More Than the Sum of Its Parts: Unlocking the Power of Network Structure for Understanding Organization and Function in Microbiomes

Plant and soil microbiomes are integral to the health and productivity of plants and ecosystems, yet researchers struggle to identify microbiome characteristics important for providing beneficial outcomes. Network analysis offers a shift in analytical framework beyond who is present to the organization or patterns of coexistence between microbes within the microbiome. Because microbial phenotypes are often significantly impacted by coexisting populations, patterns of coexistence within microbiomes are likely to be especially important in predicting functional outcomes. Here, we provide an overview of the how and why of network analysis in microbiome research, highlighting the ways in which network analyses have provided novel insights into microbiome organization and functional capacities, the diverse network roles of different microbial populations, and the eco-evolutionary dynamics of plant and soil microbiomes

Robust and Deterministic Preparation of Bosonic Logical States in a Trapped Ion

Encoding logical qubits in bosonic modes provides a potentially hardware-efficient implementation of fault-tolerant quantum information processing. Recent advancements in trapped ions and superconducting microwave cavities have led to experimental realizations of high-quality bosonic states and demonstrations of error-corrected logical qubits encoded in bosonic modes. However, current protocols for preparing bosonic code words lack robustness to common noise sources and can be experimentally challenging to implement, limiting the quality and breadth of codes that have been realized to date. Here, we combine concepts of error suppression via robust control with quantum error correction encoding and experimentally demonstrate high-fidelity, deterministic preparation of highly non-classical target bosonic states in the mechanical motion of a trapped ion. Our approach implements numerically optimized dynamical modulation of laser-driven spin-motion interactions to generate the target state in a single step. The optimized control pulses are tailored towards experimental constraints and are designed to be robust against the dominant source of error. Using these protocols, we demonstrate logical fidelities for the Gottesman-Kitaev-Preskill (GKP) state as high as $\bar{\mathcal{F}}=0.940(8)$, achieve the first realization of a distance-3 binomial logical state with an average fidelity of $\mathcal{F}=0.807(7)$, and demonstrate a 12.91(5) dB squeezed vacuum state.Comment: 12 pages, 8 figure

THE STRUCTURE OF 3,5-DI-O-BENZOYL-1,2-DIDEOXY-1-PHENYL-BETA-D-RIBOFURANOSE, C25H22O5

Mr=402.4, orthorhombic, P212~2 l, a= 4-946 (1), b= 15.887 (2), c=26.555 (2)A, V= 2086.7 (5) A 3, Z = 4, D x = 1.28 gcm -a, Cu Ka, 2 = 1.5418/k, B = 6.868 cm -1, F(000) = 848, T= 293 K, final R =0.054 for 648 observed reflections. The molecule is propeller shaped. The benzoyl groups act as protecting groups and the phenyl group is a base substitute. The crystal structure does not involve any intermolecular stacking interactions between the phenyl groups. The molecules pack in typical herring-bone-like arrays. The sugar has a fl-D configuration with C(2')-endo-C(3')-exo pucker (2T3), pseudorotation angle P = 172 (2) °, degree of pucker r m = 39 (2) °

Superconductivity at 36 K in beta-Fe1.01Se with the compression of the interlayer separation under pressure

In this letter, we report that the superconductivity transition temperature in beta-Fe1.01Se increases from 8.5 to 36.7 K under applied pressure of 8.9 GPa. It then decreases at higher pressure. A dramatic change in volume is observed at the same time Tc rises, due to a collapse of the separation between the Fe2Se2 layers. A clear transition to a linear resistivity normal state is seen on cooling at all pressures. No static magnetic ordering is observed for the whole p-T phase diagram. We also report that at higher pressure (starting around 7 GPa and completed at 38 GPa), Fe1.01Se transforms to a hexagonal NiAs-type structure and displays non-magnetic, insulating behavior. The inclusion of electron correlation in band structure caculations is necessary to describe this behavior, signifying that such correlations are important in this chemical system. Our results strongly support unconventional superconductivity in beta-Fe1.01Se.Comment: 17 pages, 4 figure

Expression of phosphorylated eIF4E-binding protein 1, but not of eIF4E itself, predicts survival in male breast cancer

Background: Male breast cancer is rare and treatment is based on data from females. High expression/activity of eukaryotic initiation factor 4E (eIF4E) denotes a poor prognosis in female breast cancer, and the eIF4E pathway has been targeted therapeutically. eIF4E activity in female breast cancer is deregulated by eIF4E over-expression and by phosphorylation of its binding protein, 4E-BP1, which relieves inhibitory association between eIF4E and 4E-BP1. The relevance of the eIF4E pathway in male breast cancer is unknown. Methods: We have assessed expression levels of eIF4E, 4E-BP1, 4E-BP2 and phosphorylated 4E-BP1 (p4E-BP1) using immunohistochemistry in a large cohort of male breast cancers (n=337) and have examined correlations with prognostic factors and survival. Results: Neither eIF4E expression or estimated eIF4E activity were associated with prognosis. However, a highly significant correlation was found between p4E-BP1 expression and disease-free survival, linking any detectable p4E-BP1 with poor survival (univariate log rank p=0.001; multivariate HR 8.8, p=0.0001). Conclusions: Our data provide no support for direct therapeutic targeting of eIF4E in male breast cancer, unlike in females. However, as p4E-BP1 gives powerful prognostic insights that are unrelated to eIF4E function, p4E-BP1 may identify male breast cancers potentially suitable for therapies directed at the upstream kinase, mTOR

A Case Matched Gender Comparison Transcriptomic Screen Identifies eIF4E and eIF5 as Potential Prognostic and Tractable Biomarkers in Male Breast Cancer

Purpose: Breast cancer (BC) affects both genders, but is understudied in men. Although still rare, male BC is being diagnosed more frequently. Treatments are wholly informed by clinical studies conducted in women, based on assumptions that underlying biology is similar. Experimental design: A transcriptomic investigation of male and female BC was performed, confirming transcriptomic data in silico. Biomarkers were immunohistochemically assessed in 697 MBCs (n=477, training; n=220, validation set) and quantified in pre- and post-treatment samples from a male BC patient receiving Everolimus and PI3K/mTOR inhibitor. Results: Gender-specific gene expression patterns were identified. eIF transcripts were up-regulated in MBC. eIF4E and eIF5 were negatively prognostic for overall survival alone (Log rank; p=0.013; HR=1.77, 1.12-2.8 and p=0.035; HR=1.68, 1.03-2.74, respectively), or when co-expressed (p=0.01; HR=2.66, 1.26-5.63), confirmed in the validation set. This remained upon multivariate Cox regression analysis (eIF4E p=0.016; HR 2.38 (1.18-4.8), eIF5 p=0.022; HR 2.55 (1.14-5.7); co-expression p=0.001; HR=7.04 (2.22-22.26)). Marked reduction in eIF4E and eIF5 expression was seen post BEZ235/Everolimus, with extended survival. Conclusions: Translational initiation pathway inhibition could be of clinical utility in male BC patients overexpressing eIF4E and eIF5. With mTOR inhibitors which target this pathway now in the clinic, these biomarkers may represent new targets for therapeutic intervention, although further independent validation is required

Framework for knowledge asset management in community projects in higher education institutions

Innovation in education encourages stakeholders to explore and apply different ways of looking at problems and solving them. Large-scale community projects (LSCPs) in a higher education institution (HEI), provide an ideal environment for combining curriculum outcomes, education innovation, real-world engagement and knowledge assets. However, current research that focuses on knowledge asset management in innovative learning is limited, and this study aims to contribute a holistic approach for managing knowledge assets in this context. In this study, we designed a knowledge asset management framework for LSCPs in higher education taking cognisance of innovative educational model characteristics. We applied the framework by mapping it to a community project module from an HEI using the elements of the framework as a guide. By using the knowledge asset management framework for LSCPs in higher education, an HEI can ensure that their community module enables strong support to the community, that students’ knowledge and skills are enhanced and that all new knowledge assets created during the project delivery, are captured and stored using innovative technology sets.http://link.springer.combookseries/558hj2020Informatic

A national clinical decision support infrastructure to enable the widespread and consistent practice of genomic and personalized medicine

<p>Abstract</p> <p>Background</p> <p>In recent years, the completion of the Human Genome Project and other rapid advances in genomics have led to increasing anticipation of an era of genomic and personalized medicine, in which an individual's health is optimized through the use of all available patient data, including data on the individual's genome and its downstream products. Genomic and personalized medicine could transform healthcare systems and catalyze significant reductions in morbidity, mortality, and overall healthcare costs.</p> <p>Discussion</p> <p>Critical to the achievement of more efficient and effective healthcare enabled by genomics is the establishment of a robust, nationwide clinical decision support infrastructure that assists clinicians in their use of genomic assays to guide disease prevention, diagnosis, and therapy. Requisite components of this infrastructure include the standardized representation of genomic and non-genomic patient data across health information systems; centrally managed repositories of computer-processable medical knowledge; and standardized approaches for applying these knowledge resources against patient data to generate and deliver patient-specific care recommendations. Here, we provide recommendations for establishing a national decision support infrastructure for genomic and personalized medicine that fulfills these needs, leverages existing resources, and is aligned with the <it>Roadmap for National Action on Clinical Decision Support </it>commissioned by the U.S. Office of the National Coordinator for Health Information Technology. Critical to the establishment of this infrastructure will be strong leadership and substantial funding from the federal government.</p> <p>Summary</p> <p>A national clinical decision support infrastructure will be required for reaping the full benefits of genomic and personalized medicine. Essential components of this infrastructure include standards for data representation; centrally managed knowledge repositories; and standardized approaches for leveraging these knowledge repositories to generate patient-specific care recommendations at the point of care.</p