Seasonal variations in carbon, nitrogen and phosphorus concentrations and C:N:P stoichiometry in different organs of a Larix principis-rupprechtii Mayr. plantation in the Qinling Mountains, China

Understanding how concentrations of elements and their stoichiometry change with plant growth and age is critical for predicting plant community responses to environmental change. Weusedlong-term field experiments to explore how the leaf, stem and root carbon (C), nitrogen (N) and phosphorous (P) concentrations and their stoichiometry changed with growth and stand age in a L.principis-rupprechtii Mayr. plantation from 2012–2015 in the Qinling Mountains, China. Our results showed that the C, N and P concentrations and stoichiometric ratios in different tissues of larch stands were affected by stand age, organ type andsampling month and displayed multiple correlations with increased stand age in different growing seasons. Generally, leaf C and N concentrations were greatest in the fast-growing season, but leaf P concentrations were greatest in the early growing season. However, no clear seasonal tendencies in the stem and root C, N and P concentrations were observed with growth. In contrast to N and P, few differences were found in organ-specific C concentrations. Leaf N:P was greatest in the fast-growing season, while C:N and C:P were greatest in the late-growing season. No clear variations were observed in stem and root C:N, C:P andN:Pthroughout the entire growing season, but leaf N:P was less than 14, suggesting that the growth of larch stands was limited by N in our study region. Compared to global plant element concentrations and stoichiometry, the leaves of larch stands had higher C, P, C:NandC:PbutlowerNandN:P,andtherootshadgreater PandC:NbutlowerN,C:Pand N:P. Our study provides baseline information for describing the changes in nutritional elements with plant growth, which will facilitates plantation forest management and restoration, and makes avaluable contribution to the global data pool on leaf nutrition and stoichiometry

Heterogeneity of pathological prion protein accumulation in the brain of moose (<i>Alces alces</i>) from Norway, Sweden and Finland with chronic wasting disease

Prion diseases are a group of neurodegenerative, transmissible, and fatal disorders that affect several animal species. They are characterized by the conformational conversion of the cellular prion protein (PrPC) into the pathological prion protein (PrPSc). In 2016, chronic wasting disease (CWD) gained great importance at European level due to the first disease detection in a wild reindeer (Rangifer tarandus) in Norway. The subsequent intensive CWD surveillance launched in cervids resulted in the detection of CWD in moose (Alces alces), with 11 cases in Norway, 3 in Finland and 4 in Sweden. These moose cases differ considerably from CWD cases in North American and reindeer in Norway, as PrPSc was detectable in the brain but not in lymphoid tissues. These facts suggest the occurrence of a new type of CWD. Here, we show some immunohistochemical features that are clearly different from CWD cases in North American and Norwegian reindeer. Further, the different types of PrPSc deposits found among moose demonstrate strong variations between the cases, supporting the postulation that these cases could carry multiple strains of CWD

Vegetarian diets are associated with healthy mood states: a cross-sectional study in Seventh Day Adventist adults

<p>Abstract</p> <p>Background</p> <p>The physical health status of vegetarians has been extensively reported, but there is limited research regarding the mental health status of vegetarians, particularly with regard to mood. Vegetarian diets exclude fish, the major dietary source of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), critical regulators of brain cell structure and function. Omnivorous diets low in EPA and DHA are linked to impaired mood states in observational and experimental studies.</p> <p>Methods</p> <p>We examined associations between mood state and polyunsaturated fatty acid intake as a result of adherence to a vegetarian or omnivorous diet in a cross-sectional study of 138 healthy Seventh Day Adventist men and women residing in the Southwest. Participants completed a quantitative food frequency questionnaire, Depression Anxiety Stress Scale (DASS), and Profile of Mood States (POMS) questionnaires.</p> <p>Results</p> <p>Vegetarians (VEG:n = 60) reported significantly less negative emotion than omnivores (OMN:n = 78) as measured by both mean total DASS and POMS scores (8.32 ± 0.88 vs 17.51 ± 1.88, <it>p </it>= .000 and 0.10 ± 1.99 vs 15.33 ± 3.10, <it>p </it>= .007, respectively). VEG reported significantly lower mean intakes of EPA (<it>p </it>< .001), DHA (<it>p </it>< .001), as well as the omega-6 fatty acid, arachidonic acid (AA; <it>p </it>< .001), and reported higher mean intakes of shorter-chain α-linolenic acid (<it>p </it>< .001) and linoleic acid (<it>p </it>< .001) than OMN. Mean total DASS and POMS scores were positively related to mean intakes of EPA (<it>p </it>< 0.05), DHA (<it>p </it>< 0.05), and AA (<it>p </it>< 0.05), and inversely related to intakes of ALA (<it>p </it>< 0.05), and LA (<it>p </it>< 0.05), indicating that participants with low intakes of EPA, DHA, and AA and high intakes of ALA and LA had better mood.</p> <p>Conclusions</p> <p>The vegetarian diet profile does not appear to adversely affect mood despite low intake of long-chain omega-3 fatty acids.</p

Effect of Neutralizing Monoclonal Antibody Treatment on Early Trajectories of Virologic and Immunologic Biomarkers in Patients Hospitalized With COVID-19

BACKGROUND: Neutralizing monoclonal antibodies (nmAbs) failed to show clear benefit for hospitalized patients with coronavirus disease 2019 (COVID-19). Dynamics of virologic and immunologic biomarkers remain poorly understood. METHODS: Participants enrolled in the Therapeutics for Inpatients with COVID-19 trials were randomized to nmAb versus placebo. Longitudinal differences between treatment and placebo groups in levels of plasma nucleocapsid antigen (N-Ag), anti-nucleocapsid antibody, C-reactive protein, interleukin-6, and D-dimer at enrollment, day 1, 3, and 5 were estimated using linear mixed models. A 7-point pulmonary ordinal scale assessed at day 5 was compared using proportional odds models. RESULTS: Analysis included 2149 participants enrolled between August 2020 and September 2021. Treatment resulted in 20% lower levels of plasma N-Ag compared with placebo (95% confidence interval, 12%-27%; P \u3c .001), and a steeper rate of decline through the first 5 days (P \u3c .001). The treatment difference did not vary between subgroups, and no difference was observed in trajectories of other biomarkers or the day 5 pulmonary ordinal scale. CONCLUSIONS: Our study suggests that nmAb has an antiviral effect assessed by plasma N-Ag among hospitalized patients with COVID-19, with no blunting of the endogenous anti-nucleocapsid antibody response. No effect on systemic inflammation or day 5 clinical status was observed. CLINICAL TRIALS REGISTRATION: NCT04501978

Reduced CSF turnover and decreased ventricular Aβ42 levels are related

International audienceBACKGROUND: The appearance of Aβ42 peptide deposits is admitted to be a key event in the pathogenesis of Alzheimer's disease, although amyloid deposits also occur in aged non-demented subjects. Aβ42 is a degradation product of the amyloid protein precursor (APP). It can be catabolized by several enzymes, reabsorbed by capillaries or cleared into cerebrospinal fluid (CSF). The possible involvement of a decrease in CSF turnover in A4β2 deposit formation is up to now poorly known. We therefore investigated a possible relationship between a reduced CSF turnover and the CSF levels of the A4β2 peptide.To this aim, CSF of 31 patients with decreased CSF turnover were studied. These patients presented chronic hydrocephalus communicating or obstructive, which required surgery (ventriculostomy or ventriculo-peritoneal shunt). Nine subjects had idiopathic normal pressure hydrocephalus (iNPH), and the other 22 chronic hydrocephalus from other origins (oCH).The Aβ42 peptide concentration was measured by an ELISA test in 31 ventricular CSF samples and in 5 lumbar CSF samples from patients with communicating hydrocephalus. RESULTS: The 5 patients with lumbar CSF analysis had similar levels of lumbar and ventricular Aβ42. A significant reduction in Aβ42 ventricular levels was observed in 24 / 31 patients with hydrocephalus. The values were lower than 300 pg/ml in 5 out of 9 subjects with iNPH, and in 15 out of 22 subjects with oCH. CONCLUSION: The decrease of CSF Aβ42 seems to occur independently of the surgical hydrocephalus aetiology. This suggests that a CSF reduced turnover may play an important role in the decrease of CSF Aβ42 concentration

Stoichiometric representation of geneproteinreaction associations leverages constraint-based analysis from reaction to gene-level phenotype prediction

Genome-scale metabolic reconstructions are currently available for hundreds of organisms. Constraint-based modeling enables the analysis of the phenotypic landscape of these organisms, predicting the response to genetic and environmental perturbations. However, since constraint-based models can only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene level by explicitly accounting for the individual fluxes of enzymes (and subunits) encoded by each gene. We show how this can be applied to different kinds of constraint-based analysis: flux distribution prediction, gene essentiality analysis, random flux sampling, elementary mode analysis, transcriptomics data integration, and rational strain design. In each case we demonstrate how this approach can lead to improved phenotype predictions and a deeper understanding of the genotype-to-phenotype link. In particular, we show that a large fraction of reaction-based designs obtained by current strain design methods are not actually feasible, and show how our approach allows using the same methods to obtain feasible gene-based designs. We also show, by extensive comparison with experimental 13C-flux data, how simple reformulations of different simulation methods with gene-wise objective functions result in improved prediction accuracy. The model transformation proposed in this work enables existing constraint-based methods to be used at the gene level without modification. This automatically leverages phenotype analysis from reaction to gene level, improving the biological insight that can be obtained from genome-scale models.DM was supported by the Portuguese Foundationfor Science and Technologythrough a post-doc fellowship (ref: SFRH/BPD/111519/ 2015). This study was supported by the PortugueseFoundationfor Science and Technology (FCT) under the scope of the strategic fundingof UID/BIO/04469/2013 unitand COMPETE2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145FEDER-000004) fundedby EuropeanRegional Development Fund under the scope of Norte2020Programa Operacional Regional do Norte. This project has received fundingfrom the European Union’s Horizon 2020 research and innovation programme under grant agreementNo 686070. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Reconstruction of Genome-Scale Active Metabolic Networks for 69 Human Cell Types and 16 Cancer Types Using INIT

Development of high throughput analytical methods has given physicians the potential access to extensive and patient-specific data sets, such as gene sequences, gene expression profiles or metabolite footprints. This opens for a new approach in health care, which is both personalized and based on system-level analysis. Genome-scale metabolic networks provide a mechanistic description of the relationships between different genes, which is valuable for the analysis and interpretation of large experimental data-sets. Here we describe the generation of genome-scale active metabolic networks for 69 different cell types and 16 cancer types using the INIT (Integrative Network Inference for Tissues) algorithm. The INIT algorithm uses cell type specific information about protein abundances contained in the Human Proteome Atlas as the main source of evidence. The generated models constitute the first step towards establishing a Human Metabolic Atlas, which will be a comprehensive description (accessible online) of the metabolism of different human cell types, and will allow for tissue-level and organism-level simulations in order to achieve a better understanding of complex diseases. A comparative analysis between the active metabolic networks of cancer types and healthy cell types allowed for identification of cancer-specific metabolic features that constitute generic potential drug targets for cancer treatment