Valérie Gailus‐Durner

This study identifies extensive phosphoproteomic remodeling in mouse sperm during maturation and capacitation, revealing key kinases and their roles in fertility.

This study evaluates ratio-based normalization in heart weight analysis using mouse data, finding that ratios often misrepresent group differences and advocating for linear models with covariate adjustment.

This study integrates proteomic data from 12 vertebrate species to identify a core sperm proteome, revealing conserved molecular pathways and validating novel proteins critical for fertility.

This study establishes TTE reference ranges for mice, showing anesthesia significantly affects cardiac function, with minimal sex differences and modest age-related changes.

This study compares TRα and TRβ knockout mice with DNA-binding-deficient mutants to show noncanonical TR signaling contributes to physiological functions beyond canonical genomic pathways.

This study shows that thyroid hormone-induced cardiac hypertrophy relies on noncanonical TR action, while heart rate regulation depends on canonical TR action, with TRβ compensating for TR absence.

This study shows TRPS1 maintains luminal progenitors in the mammary gland by repressing SRF/MRTF activity, linking it to mechanotransduction and breast cancer initiation.

The paper identifies weaning body weight as a key predictor of adult diabetes in TALLYHO/JngJ mice, highlighting its relevance to childhood obesity research.

The paper identifies monoallelic DHX9 variants as a cause of neurodevelopmental disorders and Charcot-Marie-Tooth disease, showing genotype-phenotype correlations and cellular dysfunction.

The paper reports the generation of over 5,000 new mouse mutant strains for targeted genes, significantly expanding the available genetic resources for biomedical research.

This study shows that SERF2 deletion changes amyloid fibril structure in Alzheimer's mouse models, suggesting SERF's role in modifying amyloid aggregation.

The paper integrates gene essentiality data from human and mouse screens to classify genes into FUSIL categories, identifying developmental lethal genes associated with rare diseases.

The paper introduces a method called soft windowing to improve analysis of high-throughput phenotyping data by reducing false positives and increasing significant results.