Retraction note: endoperoxide formation by an α-ketoglutarate-dependent mononuclear non-haem iron enzyme

Accepted manuscrip

SCP4-STK35/PDIK1L complex is a dual phospho-catalytic signaling dependency in acute myeloid leukemia

Acute myeloid leukemia (AML) cells rely on phospho-signaling pathways to gain unlimited proliferation potential. Here, we use domain-focused CRISPR screening and identify the nuclear phosphatase SCP4 as a dependency in AML, yet this enzyme is dispensable in normal hematopoietic progenitor cells. Using CRISPR exon scanning and gene complementation assays, we show that the catalytic function of SCP4 is essential in AML. Through mass spectrometry analysis of affinity-purified complexes, we identify the kinase paralogs STK35 and PDIK1L as binding partners and substrates of the SCP4 phosphatase domain. We show that STK35 and PDIK1L function catalytically and redundantly in the same pathway as SCP4 to maintain AML proliferation and to support amino acid biosynthesis and transport. We provide evidence that SCP4 regulates STK35/PDIK1L through two distinct mechanisms: catalytic removal of inhibitory phosphorylation and by promoting kinase stability. Our findings reveal a phosphatase-kinase signaling complex that supports the pathogenesis of AML

Complete Sequencing of pNDM-HK Encoding NDM-1 Carbapenemase from a Multidrug-Resistant Escherichia coli Strain Isolated in Hong Kong

BACKGROUND: The emergence of plasmid-mediated carbapenemases, such as NDM-1 in Enterobacteriaceae is a major public health issue. Since they mediate resistance to virtually all β-lactam antibiotics and there is often co-resistance to other antibiotic classes, the therapeutic options for infections caused by these organisms are very limited. METHODOLOGY: We characterized the first NDM-1 producing E. coli isolate recovered in Hong Kong. The plasmid encoding the metallo-β-lactamase gene was sequenced. PRINCIPAL FINDINGS: The plasmid, pNDM-HK readily transferred to E. coli J53 at high frequencies. It belongs to the broad host range IncL/M incompatibility group and is 88803 bp in size. Sequence alignment showed that pNDM-HK has a 55 kb backbone which shared 97% homology with pEL60 originating from the plant pathogen, Erwina amylovora in Lebanon and a 28.9 kb variable region. The plasmid backbone includes the mucAB genes mediating ultraviolet light resistance. The 28.9 kb region has a composite transposon-like structure which includes intact or truncated genes associated with resistance to β-lactams (bla(TEM-1), bla(NDM-1), Δbla(DHA-1)), aminoglycosides (aacC2, armA), sulphonamides (sul1) and macrolides (mel, mph2). It also harbors the following mobile elements: IS26, ISCR1, tnpU, tnpAcp2, tnpD, ΔtnpATn1 and insL. Certain blocks within the 28.9 kb variable region had homology with the corresponding sequences in the widely disseminated plasmids, pCTX-M3, pMUR050 and pKP048 originating from bacteria in Poland in 1996, in Spain in 2002 and in China in 2006, respectively. SIGNIFICANCE: The genetic support of NDM-1 gene suggests that it has evolved through complex pathways. The association with broad host range plasmid and multiple mobile genetic elements explain its observed horizontal mobility in multiple bacterial taxa

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

In-situ estimation of ice crystal properties at the South Pole using LED calibration data from the IceCube Neutrino Observatory

The IceCube Neutrino Observatory instruments about 1 km3 of deep, glacial ice at the geographic South Pole using 5160 photomultipliers to detect Cherenkov light emitted by charged relativistic particles. A unexpected light propagation effect observed by the experiment is an anisotropic attenuation, which is aligned with the local flow direction of the ice. Birefringent light propagation has been examined as a possible explanation for this effect. The predictions of a first-principles birefringence model developed for this purpose, in particular curved light trajectories resulting from asymmetric diffusion, provide a qualitatively good match to the main features of the data. This in turn allows us to deduce ice crystal properties. Since the wavelength of the detected light is short compared to the crystal size, these crystal properties do not only include the crystal orientation fabric, but also the average crystal size and shape, as a function of depth. By adding small empirical corrections to this first-principles model, a quantitatively accurate description of the optical properties of the IceCube glacial ice is obtained. In this paper, we present the experimental signature of ice optical anisotropy observed in IceCube LED calibration data, the theory and parametrization of the birefringence effect, the fitting procedures of these parameterizations to experimental data as well as the inferred crystal properties.</p

The 13th Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-IV Survey Mapping Nearby Galaxies at Apache Point Observatory

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) began observations in July 2014. It pursues three core programs: APOGEE-2,MaNGA, and eBOSS. In addition, eBOSS contains two major subprograms: TDSS and SPIDERS. This paper describes the first data release from SDSS-IV, Data Release 13 (DR13), which contains new data, reanalysis of existing data sets and, like all SDSS data releases, is inclusive of previously released data. DR13 makes publicly available 1390 spatially resolved integral field unit observations of nearby galaxies from MaNGA,the first data released from this survey. It includes new observations from eBOSS, completing SEQUELS. In addition to targeting galaxies and quasars, SEQUELS also targeted variability-selected objects from TDSS and X-ray selected objects from SPIDERS. DR13 includes new reductions ofthe SDSS-III BOSS data, improving the spectrophotometric calibration and redshift classification. DR13 releases new reductions of the APOGEE-1data from SDSS-III, with abundances of elements not previously included and improved stellar parameters for dwarf stars and cooler stars. For the SDSS imaging data, DR13 provides new, more robust and precise photometric calibrations. Several value-added catalogs are being released in tandem with DR13, in particular target catalogs relevant for eBOSS, TDSS, and SPIDERS, and an updated red-clump catalog for APOGEE.This paper describes the location and format of the data now publicly available, as well as providing references to the important technical papers that describe the targeting, observing, and data reduction. The SDSS website, http://www.sdss.org, provides links to the data, tutorials and examples of data access, and extensive documentation of the reduction and analysis procedures. DR13 is the first of a scheduled set that will contain new data and analyses from the planned ~6-year operations of SDSS-IV.PostprintPeer reviewe

Posteriori analysis on IceCube double pulse tau neutrino candidates

The IceCube Neutrino Observatory at the South Pole detects Cherenkov light emitted by charged secondary particles created by primary neutrino interactions. Double pulse waveforms can arise from charged current interactions of astrophysical tau neutrinos with nucleons in the ice and the subsequent decay of tau leptons. The previous 8-year tau double pulse analysis found three tau neutrino candidate events. Among them, the most promising one observed in 2014 is located very near the dust layer in the middle of the detector. A posterior analysis on this event will be presented in this paper, using a new ice model treatment with continuously varying nuisance parameters to do the targeted Monte Carlo re-simulation for tau and other background neutrino ensembles. The impact of different ice models on the expected signal and background statistics will also be discussed

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery