The analysis of rare chromosomal translocations in myeloproliferative disorders has highlighted the importance of aberrant tyrosine kinase signaling in the pathogenesis of these diseases. Here we have investigated samples from 679 patients and controls for the nonreceptor tyrosine kinase JAK2 V617F mutation. Of the 480 myeloproliferative disorder (MPD) samples, the proportion of positive cases per disease subtype was 30 (20%) of 152 for atypical or unclassified MPD, 2 of 134 (2%) for idiopathic hypereosinophilic syndrome, 58 of 72 (81%) for polycythemia vera, 24 of 59 (41%) essential thrombocythemia (ET), and 15 of 35 (43%) for idiopathic myelofibrosis. V617F was not identified in patients with systemic mastocytosis (n ‫؍‬ 28), chronic or acute myeloid leukemia (n ‫؍‬ 35), secondary erythrocytosis (n ‫؍‬ 4), or healthy controls (n ‫؍‬ 160). Homozygosity for V617F was seen in 43% of mutant samples and was closely correlated with chromosome 9p uniparental disomy. Homozygosity was significantly less common in ET compared with other MPD subtypes. In 53 cases analyzed, the median level of PRV1 expression was significantly higher in V617F-positive cases compared with cases without the mutation. We conclude that V617F is widespread in MPDs. IntroductionChronic myeloproliferative diseases (CMPDs) are clonal hematopoietic stem cell disorders characterized by proliferation of one or more myeloid cell lineages in the bone marrow and increased numbers of mature and immature cells in the peripheral blood. CMPDs include polycythemia vera (PV), essential thrombocythemia (ET), idiopathic myelofibrosis (IMF) and chronic myeloid leukemia (CML), plus rarer subtypes such as chronic neutrophilic leukemia (CNL), hypereosinophilic syndrome (HES), and chronic eosinophilic leukemia (CEL). These diseases overlap with myelodysplastic/myeloproliferative diseases (MDS/MPDs) such as atypical CML (aCML) and chronic myelomonocytic leukemia (CMML), in which proliferation is accompanied by dysplastic features or ineffective hematopoiesis in other lineages. 1 We refer here broadly to all these groups as myeloproliferative disorders (MPDs).Although there are strict diagnostic criteria for MPD subtypes, precise categorization remains a subject of debate 2 and furthermore, it can be difficult to differentiate some cases from reactive disorders. Only CML is characterized by a pathognomonic molecular marker, the BCR-ABL fusion, and the primary abnormalities driving excess proliferation in most other cases have been obscure. However, several lines of evidence have implicated aberrant tyrosine kinase signaling as the root cause of MPDs. Breakpoint cluster region-abelson (BCR-ABL) itself is a constitutively active tyrosine kinase that is believed to be the primary, and probably the only, driving force behind chronic-phase CML. 3 Other gene fusions have been identified in rare cases of aCML, CMML, and HES/CEL that involve the tyrosine kinases PDGFRA, PDGFRB, FGFR1, and JAK2. 4,5 In addition, the KIT receptor is activated by point mutation in the majority...

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Since the turn of the new century, the increasing demand for high-performance energy storage systems has generated considerable interest in rechargeable ion batteries.

The loss of sulfur in the cathode of a lithium sulfur battery (LSB) severely hinders the practical application of LSBs, and so do the insulativity of S and its lithiation end products. The incorporation of MXene can significantly improve the performance of LSBs; however, the underlying mechanism at the atomic scale has not been deeply explored. In the present work, by using density functional theory calculations, we systemically studied the interactions of lithium (poly)­sulfides (Li2S m ) on Ti-based bare MXenes (Ti n X n–1) and surface functionalized Ti2C with −F, −O, and −OH groups. Through analyzing the geometric and electronic structures, binding energies, and deformation charge densities of Li2S m adsorbed MXenes, we found that the strong Ti–S bonds dominate the interactions between Li2S m and MXenes. The strong Coulombic interactions help cathodes to confine S from dissolution. Besides, the conductivities of MXenes and Li2S m @MXenes are beneficial for the overall performance of the LSB. These will provide in-depth theoretical guidance support for the utilization of MXene in LSBs.

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Common lung diseases are first diagnosed via chest X-rays. Here, we show that a fully automated deep-learning pipeline for chest-X-ray-image standardization, lesion visualization and disease diagnosis can identify viral pneumonia caused by Coronavirus disease 2019 (COVID-19), assess its severity, and discriminate it from other types of pneumonia. The deep-learning system was developed by using a heterogeneous multicentre dataset of 145,202 images, and tested retrospectively and prospectively with thousands of additional images across four patient cohorts and multiple countries. The system generalized across settings, discriminating between viral pneumonia, other types of pneumonia and absence of disease with areas under the receiver operating characteristic curve (AUCs) of 0.88–0.99, between severe and non-severe COVID-19 with an AUC of 0.87, and between severe or non-severe COVID-19 pneumonia and other viral and non-viral pneumonia with AUCs of 0.82–0.98. In an independent set of 440 chest X-rays, the system performed comparably to senior radiologists, and improved the performance of junior radiologists. Automated deep-learning systems for the assessment of pneumonia could facilitate early intervention and provide clinical-decision support.

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