[Quantitative analysis of lipid metabolism-related differential proteins in patients with alcoholic liver disease]

Objective: To screen and identify differential proteins, analyze lipid metabolism-related proteins and pathways, and explore their functions and biological processes in liver tissue of patients with alcoholic liver disease using tandem mass tag (TMT) labeling technology. Methods: Liver tissues that met the inclusion criteria were collected. Eight samples from patients with alcoholic cirrhosis and three samples from the normal control group were screened out. The TMT technique was used to screen differential proteins, perform signaling pathway enrichment analysis, and analyze protein interaction networks to explore the biological processes involved in them. Results: Proteomic analysis identified 2 741 kinds of differentially expressed proteins in the two groups of data with statistical significance (P < 0.05). The standard criteria of P < 0.05 and |log2(foldchange)| > 1 had screened out 106 kinds of differentially expressed proteins. Compared with the control group, the alcoholic liver disease group had 12 kinds of up-regulated proteins and 94 kinds of down-regulated proteins. Among them, there were 2 kinds of up-regulated differential proteins related to lipid metabolism and 14 kinds of down-regulated differential proteins. The results of bioinformatics analysis showed that these proteins were primarily involved in biological processes such as lipid transport, regulation of lipase activity, fatty acid binding, and cholesterol metabolism in lipid metabolism and also had a close link to signal pathways related to lipid metabolism such as peroxisome proliferator-activated receptor signaling pathways, cholesterol metabolism, triglyceride metabolism, and regulation of lipolysis in adipocytes. Conclusion: The 16 kinds of lipid metabolism-related differential proteins may be the key proteins in the pathogenesis of alcoholic liver disease.

Measurement of Sequential ϒ Suppression in Au+Au Collisions at sqrt[s_{NN}]=200 GeV with the STAR Experiment

We report on measurements of sequential ϒ suppression in Au+Au collisions at sqrt[s_{NN}]=200  GeV with the STAR detector at the Relativistic Heavy Ion Collider (RHIC) through both the dielectron and dimuon decay channels. In the 0%-60% centrality class, the nuclear modification factors (R_{AA}), which quantify the level of yield suppression in heavy-ion collisions compared to p+p collisions, for ϒ(1S) and ϒ(2S) are 0.40±0.03(stat)±0.03(sys)±0.09(norm) and 0.26±0.08(stat)±0.02(sys)±0.06(norm), respectively, while the upper limit of the ϒ(3S) R_{AA} is 0.17 at a 95% confidence level. This provides experimental evidence that the ϒ(3S) is significantly more suppressed than the ϒ(1S) at RHIC. The level of suppression for ϒ(1S) is comparable to that observed at the much higher collision energy at the Large Hadron Collider. These results point to the creation of a medium at RHIC whose temperature is sufficiently high to strongly suppress excited ϒ states.

A8 MICROBIAL ACTIVATION OF INTESTINAL DENDRITIC CELLS IS CRITICAL FOR THE ESTABLISHMENT OF NORMAL BEHAVIOR

Background

Accumulating evidence suggests that gut microbiota affects brain development and its function. It is well known that compared with conventional mice (SPF), germ-free (GF) mice display higher exploratory behavior, which normalizes after bacterial colonization. However, little is known about the underlying mechanisms and first critical steps initiating microbiota-gut-brain communication, which lead to establishment of normal behavior.

Purpose

To investigate the role of immune system in the establishment of normal behavior after bacterial colonization.

Method

We assessed behavior in GF mice before and after colonization with SPF microbiota, Altered Schaedler Flora (ASF) or the single bacterial strain E. coli JM83, and compared them to SPF mice, using the light-dark preference and tail suspension tests. Levels of brain-derived neurotrophic factor (BDNF) and c-Fos expression were measured by immunofluorescence in the hippocampus and amygdala. Colonic and brain gene expression were assessed using a NanoString technology. The immunodeficient MyD88-/- Ticam1- and SCID mice were used to study the role of the innate and adaptive immune systems. To demonstrate the role of the dendritic cells (DCs), we measured behavior before and after mono-colonization with E. coli JM83 in GF mice treated with cosalane and fingolimod, that inhibit DCs activation and migration, respectively. Brain levels of CD11b, CD11c and CD103 as DCs markers was assessed by immunofluorescence.

Result(s)

Compared to SPF mice, GF mice showed higher exploratory and less depressive-like behavior. The ex-germ-free mice colonized with ASF microbiota, or mono-colonized with E. coli JM83 showed similar normalization of behavior as those colonized with SPF microbiota. Mono-colonization with E. coli reduced both BDNF and c-fos levels in the hippocampus and amygdala. While colonization of GF SCID mice induced same change in behavior as in wild-type mice, GF MyD88-/-Ticam1-/- mice did not alter their behavior. Mono-colonization affected multiple genes in the colon and the brain, associated with innate immunity and neural plasticity. Treatment with both cosalane and fingolimod prevented behavioral changes after colonization, which was paralleled by absence of CD11b+CD103+CD11c+ cells in the brain, otherwise found in high numbers in control mono-colonized mice and absent in germ-free mice.

Conclusion(s)

The innate immune system, through activation and migration of intestinal dendritic cells into the brain, initiates the neuro-immune signaling within the gut-brain axis and leads to normalization of behavior after bacterial colonization. Our findings may impact several psychiatric conditions, in which altered innate immune signaling has been implicated.

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CIHR, Other

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Balsam Family Foundation

Disclosure of Interest

None Declared

Beam Energy Dependence of Fifth- and Sixth-Order Net-Proton Number Fluctuations in Au+Au Collisions at RHIC

We report the beam energy and collision centrality dependence of fifth and sixth order cumulants (C_{5}, C_{6}) and factorial cumulants (κ_{5}, κ_{6}) of net-proton and proton number distributions, from center-of-mass energy (sqrt[s_{NN}]) 3 GeV to 200 GeV Au+Au collisions at RHIC. Cumulant ratios of net-proton (taken as proxy for net-baryon) distributions generally follow the hierarchy expected from QCD thermodynamics, except for the case of collisions at 3 GeV. The measured values of C_{6}/C_{2} for 0%-40% centrality collisions show progressively negative trend with decreasing energy, while it is positive for the lowest energy studied. These observed negative signs are consistent with QCD calculations (for baryon chemical potential, μ_{B}≤110  MeV) which contains the crossover transition range. In addition, for energies above 7.7 GeV, the measured proton κ_{n}, within uncertainties, does not support the two-component (Poisson+binomial) shape of proton number distributions that would be expected from a first-order phase transition. Taken in combination, the hyperorder proton number fluctuations suggest that the structure of QCD matter at high baryon density, μ_{B}∼750  MeV at sqrt[s_{NN}]=3  GeV is starkly different from those at vanishing μ_{B}∼24  MeV at sqrt[s_{NN}]=200  GeV and higher collision energies.

A matter of the beehive sound: Can honey bees alert the pollution out of their hives?

Honey bees (Apis spp.) are often used as biological indicators of environmental changes. Recently, bees have been explored to monitor air contaminants by listening to the beehive sound. The beehive sound is believed to encode information on bee responses to chemicals outside their hives. Here we conducted an experiment to address this. First, we randomly fed colonies with pure syrup (PS), acetone-laced syrup (AS), or ethyl acetate-laced syrup (ES) in front of the beehives and collect the beehive sound. Based on the audio data, we build machine learning (ML) models to identify the types of syrup. The result shows that ML models achieved over 90% accuracy for identifying syrup types, indicating that the bees inside their hives emitted the sound associated with the chemicals outside their hives. Then, we sequentially fed the colonies in the order of PS, ES, and AS (the first session) and again in the reverse order (the second session), but did not remove the accumulated ES or AS in the alternative feeding experiment. Based on the audio data, the identification accuracy of both ES and AS by the ML model built on the randomly feeding experiment was different, indicating that the accumulated chemical residuals could confuse the ML models. Therefore, the beehive sound-based environmental monitoring should simultaneously consider the responses of bees to the chemicals outside their hives and their responses to those accumulated inside their hives, which may act simultaneously.

The KNee OsteoArthritis Prediction (KNOAP2020) challenge: An image analysis challenge to predict incident symptomatic radiographic knee osteoarthritis from MRI and X-ray images

OBJECTIVES

The KNee OsteoArthritis Prediction (KNOAP2020) challenge was organized to objectively compare methods for the prediction of incident symptomatic radiographic knee osteoarthritis within 78 months on a test set with blinded ground truth.

DESIGN

The challenge participants were free to use any available data sources to train their models. A test set of 423 knees from the Prevention of Knee Osteoarthritis in Overweight Females (PROOF) study consisting of magnetic resonance imaging (MRI) and X-ray image data along with clinical risk factors at baseline was made available to all challenge participants. The ground truth outcomes, i.e., which knees developed incident symptomatic radiographic knee osteoarthritis (according to the combined ACR criteria) within 78 months, were not provided to the participants. To assess the performance of the submitted models, we used the area under the receiver operating characteristic curve (ROCAUC) and balanced accuracy (BACC).

RESULTS

Seven teams submitted 23 entries in total. A majority of the algorithms were trained on data from the Osteoarthritis Initiative. The model with the highest ROCAUC (0.64 (95% confidence interval (CI): 0.57-0.70)) used deep learning to extract information from X-ray images combined with clinical variables. The model with the highest BACC (0.59 (95% CI: 0.52-0.65)) ensembled three different models that used automatically extracted X-ray and MRI features along with clinical variables.

CONCLUSION

The KNOAP2020 challenge established a benchmark for predicting incident symptomatic radiographic knee osteoarthritis. Accurate prediction of incident symptomatic radiographic knee osteoarthritis is a complex and still unsolved problem requiring additional investigation.

Outreach, Screening, and Randomization of APOE ε4 Carriers into an Alzheimer's Prevention Trial: A global Perspective from the API Generation Program

BACKGROUND

Alzheimer's disease (AD) prevention trials require a large outreach and screening funnel to identify cognitively unimpaired adults who meet the study's inclusion criteria, such as certain clinical or demographic criteria, genetic risk factors, and/or biomarker evidence of the disease.

OBJECTIVES

Describe tactics and strategies to identify and enroll cognitively unimpaired adults with one (heterozygotes [HT]) or two (homozygotes [HM]) copies of the APOE ε4 allele, a genetic risk factor for dementia due to AD, into the Alzheimer's Prevention Initiative (API) Generation Program, the largest and only prevention trials for late onset AD using this enrichment technique.

DESIGN AND SETTING

The Generation Program was comprised of two global, randomized, double-blind, placebo-controlled, parallel group adaptive design with variable treatment duration clinical trials. Generation Study 1 randomized participants into one of two cohorts: Cohort 1 which evaluated CAD106 vs. placebo or Cohort 2 which evaluated umibecestat vs placebo. Generation Study 2 randomized participants into two doses of umibecestat vs. placebo. The Generation Program was terminated early in 2019, while enrollment was still occurring.

PARTICIPANTS

Both Generation Study 1 and Generation Study 2 enrolled cognitively unimpaired APOE ε4 HMs aged 60-75; Generation Study 2 also enrolled APOE ε4 HTs ages 60-75 with elevated brain amyloid.

METHODS AND MEASUREMENTS

Describe results of the centralized and localized outreach, recruitment, screening strategies and tactics as well as characteristics of sites successful at enrolling genetically eligible participants, with a particular focus on APOE ε4 HMs given the 2-3% prevalence of this genotype.

RESULTS

At the time the trial program was terminated, 35,333 individuals had consented to the optional prescreening ICF1a/ICFA and provided a sample of DNA for APOE genotyping, 1,138 APOE ε4 HMs consented to screening for Generation Study 1 (ICF1b), and 1,626 APOE ε4 carriers were randomized into either Generation Study 1 or Generation Study 2. Genetic testing registries, partnerships with genetic testing/counseling companies, and the optional prescreening ICF1a/ICFA were the most successful strategies for identifying genetically eligible participants for screening.

CONCLUSIONS

It is feasible to recruit, screen and randomize cognitively unimpaired APOE ε4 carriers, particularly APOE ε4 HMs for a global AD prevention trial. The Generation Program was on track to complete enrollment by end of 2019. Factors that were key to this success included: working with sites to develop customizable outreach, recruitment, and screening programs specific to their site needs, providing forums for sites to exchange best practices, and developing partnerships between the sponsor team and trial sites.

Collision-System and Beam-Energy Dependence of Anisotropic Flow Fluctuations

Elliptic flow measurements from two-, four-, and six-particle correlations are used to investigate flow fluctuations in collisions of U+U at sqrt[s_{NN}]=193  GeV, Cu+Au at sqrt[s_{NN}]=200  GeV and Au+Au spanning the range sqrt[s_{NN}]=11.5-200  GeV. The measurements show a strong dependence of the flow fluctuations on collision centrality, a modest dependence on system size, and very little if any, dependence on particle species and beam energy. The results, when compared to similar LHC measurements, viscous hydrodynamic calculations, and trento model eccentricities, indicate that initial-state-driven fluctuations predominate the flow fluctuations generated in the collisions studied.

[Research progress in the association of periodontitis and gestational diabetes mellitus]

Periodontitis is the main cause of adult tooth loss, which seriously affects oral health and acts as a high-risk factor for varieties of systemic diseases. Gestational diabetes mellitus (GDM) is defined as glucose intolerance occurred or firstly identified during pregnancy. Prevalence of GDM is increasing over the past years worldwide. Besides adverse effects toward maternal and infant health in perinatal period, GDM also has long-term effects. Current studies have demonstrated that there is a bidirectional relationship between periodontitis and diabetes; however, the exact relationship between periodontitis and GDM remains elusive. In this paper, first reviewed the clinical association of periodontitis and GDM, and then discussed the underlying mechanisms of the two diseases, finally summarized the positive effect of periodontal therapy in controlling GDM. This paper will provide theoretical basis for the prevention diagnosis and therapy for the related diseases, promoting the maternal and infant health.

Synthesis and Electrochemical Performance of V6O13 Nanosheets Film Cathodes for LIBs

V₆O₁₃ thin films were deposited on indium-doped tin oxide (ITO) conductive glass by a concise low-temperature liquid-phase deposition method and through heat treatment. The obtained films were directly used as electrodes without adding any other media. The results indicate that the film annealed at 400 °C exhibited an excellent cycling performance, which remained at 82.7% of capacity after 100 cycles. The film annealed at 400 °C with diffusion coefficients of 6.08 × 10^-12 cm²·s^-1 (Li⁺ insertion) and 5.46 × 10^-12 cm²·s^-1 (Li⁺ extraction) in the V₆O₁₃ film electrode. The high diffusion coefficients could be ascribed to the porous morphology composed of ultrathin nanosheets. Moreover, the film endured phase transitions during electrochemical cycling, the V₆O₁₃ partially transformed to Li_0.6V_1.67O_3.67, Li₃VO₄, and VO₂ with the insertion of Li⁺ into the lattice, and Li_0.6V_1.67O_3.67, Li₃VO₄, and VO₂ partially reversibly transformed backwards to V₆O₁₃ with the extraction of Li⁺ from the lattice. The phase transition can be attributed to the unique structure and morphology with enough active sites and ions diffusion channels during cycles. Such findings reveal a bright idea to prepare high-performance cathode materials for LIBs.

Carbon-coated iron nanopowder as a sintering aid for water-atomized iron powder

The paper examines the influence of carbon coating on iron nanopowder used as a sintering aid for water-atomized iron powder. Iron nanopowder without such a coating was used as a reference sintering aid to isolate the influence of the carbon coating. Both nanopowder variants were characterised using XPS and HRTEM. The results showed a core–shell structure for both variants. The iron nanopowder is covered by a 3–4 nm thick iron oxide layer, while the carbon-coated iron nanopowder is encapsulated with several nanometric carbon layers. Thermogravimetry conducted in a pure hydrogen environment shows a multipeak behaviour for the carbon-coated iron nanopowder, while a single peak behaviour is observed for the iron nanopowder. Two types of micro/nanobimodal powders were obtained by mixing the nanopowder with water-atomized iron powder. Improved linear shrinkage was observed during sintering when the carbon-coated iron nanopowder was added. This can be explained by the reduction in surface diffusion in the nanopowder caused by the carbon coating, which allows the nanopowder to sinter at higher temperatures and improves densification. Carbon and oxygen analysis, density measurements, optical microscopy and JMatPro calculations were also performed.