Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation

TÜRKİYE'NİN GÜNEYBATISINDAKİ (ORTA TOROSLAR) ALLOKTON GÜMÜŞLÜ BİRİMİNDE BULUNAN ALT JURA RADYOLERLERİ

Mesozoyik radyolerleri, yakın zamanlara kadar, biyostratigrafik etütlerde dikkate alınmamaktaydı. Söz konusu grubu oluşturan planktonik mikrofosillerin çok küçük ve evrensel olarak uzun bir zaman aralığında yaşamış olmaları, araştırmacılar tarafından biyostratigrafik etütlerde dikkate alınmamalarına yol açmıştır. Halen devam etmekte olan çalışmalar, radyolerlerin, Mesozoyikte hızlı bir evrim gösterdiklerine işaret etmektedir. Gerçekten de bazı cinsler ve türler kısa zaman aralığında yaşamış, özel ortam ve koşul aramamıştır. Günümüzde radyolarit çörtlerde bulunan numunelerin matriksten ayrılmasının mümkün olabilmesi nedeniyle radyolerler, stratigrafinin ve kompleks orojenik kuşaklardaki yapının yorumlanmasında çok önemli bir yer tutmaktadırlar (örneğin Oman'daki Şemail ofiyolitleri ve Hawasina kompleksi gibi). Bu yayında, Türkiye'deki Alt Jurada bulunan yeni onbir tür ve üç cinsle birlikte Kuzey Amerikandaki Jurada bulunan iki yeni türün tanımı yapılmaktadır

RADIO-CHIMIOTHERAPIE ADJUVANTE DES ADENOCARCINOMES DU PANCREAS (ETUDE RETROSPECTIVE MONOCENTRIQUE DE 24 CAS ET REVUE DE LA LITTERATURE)

NANTES-BU Médecine pharmacie (441092101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Which DTW Method Applied to Marine Univariate Time Series Imputation

Missing data are ubiquitous in any domains of applied sciences. Processing datasets containing missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Therefore, the aim of this paper is to build a framework for filling missing values in univariate time series and to perform a comparison of different similarity metrics used for the imputation task. This allows to suggest the most suitable methods for the imputation of marine univariate time series. In the first step, the missing data are completed on various mono-dimensional time series. To fill a missing sub-sequence (gap) in a time series, we first find the most similar sub-sequence to the sub-sequence before (resp. after) this gap according a Dynamic Time Warping (DTW)-cost. Then we complete the gap by the next (resp. previous) sub-sequence of the most similar one. Through experiments results on 5 different datasets we conclude that i) DTW gives the best results when considering the accuracy of imputation values and ii) Adaptive Feature Based DTW (AFBDTW) metric yields very similar shape of imputation values similar to the one of true values

DTW-Approach for uncorrelated multivariate time series imputation

Missing data are inevitable in almost domains of applied sciences. Data analysis with missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Some well-known methods for multivariate time series imputation require high correlations between series or their features. In this paper, we propose an approach based on the shape-behaviour relation in low/un-correlated multivariate time series under an assumption of recurrent data. This method involves two main steps. Firstly, we find the most similar sub-sequence to the sub-sequence before (resp.after) a gap based on the shape-features extraction and Dynamic Time Warping algorithms. Secondly, we fill in the gap by the next (resp.previous) sub-sequence of the most similar one on the signal containing missing values. Experimental results show that our approach performs better than several related methods in case of multivariate time series having low/non-correlations and effective information on each signal

Le livre technique avant le xxe siècle

L'histoire du livre technique constitue un champ neuf et peu développé. Si elle est relativement moins connue que celle du livre de science ou de la littérature artistique, elle concerne pourtant une production extrêmement riche, qui représente et met à l'œuvre l'intelligence pratique et l'esprit d'invention. Il suffit de penser aux Descriptions des arts et métiers, commandées au plus haut sommet de l'État sous l'Ancien Régime, aux spectaculaires « théâtres de machines », aux manuels de fonctionnaires circulant dans tout l'empire chinois, aux multiples traités qui ont formé des générations d'ingénieurs ou encore aux guides techniques destinés à améliorer les pratiques des artisans et des agriculteurs, pour comprendre qu'il s'agit d'une littérature importante à caractère universel faisant l'objet de circulations intenses entre les différentes parties du globe. L'objet de ce livre est à la fois de combler une lacune du champ historique et d'interroger les relations entre l'économie du livre et le monde de la technique afin d'analyser la catégorie du livre technique à travers ses formes, ses fonctions, ses modes de diffusion et d'appropriation, avant le xxe siècle. Cet ouvrage contribue ainsi au dynamisme de l'histoire des techniques, soucieuse d'affirmer sa dimension culturelle, comme une histoire des savoirs et des représentations, et de s'inscrire dans les débats de l'histoire globale