Low-energy protons from targets bombarded by 15-MeV deuterons

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 1954.Vita.Includes bibliographical references (leaves 82-83).by Frank A. Aschenbrenner.Ph.D

Novel role of Ras-GTPase Activating Protein SH3 Domain-Binding Protein G3BP in adhesion and migration of 32D myeloid progenitor cells

Rho GTPases are involved in homing and mobilization of hematopoietic stem and progenitor cells due to their impact on cytoskeleton remodeling. We have previously shown that inhibition of Rho, Rac and Cdc42 clearly impairs adhesion of normal and leukemic hematopoietic progenitor cells (HPC) to fibronectin and migration in a three-dimensional stromal cell model. Here, we identified the Ras GTPase-Activating Protein SH3 Domain-Binding Protein (G3BP) as a target gene of Rho GTPases and analysed its role in regulating HPC motility. Overexpression of G3BP significantly enhanced adhesion of murine 32D HPC to fibronectin and human umbilical vein endothelial cells, increased the proportion of adherent cells in a flow chamber assay and promoted cell migration in a transwell assay and a three-dimensional stromal cell model suggesting a strong impact on the cytoskeleton. Immunofluorescent staining of G3BP-overexpressing fibroblasts revealed a Rho-like phenotype characterized by formation of actin stress fibers in contrast to the Rac-like phenotype of control fibroblasts. This is the first report implicating a role for G3BP in Rho GTPase-mediated signalling towards adhesion and migration of HPC. Our results may be of clinical importance, since G3BP was found overexpressed in human cancers

Reference Network and Localization Architecture for Smart Manufacturing based on 5G

5G promises to shift Industry 4.0 to the next level by allowing flexible production. However, many communication standards are used throughout a production site, which will stay so in the foreseeable future. Furthermore, localization of assets will be equally valuable in order to get to a higher level of automation. This paper proposes a reference architecture for a convergent localization and communication network for smart manufacturing that combines 5G with other existing technologies and focuses on high-mix low-volume application, in particular at small and medium-sized enterprises. The architecture is derived from a set of functional requirements, and we describe different views on this architecture to show how the requirements can be fulfilled. It connects private and public mobile networks with local networking technologies to achieve a flexible setup addressing many industrial use cases.Comment: 10 pages; submitted to 6th International Conference on System-Integrated Intelligence. Intelligent, flexible and connected systems in products and production, 7-9 September Genova, Ital

Harvest of the Oleaginous Microalgae Scenedesmus obtusiusculus by Flocculation From Culture Based on Natural Water Sources

Harvest and dewatering poses a significant economical burden for industrial algae biomass production. To mitigate these effects, energy efficient techniques for these process steps have to be developed. Flocculation of the microalgae Scenedesmus obtusiusculus in salt based medium was induced by pH-shift and alternatively by addition of two biological flocculants, chitosan, and the commercial tannin CFL-PT. This is the first time that CFL-PT is used as an algae flocculant particularly focusing on harvesting of halophilic strains. The method was characterized and subsequently optimized. In comparison to biological flocculants, induction by pH shift is far cheaper, but due to buffering effects of the brackish cultivation medium infeasible amounts of base are required to raise the pH-value. tannin appears to be superior compared to chitosan not only in the absence of algae organic matter (AOM), but tannin-based harvest is also more robust regarding culture pH in presence of AOM. A higher flocculant-demand for modified tannin compared to chitosan is offset by the lower price. Given the employed strain and cultivation conditions, cultivation time had no pronounced effect on flocculation efficiencies (FE) while algae zeta-potential and bacterial communities also remained stable

Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors

INTRODUCTION COVID-19 became a global pandemic partially as a result of the lack of easily deployable, broad-spectrum oral antivirals, which complicated its containment. Even endemically, and with effective vaccinations, it will continue to cause acute disease, death, and long-term sequelae globally unless there are accessible treatments. COVID-19 is not an isolated event but instead is the latest example of a viral pandemic threat to human health. Therefore, antiviral discovery and development should be a key pillar of pandemic preparedness efforts. RATIONALE One route to accelerate antiviral drug discovery is the establishment of open knowledge bases, the development of effective technology infrastructures, and the discovery of multiple potent antivirals suitable as starting points for the development of therapeutics. In this work, we report the results of the COVID Moonshot—a fully open science, crowdsourced, and structure-enabled drug discovery campaign—against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro). This collaboration may serve as a roadmap for the potential development of future antivirals. RESULTS On the basis of the results of a crystallographic fragment screen, we crowdsourced design ideas to progress from fragment to lead compounds. The crowdsourcing strategy yielded several key compounds along the optimization trajectory, including the starting compound of what became the primary lead series. Three additional chemically distinct lead series were also explored, spanning a diversity of chemotypes. The collaborative and highly automated nature of the COVID Moonshot Consortium resulted in >18,000 compound designs, >2400 synthesized compounds, >490 ligand-bound x-ray structures, >22,000 alchemical free-energy calculations, and >10,000 biochemical measurements—all of which were made publicly available in real time. The recently approved antiviral ensitrelvir was identified in part based on crystallographic data from the COVID Moonshot Consortium. This campaign led to the discovery of a potent [median inhibitory concentration (IC50) = 37 ± 2 nM] and differentiated (noncovalent and nonpeptidic) lead compound that also exhibited potent cellular activity, with a median effective concentration (EC50) of 64 nM in A549-ACE2-TMPRSS2 cells and 126 nM in HeLa-ACE2 cells without measurable cytotoxicity. Although the pharmacokinetics of the reported compound is not yet optimal for therapeutic development, it is a promising starting point for further antiviral discovery and development. CONCLUSION The success of the COVID Moonshot project in producing potent antivirals, building open knowledge bases, accelerating external discovery efforts, and functioning as a useful information-exchange hub is an example of the potential effectiveness of open science antiviral discovery programs. The open science, patent-free nature of the project enabled a large number of collaborators to provide in-kind support, including synthesis, assays, and in vitro and in vivo experiments. By making all data immediately available and ensuring that all compounds are purchasable from Enamine without the need for materials transfer agreements, we aim to accelerate research globally along parallel tracks. In the process, we generated a detailed map of the structural plasticity of Mpro, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data to spur further research into antivirals and discovery methodologies. We hope that this can serve as an alternative model for antiviral discovery and future pandemic preparedness. Further, the project also showcases the role of machine learning, computational chemistry, and high-throughput structural biology as force multipliers in drug design. Artificial intelligence and machine learning algorithms help accelerate chemical synthesis while balancing multiple competing molecular properties. The design-make-test-analyze cycle was accelerated by these algorithms combined with planetary-scale biomolecular simulations of protein-ligand interactions and rapid structure determination

The cross-sectional GRAS sample: A comprehensive phenotypical data collection of schizophrenic patients

<p>Abstract</p> <p>Background</p> <p>Schizophrenia is the collective term for an exclusively clinically diagnosed, heterogeneous group of mental disorders with still obscure biological roots. Based on the assumption that valuable information about relevant genetic and environmental disease mechanisms can be obtained by association studies on patient cohorts of ≥ 1000 patients, if performed on detailed clinical datasets and quantifiable biological readouts, we generated a new schizophrenia data base, the GRAS (Göttingen Research Association for Schizophrenia) data collection. GRAS is the necessary ground to study genetic causes of the schizophrenic phenotype in a 'phenotype-based genetic association study' (PGAS). This approach is different from and complementary to the genome-wide association studies (GWAS) on schizophrenia.</p> <p>Methods</p> <p>For this purpose, 1085 patients were recruited between 2005 and 2010 by an invariable team of traveling investigators in a cross-sectional field study that comprised 23 German psychiatric hospitals. Additionally, chart records and discharge letters of all patients were collected.</p> <p>Results</p> <p>The corresponding dataset extracted and presented in form of an overview here, comprises biographic information, disease history, medication including side effects, and results of comprehensive cross-sectional psychopathological, neuropsychological, and neurological examinations. With >3000 data points per schizophrenic subject, this data base of living patients, who are also accessible for follow-up studies, provides a wide-ranging and standardized phenotype characterization of as yet unprecedented detail.</p> <p>Conclusions</p> <p>The GRAS data base will serve as prerequisite for PGAS, a novel approach to better understanding 'the schizophrenias' through exploring the contribution of genetic variation to the schizophrenic phenotypes.</p

Control of the thymic medulla and its influence on αβT-cell development

The thymus is a primary lymphoid tissue that supports the generation of αβT cells. In this review, we describe the processes that give rise to the thymus medulla, a site that nurtures self‐tolerant T‐cell generation following positive selection events that take place in the cortex. To summarize the developmental pathways that generate medullary thymic epithelial cells (mTEC) from their immature progenitors, we describe work on both the initial emergence of the medulla during embryogenesis, and the maintenance of the medulla during postnatal stages. We also investigate the varying roles that receptors belonging to the tumor necrosis factor receptor superfamily have on thymus medulla development and formation, and highlight the impact that T‐cell development has on thymus medulla formation. Finally, we examine the evidence that the thymic medulla plays an important role during the intrathymic generation of distinct αβT‐cell subtypes. Collectively, these studies provide new insight into the development and functional importance of medullary microenvironments during self‐tolerant T‐cell production in the thymus

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity.

Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism, and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems-based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design, and personalized medicine approaches for COVID-19