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The apoptosis of bronchial and alveolar epithelial cells plays a key role in chronic obstructive pulmonary disease (COPD). The endoplasmic reticulum (ER) stress induced by cigarette smoke contributes to apoptosis. Previous studies demonstrated that melatonin prevented the development of COPD. In addition, silent information regulator 1 (SIRT1) had a protective effect against COPD. However, it remains unclear whether SIRT1 is involved in the protection of melatonin against COPD. In this study, 32 male Wistar rats were randomly assigned to 4 groups: Control, COPD, COPD + Mel, and COPD + Mel + EX527. Rats were challenged with cigarette smoke and lipopolysaccharide with or without melatonin or EX527 (a selective inhibitor of SIRT1). The lung histopathology, apoptotic index, as well as the protein expressions of cleaved caspase-3, SIRT1, C/EBP homologous protein, and caspase-12 in the lung tissues were measured. These results demonstrated that melatonin attenuated apoptosis and ER stress in the lung tissues of rats with COPD. In addition, melatonin increased SIRT1 expression in lung tissues of rats with COPD, while inhibition of SIRT1 by EX527 upregulated ER stress and abolished the protective effect of melatonin against apoptosis. In conclusion, these findings suggested that melatonin protected against COPD by attenuating apoptosis and ER stress via upregulating SIRT1 expression in rats. Key words: COPD, melatonin, apoptosis, endoplasmic reticulum stress, SIRT1. L'apoptose des cellules epitheliales bronchiques et alveolaires joue un role cle dans les maladies pulmonaires obstructives chroniques (MPOC). Par ailleurs, le stress du reticulum endoplasmique (RE) engendre par la fumee de cigarette contribue a l'apoptose. Des etudes anterieures ont montre que la melatonine (Mel) permet de prevenir l'apparition des MPOC. De plus, SIRT1 (pour<>) a un effet protecteur contre les MPOC. Cependant, il reste a clarifier si SIRT1 joue un role dans la protection que la Mel exerce contre les MPOC. Dans cette etude, nous avons reparti aleatoirement 32 rats Wistar males dans 4 groupes: temoin, MPOC, MPOC + Mel et MPOC + Mel + EX527. Nous avons expose les rats a des epreuves de provocation a la fumee de cigarette et a des lipopolysaccharydes avec ou sans Mel ou EX527 (un inhibiteur selectif de SIRT1). Nous avons etudie l'histopathologie du poumon, l'indice apoptotique, ainsi que mesure l'expression en proteines de la caspase 3 clivee, de SIRT1, de la proteine homologue a C/EBP et de la caspase 12 dans les tissus pulmonaires. Ces resultats ont montre que la Mel permettait d'attenuer l'apoptose et le stress du RE dans les tissus pulmonaires de rats atteints de MPOC. De plus, la Mel entrainait une augmentation de l'expression de SIRT1 dans les tissus pulmonaires de rats atteints de MPOC, tandis que l'inhibition de SIRT1 par l'EX527 entrainait une regulation a la hausse du stress du RE, avec une annihilation de l'effet protecteur qu'exerce la Mel contre l'apoptose. En conclusion, ces resultats ont laisse entendre que la Mel aurait exerce un effet protecteur contre les MPOC en attenuant l'apoptose et le stress du RE par l'intermediaire d'une regulation a la hausse de l'expression de SIRT1 chez le rat. [Traduit par la Redaction] Mots-cles: MPOC, melatonine, apoptose, stress du reticulum endoplasmique, SIRT1., Introduction Chronic obstructive pulmonary disease (COPD) is predicted to be the third-leading cause of death by 2020 and has become a major health problem worldwide (GBD 2015 Mortality and Causes [...]

The Naxiguole Banded Iron Formation (BIF), located in the Eastern Kunlun Orogenic Belt, Northwest China, is hosted by the Jinshuikou Group and has a Fe of 75 Mt at a grade of 15–28.83 wt.% Fe. In this paper, we use integrated petrological, geochemical, and geochronological data to limit the age and origin of the Naxiguole BIF. Country rocks mainly comprise marble, felsic paragneiss, plagioclase amphibolite schist, and biotite plagioclase gneiss. The features of sedimentary structure (blastopsammitic texture and blastobedding structure) and trace elements (e.g. La, Ni, Zr) from the country rock indicate that their protoliths are sedimentary rock. The 141 detrital zircons from the Jinshuikou Group yield a minimum age of 908 Ma, which can be considered the upper limit for the Naxiguole BIF. According to the age (602 Ma) of the mafic rocks intruding into the Jinshuikou Group, it is reasonable to assume that the formation age of BIF can be limited at 908–602 Ma (i.e. Neoproterozoic). The high contents of Al2O3 + TiO2 (3–6 wt.%), ΣREE (36–135 ppm) for BIF samples suggest that terrestrial clastic material contributed to BIF formation. The BIF samples show seawater-like features, such as depletion in LREEs, positive Y anomaly and high Y/Ho ratios (30.7–57.5, average = 42.5), implying that the Naxiguole BIF precipitated from seawater. The positive Eu/Eu*PAAS anomalies (average 1.52) suggest the influence of high-T hydrothermal fluids. Based on positive Eu anomalies and high terrestrial clastic components and no obvious Ce anomalies, the Naxiguole BIF was formed in an anoxic or suboxic sedimentary basin within active continental island arc, and is similar to Superior-type BIFs worldwide. [ABSTRACT FROM AUTHOR]

The East Kunlun Orogen (EKO) is located in the western part of China and has witnessed the Late Permian–Triassic tectonic evolution involving the A'nyemaqen Ocean (a part of the Palaeo‐Tethys Ocean). In this study, geochronology, geochemistry, and Hf isotope analysis of Late Permian–Triassic granitoids were carried out. Zircon U–Pb dating of Dachagou granodiorite and monzogranite in the western part of the EKO (W–EKO) is 233.4 ± 1.1 and 225.8 ± 1.2 Ma, respectively. The Dachagou granodiorite and monzogranite are characterized by low values of 10, 000 Ga/Al ratios (1.75–2.06, 1.42–1.60) similar to those of I‐type granite. The εHf (t) (−2.4 to +0.1, −3.0 to +0.2) indicate that the magma forming these granites was derived from a mafic Mesoproterozoic lower crust. Zircon U–Pb age of Lalingzaohuo quartz diorite is 244.5 ± 2.6 Ma, and its εHf(t) values (−0.7 to +2.5) indicate the origin of crust–mantle mixing. Zircon U–Pb ages for Nagengkangqieer granodiorite and monzogranite in the eastern part of the EKO (E–EKO) are 250.1 ± 2.8 and 238.9 ± 2.2 Ma, respectively. These rocks are also characterized by low 10, 000 Ga/Al ratios (2.37–2.66 and 2.49–2.63) again similar to I‐type granite. The εHf(t) (−3.9 to 0.4, −3.3 to 1.1) indicate that the magma was derived from the crustal materials. As contemporaneous rocks, the Dachagou and Nagengkangqieer granodiorites and the Lalingzaohuo quartz diorites are formed in a subduction environment. However, the Dachagou and Nagengkangqieer monzogranites are formed in a collision environment. Based on this result, the closure time of the W–EKO and E–EKO of the A'nyemaqen Ocean had an age gap of ~15 Ma, hence the closure mode of the A'nyemaqen Ocean should be a "scissor‐type" closure. [ABSTRACT FROM AUTHOR]

It is crucial to extract knowledge from past accidents to prevent future ones. To this end, narrative classification is required in text mining. This autocoding process can be seen as a multiclass classification problem with an imbalanced data set. We evaluated the performance of several state-of-the-art machine learning methods, including 10 shallow learning methods (Rocchio, k -nearest neighbors, linear regression, naive Bayes, decision tree, random forest, gradient boosting, bootstrap aggregating, support vector machine (SVM), and shallow neural network), and five deep learning methods [deep neural network, convolutional neural network (CNN), recurrent neural network with long short-term memory, and a gated recurrent unit, and recurrent CNN]. The input data set contained 4,770 construction accident reports from the Occupational Safety and Health Administration (OSHA). After the narratives were relabeled based on the Occupational Injury and Illness Classification System (OIICS), the accuracy of all shallow classifiers was significantly improved compared with that reported in previous studies. SVM and CNN achieved the highest accuracy of 0.91 and 0.90 among the shallow and deep learning methods, respectively. Misclassifications occur because training data sets lack rich diversity for minority classes, some cases belong to multiple classes, and some divisions have the same key feature words. In the future, when a new data set is available, we can use learned patterns to classify them with high accuracy in practice. [ABSTRACT FROM AUTHOR]