Deguilloux M.-F.,University of Bordeaux 1 |
Pemonge M.-H.,University of Bordeaux 1 |
Dubut V.,University of Bordeaux 1 |
Hanni C.,CNRS Lyon Institute of Functional Genomics |
And 4 more authors.
American Journal of Physical Anthropology | Year: 2011
Molecular anthropology has been widely used to infer the origin and processes of the colonization of Polynesia. However, there are still a lack of representative geographical studies of Eastern Polynesia and unchallenged genetic data about ancient Polynesian people. The absence of both of these elements prevents an accurate description of the demographic processes of internal dispersion within the Polynesian triangle. This study provides a twofold analysis of ancient and modern mtDNA in the eastern part of French Polynesia: the Gambier Islands. The paleogenetic analyses conducted on burials of the Temoe Atoll (14 th-17 th centuries) represent the first fully authenticated ancient human sequences from Polynesia. The identification of the "Melanesian" Q1 mtDNA lineage in ancient human remains substantiates the Near Oceanic contribution to the early gene pool of this region. Modern samples originate from Mangareva Island. Genealogical investigations enable us to reliably identify the conservation of the Melanesian component in Easternmost Polynesia, despite recent European colonization. Finally, the identification of rare mutations in sequences belonging to haplogroup B4a1a1a provides new perspectives to the debate on the internal peopling of the Polynesian region. Altogether, the results laid out in our study put the emphasis on the necessity of controlled sampling when discussing the internal settlement of Polynesia. Am J Phys Anthropol, 2011. © 2010 Wiley-Liss, Inc.
Bouazizi E.,University of Tunis |
Naeck R.,Center Hospitalier Intercommunal Of Toulon La Seyne |
D'Amore D.,Center Hospitalier Intercommunal Of Toulon La Seyne |
Mateo M.-F.,Center Hospitalier Intercommunal Of Toulon La Seyne |
And 8 more authors.
Biomedical Signal Processing and Control | Year: 2016
Polysomnography (PSG) is the recording during sleep of multiple physiological parameters enabling to diagnose sleep disorders and to characterize sleep fragmentation. From PSG several sleep characteristics such as the micro arousal rate (MAR), the number of sleep stages shifts (SSS) and the rate of intra sleep awakenings (ISA) can be deduced each having its own fragmentation threshold value and each being more or less important (weight) in the clinician's diagnosis according to his specialization (pulmonologist, neurophysiologist and technical expert). In this work we propose a mathematical model of sleep fragmentation diagnosis based on these three main sleep characteristics (MAR, SSS, ISA) each having its own threshold and weight values for each clinician. Then, a database of 111 PSG consisting of 55 healthy adults and 56 adult patients with a suspicion of obstructive sleep apnoea syndrome (OSAS), has been diagnosed by nine clinicians divided into three groups (three pulmonologists, three neurophysiologists and three technical experts) representing a panel of polysomnography experts usually working in a hospital. This has enabled to determine statistically the thresholds and weights values which characterize each clinician's diagnosis. Thus, we show that the agreement between each clinician's diagnosis and each corresponding mathematical model goes from substantial (κ > 61%) to almost perfect (κ > 81%), according to their specialization and so, that the mean value of the agreements of each group is also substantial (κ > 73%) despite the existing variability between clinicians. It follows from this result that our mathematical model of sleep fragmentation diagnosis is a posteriori validated for each clinician. © 2015 Elsevier Ltd. All rights reserved.