CRV (Netherlands)

Patients with Chronic Obstructive Pulmonary Disease (COPD) often experience limited health literacy, hampering health status assessment via standard questionnaires like the Clinical COPD Questionnaire (CCQ). We aimed to develop and validate a modified, literacy-sensitive version, the CCQgraphic (CCQg), for all patients with COPD co-designed with a large stakeholder group. CCQ items were rephrased and complemented with graphics, followed by optimization through semi-structured interviews with patients with limited health literacy. In adequate health literacy (n = 64) concordance of CCQg and CCQ was 0.88 (95% CI: 0.82-0.92). Correlation with the COPD Assessment Test (CAT) was 0.81 (95% CI: 0.70–0.88). Agreement showed a mean bias of 0.22 (95% CI: 0.10–0.34, P < 0.001) with higher scores on mental and functional domains compared to the original CCQ. Test-retest reliability in limited health literacy (n = 25) was high, CCC = 0.93 (95% CI: 0.86–0.97). The majority (88%) rated the CCQg as equal or better to the original. The CCQg offers a validated, literacy-sensitive tool, narrowing the gap in health status assessment for patients with COPD with varying literacy skills.

The energy transition has caused severe congestion in distribution networks, leading to economic and societal challenges. In the Netherlands, grid congestion hampers business growth and incurs significant costs per MWh of energy not delivered. Local electricity markets (LEMs) offer a potential solution to grid congestion by enabling local energy trading, which aligns local production and consumption to improve grid utilization. However, real-world adoption faces challenges in ensuring adequate market conditions, such as sufficient liquidity and complementarity between production and consumption profiles. This study analyzes the energy profiles of Dutch wholesale market participants serving energy communities, industrial parks, and decentralized governments, using real-life 15-minute interval data from the ENTRNCE Trader platform in 2024. The Dutch case study demonstrates that these diverse consumption and production profiles are indeed complementary and capable of trading locally under real-world conditions. Moreover, the findings reveal that the volume of energy traded locally can be further increased after implementing a LEM. This suggests that, in general, LEMs could achieve sufficient liquidity when these diverse profiles combine, paving the way for both time and financial investment in their development.

Heat stress is a major environmental challenge affecting dairy cattle, leading to behavioral changes, production losses, and welfare concerns. As heat stress events intensify and become more frequent due to climate change, identifying animals that are able to maintain high production levels during heat stress events, commonly referred to as heat tolerance, is crucial for sustainable dairy production. In this study, we develop a pipeline to quantify the population-wise impact of heat stress on a dairy cattle population and subsequently define individual-based heat tolerance traits. Data from 677,318 Dutch Holstein cows were analyzed, including 15.6 million mid-infrared spectra and 762 million records from automated milking systems. An iterative approach using kernel regression was employed to estimate the population-wise effects of heat stress. Results indicate that fat and protein percentages decrease approximately linearly with increasing temperature-humidity index (THI), with an absolute reduction of 0.3% as THI increases from 30 to 70. In contrast, milk yield remains stable until a THI of 60, after which production losses increase quadratically, reaching a loss of 5.0% at a THI of 75. We subsequently define the heat tolerance phenotype of an animal as the slope from a linear regression model of the residuals of the population-wise models against THI for milk yield, concentration of fat, protein, lactose, and specific fatty acids. Compared with reaction-norm models, individual records per cow are combined into one joint record before model fitting, thus reducing computing times and allowing more flexibility in the design of the model. Heritabilities for heat tolerance traits ranged from 0.05 to 0.12, and genetic variances indicate substantial potential for breeding as an improvement of the population by 1 genetic standard deviation would already offset 69% of the losses in fat percentage, 65% in protein percentage, and 11% in milk yield. Heat tolerance based on milk yield showed favorable correlations with most commercial traits, whereas heat tolerance based on fat and protein percentage showed negative correlations with health and resilience. A GWAS using both SNPs and haplotype blocks from the software HaploBlocker identified potential QTL across the genome, with particularly strong signals on BTA5, 14, and 20. These findings support the long-term potential of genetic improvement through breeding for heat tolerance but highlight the need for complementary management strategies to mitigate heat stress impacts in the short term.

Meiotic recombination is an essential biological process that ensures proper chromosome segregation and creates genetic diversity. Individual variation in global recombination rates has been shown to be heritable in several species, and variants significantly associated with this trait have been identified. Recombination on the sex chromosome has often been ignored in these studies although this trait may be particularly interesting as it may correspond to a biological process distinct from that on autosomes. For instance, recombination in males is restricted to the pseudo-autosomal region (PAR). We herein used a large cattle pedigree with more than 100,000 genotyped animals to improve the genetic map of the X chromosome and to study the genetic architecture of individual variation in recombination rate on the sex chromosome (XRR). The length of the genetic map was 46.4 and 121.2 cM in males and females, respectively, but the recombination rate in the PAR was six times higher in males. The heritability of CO counts on the X chromosome was comparable to that of autosomes in males (0.011) but larger than that of autosomes in females (0.024). XRR was highly correlated (0.76) with global recombination rate (GRR) in females, suggesting that both traits might be governed by shared variants. In agreement, a set of eleven previously identified variants associated with GRR had correlated effects on female XRR (0.86). In males, XRR and GRR appeared to be distinct traits, although more accurate CO counts on the PAR would be valuable to confirm these results.

BackgroundSequence-based genome-wide association studies (GWAS) provide high statistical power to identify candidate causal mutations when a large number of individuals with both sequence variant genotypes and phenotypes is available. A meta-analysis combines summary statistics from multiple GWAS and increases the power to detect trait-associated variants without requiring access to data at the individual level of the GWAS mapping cohorts. Because linkage disequilibrium between adjacent markers is conserved only over short distances across breeds, a multi-breed meta-analysis can improve mapping precision.ResultsTo maximise the power to identify quantitative trait loci (QTL), we combined the results of nine within-population GWAS that used imputed sequence variant genotypes of 94,321 cattle from eight breeds, to perform a large-scale meta-analysis for fat and protein percentage in cattle. The meta-analysis detected (p ≤ 10−8) 138 QTL for fat percentage and 176 QTL for protein percentage. This was more than the number of QTL detected in all within-population GWAS together (124 QTL for fat percentage and 104 QTL for protein percentage). Among all the lead variants, 100 QTL for fat percentage and 114 QTL for protein percentage had the same direction of effect in all within-population GWAS. This indicates either persistence of the linkage phase between the causal variant and the lead variant across breeds or that some of the lead variants might indeed be causal or tightly linked with causal variants. The percentage of intergenic variants was substantially lower for significant variants than for non-significant variants, and significant variants had mostly moderate to high minor allele frequencies. Significant variants were also clustered in genes that are known to be relevant for fat and protein percentages in milk.ConclusionsOur study identified a large number of QTL associated with fat and protein percentage in dairy cattle. We demonstrated that large-scale multi-breed meta-analysis reveals more QTL at the nucleotide resolution than within-population GWAS. Significant variants were more often located in genic regions than non-significant variants and a large part of them was located in potentially regulatory regions.

BackgroundPredicting clinical outcomes after cardiac resynchronization therapy (CRT) and its optimization remain a challenge. We sought to determine whether pre‐ and postimplantation QRS area (QRSarea) predict clinical outcomes after CRT.Methods and ResultsIn this retrospective study, QRSarea, derived from pre‐ and postimplantation vectorcardiography, were assessed in relation to the primary end point of cardiac mortality after CRT with or without defibrillation. Other end points included total mortality, total mortality or heart failure (HF) hospitalization, total mortality or major adverse cardiac events, and the arrhythmic end point of sudden cardiac death or ventricular arrhythmias with or without a shock. In patients (n=380, age 72.0±12.4 years, 68.7% male) undergoing CRT over 7.7 years (median follow‐up: 3.8 years [interquartile range 2.3–5.3]), preimplantation QRSarea ≥102 μVs predicted cardiac mortality (HR: 0.36; P<0.001), independent of QRS duration (QRSd) and morphology (P<0.001). A QRSarea reduction ≥45 μVs after CRT predicted cardiac mortality (HR: 0.19), total mortality (HR: 0.50), total mortality or heart failure hospitalization (HR: 0.44), total mortality or major adverse cardiac events (HR: 0.43) (all P<0.001) and the arrhythmic end point (HR: 0.26; P<0.001). A concomitant reduction in QRSarea and QRSd was associated with the lowest risk of cardiac mortality and the arrhythmic end point (both HR: 0.12, P<0.001).ConclusionsPre‐implantation QRSarea, derived from vectorcardiography, was superior to QRSd and QRS morphology in predicting cardiac mortality after CRT. A postimplant reduction in both QRSarea and QRSd was associated with the best outcomes, including the arrhythmic end point.