ABSP: an automated R tool to efficiently analyze region-specific CpG methylation from bisulfite sequencing PCR.

Motivation: Nowadays, epigenetic gene regulations are studied in each part of the biology, from embryonic development to diseases such as cancers and neurodegenerative disorders. Currently, to quantify and compare CpG methylation levels of a specific region of interest, the most accessible technique is the bisulfite sequencing PCR (BSP). However, no existing user-friendly tool is able to analyze data from all approaches of BSP.

Quantitative modeling of pentose phosphate pathway response to oxidative stress reveals a cooperative regulatory strategy.

Living cells use signaling and regulatory mechanisms to adapt to environmental stresses. Adaptation to oxidative stress involves the regulation of many enzymes in both glycolysis and pentose phosphate pathways (PPP), so as to support PPP-driven NADPH recycling for antioxidant defense. The underlying regulatory logic is investigated by developing a kinetic modeling approach fueled with metabolomics and C-fluxomics datasets from human fibroblast cells.

Protein level variability determines phenotypic heterogeneity in proteotoxic stress response.

Cell-to-cell variability in stress response is a bottleneck for the construction of accurate and predictive models which could guide clinical diagnosis and treatment of certain diseases, for example, cancer. Indeed, such phenotypic heterogeneity can lead to fractional killing and persistence of a subpopulation of cells which are resistant to a given treatment. The heat shock response network plays a major role in protecting the proteome against several types of injuries.

Transcriptomic Analysis of Breast Cancer Stem Cells and Development of a pALDH1A1:mNeptune Reporter System for Live Tracking.

Many solid cancers are hierarchically organized with a small number of cancer stem cells (CSCs) able to regrow a tumor, while their progeny lacks this feature. Breast CSC is known to contribute to therapy resistance. The study of those cells is usually based on their cell-surface markers like CD44 /CD24 or their aldehyde dehydrogenase (ALDH) activity.

Dynamical thermal dose models and dose time-profile effects.

Models of dose-effect relationships seek systematic and predictive descriptions of how cell survival depends on the level and duration of the stressor. The CEM43 thermal dose model has been empirically derived more than thirty years ago and still serves as a benchmark for hyperthermia protocols despitethe advent of regulatory network models. In this paper, we propose and realize a simple experimental test to assess whether mechanistic models can prove more reliable indicators for some protocols.