Chinese hamster ovary (CHO) cells are extensively used for the production of glycoprotein therapeutics proteins, for which N-linked glycans are a critical quality attribute due to their influence on activity and immunogenicity. Manipulation of protein glycosylation is commonly achieved through cell or process engineering, which are often guided by mathematical models. However, each study considers a unique glycosylation reaction network that is tailored around the cell line and product at hand. Herein, we use 200 glycan datasets for both recombinantly produced and native proteins from different CHO cell lines to reconstruct a comprehensive reaction network, CHOGlycoNET, based on the individual minimal reaction networks describing each dataset. CHOGlycoNET is used to investigate the distribution of mannosidase and glycosyltransferase enzymes in the Golgi apparatus and identify key network reactions using machine learning and dimensionality reduction techniques. CHOGlycoNET can be used for accelerating glycomodel development and predicting the effect of glycoengineering strategies. Finally, CHOGlycoNET is wrapped in a SBML file to be used as a standalone model or in combination with CHO cell genome scale models.

Background & aims

Malnutrition may be a hidden but relevant health condition in individuals with obesity and osteoarthritis. The Global Leadership Initiative on Malnutrition (GLIM) consensus includes muscle mass as one of the key phenotypic criteria, potentially enhancing its ability to detect malnutrition in individuals with obesity. We comprehensively profiled the nutritional status of individuals with obesity and advanced knee osteoarthritis and explored associations with health outcomes.

Methods

Data from the Prevention Of MusclE Loss in Osteoarthritis (POMELO) study was used, which included individuals with knee osteoarthritis and BMI≥35 kg/m². Nutritional status was evaluated using the GLIM and sarcopenic obesity (SO) criteria. Low muscle mass (dual-energy x-ray absorptiometry), inflammation (C-reactive protein [CRP]), low muscle strength (handgrip/BMI), objective physical function (chair-stand test, 6-min walk test), and self-reported measures (quality of life, arthritis symptoms, and self-efficacy) were evaluated. Linear regressions were performed between GLIM-malnutrition and health outcomes, adjusted by age.

Results

Forty-six individuals (73.9% female, age 64.2 ± 6.7 years, BMI 42.4 ± 4.7 kg/m²) were included. Regarding nutritional status, 26.1% were classified with malnutrition (i.e., defined by the combination of low muscle mass and elevated CRP concentration), 26.1% with SO, and 13% shared both conditions. Individuals with malnutrition presented with worse self-reported physical function (WOMAC function: 38.0 ± 6.6 vs. 32.0 ± 12.5, p = 0.04) and lower arthritis self-efficacy ('other symptoms' component: 5.1 ± 1.9 vs. 6.3 ± 1.7, p = 0.04) compared to those without malnutrition. A trend was identified for lower quality of life (visual analog scale 46.8 ± 12.3 vs. 58.3 ± 20.5, p = 0.06) in those with malnutrition. Poor lipid control (R² = 0.15, β = 0.76, 95% CI 0.08-1.44, p = 0.030), body fat (R² = 0.14, β = 5.56, 95% CI 1.01-10.11, p = 0.018), and poor arthritis self-efficacy (R² = 0.09, β = -1.23, 95% CI -2.39-0.06, p = 0.040) were also associated with malnutrition.

Conclusions

Participants presented with high malnutrition rates (1 out of 4), and half of them also had SO. Malnutrition was associated with abnormal metabolic parameters, lower arthritis self-efficacy, and worse self-reported physical function. An early nutritional assessment and intervention may be imperative for individuals with osteoarthritis and obesity to mitigate health consequences.

Background

Psoriasis is a chronic skin disease associated with deregulated interplays between immune cells and keratinocytes. Neutrophil accumulation in the skin is a histological feature that characterizes psoriasis. However, the role of neutrophils in psoriasis onset and development remains poorly understood.

Methods

In this study, we utilized the model of psoriasiform dermatitis, caused by the repeated topical application of an imiquimod containing cream, in neutrophil-depleted mice or in mice carrying impairment in neutrophil functions, including p47phox -/- mice (lacking a cytosolic subunit of the phagocyte nicotinamide adenine dinucleotide phosphate - NADPH - oxidase) and Sykfl/fl MRP8-cre+ mice (carrying the specific deletion of the Syk kinase in neutrophils only), to elucidate the specific contribution of neutrophils to psoriasis development.

Results

By analyzing disease development/progression in neutrophil-depleted mice, we now report that neutrophils act as negative modulators of disease propagation and exacerbation by inhibiting gammadelta T cell effector functions via nicotinamide adenine dinucleotide phosphate (NADPH) oxidase-mediated reactive oxygen species (ROS) production. We also report that Syk functions as a crucial molecule in determining the outcome of neutrophil and γδ T cell interactions. Accordingly, we uncover that a selective impairment of Syk-dependent signaling in neutrophils is sufficient to reproduce the enhancement of skin inflammation and γδ T cell infiltration observed in neutrophil-depleted mice.

Conclusions

Overall, our findings add new insights into the specific contribution of neutrophils to disease progression in the IMQ-induced mouse model of psoriasis, namely as negative regulatory cells.

HIV-1 can downregulate HLA-C on infected cells, using the viral protein Vpu, and the magnitude of this downregulation varies widely between primary HIV-1 variants. The selection pressures that result in viral downregulation of HLA-C in some individuals, but preservation of surface HLA-C in others are not clear. To better understand viral immune evasion targeting HLA-C, we have characterized HLA-C downregulation by a range of primary HIV-1 viruses. 128 replication competent viral isolates from 19 individuals with effective anti-retroviral therapy, show that a substantial minority of individuals harbor latent reservoir virus which strongly downregulates HLA-C. Untreated infections display no change in HLA-C downregulation during the first 6 months of infection, but variation between viral quasispecies can be detected in chronic infection. Vpu molecules cloned from plasma of 195 treatment naïve individuals in chronic infection demonstrate that downregulation of HLA-C adapts to host HLA genotype. HLA-C alleles differ in the pressure they exert for downregulation, and individuals with higher levels of HLA-C expression favor greater viral downregulation of HLA-C. Studies of primary and mutant molecules identify 5 residues in the transmembrane region of Vpu, and 4 residues in the transmembrane domain of HLA-C, which determine interactions between Vpu and HLA. The observed adaptation of Vpu-mediated downregulation to host genotype indicates that HLA-C alleles differ in likelihood of mediating a CTL response that is subverted by viral downregulation, and that preservation of HLA-C expression is favored in the absence of these responses. Finding that latent reservoir viruses can downregulate HLA-C could have implications for HIV-1 cure therapy approaches in some individuals.

A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). Methods made use of modern machine learning tools and were based on unsupervised learning (autoencoders, generative adversarial networks, normalizing flows), weakly supervised learning, and semi-supervised learning. This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders.

A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders.

The search for Higgs bosons in both the standard model and its extensions is well under way at the Tevatron. As the integrated luminosity collected increases into the multiple inverse femptobarn range, these searches are becoming very interesting indeed. Meanwhile, the construction of the Large Hadron Collider (LHC) and its associated experiments at CERN are nearing completion. In this TeV4LHC workshop, it was realized that any experience at the Tevatron with respect to backgrounds, experimental techniques and theoretical calculations that can be verified at the Tevatron which have relevance for future measurements at the LHC were important. Studies and contributions to these efforts were made in three broad categories: theoretical calculations of Higgs production and decay mechanisms; theoretical calculations and discussions pertaining to non-standard model Higgs bosons; and experimental reviews, analyses and developments at both the Tevatron and the upcoming LHC experiments. All of these contributions represent real progress towards the elucidation of the mechanism of electroweak symmetry breaking.

This white paper addresses the hypothesis of light sterile neutrinos based on recent anomalies observed in neutrino experiments and the latest astrophysical data.

This is the third out of five chapters of the final report [1] of the Workshop on Physics at HL-LHC, and perspectives on HE-LHC [2]. It is devoted to the study of the potential, in the search for Beyond the Standard Model (BSM) physics, of the High Luminosity (HL) phase of the LHC, defined as $3~\mathrm{ab}^{-1}$ of data taken at a centre-of-mass energy of $14~\mathrm{TeV}$, and of a possible future upgrade, the High Energy (HE) LHC, defined as $15~\mathrm{ab}^{-1}$ of data at a centre-of-mass energy of $27~\mathrm{TeV}$. We consider a large variety of new physics models, both in a simplified model fashion and in a more model-dependent one. A long list of contributions from the theory and experimental (ATLAS, CMS, LHCb) communities have been collected and merged together to give a complete, wide, and consistent view of future prospects for BSM physics at the considered colliders. On top of the usual standard candles, such as supersymmetric simplified models and resonances, considered for the evaluation of future collider potentials, this report contains results on dark matter and dark sectors, long lived particles, leptoquarks, sterile neutrinos, axion-like particles, heavy scalars, vector-like quarks, and more. Particular attention is placed, especially in the study of the HL-LHC prospects, to the detector upgrades, the assessment of the future systematic uncertainties, and new experimental techniques. The general conclusion is that the HL-LHC, on top of allowing to extend the present LHC mass and coupling reach by $20-50\%$ on most new physics scenarios, will also be able to constrain, and potentially discover, new physics that is presently unconstrained. Moreover, compared to the HL-LHC, the reach in most observables will generally more than double at the HE-LHC, which may represent a good candidate future facility for a final test of TeV-scale new physics.

We report a search for narrow resonances, produced in p p̄ collisions at √ s=1.96 TeV, that decay into muon pairs with invariant mass between 6.3 and 9.0 GeV/c 2. The data, collected with the CDF II detector at the Fermilab Tevatron collider, correspond to an integrated luminosity of 630 pb -1. We use the dimuon invariant mass distribution to set 90% upper credible limits of about 1% to the ratio of the production cross section times muonic branching fraction of possible narrow resonances to that of the Υ(1S) meson. © 2009 Springer-Verlag.