Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction

The first paradigm of plant breeding involves direct selection-based phenotypic observation, followed by predictive breeding using statistical models for quantitative traits constructed based on genetic experimental design and, more recently, by incorporation of molecular marker genotypes. However, plant performance or phenotype (P) is determined by the combined effects of genotype (G), envirotype (E), and genotype by environment interaction (GEI). Phenotypes can be predicted more precisely by training a model using data collected from multiple sources, including spatiotemporal omics (genomics, phenomics, and enviromics across time and space). Integration of 3D information profiles (G-P-E), each with multidimensionality, provides predictive breeding with both tremendous opportunities and great challenges. Here, we first review innovative technologies for predictive breeding. We then evaluate multidimensional information profiles that can be integrated with a predictive breeding strategy, particularly envirotypic data, which have largely been neglected in data collection and are nearly untouched in model construction. We propose a smart breeding scheme, integrated genomic-enviromic prediction (iGEP), as an extension of genomic prediction, using integrated multiomics information, big data technology, and artificial intelligence (mainly focused on machine and deep learning). We discuss how to implement iGEP, including spatiotemporal models, environmental indices, factorial and spatiotemporal structure of plant breeding data, and cross-species prediction. A strategy is then proposed for prediction-based crop redesign at both the macro (individual, population, and species) and micro (gene, metabolism, and network) scales. Finally, we provide perspectives on translating smart breeding into genetic gain through integrative breeding platforms and open-source breeding initiatives. We call for coordinated efforts in smart breeding through iGEP, institutional partnerships, and innovative technological support

Retroviral gene transfer is inhibited by chondroitin sulfate proteoglycans/glycosaminoglycans in malignant pleural effusions

Gene therapy may be an important adjuvant for treating cancer in the pleural space. The initial results of retroviral gene transfer to cancer cells in malignant pleural effusions revealed that transduction was markedly inhibited, and studies to characterize the inhibitory factor(s) were performed. The inhibition was contained within the soluble, rather than cellular, components of the effusions and was demonstrated with amphotropic, gibbon ape leukemia virus, and vesicular stomatitis virus-glycoprotein pseudotyped retroviral vectors. After excluding complement proteins, a series of studies identified chondroitin sulfates (CSs) as the inhibitory substances. First, treatment of the effusions with mammalian hyaluronidase or chondroitinases, but not Streptomyces hyaluronidase, abolished the inhibitory activity. Second, addition of exogenous CS glycosaminoglycans mimicked the inhibition observed with pleural effusions. Third, immunoassays and biochemical analyses of malignant pleural effusion specimens revealed CS in relevant concentrations within pleural fluid. Fourth, proteoglycans/glycosaminoglycans isolated from the effusions inhibited retroviral gene transfer. Analyses of the mechanism of inhibition indicate that the chondroitin sulfates interact with vector in solution rather than at the target cell surface. These results suggest that drainage of the malignant pleural effusion, and perhaps enzymatic pretreatment of the pleural cavity, will be necessary for efficient retroviral vector mediated gene delivery to pleural metastases

Epidemiology and outcomes of Clostridium difficile infection in allogeneic hematopoietic cell and lung transplant recipients

BackgroundClostridium difficile infection (CDI) is a common complication of lung and allogeneic hematopoietic cell (HCT) transplant, but the epidemiology and outcomes of CDI after transplant are poorly described.MethodsWe performed a prospective, multicenter study of CDI within 365 days post‐allogeneic HCT or lung transplantation. Data were collected via patient interviews and medical chart review. Participants were followed weekly in the 12 weeks post‐transplant and while hospitalized and contacted monthly up to 18 months post‐transplantation.ResultsSix sites participated in the study with 614 total participants; 4 enrolled allogeneic HCT (385 participants) and 5 enrolled lung transplant recipients (229 participants). One hundred and fifty CDI cases occurred within 1 year of transplantation; the incidence among lung transplant recipients was 13.1% and among allogeneic HCTs was 31.2%. Median time to CDI was significantly shorter among allogeneic HCT than lung transplant recipients (27 days vs 90 days; P = .037). CDI was associated with significantly higher mortality from 31 to 180 days post‐index date among the allogeneic HCT recipients (Hazard ratio [HR] = 1.80; P = .007). There was a trend towards increased mortality among lung transplant recipients from 120 to 180 days post‐index date (HR = 4.7, P = .09).ConclusionsThe epidemiology and outcomes of CDI vary by transplant population; surveillance for CDI should continue beyond the immediate post‐transplant period.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143790/1/tid12855_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143790/2/tid12855.pd

An error tolerant memory aid for reduced cognitive load in number copying tasks

Number copying tasks are still common despite increased digitalization of services. Number copying tasks are cognitively and visually demanding, errors are easily introduced and the process is often perceived as laborious. This study proposes an alternative scheme based on dictionary coding that reduces the cognitive load on the user by a factor of five. The strategy has several levels of error detection and error correction characteristics and is easy to implemen

Group Formation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68807/2/10.1177_104649647300400206.pd

Measurement of the B0-anti-B0-Oscillation Frequency with Inclusive Dilepton Events

The $B^0$-$\bar B^0$ oscillation frequency has been measured with a sample of 23 million \B\bar B pairs collected with the BABAR detector at the PEP-II asymmetric B Factory at SLAC. In this sample, we select events in which both B mesons decay semileptonically and use the charge of the leptons to identify the flavor of each B meson. A simultaneous fit to the decay time difference distributions for opposite- and same-sign dilepton events gives $\Delta m_d = 0.493 \pm 0.012{(stat)}\pm 0.009{(syst)}$ ps$^{-1}$.Comment: 7 pages, 1 figure, submitted to Physical Review Letter

Search for a W' boson decaying to a bottom quark and a top quark in pp collisions at sqrt(s) = 7 TeV

Results are presented from a search for a W' boson using a dataset corresponding to 5.0 inverse femtobarns of integrated luminosity collected during 2011 by the CMS experiment at the LHC in pp collisions at sqrt(s)=7 TeV. The W' boson is modeled as a heavy W boson, but different scenarios for the couplings to fermions are considered, involving both left-handed and right-handed chiral projections of the fermions, as well as an arbitrary mixture of the two. The search is performed in the decay channel W' to t b, leading to a final state signature with a single lepton (e, mu), missing transverse energy, and jets, at least one of which is tagged as a b-jet. A W' boson that couples to fermions with the same coupling constant as the W, but to the right-handed rather than left-handed chiral projections, is excluded for masses below 1.85 TeV at the 95% confidence level. For the first time using LHC data, constraints on the W' gauge coupling for a set of left- and right-handed coupling combinations have been placed. These results represent a significant improvement over previously published limits.Comment: Submitted to Physics Letters B. Replaced with version publishe