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Placental gene expression of the AMPK signaling pathway in association with gestational exposure to ambient air pollution
No full textObjective: Prenatal ambient air pollution exposure is able to reach the fetus by crossing the placenta, a highly metabolically active organ. The adenosine monophosphate-activated protein kinase (AMPK) signaling pathway is a crucial regulator of the placental cellular metabolism, necessary for normal placental and fetal development. This study investigates the association between in utero exposure to BC, NO2, and PM2.5, and differences in placental gene expression of the AMPK signaling pathway at birth. Material and methods: Transcription data from 182 placentas of the ENVIRONAGE birth cohort were obtained through microarray analysis. Exposure levels were estimated using a spatio-temporal model for the mothers' residential address during pregnancy. The associations between transcription levels of 76 genes, clustered by the cascades of the AMPK signaling pathway, and the air pollution exposures during different time windows of pregnancy were analyzed using a mixed-effects model adjusting for potential confounders. Results: Higher prenatal levels of BC, NO2, and PM2.5 were associated with downregulated gene expression of the central AMPK gene cluster and multiple upstream and downstream cascades of the AMPK signaling pathway. In a multi-pollutant model, the observed patterns of downregulation remained, supporting the robustness of the associations when considering co-exposure to different air pollutants. Conclusion: This study provides new insights into the possible adverse effects of ambient air pollution exposure on placental development, affecting the placental metabolism at the transcript level. Whether reduced placental AMPK signaling may play a role in air pollution-induced birth outcomes and their long-term consequences needs to be further addressed
Risk of new HIV diagnosis by intersecting migration, socioeconomic, and mental health vulnerabilities in the Netherlands:a nationwide analysis of the ATHENA cohort and Statistics Netherlands registry data
No full textBackground: To further reduce new HIV diagnoses in the Netherlands, individual and structural barriers hindering prevention must be addressed. We aimed to estimate the disproportional burden of new HIV diagnoses and explore how intersecting socio-demographic, socio-economic, and health-related factors jointly influence the risk of a new HIV diagnosis. Methods: We combined data from the ATHENA cohort, an ongoing nationwide HIV cohort, with registry data from Statistics Netherlands. We selected individuals with a new HIV diagnosis between 1 January 2012 and 31 December 2023 and matched them to individuals from the general population. We assessed determinants of a new HIV diagnosis using a multivariable generalized linear model. We used Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to quantify the joint and individual contribution of intersecting variables. Findings: 6055 men and 1020 women were newly diagnosed with HIV. Having a migration background and a low to middle income or income below the poverty line was associated with a higher risk of a new HIV diagnosis for both men (low to middle: adjusted odd ratio (aOR) = 1.24, 95% confidence interval (CI) = 1.17–1.31; below the poverty line: aOR = 1.75, 95% CI = 1.62–1.89) and women (low to middle: aOR = 2.49, 95% CI = 2.05–3.01; below the poverty line: aOR = 4.71, 95% CI = 3.80–5.83). Use of mental health care (aOR = 1.14, 95% CI = 1.01–1.27) or antidepressants (aOR = 1.66, 95% CI = 1.50–1.84) also increased the risk among men; while receiving social welfare (aOR = 1.39, 95% CI = 1.15–1.67) and use of antipsychotic medication (aOR = 1.66, 95% CI = 1.21–2.28) increased the risk among women. Of all intersections identified in MAIHDA, men with a first-generation migration background, income below the poverty line, and who used antidepressants had the highest predicted probability of an HIV diagnosis (0.036%, 95% confidence interval (CI) = 0.025–0.052). Women with a first-generation background, income below the poverty line, who received social welfare, and who used antipsychotic medication had the highest predicted risk (0.019%, 95% CI = 0.011–0.035). Interpretation: A disproportionally higher burden of a new HIV diagnosis was observed for individuals with a migration background and economic and mental health vulnerabilities. HIV prevention and testing need to be reinforced in these groups. Funding: Dutch Ministry of Health, Welfare and Sport; TKI Health Holland
Brain development and musical skills:A longitudinal twin study on brain developmental trajectories and sensorimotor synchronization
No full textThere are individual differences in brain developmental patterns, yet it is unknown to what extent these may be driven by enriched experiences. Moreover, it is not well known whether enriched experiences may result in attenuated or accelerated brain development. Studying the relation between music performance and the brain using a large longitudinal twin study provides a framework for better understanding the genetic and environmental effects on brain development in childhood. The present region-of-interest study tested whether individual differences in sensorimotor synchronization with an auditorily cued finger tapping task are related to individual differences in developmental brain trajectories and if this relation was genetically or environmentally driven. The present study included a longitudinal twin design with up to 3 MRI waves of data (7–14 years old; N<inf>t1</inf> = 418, N<inf>T2</inf> = 367, N<inf>T3</inf> = 228). In line with our preregistered hypotheses, results showed that attenuated patterns of brain development in 27 % of motor and affective ROIs were associated with SMS performance independent of socio-economic status effects. Furthermore, brain-behavior associations were at least partly driven by shared and unique environmental/measurement error effects, in addition to genetic influences. Possibly, attenuated brain development may be indicative of prolonged brain plasticity related to enriched environmental experiences, such as musical training, in addition to predisposing genetic factors
De tekortschietende Nederlandse conceptwet implementatie anti-SLAPP-richtlijn:Aanbevelingen om te voorkomen dat de richtlijn een papieren tijger wordt
No full textStrategische rechtszaken tegen publieke participatie (SLAPP’s) vormen wereldwijd een ernstige bedreiging voor het recht op vrijheid van meningsuiting en het recht op informatie. Ter bescherming van SLAPPdoelwitten is in de EU de anti-SLAPP-richtlijn aangenomen. Deze richtlijn bevat minimumnormen voor nationale procedurele waarborgen in grensoverschrijdende burgerlijke zaken, die uiterlijk op 7 mei 2026 door de EU-lidstaten, met uitzondering van Denemarken, moeten worden geïmplementeerd. In deze bijdrage wordt betoogd dat het Nederlandse wetsvoorstel ter implementatie van de anti-SLAPP-richtlijn tekortschiet, waardoor geen effectieve bescherming voor SLAPP-doelwitten wordt geboden. Daarnaast worden aanbevelingen gedaan voor een effectieve en brede anti-SLAPP-bescherming in Nederland
Cross-border victims in the Netherlands
No full textThis chapter presents the situation of cross-border victims in the Netherlands, a country that is a major tourist destination, as well as an important travel, migration, and economic hub (with Schiphol Airport and the Rotterdam Harbour). The Netherlands also serves as a destination for large numbers of labour and refugee immigrants. The author observes that while the legal framework of victims’ rights is well established, the legal and policy framework relevant to cross-border victims in the Netherlands remains a developing field. The chapter includes a summary of the current state of victim rights in the Netherlands, with particular attention paid to the rights available to cross-border victims (foreign residents who were victimized in the Netherlands and Dutch residents victimized abroad). It also discusses victim support services and the access cross-border victims have to these services in practice, drawing heavily on the author's interviews with four practitioners and policymakers working in the field of criminal justice or victim support. The chapter ends with examples of good practices in the field of confiscation and residence rights, as well as some closing remarks on the desired development of victim support and protection
Automatic localization of myocardial infarction using vectorcardiography
No full textFor patients experiencing myocardial infarction (MI), localizing the affected cardiac region using electrocardiography (ECG) can reduce the time to reperfusion therapy, reducing morbidity and mortality. Extracting relevant information from ECG signals is not trivial, and computational methods have been developed aiming to assist physicians in making faster and better decisions in emergency situations. However, their clinical adoption remains limited due to the high false alarm rates consequence of the low generalizability of these methods. This research compares the performance of three machine learning techniques - Lasso, Support Vector Machine, and Gradient Boosting Machine - with varying degrees of complexity in localizing MI. Vectorcardiography-derived features were used as input to the models due to their ability to capture spatial and temporal information regarding the heart's electrical activity. An autoencoder was employed to smooth the feature space, facilitating more efficient model training and improving generalization. To further address generalizability challenges, an inter-patient validation approach was employed. Models were trained on the PTB-XL dataset and externally validated on the PTB Diagnostic dataset. Results demonstrate that Lasso, a simpler model, achieved the highest AUC of 0.74 on the external dataset, outperforming more complex models such as SVM (0.72) and GBM (0.68). Also, the combination of Lasso with the autoencoder provided superior generalization compared to other state-of-the-art methods reported in the MI localization literature. This highlights the proposed method's suitability for clinical settings, where model generalizability and reliability are critical. Furthermore, our method offers the advantage of explainability, allowing the extraction of clinical and physiological insights from the data and bridging the gap between computational methods and clinicians
Perinatal Exposure to the Neonicotinoid Thiacloprid Impacts Transcription of Neuroplasticity and Neuroendocrine Markers in Mice but Not in the Zebrafish Model
No full textNeonicotinoids are widely used insecticides in agriculture, aquaculture, pet care, and urban pest control. Initially developed to selectively target the insect cholinergic system, their extensive use has raised concerns about adverse effects on nontarget vertebrates. This study investigated the developmental neurotoxicity of the neonicotinoid thiacloprid using two vertebrate models: zebrafish and mice. Transgenic cyp19a1b-GFP zebrafish eleutheroembryos, which report estrogenic activity, were exposed to thiacloprid (10-6-10-8 M) for 4-5 days. No significant changes were observed in GFP expression or neuroplasticity and neuroendocrine markers, suggesting a limited impact in this aquatic model. In contrast, prenatal exposure of mice to thiacloprid (0.06, 0.6, or 6 mg/kg/day from embryonic day 6.5 to 15.5) produced dose-, sex-, and region-specific alterations in brain gene expression during adolescence (postnatal day 35). At low to mid doses, markers of neurogenesis and plasticity, such as doublecortin in the amygdala, neurogenin, nestin, and PCNA in the hippocampus and cerebellum, were upregulated. However, high-dose exposure (6 mg/kg/day) led to reduced expression of these markers, including BDNF in the hypothalamus and PCNA in the hippocampus, particularly in females. These results indicate that thiacloprid, even at low doses, can subtly but significantly affect mammalian brain development. Further research is needed to assess the neurodevelopmental risks of neonicotinoids in vertebrates, including humans
Minimum sample size calculation for radiomics-based binary outcome prediction models:Theoretical framework and practical example
No full textBACKGROUND AND PURPOSE: Determining the appropriate sample size for developing robust radiomics-based binary outcome prediction models and identifying the maximum number of predictors safely allowable within a fixed dataset size remain critical yet challenging tasks. This study aims to propose and demonstrate a structured method for addressing these issues, enhancing methodological rigor and practicality in radiomics research. MATERIALS AND METHODS: We introduce a comprehensive sample size calculation framework for binary outcome prediction models in radiomic studies. The proposed approach integrates three key criteria: (1) maintaining a global shrinkage factor (S) = 0.9 to control model overfitting, (2) ensuring a minimal absolute difference between apparent and adjusted performance metrics, and (3) precisely estimating the overall outcome risk. Additionally, we develop an accessible online calculation tool enabling researchers to efficiently determine either the minimum sample size or the maximum number of predictors permissible, based on clearly defined statistical parameters. RESULTS: The presented method systematically addresses model overfitting by integrating a global shrinkage factor into the calculation, providing robust estimates compared with traditional heuristic approaches ("rules of thumb"). Practical examples demonstrate that this structured method effectively balances predictive accuracy and generalizability, while the online tool provides researchers with a user-friendly platform to perform the necessary calculations. CONCLUSION: Clear justification of sample size decisions is essential for developing reliable predictive models in radiomics research. By adopting a structured and rigorous calculation method, researchers can effectively minimize overfitting, ensure accurate risk estimation, and substantially enhance the reliability and validity of their predictive models