Abrupt end of the last interglacial s.s. in north-east France

Close study of past interglacials might indicate how and when the present interglacial will end and whether the limit is heading towards a warming or a cooling. No certain prediction has been possible because of man's interference with the environment. But it is reported that when exploring the records of past temperate intervals frequent signs of abrupt changes of local environment were observed. In particular, abrupt shifts in forest composition end each Pleistocene interglacial whose record was studied in detail. In Grand Pile (north-east France), the Eemian (s.s.) (oxygen isotope substage 5e) temperate forest was replaced by a pine-spruce-birch taiga within ~150+/-75 yr. These results are based on rich pollen content of continuously deposited laminated gyttja and on the assumption of a constant sedimentation rate during the last 11000-yr long interglacial.Anglai

A Machine Learning Approach to Predict Interdose Vancomycin Exposure

International audienceIntroduction Estimation of vancomycin area under the curve (AUC) is challenging in the case of discontinuous administration. Machine learning approaches are increasingly used and can be an alternative to population pharmacokinetic (POPPK) approaches for AUC estimation. The objectives were to train XGBoost algorithms based on simulations performed in a previous POPPK study to predict vancomycin AUC from early concentrations and a few features (i.e. patient information) and to evaluate them in a real-life external dataset in comparison to POPPK. Patients and Methods Six thousand simulations performed from 6 different POPPK models were split into training and test sets. XGBoost algorithms were trained to predict trapezoidal rule AUC a priori or based on 2, 4 or 6 samples and were evaluated by resampling in the training set and validated in the test set. Finally, the 2-sample algorithm was externally evaluated on 28 real patients and compared to a state-of-the-art POPPK model-based averaging approach. Results The trained algorithms showed excellent performances in the test set with relative mean prediction error (MPE)/ imprecision (RMSE) of the reference AUC = 3.3/18.9, 2.8/17.4, 1.3/13.7% for the 2, 4 and 6 samples algorithms respectively. Validation in real patient showed flexibility in sampling time post-treatment initiation and excellent performances MPE/ RMSE<1.5/12% for the 2 samples algorithm in comparison to different POPPK approaches. Conclusions The Xgboost algorithm trained from simulation and evaluated in real patients allow accurate and precise prediction of vancomycin AUC. It can be used in combination with POPPK models to increase the confidence in AUC estimation. KEY WORDS machine learning • model informed precision dosing • population pharmacokinetics • simulations • vancomycin * Jean-Baptiste Woillar

The Impact on Europe of Large-Scale Climatic Changes: The Onset of Glaciation and the Last Deglaciation

International audienc

A pre-Late Devensian pollen site from Camp Fauld, Buchan, north-east Scotland

Recent investigations at Camp Fauld in Buchan, Scotland have yielded two peat deposits of pre-late Devensian age. Percentage pollen diagrams are presented. One peat is radiocarbon-dated to 34-39 ka sp, which prompts correlation with the Hengelo-Denekamp sequence of NW continental Europe, but the pollen evidence, revealing the presence of a birch-pine woodland, suggests an earlier stage. The second peat deposit records an open shrub-tundra in which Bruckenthalia spiculifolia is present. The peat yielded a radiocarbon date of 40-51 ka sp, but is suspected of having been contaminated by younger carbon. That suspicion and the presence of Bruckenthalia suggest that a correlation, based on the radiocarbon date, with the Glinde interstadial, identified in NW Germany, would be incorrect. Correlation with other Scottish pre-late Devensian sites has proved to be difficult