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Biology subjects

Dussauge, M.

Publications and source records attributed to Dussauge, M..

2 recordsLinked to original sources

Linking transcriptome to cell behavior in real time uncovers molecular fate-asymmetry and a quiescence cycle among adult neural stem cells

Adult neural stem cells (NSCs) are transcriptionally heterogeneous, yet the relationship between molecular heterogeneities and individual NSC trajectories remains unclear. Here, we link transcriptional identities with cellular features and measures of real time to identify molecular trajectories hidden within transcriptomic space. Among self-renewing NSCs, we resolve single-cell molecular transitions associated with fate asymmetry at division. We also show that individual self-renewing NSCs progressively transition from molecular states of deep to shallow quiescence during prolonged quiescence phases. Together, this work reveals individual NSC trajectories within transcriptomic space during fate decisions and state transitions. In particular, it highlights the existence of a transcriptionally encoded quiescence cycle followed by adult NSCs, independent of lineage progression, that balances division with cell growth to sustain self-renewal over time.

developmental biology↗

A single decreasing ramp friction sprint for torque-cadence relationship assessment during cycling

This study aimed to introduce and validate a novel method for assessing dynamic fatigue components through a single-sprint test, addressing the limitations of traditional multi-sprint evaluations. We tested this method on twenty-one participants by computing torque-cadence relationships from two iso-friction sprints at varying friction levels (3% and 9% of body mass), the traditional combination of these iso-friction sprints and a novel decreasing ramp friction sprint (FrD). The accuracy of this new method through fatigue was also tested with ten 6-s FrD sprints interspersed with a 24-s passive rest. FrD outperformed single iso-friction sprints and provided accurate and valid torque-cadence relationships parameters estimates (T0, C0, and Pmax) with systematic bias < 3%, typical error of estimate < 6% and very high r2 (median of 0.962). The quality of the input data from this method was also high, as evidenced by the well-distributed and wide-range cadence spectrum (51.3% of C0; skewness = -0.51, p < 0.05) and was maintained throughout the fatiguing exercise. Our novel method not only allows the dynamic fatigue components evaluation with only one sprint but also maintains accuracy and validity across varying fatigue states, offering significant advantages for both research and practical applications.

physiology↗