Triglyceride-rich lipoproteins prevent septic death in rats.

Triglyceride-rich lipoproteins bind and inactive bacterial endotoxin in vitro and prevent death when given before a lethal dose of endotoxin in animals. However, lipoproteins have not yet been demonstrated to improve survival in polymicrobial gram-negative sepsis. We therefore tested the ability of triglyceride-rich lipoproteins to prevent death after cecal ligation and puncture (CLP) in rats. Animals were given bolus infusions of either chylomicrons (1 g triglyceride/kg per 4 h) or an equal volume of saline for 28 h after CLP. Chylomicron infusions significantly improved survival (measured at 96 h) compared with saline controls (80 vs 27%, P < or = 0.03). Chylomicron infusions also reduced serum levels of endotoxin, measured 90 min (26 +/- 3 vs 136 +/- 51 pg/ml, mean +/- SEM, P < or = 0.03) and 6 h (121 +/- 54 vs 1,026 +/- 459 pg/ml, P < or = 0.05) after CLP. The reduction in serum endotoxin correlated with a reduction in serum tumor necrosis factor, measured 6 h after CLP (0 +/- 0 vs 58 +/- 24 pg/ml, P < or = 0.03), suggesting that chylomicrons improve survival in this model by limiting macrophage exposure to endotoxin and thereby reducing secretion of inflammatory cytokines. Infusions of a synthetic triglyceride-rich lipid emulsion (Intralipid; KabiVitrum, Inc., Alameda, CA) (1 g triglyceride/kg) also significantly improved survival compared with saline controls (71 vs 27%, P < or = 0.03). These data demonstrate that triglyceride-rich lipoproteins can protect animals from lethal polymicrobial gram-negative sepsis

Plant communities affect arbuscular mycorrhizal fungal diversity and community composition in grassland microcosms

The diversity of arbuscular mycorrhizal (AM) fungi was investigated in an unfertilized limestone grassland soil supporting different synthesized vascular plant assemblages that had developed for 3 yr. The experimental treatments comprised: bare soil; monocultures of the nonmycotrophic sedge Carex flacca; monocultures of the mycotrophic grass Festuca ovina; and a species-rich mixture of four forbs, four grasses and four sedges. The diversity of AM fungi was analysed in roots of Plantago lanceolata bioassay seedlings using terminal-restriction fragment length polymorphism (T-RFLP). The extent of AM colonization, shoot biomass and nitrogen and phosphorus concentrations were also measured. The AM diversity was affected significantly by the floristic composition of the microcosms and shoot phosphorus concentration was positively correlated with AM diversity. The diversity of AM fungi in P. lanceolata decreased in the order: bare soil > C. flacca > 12 species > F. ovina. The unexpectedly high diversity in the bare soil and sedge monoculture likely reflects differences in the modes of colonization and sources of inoculum in these treatments compared with the assemblages containing established AM-compatible plants

Evidence for a fractional quantum Hall state with anisotropic longitudinal transport

At high magnetic fields, where the Fermi level lies in the N=0 lowest Landau level (LL), a clean two-dimensional electron system (2DES) exhibits numerous incompressible liquid phases which display the fractional quantized Hall effect (FQHE) (Das Sarma and Pinczuk, 1997). These liquid phases do not break rotational symmetry, exhibiting resistivities which are isotropic in the plane. In contrast, at lower fields, when the Fermi level lies in the $N\ge2$ third and several higher LLs, the 2DES displays a distinctly different class of collective states. In particular, near half filling of these high LLs the 2DES exhibits a strongly anisotropic longitudinal resistance at low temperatures (Lilly et al., 1999; Du et al., 1999). These "stripe" phases, which do not exhibit the quantized Hall effect, resemble nematic liquid crystals, possessing broken rotational symmetry and orientational order (Koulakov et al., 1996; Fogler et al., 1996; Moessner and Chalker, 1996; Fradkin and Kivelson, 1999; Fradkin et al, 2010). Here we report a surprising new observation: An electronic configuration in the N=1 second LL whose resistivity tensor simultaneously displays a robust fractionally quantized Hall plateau and a strongly anisotropic longitudinal resistance resembling that of the stripe phases.Comment: Nature Physics, (2011

Composite Fermion Metals from Dyon Black Holes and S-Duality

We propose that string theory in the background of dyon black holes in four-dimensional anti-de Sitter spacetime is holographic dual to conformally invariant composite Dirac fermion metal. By utilizing S-duality map, we show that thermodynamic and transport properties of the black hole match with those of composite fermion metal, exhibiting Fermi liquid-like. Built upon Dirac-Schwinger-Zwanziger quantization condition, we argue that turning on magnetic charges to electric black hole along the orbit of Gamma(2) subgroup of SL(2,Z) is equivalent to attaching even unit of statistical flux quanta to constituent fermions. Being at metallic point, the statistical magnetic flux is interlocked to the background magnetic field. We find supporting evidences for proposed holographic duality from study of internal energy of black hole and probe bulk fermion motion in black hole background. They show good agreement with ground-state energy of composite fermion metal in Thomas-Fermi approximation and cyclotron motion of a constituent or composite fermion excitation near Fermi-point.Comment: 30 pages, v2. 1 figure added, minor typos corrected; v3. revised version to be published in JHE

Classification Criteria for Intermediate Uveitis, Non–Pars Planitis Type

Purpose: To determine classification criteria for intermediate uveitis, non-pars planitis type (IU- NPP, also known as undifferentiated intermediate uveitis) / Design: Machine learning of cases with IU-NPP and 4 other intermediate uveitides. / Methods: Cases of intermediate uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the intermediate uveitides. The resulting criteria were evaluated on the validation set. / Results: Five hundred eighty-nine of cases of intermediate uveitides, including 114 cases of IU-NPP, were evaluated by machine learning. The overall accuracy for intermediate uveitides was 99.8% in the training set and 99.3% in the validation set (95% confidence interval 96.1, 99.9). Key criteria for IU-NPP included unilateral or bilateral intermediate uveitis with neither 1) snowballs in the vitreous nor 2) snowbanks on the pars plana. Other key exclusions included: 1) multiple sclerosis, 2) sarcoidosis, and 3) syphilis. The misclassification rates for pars planitis were 0 % in the training set and 0% in the validation set, respectively. / Conclusions: The criteria for IU-NPP had a low misclassification rate and appeared to perform well enough for use in clinical and translational research

Classification Criteria for Multiple Sclerosis-Associated Intermediate Uveitis

PURPOSE: The purpose of this study was to determine classification criteria for multiple sclerosis-associated intermediate uveitis. DESIGN: Machine learning of cases with multiple sclerosis-associated intermediate uveitis and 4 other intermediate uveitides. METHODS: Cases of intermediate uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used in the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the intermediate uveitides. The resulting criteria were evaluated in the validation set. RESULTS: A total of 589 cases of intermediate uveitides, including 112 cases of multiple sclerosis-associated intermediate uveitis, were evaluated by machine learning. The overall accuracy for intermediate uveitides was 99.8% in the training set and 99.3% in the validation set (95% confidence interval: 96.1-99.9). Key criteria for multiple sclerosis-associated intermediate uveitis included unilateral or bilateral intermediate uveitis and multiple sclerosis diagnosed by the McDonald criteria. Key exclusions included syphilis and sarcoidosis. The misclassification rates for multiple sclerosis-associated intermediate uveitis were 0 % in the training set and 0% in the validation set. CONCLUSIONS: The criteria for multiple sclerosis-associated intermediate uveitis had a low misclassification rate and appeared to perform sufficiently well enough for use in clinical and translational research

Bounding wide composite vector resonances at the LHC

In composite Higgs models (CHMs), electroweak precision data generically push colourless composite vector resonances to a regime where they dominantly decay into pairs of light top partners. This greatly attenuates their traces in canonical collider searches, tailored for narrow resonances promptly decaying into Standard Model final states. By reinterpreting the CMS same-sign dilepton (SS2$\ell$) analysis at the Large Hadron Collider (LHC), originally designed to search for top partners with electric charge $5/3$, we demonstrate its significant coverage over this kinematical regime. We also show the reach of the 13 TeV run of the LHC, with various integrated luminosity options, for a possible upgrade of the SS2$\ell$ search. The top sector of CHMs is found to be more fine-tuned in the presence of colourless composite resonances in the few TeV range.Comment: 9 pages, 5 figures. Minor corrections for publication in JHE

Enabling rational gut microbiome manipulations by understanding gut ecology through experimentally-evidenced in silico models

© 2021 The Author(s). The gut microbiome has emerged as a contributing factor in non-communicable disease, rendering it a target of health-promoting interventions. Yet current understanding of the host-microbiome dynamic is insufficient to predict the variation in intervention outcomes across individuals. We explore the mechanisms that underpin the gut bacterial ecosystem and highlight how a more complete understanding of this ecology will enable improved intervention outcomes. This ecology varies within the gut over space and time. Interventions disrupt these processes, with cascading consequences throughout the ecosystem. In vivo studies cannot isolate and probe these processes at the required spatiotemporal resolutions, and in vitro studies lack the representative complexity required. However, we highlight that, together, both approaches can inform in silico models that integrate cellular-level dynamics, can extrapolate to explain bacterial community outcomes, permit experimentation and observation over ecological processes at high spatiotemporal resolution, and can serve as predictive platforms on which to prototype interventions. Thus, it is a concerted integration of these techniques that will enable rational targeted manipulations of the gut ecosystem.University of Sydney’s Centre for Advanced Food and Engineering; JPMO acknowledges a PhD scholarship from the Faculty of Engineering at the University of Sydney. ERS acknowledges the financial support from the à Beckett Cancer Research Trust (University of Sydney Fellowship)

High throughput genome scale modeling predicts microbial vitamin requirements contribute to gut microbiome community structure

Data availability statement: All data generated or analyzed during this study are included in this published article and its supplementary information files.Copyright © 2022 The Author(s). Human gut microbiome structure and emergent metabolic outputs impact health outcomes. However, what drives such community characteristics remains underexplored. Here, we rely on high throughput genomic reconstruction modeling, to infer the metabolic attributes and nutritional requirements of 816 gut strains, via a framework termed GEMNAST. This has been performed in terms of a group of human vitamins to examine the role vitamin exchanges have at different levels of community organization. We find that only 91 strains can satisfy their vitamin requirements (prototrophs) while the rest show various degrees of auxotrophy/specialization, highlighting their dependence on external sources, such as other members of the microbial community. Further, 79% of the strains in our sample were mapped to 11 distinct vitamin requirement profiles with low phylogenetic consistency. Yet, we find that human gut microbial community enterotype indicators display marked metabolic differences. Prevotella strains display a metabolic profile that can be complemented by strains from other genera often associated with the Prevotella enterotype and agrarian diets, while Bacteroides strains occupy a prototrophic profile. Finally, we identify pre-defined interaction modules (IMs) of gut species from human and mice predicted to be driven by, or highly independent of vitamin exchanges. Our analysis provides mechanistic grounding to gut microbiome stability and to co-abundance-based observations, a fundamental step toward understanding emergent processes that influence health outcomes. Further, our work opens a path to future explorations in the field through applications of GEMNAST to additional nutritional dimensions.University of Sydney (PhD scholarship and à Beckett Cancer Research Trust Fellowship)

Electronic transport in polycrystalline graphene

Most materials in available macroscopic quantities are polycrystalline. Graphene, a recently discovered two-dimensional form of carbon with strong potential for replacing silicon in future electronics, is no exception. There is growing evidence of the polycrystalline nature of graphene samples obtained using various techniques. Grain boundaries, intrinsic topological defects of polycrystalline materials, are expected to dramatically alter the electronic transport in graphene. Here, we develop a theory of charge carrier transmission through grain boundaries composed of a periodic array of dislocations in graphene based on the momentum conservation principle. Depending on the grain boundary structure we find two distinct transport behaviours - either high transparency, or perfect reflection of charge carriers over remarkably large energy ranges. First-principles quantum transport calculations are used to verify and further investigate this striking behaviour. Our study sheds light on the transport properties of large-area graphene samples. Furthermore, purposeful engineering of periodic grain boundaries with tunable transport gaps would allow for controlling charge currents without the need of introducing bulk band gaps in otherwise semimetallic graphene. The proposed approach can be regarded as a means towards building practical graphene electronics.Comment: accepted in Nature Material