Background COVID-19 has spread globally. Epidemiological susceptibility to COVID-19 has been reported in patients with cancer. We aimed to systematically characterise clinical features and determine risk factors of COVID-19 disease severity for patients with cancer and COVID-19. MethodsIn this multicentre, retrospective, cohort study, we included all adult patients (aged ≥18 years) with any type of malignant solid tumours and haematological malignancy who were admitted to nine hospitals in Wuhan, China, with laboratory-confirmed COVID-19 between Jan 13 and March 18, 2020. Enrolled patients were statistically matched (2:1) with patients admitted with COVID-19 who did not have cancer with propensity score on the basis of age, sex, and comorbidities. Demographic characteristics, laboratory examinations, illness severity, and clinical interventions were compared between patients with COVID-19 with or without cancer as well as between patients with cancer with non-severe or severe COVID-19. COVID-19 disease severity was defined on admission on the basis of the WHO guidelines. Univariable and multivariable logistic regression, adjusted for age, sex, comorbidities, cancer type, tumour stage, and antitumour treatments, were used to explore risk factors associated with COVID-19 disease severity. This study was registered in the Chinese Clinical Trial Register, ChiCTR2000030807. Findings Between Jan 13 and March 18, 2020, 13 077 patients with COVID-19 were admitted to the nine hospitals in Wuhan and 232 patients with cancer and 519 statistically matched patients without cancer were enrolled. Median follow-up was 29 days (IQR 22-38) in patients with cancer and 27 days (20-35) in patients without cancer. Patients with cancer were more likely to have severe COVID-19 than patients without cancer (148 [64%] of 232 vs 166 [32%] of 519; odds ratio [OR] 3•61 [95% CI 2•59-5•04]; p<0•0001). Risk factors previously reported in patients without cancer, such as older age; elevated interleukin 6, procalcitonin, and D-dimer; and reduced lymphocytes were validated in patients with cancer. We also identified advanced tumour stage (OR 2•60, 95% CI 1•05-6•43; p=0•039), elevated tumour necrosis factor α (1•22, 1•01-1•47; p=0•037), elevated N-terminal pro-B-type natriuretic peptide (1•65, 1•03-2•78; p=0•032), reduced CD4+ T cells (0•84, 0•71-0•98; p=0•031), and reduced albumin-globulin ratio (0•12, 0•02-0•77; p=0•024) as risk factors of COVID-19 severity in patients with cancer. Interpretation Patients with cancer and COVID-19 were more likely to deteriorate into severe illness than those without cancer. The risk factors identified here could be helpful for early clinical surveillance of disease progression in patients with cancer who present with COVID-19.

The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST, also called the Guo Shou Jing Telescope) is a special reflecting Schmidt telescope. LAMOST's special design allows both a large aperture (effective aperture of 3.6 m-4.9 m) and a wide field of view (FOV) (5 • ). It has an innovative active reflecting Schmidt configuration which continuously changes the mirror's surface that adjusts during the observation process and combines thin deformable mirror active optics with segmented active optics. Its primary mirror (6.67 m×6.05 m) and active Schmidt mirror (5.74 m×4.40 m) are both segmented, and composed of 37 and 24 hexagonal sub-mirrors respectively. By using a parallel controllable fiber positioning technique, the focal surface of 1.75 m in diameter can accommodate 4000 optical fibers. Also, LAMOST has 16 spectrographs with 32 CCD cameras. LAMOST will be the telescope with the highest rate of spectral acquisition. As a national large scientific project, the LAMOST project was formally proposed in 1996, and approved by the Chinese government in 1997. The construction started in 2001, was completed in 2008 and passed the official acceptance in June 2009. The LAMOST pilot survey was started in October 2011 and the spectroscopic survey will launch in September 2012. Up to now, LAMOST has released more than 480 000 spectra of objects. LAMOST will make an important contribution to the study of the large-scale structure of the Universe, structure and evolution of the Galaxy, and cross-identification of multiwaveband properties in celestial objects.

The generation of hydrogen from water using sunlight could potentially form the basis of a clean and renewable source of energy. Various water-splitting methods have been investigated previously, but the use of photocatalysts to split water into stoichiometric amounts of H2 and O2 (overall water splitting) without the use of external bias or sacrificial reagents is of particular interest because of its simplicity and potential low cost of operation. However, despite progress in the past decade, semiconductor water-splitting photocatalysts (such as (Ga1-xZnx)(N1-xOx)) do not exhibit good activity beyond 440 nm (refs 1,2,9) and water-splitting devices that can harvest visible light typically have a low solar-to-hydrogen efficiency of around 0.1%. Here we show that cobalt(II) oxide (CoO) nanoparticles can carry out overall water splitting with a solar-to-hydrogen efficiency of around 5%. The photocatalysts were synthesized from non-active CoO micropowders using two distinct methods (femtosecond laser ablation and mechanical ball milling), and the CoO nanoparticles that result can decompose pure water under visible-light irradiation without any co-catalysts or sacrificial reagents. Using electrochemical impedance spectroscopy, we show that the high photocatalytic activity of the nanoparticles arises from a significant shift in the position of the band edge of the material.

Although aerobic glycolysis (the Warburg effect) is a hallmark of cancer, key questions, including when, how, and why cancer cells become highly glycolytic, remain less clear. For a largely unknown regulatory mechanism, a rate-limiting glycolytic enzyme pyruvate kinase M2 (PKM2) isoform is exclusively expressed in embryonic, proliferating, and tumor cells, and plays an essential role in tumor metabolism and growth. Because the receptor tyrosine kinase/PI3K/ AKT/mammalian target of rapamycin (RTK/PI3K/AKT/mTOR) signaling cascade is a frequently altered pathway in cancer, we explored its potential role in cancer metabolism. We identified mTOR as a central activator of the Warburg effect by inducing PKM2 and other glycolytic enzymes under normoxic conditions. PKM2 level was augmented in mouse kidney tumors due to deficiency of tuberous sclerosis complex 2 and consequent mTOR activation, and was reduced in human cancer cells by mTOR suppression. mTOR up-regulation of PKM2 expression was through hypoxia-inducible factor 1α (HIF1α)-mediated transcription activation, and c-Myc-heterogeneous nuclear ribonucleoproteins (hnRNPs)-dependent regulation of PKM2 gene splicing. Disruption of PKM2 suppressed oncogenic mTOR-mediated tumorigenesis. Unlike normal cells, mTOR hyperactive cells were more sensitive to inhibition of mTOR or glycolysis. Dual suppression of mTOR and glycolysis synergistically blunted the proliferation and tumor development of mTOR hyperactive cells. Even though aerobic glycolysis is not required for breach of senescence for immortalization and transformation, the frequently deregulated mTOR signaling during multistep oncogenic processes could contribute to the development of the Warburg effect in many cancers. Components of the mTOR/HIF1α/Myc-hnRNPs/PKM2 glycolysis signaling network could be targeted for the treatment of cancer caused by an aberrant RTK/PI3K/AKT/mTOR signaling pathway.PTEN | tuberous sclerosis 1 | hexokinase II | lactate dehydrogenase-B | glyceraldehyde 3-phosphate dehydrogenase U nlike in normal cells, glycolysis is induced by hypoxia, and cancer cells preferentially metabolize glucose by glycolysis, even in an aerobic environment (1-3). Increased glucose consumption and an elevated rate of lactate production by cancer cells are characteristics of glycolysis, first described by Otto Warburg in the 1920s and thereafter known as the Warburg effect (4). Because this altered metabolism can occur even in the presence of oxygen, glycolysis presumably confers a selective advantage for the survival and proliferation of cancer cells. This catabolic process is, however, inefficient for energy production in that it generates only 2 mol of ATP, instead of an additional 36 mol through the tricarboxylic acid (TCA) cycle, in the presence of oxygen by using 1 mol of glucose (2, 3, 5).Although the Warburg effect is a well-recognized hallmark of cancer metabolism, its regulatory mechanism is still largely obscure. Critical issues, including how and when cancer cells acquire this highly glycolytic phenoty...

The Large sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) general survey is a spectroscopic survey that will eventually cover approximately half of the celestial sphere and collect 10 million spectra of stars, galaxies and QSOs. Objects in both the pilot survey and the first year regular survey are included in the LAMOST DR1. The pilot survey started in October 2011 and ended in June 2012, and the data have been released to the public as the LAMOST Pilot Data Release in August 2012. The regular survey started in September 2012, and completed its first year of operation in June 2013. The LAMOST DR1 includes a total of 1202 plates containing 2 955 336 spectra, of which 1 790 879 spectra have observed signalto-noise ratio (SNR) ≥ 10. All data with SNR ≥ 2 are formally released as LAMOST DR1 under the LAMOST data policy. This data release contains a total of 2 204 696 spectra, of which 1 944 329 are stellar spectra, 12 082 are galaxy spectra and 5017 are quasars. The DR1 not only includes spectra, but also three stellar catalogs with measured parameters: late A,FGK-type stars with high quality spectra (1 061 918 entries), A-type stars (100 073 entries), and M-type stars (121 522 entries). This paper introduces the survey design, the observational and instrumental limitations, data reduction and analysis, and some caveats. A description of the FITS structure of spectral files and parameter catalogs is also provided.

A simple yet general swelling-deswelling microencapsulation strategy has been developed to achieve well dispersed and intimately passivated crystalline organic-inorganic perovskites nanoparticles within polymer matrixes and results in a series of highly luminescent CH NH PbBr (MAPbBr )-polymer composite films with unprecedented water and thermal stabilities and superior color purity.

New heptamethine cyanine dyes with an alkylamino group at the central position were found to exhibit a large Stokes shift (>140 nm) and strong fluorescence. They were suggested to be a new paradigm for excited-state intramolecular charge transfer (ICT). The configuration change of the bridgehead amine accompanying ICT was investigated in different viscosity and pH media.

Summary: Structural and physiochemical descriptors extracted from sequence data have been widely used to represent sequences and predict structural, functional, expression and interaction profiles of proteins and peptides as well as DNAs/RNAs. Here, we present iFeature, a versatile Python-based toolkit for generating various numerical feature representation schemes for both protein and peptide sequences. iFeature is capable of calculating and extracting a comprehensive spectrum of 18 major sequence encoding schemes that encompass 53 different types of feature descriptors. It also allows users to extract specific amino acid properties from the AAindex database. Furthermore, iFeature integrates 12 different types of commonly used feature clustering, selection and dimensionality reduction algorithms, greatly facilitating training, analysis and benchmarking of machine-learning models. The functionality of iFeature is made freely available via an online web server and a stand-alone toolkit. Availability and implementation: