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ChronoLog is a new tool for computer-assisted chronological research. It allows its users to build models featuring chronological sequences (such as dynasties, stratigraphic sequences and historical periods) and synchronisms between the items of these sequences. Each item (reign of a king, archaeological stratum, historical period) can be provided with an exact or approximated start date, end date and duration. The software uses this information to compute the tightest possible estimates (expressed as ranges) for each date and duration. The tool also checks the validity of the model, and reports cases where the encoded data are contradictory. Such a tool is important as it allows users to examine large chronological models that are otherwise too difficult to study manually. The tool is used in an interactive way, allowing to immediately assess the impact of a given hypothesis on the overall chronological network. Users can thus check the impact of altered dates for a given king, or the addition of a new synchronism between two strata. They can also test hypotheses, in order to check, for example, if two kings were contemporaries. The software runs fast, allowing users to obtain instantaneous answers to the above-described queries. The presentation will feature a demo of ChronoLog and a case study.

The ability of pathogens to sense and respond to changes enables them to adapt and survive in hostile environments. In particular, microbes have developed a mechanism called quorum sensing, in which they produce, detect and respond to small, secreted molecules. One of the deadliest pathogens in humans is the parasite Plasmodium falciparum (Pf), the infectious agent of the malaria disease, accounting for the death of about half a million people annually. Here, we reveal that these parasites employ a quorum sensing-like mechanism to respond to their own density and coordinate their asexual growth during the blood stage of their life cycle. Namely, Pf parasites govern their own cell density by secreting active molecule(s). Using a combination of biochemical techniques, we chemically characterized the active fraction (autoinducer-like molecule) and revealed it to be a hydrophilic, positively charged molecule of a size ranging from 100Da to 4,000Da. Further purification using high-pressure liquid chromatography (HPLC) enabled the putative detection of two metabolites. Our finding suggests that malaria parasites signal each other to coordinate their asexual growth pattern is a previously unrecognized survival strategy. Identification and further investigation of the active secreted molecule can potentially lead to the development of anti-malaria drugs.

Magnetic Resonance Spectroscopy (MRS) can be used to measure the in-vivo concentrations of several metabolites in the brain non-invasively. I will present our work using MRS to study two aspects of brain metabolism. First, I'll talk about our work on functional MRS, whereby we look at neurochemical changes during or after learning or function. In the second half of the talk, I will focus on new methods we're developing in the lab, and in particular on our ability to measure the thermal relaxation times of metabolites, which probe specific cellular and subcellular microenvironments. I will present some preliminary data showing where and how this could be useful.