for different clinical endpoints. Magnetic resonance (MR) image harmonization and registration was performed as part of the workflow. Subsequently, an automated tool for the detection and segmentation of tumors was trained and internally validated. The Dice similarity coefficient obtained for the independent validation dataset was 0.997, indicating compatibility with the manual segmentation variability. Following this, radiomics and deep features were extracted and correlated with clinical endpoints. Finally, reproducible and relevant imaging quantitative features were integrated with clinical and molecular data to enrich both the predictive models and a set of visual analytics tools, making the PRIMAGE platform a complete clinical decision aid system. In order to ensure the advancement of research in this field and to foster engagement with the wider research community, the PRIMAGE data repository and platform are currently being integrated into the European Federation for Cancer Images (EUCAIM), which is the largest European cancer imaging research infrastructure created to date., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Rehabilitative treatments that promote neuroplasticity are believed to improve recovery after stroke. Animal studies have shown that cardiovascular exercise (CE) promotes neuroplasticity but the effects of this intervention on the human brain and its implications for the functional recovery of patients remain unclear. The use of biomarkers has enabled the assessment of cellular and molecular events that occur in the central nervous system after brain injury. Some of these biomarkers have proven to be particularly valuable for the diagnosis of severity, prognosis of recovery, as well as for measuring the neuroplastic response to different treatments after stroke., Objectives: To provide a critical analysis on the current evidence supporting the use of neurophysiological, neuroimaging, and blood biomarkers to assess the neuroplastic response to CE in individuals poststroke., Results: Most biomarkers used are responsive to the effects of acute and chronic CE interventions, but the response appears to be variable and is not consistently associated with functional improvements. Small sample sizes, methodological variability, incomplete information regarding patient's characteristics, inadequate standardization of training parameters, and lack of reporting of associations with functional outcomes preclude the quantification of the neuroplastic effects of CE poststroke using biomarkers., Conclusion: Consensus on the optimal biomarkers to monitor the neuroplastic response to CE is currently lacking. By addressing critical methodological issues, future studies could advance our understanding of the use of biomarkers to measure the impact of CE on neuroplasticity and functional recovery in patients with stroke., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Immune checkpoint inhibitors (ICI) have emerged as an important therapeutic approach for patients with cancers including bladder cancer (BC). This commentary describes a recent study that demonstrated that the loss of Y chromosome (LOY) and/or loss of specific genes on Y chromosome confers an aggressive phenotype to BC because of T cell dysfunction resulting in CD8 + T cell exhaustion. Loss of expression of Y chromosome genes KDM5D and UTY was similarly associated with an unfavorable prognosis in patients with BC as these genes were partially responsible for the impaired anti-tumor immunity in LOY tumors. From a clinical perspective, the study showed that tumors with LOY may be susceptible to treatment with ICIs., (© 2024. The Author(s), under exclusive licence to Springer Healthcare Ltd., part of Springer Nature.)

The onset of COVID-19 coincided with the peak growth of video game usage, with 2.7 billion gamers in 2020. During the pandemic, gaming and streaming platforms offered an entertaining, social, and safe alternative to recreation during severe lockdowns and social isolations. This study aimed to examine the impact of the COVID-19 pandemic on health-related outcomes in self-proclaimed video gamers based on the type of lockdown experienced and to discuss the potential role of video games during times of preventive lockdown measures. This was a cross-sectional international survey constructed by two academic institutions, NYIT (NY, USA) and McGill University (Montreal, Canada), and Adamas Esports (BC, Canada). The survey consisted of questions including demographics, multiple choice, ratings, and Likert scales relating to the periods prior to and during the COVID-19 lockdowns. There were 897 respondents from North America (72.7%), Europe (10.9%), Asia (4.9%), and other countries (11.5%), with a mean age of 22 years. Significant increases in game time were reported in casual and competitive gamers during the first months of the pandemic. The level of gaming, type of lockdown, and physical activity level prior to the pandemic were examined as potential moderating factors. Significant increases in sedentary behaviors (video game time and sitting time) were observed, while physical activity levels remained unchanged in most participants, regardless of the type of lockdown. Sleep time, but not sleep quality, increased, while mental health exhibited opposing effects, influenced by the type of lockdown and gaming competition levels. Video games, when played moderately, could offer a cost-effective, safe strategy to promote socialization and mental health and improve the overall well-being of the non-gaming and gaming population during pandemic times when strict lockdowns are in place.

Objectives: To externally validate and assess the accuracy of a previously trained fully automatic nnU-Net CNN algorithm to identify and segment primary neuroblastoma tumors in MR images in a large children cohort., Methods: An international multicenter, multivendor imaging repository of patients with neuroblastic tumors was used to validate the performance of a trained Machine Learning (ML) tool to identify and delineate primary neuroblastoma tumors. The dataset was heterogeneous and completely independent from the one used to train and tune the model, consisting of 300 children with neuroblastic tumors having 535 MR T2-weighted sequences (486 sequences at diagnosis and 49 after finalization of the first phase of chemotherapy). The automatic segmentation algorithm was based on a nnU-Net architecture developed within the PRIMAGE project. For comparison, the segmentation masks were manually edited by an expert radiologist, and the time for the manual editing was recorded. Different overlaps and spatial metrics were calculated to compare both masks., Results: The median Dice Similarity Coefficient (DSC) was high 0.997; 0.944-1.000 (median; Q1-Q3). In 18 MR sequences (6%), the net was not able neither to identify nor segment the tumor. No differences were found regarding the MR magnetic field, type of T2 sequence, or tumor location. No significant differences in the performance of the net were found in patients with an MR performed after chemotherapy. The time for visual inspection of the generated masks was 7.9 ± 7.5 (mean ± Standard Deviation (SD)) seconds. Those cases where manual editing was needed (136 masks) required 124 ± 120 s., Conclusions: The automatic CNN was able to locate and segment the primary tumor on the T2-weighted images in 94% of cases. There was an extremely high agreement between the automatic tool and the manually edited masks. This is the first study to validate an automatic segmentation model for neuroblastic tumor identification and segmentation with body MR images. The semi-automatic approach with minor manual editing of the deep learning segmentation increases the radiologist's confidence in the solution with a minor workload for the radiologist.

Dysregulated inflammasome activity, particularly of the NLRP3 inflammasome, is associated with the development of several inflammatory diseases. The study of molecules directly targeting NLRP3 is an emerging field in the discovery of new therapeutic compounds for the treatment of inflammatory disorders. Friedelane triterpenes are biologically active phytochemicals having a wide range of activities including anti-inflammatory effects. In this work, we evaluated the potential anti-inflammatory activity of phenolic and quinonemethide nor-triterpenes (1-11) isolated from Maytenus retusa and some semisynthetic derivatives (12-16) through inhibition of the NLRP3 inflammasome in macrophages. Among them, we found that triterpenes 6 and 14 were the most potent, showing markedly reduced caspase-1 activity, IL-1β secretion (IC 50  = 1.15 µM and 0.19 µM, respectively), and pyroptosis (IC 50  = 2.21 µM and 0.13 µM, respectively). Further characterization confirmed their selective inhibition of NLRP3 inflammasome in both canonical and non-canonical activation pathways with no effects on AIM2 or NLRC4 inflammasome activation., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Inc.)

A set of new dihydroquinoline embelin derivatives was obtained from the reaction of the natural benzoquinone embelin ( 1 ) with anilines and aromatic aldehydes in the presence of AgOTf. The synthesis of these compounds involves the formation of a Knoevenagel adduct, followed by nucleophilic addition of aniline and subsequent electrocyclic ring closure. The scope of the reaction regarding the aldehydes and anilines was determined. Quinoline derivatives were also obtained from the corresponding dihydroquinolines under oxidation with DDQ. The cardioprotective activity of the synthesized compounds was screened using a doxorubicin-induced cardiotoxicity model in H9c2 cardiomyocytes. Some structure-activity relationships were outlined, and the best activities were achieved with quinoline-embelin derivatives having a 4-nitrophenyl group attached at the pyridine ring. The obtained results indicated that embelin derivatives 4i , 6a , 6d , 6k , and 6m could have potential as cardioprotective agents, as they attenuated a DOX-induced cardiotoxicity effect acting on oxidative stress and apoptosis.