1. |
- Li, Yonghong, et al.
(author)
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Microbial profiling identifies potential key drivers in gastric cancer patients
- 2021
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In: Biotechnology and Biotechnological Equipment. - : Informa UK Limited. - 1310-2818 .- 1314-3530. ; 35:1, s. 496-503
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Journal article (peer-reviewed)abstract
- Gastric cancer (GC) is the fifth most commonly diagnosed cancer and the third leading cause of cancer-related death in the world. Microbiota is believed to be associated with GC. Growing evidences showed Helicobacter pylori played a key role in GC development. However, little was known about the microbiota in gastric juices and tissues in GC patients, and thus it was difficult to understand other potential microbial causation for GC. Here, we collected the gastric juice and surgically removed gastric tissues from GC patients to give insight into GC microbiota. Most microbes identified in the gastric samples were opportunistic pathogens or resident flora of the human microbiota. Further network analyses identified five opportunistic pathogens as keystone species. H. pylori is the direct cause of GC, but other opportunistic microbes might also function in GC development. The microbiota in the gastric juice and gastric tissue of the GC patients were complex, and some dominant opportunistic pathogens contributed to the GC development. This study introduces microbiota in gastric juice, gastric normal tissue and gastric cancer tissue of GC patients, and highlights the potential keystone microbes functioned during GC development.
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2. |
- Meng, Boyang, et al.
(author)
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Uniformity, Periodicity and Symmetry Characteristics of Forces Fluctuation in Helical-Edge Milling Cutter
- 2021
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In: Applied Sciences. - : MDPI AG. - 2076-3417. ; 11:6
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Journal article (peer-reviewed)abstract
- Under most processing conditions, the milling force is expected to be stable and not to fluctuate, in order to improve the processing quality. This study focuses on analyzing the force fluctuation characteristics under conditions of different processing and cutter parameters. An original model is proposed to predict the force fluctuation during the milling process of a helical-edge cutter. At the same time, three force fluctuation characteristics related to the axial cutting depth and cutter parameters are determined: uniformity, periodicity and symmetry. The corresponding mathematical derivation and proof method are given for the first time through a force transformation of projecting the superposition chip thickness on a virtual cutting edge. On this basis, a fast estimation method and an accurate simulation method for force fluctuation prediction are established to quantify the intensity of force fluctuations under different parameters. Both two prediction methods and the experimental cutting tests validate the proposed theory effectively. The result shows a high potential of the proposed theory for studying the force behavior under different milling parameters or cutter parameters and at least 75% of the test workload can be reduced.
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3. |
- Wang, Luan, et al.
(author)
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Different Distribution of Core Microbiota in Upper Soil Layer in Two Places of North China Plain
- 2022
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In: Open Microbiology Journal. - : Bentham Science Publishers Ltd.. - 1874-2858 .- 1874-2858. ; 16:1
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Journal article (peer-reviewed)abstract
- Backgrounds: Soils harbor diverse bacteria, and these bacteria play important roles in soil nutrition cycling and carbon storage. Numerous investigations of soil microbiota had been performed, and the core microbiota in different soil or vegetation soil types had been described. The upper layer of soil, as a source of organic matter, is important and affected by the habitats and dominant bacteria. However, the complexity of soil environments and relatively limited information of many geographic areas had attracted great attention on comprehensive exploration of soil microbes in enormous types of soil. Methods: To reveal the core upper layer soil microbiota, soil samples from metropolis and countryside regions in the North China Plain were investigated using high-throughput sequencing strategy. Results: The results showed that the most dominant bacteria are Proteobacteria (38.34%), Actinobacteria (20.56%), and Acidobacteria (15.18%). At the genus-level, the most abundant known genera are Gaiella (3.66%), Sphingomonas (3.6%), Acidobacteria Gp6 (3.52%), and Nocardioides (2.1%). Moreover, several dominant operational taxanomy units OTUs, such as OTU_3 and OTU_17, were identified to be associated with the soil environment. Microbial distributions of the metropolis samples were different from the countryside samples, which may reflect the environments in the countryside were more diverse than in the metropolis. Microbial diversity and evenness were higher in the metropolis than in the countryside, which might due to the fact that human activity increased the microbial diversity in the metropolis. Conclusion: The upper layer soil core microbiota of the North China Plain were complex, and microbial distributions in these two places might be mainly affected by the human activity and environmental factors, not by the distance. Our data highlights the upper layer soil core microbiota in North China Plain, and provides insights for future soil microbial distribution studies in central China.
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4. |
- Aronov, Boris, et al.
(author)
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Are Friends of My Friends Too Social? Limitations of Location Privacy in a Socially-Connected World
- 2018
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In: PROCEEDINGS OF THE 2018 THE NINETEENTH INTERNATIONAL SYMPOSIUM ON MOBILE AD HOC NETWORKING AND COMPUTING (MOBIHOC 18). - New York, NY, USA : ASSOC COMPUTING MACHINERY. - 9781450357708 ; , s. 280-289
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Conference paper (peer-reviewed)abstract
- With the ubiquitous adoption of smartphones and mobile devices, it is now common practice for ones location to be sensed, collected and likely shared through social platforms. While such data can be helpful for many applications, users start to be aware of the privacy issue in handling location and trajectory data. While some users may voluntarily share their location information (e.g., for receiving location-based services, or for crowdsourcing systems), their location information may lead to information leaks about the whereabouts of other users, through the co-location of events when two users are at the same location at the same time and other side information, such as upper bounds of movement speed. It is therefore crucial to understand how much information one can derive about others positions through the co-location of events and occasional GPS location leaks of some of the users. In this paper we formulate the problem of inferring locations of mobile agents, present theoretically-proven bounds on the amount of information that could be leaked in this manner, study their geometric nature, and present algorithms matching these bounds. We will show that even if a very weak set of assumptions is made on trajectories patterns, and users are not obliged to follow any reasonable patterns, one could infer very accurate estimation of users locations even if they opt not to share them. Furthermore, this information could be obtained using almost linear-time algorithms, suggesting the practicality of the method even for huge volumes of data.
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5. |
- Boyang, M., et al.
(author)
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Open architecture CNC system based on soft-integrated communication
- 2018
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In: Procedia CIRP. - : Elsevier. - 2212-8271. ; , s. 671-676
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Conference paper (peer-reviewed)abstract
- The open architecture computer numerical control (OACNC) system meets the individualized demand of modern industry for its characteristics of flexibility, adaptability, versatility, and expansibility. Existing OACNC systems depend on specialized software which reduces the openness of the OACNC system. This paper introduces a new OACNC system based on a soft-integrated communication module. The module improves the data exchange principle in communication shared memory and is built by open API. Therefore the OACNC system can be compatible with different communication protocols between periodic and aperiodic. Then a case is proposed to test the compatibility and extensibility of the system. Finally, the prospect of the OACNC system and future research is discussed.
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6. |
- Chen, Xin, 1980, et al.
(author)
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Dataset for suppressors of amyloid-beta toxicity and their functions in recombinant protein production in yeast
- 2022
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In: Data in Brief. - : Elsevier BV. - 2352-3409. ; 42
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Journal article (peer-reviewed)abstract
- The production of recombinant proteins at high levels often induces stress-related phenotypes by protein misfolding or aggregation. These are similar to those of the yeast Alzheimer's disease (AD) model in which amyloid-beta peptides (A beta 42) were accumulated [1,2] . We have previously identified suppressors of A beta 42 cytotoxicity via the genome-wide synthetic genetic array (SGA) [3] and here we use them as metabolic engineering targets to evaluate their potentiality on recombinant protein production in yeast Saccharomyces cerevisiae. In order to investigate the mechanisms linking the genetic modifications to the improved recombinant protein production, we perform systems biology approaches (transcriptomics and proteomics) on the resulting strain and intermediate strains. The RNAseq data are preprocessed by the nf-core/RNAseq pipeline and analyzed using the Platform for Integrative Analysis of Omics (PIANO) package [4] . The quantitative proteome is analyzed on an Orbitrap Fusion Lumos mass spectrometer interfaced with an Easy-nLC1200 liquid chromatography (LC) system. LC-MS data files are processed by Proteome Discoverer version 2.4 with Mascot 2.5.1 as a database search engine. The original data presented in this work can be found in the research paper titled "Suppressors of Amyloid-beta Toxicity Improve Recombinant Protein Produc-tion in yeast by Reducing Oxidative Stress and Tuning Cellu-lar Metabolism", by Chen et al. [5] . (C) 2022 The Author(s). Published by Elsevier Inc.
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7. |
- Chen, Xin, 1980, et al.
(author)
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Suppressors of amyloid-β toxicity improve recombinant protein production in yeast by reducing oxidative stress and tuning cellular metabolism
- 2022
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In: Metabolic Engineering. - : Elsevier BV. - 1096-7176 .- 1096-7184. ; 72, s. 311-324
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Journal article (peer-reviewed)abstract
- High-level production of recombinant proteins in industrial microorganisms is often limited by the formation of misfolded proteins or protein aggregates, which consequently induce cellular stress responses. We hypothesized that in a yeast Alzheimer's disease (AD) model overexpression of amyloid-β peptides (Aβ42), one of the main peptides relevant for AD pathologies, induces similar phenotypes of cellular stress. Using this humanized AD model, we previously identified suppressors of Aβ42 cytotoxicity. Here we hypothesize that these suppressors could be used as metabolic engineering targets to alleviate cellular stress and improve recombinant protein production in the yeast Saccharomyces cerevisiae. Forty-six candidate genes were individually deleted and twenty were individually overexpressed. The positive targets that increased recombinant α-amylase production were further combined leading to an 18.7-fold increased recombinant protein production. These target genes are involved in multiple cellular networks including RNA processing, transcription, ER-mitochondrial complex, and protein unfolding. By using transcriptomics and proteomics analyses, combined with reverse metabolic engineering, we showed that reduced oxidative stress, increased membrane lipid biosynthesis and repressed arginine and sulfur amino acid biosynthesis are significant pathways for increased recombinant protein production. Our findings provide new insights towards developing synthetic yeast cell factories for biosynthesis of valuable proteins.
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8. |
- Diesen, Elias, et al.
(author)
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Ultrafast Adsorbate Excitation Probed with Subpicosecond-Resolution X-Ray Absorption Spectroscopy
- 2021
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In: Physical Review Letters. - 0031-9007 .- 1079-7114. ; 127:1
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Journal article (peer-reviewed)abstract
- We use a pump-probe scheme to measure the time evolution of the C K-edge x-ray absorption spectrum from CO/Ru(0001) after excitation by an ultrashort high-intensity optical laser pulse. Because of the short duration of the x-ray probe pulse and precise control of the pulse delay, the excitation-induced dynamics during the first picosecond after the pump can be resolved with unprecedented time resolution. By comparing with density functional theory spectrum calculations, we find high excitation of the internal stretch and frustrated rotation modes occurring within 200 fs of laser excitation, as well as thermalization of the system in the picosecond regime. The ∼100 fs initial excitation of these CO vibrational modes is not readily rationalized by traditional theories of nonadiabatic coupling of adsorbates to metal surfaces, e.g., electronic frictions based on first order electron-phonon coupling or transient population of adsorbate resonances. We suggest that coupling of the adsorbate to nonthermalized electron-hole pairs is responsible for the ultrafast initial excitation of the modes.
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9. |
- LaRue, Jerry, et al.
(author)
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Symmetry-resolved CO desorption and oxidation dynamics on O/Ru(0001) probed at the C K-edge by ultrafast x-ray spectroscopy
- 2022
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In: Journal of Chemical Physics. - : AIP Publishing. - 0021-9606 .- 1089-7690. ; 157:16
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Journal article (peer-reviewed)abstract
- We report on carbon monoxide desorption and oxidation induced by 400 nm femtosecond laser excitation on the O/Ru(0001) surface probed by time-resolved x-ray absorption spectroscopy (TR-XAS) at the carbon K-edge. The experiments were performed under constant background pressures of CO (6 × 10−8 Torr) and O2 (3 × 10−8 Torr). Under these conditions, we detect two transient CO species with narrow 2π* peaks, suggesting little 2π* interaction with the surface. Based on polarization measurements, we find that these two species have opposing orientations: (1) CO favoring a more perpendicular orientation and (2) CO favoring a more parallel orientation with respect to the surface. We also directly detect gas-phase CO2 using a mass spectrometer and observe weak signatures of bent adsorbed CO2 at slightly higher x-ray energies than the 2π* region. These results are compared to previously reported TR-XAS results at the O K-edge, where the CO background pressure was three times lower (2 × 10−8 Torr) while maintaining the same O2 pressure. At the lower CO pressure, in the CO 2π* region, we observed adsorbed CO and a distribution of OC–O bond lengths close to the CO oxidation transition state, with little indication of gas-like CO. The shift toward “gas-like” CO species may be explained by the higher CO exposure, which blocks O adsorption, decreasing O coverage and increasing CO coverage. These effects decrease the CO desorption barrier through dipole–dipole interaction while simultaneously increasing the CO oxidation barrier.
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10. |
- Li, Gang, 1991, et al.
(author)
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Bayesian genome scale modelling identifies thermal determinants of yeast metabolism
- 2021
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 12:1
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Journal article (peer-reviewed)abstract
- The molecular basis of how temperature affects cell metabolism has been a long-standing question in biology, where the main obstacles are the lack of high-quality data and methods to associate temperature effects on the function of individual proteins as well as to combine them at a systems level. Here we develop and apply a Bayesian modeling approach to resolve the temperature effects in genome scale metabolic models (GEM). The approach minimizes uncertainties in enzymatic thermal parameters and greatly improves the predictive strength of the GEMs. The resulting temperature constrained yeast GEM uncovers enzymes that limit growth at superoptimal temperatures, and squalene epoxidase (ERG1) is predicted to be the most rate limiting. By replacing this single key enzyme with an ortholog from a thermotolerant yeast strain, we obtain a thermotolerant strain that outgrows the wild type, demonstrating the critical role of sterol metabolism in yeast thermosensitivity. Therefore, apart from identifying thermal determinants of cell metabolism and enabling the design of thermotolerant strains, our Bayesian GEM approach facilitates modelling of complex biological systems in the absence of high-quality data and therefore shows promise for becoming a standard tool for genome scale modeling.
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