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BackgroundAs differentiating between lipomas and atypical lipomatous tumors (ALTs) based on imaging is challenging and requires biopsies, radiomics has been proposed to aid the diagnosis. This study aimed to externally and prospectively validate a radiomics model differentiating between lipomas and ALTs on MRI in three large, multi-center cohorts, and extend it with automatic and minimally interactive segmentation methods to increase clinical feasibility.MethodsThree study cohorts were formed, two for external validation containing data from medical centers in the United States (US) collected from 2008 until 2018 and the United Kingdom (UK) collected from 2011 until 2017, and one for prospective validation consisting of data collected from 2020 until 2021 in the Netherlands. Patient characteristics, MDM2 amplification status, and MRI scans were collected. An automatic segmentation method was developed to segment all tumors on T1-weighted MRI scans of the validation cohorts. Segmentations were subsequently quality scored. In case of insufficient quality, an interactive segmentation method was used. Radiomics performance was evaluated for all cohorts and compared to two radiologists.FindingsThe validation cohorts included 150 (54% ALT), 208 (37% ALT), and 86 patients (28% ALT) from the US, UK and NL. Of the 444 cases, 78% were automatically segmented. For 22%, interactive segmentation was necessary due to insufficient quality, with only 3% of all patients requiring manual adjustment. External validation resulted in an AUC of 0.74 (95% CI: 0.66, 0.82) in US data and 0.86 (0.80, 0.92) in UK data. Prospective validation resulted in an AUC of 0.89 (0.83, 0.96). The radiomics model performed similar to the two radiologists (US: 0.79 and 0.76, UK: 0.86 and 0.86, NL: 0.82 and 0.85).InterpretationThe radiomics model extended with automatic and minimally interactive segmentation methods accurately differentiated between lipomas and ALTs in two large, multi-center external cohorts, and in prospective validation, performing similar to expert radiologists, possibly limiting the need for invasive diagnostics.FundingHanarth fonds.

In relational event networks, the tendency for actors to interact with each other depends greatly on the past interactions between the actors in a social network. Both the volume of past interactions and the time that has elapsed since the past interactions affect the actors' decision-making to interact with other actors in the network. Recently occurred events may have a stronger influence on current interaction behavior than past events that occurred a long time ago--a phenomenon known as "memory decay". Previous studies either predefined a short-run and long-run memory or fixed a parametric exponential memory decay using a predefined half-life period. In real-life relational event networks, however, it is generally unknown how the influence of past events fades as time goes by. For this reason, it is not recommendable to fix memory decay in an ad-hoc manner, but instead we should learn the shape of memory decay from the observed data. In this paper, a novel semi-parametric approach based on Bayesian Model Averaging is proposed for learning the shape of the memory decay without requiring any parametric assumptions. The method is applied to relational event history data among socio-political actors in India and a comparison with other relational event models based on predefined memory decays is provided.

Abstract Isolated REM Sleep Behavior Disorder (iRBD) is considered a prodrome of Parkinson’s disease (PD). We investigate whether the potentially disease-modifying compound acetyl-DL-leucine (ADLL; 5 g/d) has an effect on prodromal PD progression in 2 iRBD-patients. Outcome parameters are RBD-severity sum-score (RBD-SS-3), dopamine-transporter single-photon emission computerized tomography (DAT-SPECT) and metabolic “Parkinson-Disease-related-Pattern (PDRP)”-z-score in 18F-fluorodeoxyglucose positron emission tomography (FDG-PET). After 3 weeks ADLL-treatment, the RBD-SS-3 drops markedly in both patients and remains reduced for >18 months of ADLL-treatment. In patient 1 (female), the DAT-SPECT putaminal binding ratio (PBR) decreases in the 5 years pretreatment from normal (1.88) to pathological (1.22) and the patient’s FDG-PET-PDRP-z-score rises from 1.72 to 3.28 (pathological). After 22 months of ADLL-treatment, the DAT-SPECT-PBR increases to 1.67 and the FDG-PET-PDRP-z-score stabilizes at 3.18. Similar results are seen in patient 2 (male): his DAT-SPECT-PBR rises from a pretreatment value of 1.42 to 1.72 (close to normal) and the FDG-PET-PDRP-z-score decreases from 1.02 to 0.30 after 18 months of ADLL-treatment. These results support exploration of whether ADLL may have disease-modifying properties in prodromal PD.

Involving students in shaping their own education allows for more suitable, acceptable and effective education. We focus on how student voice is embodied in the context of teaching and learning as well as relevant factors for implementation and the impact of student voice activities on students' personal development and school connectedness. This systematic literature review provides an overview of qualitative studies which focus on involving 12-20 year-old students in co-creation and decision-making in the context of teaching and learning. The 15 included studies indicate that students were involved in various phases and were assigned multiple roles and responsibilities. There was a tendency to include students as advisors in planning, as co-researchers in acting/observing and as reviewers in reflecting. Relevant factors for implementation were knowledge, skills, beliefs about capabilities, optimism, emotions, social/professional role and identity, and social influences. Those students who participated increased their skills, confidence and ownership. Ongoing challenges remain with granting students various opportunities for taking diverse roles in each research phase. Future research is needed in more diverse school contexts and which assesses the long-term impact on students' development and their health, well-being and social position.

Abstract Background Persistent infections with high-risk human papillomavirus (hrHPV) can cause cervical squamous intraepithelial lesions (SIL) that may progress to cancer. The cervicovaginal microbiome (CVM) correlates with SIL, but the temporal composition of the CVM after hrHPV infections has not been fully clarified. Methods To determine the association between the CVM composition and infection outcome, we applied high-resolution microbiome profiling using the circular probe-based RNA sequencing technology on a longitudinal cohort of cervical smears obtained from 141 hrHPV DNA-positive women with normal cytology at first visit, of whom 51 were diagnosed by cytology with SIL six months later. Results Here we show that women with a microbial community characterized by low diversity and high Lactobacillus crispatus abundance at both visits exhibit low risk to SIL development, while women with a microbial community characterized by high diversity and Lactobacillus depletion at first visit have a higher risk of developing SIL. At the level of individual species, we observed that a high abundance for Gardnerella vaginalis and Atopobium vaginae at both visits associate with SIL outcomes. These species together with Dialister micraerophilus showed a moderate discriminatory power for hrHPV infection progression. Conclusions Our results suggest that the CVM can potentially be used as a biomarker for cervical disease and SIL development after hrHPV infection diagnosis with implications on cervical cancer prevention strategies and treatment of SIL.

Summary: Background: As differentiating between lipomas and atypical lipomatous tumors (ALTs) based on imaging is challenging and requires biopsies, radiomics has been proposed to aid the diagnosis. This study aimed to externally and prospectively validate a radiomics model differentiating between lipomas and ALTs on MRI in three large, multi-center cohorts, and extend it with automatic and minimally interactive segmentation methods to increase clinical feasibility. Methods: Three study cohorts were formed, two for external validation containing data from medical centers in the United States (US) collected from 2008 until 2018 and the United Kingdom (UK) collected from 2011 until 2017, and one for prospective validation consisting of data collected from 2020 until 2021 in the Netherlands. Patient characteristics, MDM2 amplification status, and MRI scans were collected. An automatic segmentation method was developed to segment all tumors on T1-weighted MRI scans of the validation cohorts. Segmentations were subsequently quality scored. In case of insufficient quality, an interactive segmentation method was used. Radiomics performance was evaluated for all cohorts and compared to two radiologists. Findings: The validation cohorts included 150 (54% ALT), 208 (37% ALT), and 86 patients (28% ALT) from the US, UK and NL. Of the 444 cases, 78% were automatically segmented. For 22%, interactive segmentation was necessary due to insufficient quality, with only 3% of all patients requiring manual adjustment. External validation resulted in an AUC of 0.74 (95% CI: 0.66, 0.82) in US data and 0.86 (0.80, 0.92) in UK data. Prospective validation resulted in an AUC of 0.89 (0.83, 0.96). The radiomics model performed similar to the two radiologists (US: 0.79 and 0.76, UK: 0.86 and 0.86, NL: 0.82 and 0.85). Interpretation: The radiomics model extended with automatic and minimally interactive segmentation methods accurately differentiated between lipomas and ALTs in two large, multi-center external cohorts, and in prospective validation, performing similar to expert radiologists, possibly limiting the need for invasive diagnostics. Funding: Hanarth fonds.

Various contextualized and cross-linguistic approaches of grammar teaching have yielded significant transfer effects on both metalinguistic knowledge and proficiency in reading, writing, listening, and speaking in the first and second languages. Nevertheless, a similar approach is absent in language teaching in the Netherlands, perpetuating the discrepancy between the intended, implemented, and attained objectives. This study endeavors to remedy this discrepancy by examining the effective characteristics of teaching materials promoting language awareness. To this end, a contextualized, cross-linguistic lesson series on the concept of ‘syntactical function’ was designed, targeting upper secondary students (aged 15-16) drawing from four design principles and an analysis of the Dutch, the English and the German language. Subsequently, the lesson series underwent expert consultation, focus group interviews and various impact measurements, yielding a significant positive influence on students’ motivation and language awareness in all three languages. This underlines the potential value of teaching materials promoting language awareness.

Relational event models (REMs) are the primary choice for the analysis of relational-event network data. However, the standard REM assumes static parameters, which hinders the modeling of time-varying dynamics. This assumption might be too restrictive in real-life scenarios, making a model that allows for time-varying parameters more valuable. We introduce a state-space extension of the relational event model as a way to tackle this problem. The model has three main attributes. First, it provides a statistical framework of the temporal change of the parameters. Second, it enables the forecasting of future parameter values (which can be utilized to simulate new networks that can account for temporal dynamics in out-of-sample predictions). Third, it requires smaller data structures to be loaded into computer memory compared to the standard REM; this makes the model easily scalable to large networks. We conduct empirical analyses on bike-sharing data, corporate communications, and interactions among socio-political actors to illustrate model usage and applicability.

Abstract Parkinson’s disease (PD) is characterized by a progressive loss of dopaminergic neurons in the substantia nigra. Recent literature has proposed two subgroups of PD. The “body-first subtype” is associated with a prodrome of isolated REM-sleep Behavior Disorder (iRBD) and a relatively symmetric brain degeneration. The “brain-first subtype” is suggested to have a more asymmetric degeneration and a prodromal stage without RBD. This study aims to investigate the proposed difference in symmetry of the degeneration pattern in the presumed body and brain-first PD subtypes. We analyzed 123I-FP-CIT (DAT SPECT) and 18F-FDG PET brain imaging in three groups of patients (iRBD, n = 20, de novo PD with prodromal RBD, n = 22, and de novo PD without RBD, n = 16) and evaluated dopaminergic and glucose metabolic symmetry. The RBD status of all patients was confirmed with video-polysomnography. The PD groups did not differ from each other with regard to the relative or absolute asymmetry of DAT uptake in the putamen (p = 1.0 and p = 0.4, respectively). The patient groups also did not differ from each other with regard to the symmetry of expression of the PD-related metabolic pattern (PDRP) in each hemisphere. The PD groups had no difference in symmetry considering mean FDG uptake in left and right regions of interest and generally had the same degree of symmetry as controls, while the iRBD patients had nine regions with abnormal left–right differences (p

National energy systems require flexibility to accommodate increasing amounts of variable renewable energy. This flexibility can be provided by demand-side management (DSM) from industry. However, the flexibility potential depends on the characteristics of each industrial process. The enormous diversity of industrial processes makes it challenging to evaluate the total flexibility provision from industry to sector-coupled energy systems. In this work, we quantify the maximum cost reductions due to industrial DSM in the net-zero sector-coupled Swiss energy system, and the relationship between cost reductions and various industrial process characteristics. We analyze the flexibility of industrial processes using a generic, process-agnostic model. Our results show that industrial DSM can reduce total energy system costs by up to 4.4%, corresponding to 20% of industry-related energy costs. The value of flexibility from industrial DSM depends not only on the process characteristics but also on the system’s flexibility alternatives, particularly for flexibility over seasonal time horizons. As one specific option for industrial DSM, we find that thermal energy storage (TES) technologies available today could realize between 28% and 61% of the maximum cost reductions from industrial DSM, making TES a promising DSM solution and showing that industrial DSM is an accessible and cost-effective flexibility option.

Abstract Background In the last decade, technical innovations have resulted in the development of several minimally invasive diagnostic cancer tools. Within women at high risk of developing ovarian cancer (OC) or endometrial cancer (EC) due to a hereditary cancer syndrome, there is an urgent need for minimally invasive and patient‐friendly methods to detect OC and EC at an early stage. Materials and Methods We performed a systematic search of studies using DNA methylation or mutation analysis, microbiome, or proteomics performed on cervicovaginal specimens (smear, swab, or tampon) intended to detect OC and EC published until January 2024. Results Included studies (n = 36) showed high heterogeneity in terms of biomarkers used and outcomes, and only a few studies reported on the detection of biomarkers in high‐risk subgroups. Conclusion Based on the findings in this review, DNA methylation techniques seem to be the most promising for detecting OC and EC at early stages in the general population. Future validation of cervicovaginal DNA methylation techniques is needed to determine whether this technique might be beneficial in hereditary high‐risk subgroups.

Key Clinical Message We describe a premature hydropic infant with Noonan syndrome and a therapy refractory chylothorax. This was shown to be due to a central conducting lymphatic anomaly. After therapy with a MEK‐inhibitor the infant recovered clinically and radiologically completely, possibly by restoring lymphatic valve function.

Summary: The energy transition is a multinational challenge to mitigate climate change, with a joint reduction target for greenhouse gas emissions. Simultaneously, each country is interested in minimizing its own energy supply cost. Still, most energy system models neglect national interests when identifying cost-optimal transition pathways. We design the European energy system transition until 2050, considering competition between countries in a shared electricity and carbon market using bilevel optimization. We find that national objectives substantially impact the transition pathway: Compared to the model solved using the common centralized optimization, the overall installed capacity increases by just 3% when including national interests. However, the distribution of the installed capacity changes dramatically by more than 40% in most countries. Our results underline the risk of miscalculating the need for national capacity expansion when neglecting stakeholder representation in energy system models and demonstrate the need for cooperation for an efficient energy transition.

Abstract Immune checkpoint inhibitors (ICI) improve overall survival in patients with metastatic urothelial cancer (mUC), but therapeutic success at the individual patient level varies significantly. Here we identify predictive markers of response, based on whole-genome DNA (n = 70) and RNA-sequencing (n = 41) of fresh metastatic biopsy samples, collected prior to treatment with pembrolizumab. We find that PD-L1 combined positivity score does not, whereas tumor mutational burden and APOBEC mutagenesis modestly predict response. In contrast, T cell-to-stroma enrichment (TSE) score, computed from gene expression signature data to capture the relative abundance of T cells and stromal cells, predicts response to immunotherapy with high accuracy. Patients with a positive and negative TSE score show progression free survival rates at 6 months of 67 and 0%, respectively. The abundance of T cells and stromal cells, as reflected by the TSE score is confirmed by immunofluorescence in tumor tissue, and its good performance in two independent ICI-treated cohorts of patients with mUC (IMvigor210) and muscle-invasive UC (ABACUS) validate the predictive power of the TSE score. In conclusion, the TSE score represents a clinically applicable metric that potentially supports the prospective selection of patients with mUC for ICI treatment.

Although the curriculum ideally serves the interests of its recipients, student perspectives have been marginalised in curriculum negotiation. Our objective is to better meet the needs and wishes of vocational education students by including them in planning, acting/observing and reflecting on the citizenship education curriculum. In this participatory action research project students were made responsible for designing, developing and delivering a lesson for their peers. Data collection consisted of interviews, focus group discussions and observations during three action rounds involving five classes. Even though many teachers were initially sceptical about their students' abilities, it turned out that students enjoyed engaging in curriculum negotiation. Students were the main drivers of the curriculum. Relevant factors for implementation were: teachers' beliefs about student capabilities and attitudes, changing roles and responsibilities, and safe and constructive classroom dynamics. Students were exposed to a wide variety of skills and challenges. Future research should focus on studying the same participants during multiple implementation rounds. Also, opportunities for curriculum negotiation activities within other topics should be explored. Lastly, a more rigid analysis of the learning outcomes as well as the impact on personal development of students and teachers would be recommended.