Geriatric nutrition risk index: a more powerful index identifying muscle mass loss in patients with rheumatoid arthritis.

OBJECTIVE: To explore the association of geriatric nutrition risk index (GNRI), a traditional albumin-body weight calculation, with myopenia in patients with rheumatoid arthritis (RA) and compare its ability to identify myopenia with protein indicators. METHODS: This cross-sectional study was carried out based on a Chinese RA cohort. Clinical data and protein indicators (including albumin, globulin, albumin to globulin ratio, prealbumin, hemoglobin) were collected. GNRI was estimated by serum albumin and body weight. Myopenia was indicated as muscle mass loss measured by bioelectric impedance analysis. RESULTS: There were 789 RA patients included with mean age 52.6 ± 12.6 years and 77.6% female. There were 41.3%, 18.0%, 27.5%, 13.2% patients with no (GNRI > 98), low (GNRI 92 to ≤ 98), moderate (GNRI 82 to < 92), and major nutrition-related risk (GNRI < 82). There were 406 (51.5%) RA patients with myopenia, RA patients with major nutrition-related risk had the highest prevalence of myopenia (87.5% vs. 73.3% vs. 50.0% vs. 26.1%). Multivariate logistic analysis showed that compared with no risk, RA patients with low (OR = 3.23, 95% CI: 1.86-5.61), moderate (OR = 9.56, 95% CI: 5.70-16.01), and major nutrition-related risk (OR = 28.91, 95% CI: 13.54-61.71) were associated with higher prevalence of myopenia. Receiver operating characteristic curves showed that GNRI (AUC = 0.79) performed a better identifiable ability toward myopenia than serum albumin (AUC = 0.66) or others indicators (AUC range 0.59 to 0.65), respectively. CONCLUSION: GNRI, an objective and convenient albumin-weight index, may be preferable for identifying myopenia in RA patients. Key Points • We firstly elucidated the association of GNRI with muscle mass loss among RA patients, and compared its ability to identify muscle mass loss with serum albumin or other protein indicators. • Major nutrition-related risk identified by GNRI showed the highest risk of muscle mass loss, GNRI demonstrated a greater ability to identify myopenia in RA patients. which indicated GNRI was an objective and convenient albumin-weight index to identify myopenia in RA patients.

A moderate anticoccidial effect of cedrol on Eimeria tenella in broiler chickens.

As drug-resistant strains of Eimeria have emerged and concerns about drug residues in poultry have grown, there is renewed interest in identifying natural alternatives to control coccidiosis. Cedrol, a natural sesquiterpene alcohol, was used in this study to test anticoccidial efficacy in chicks. Both the control and treatment groups were orally challenged with 2 × 104 oocysts per chicken. Chicks administered with cedrol had reduced oocyst count, an increase in the relative weight gain rate of chicks, and a decrease in severe swelling of the cecum. Based on the above, ACI was calculated and the cedrol group reached moderate anti-coccidial activity (169.34). In chickens treated with cedrol, there were no changes in serum biochemical parameters, but oxidative stress biomarkers and cytokine levels associated with anticoccidial response were altered. These changes suggest that the administered concentration of cedrol did not have any adverse effects on the chickens while enhancing their antioxidant capacity and immunity, leading to an improved anticoccidial ability. In conclusion, this study shows that the addition of cedrol in poultry production has an anticoccidial effect and successfully improves growth performance during the growth period.

Activation of ß2-adrenergic receptors prevents AD-type synaptotoxicity via epigenetic mechanisms.

We previously reported that prolonged exposure to an enriched environment (EE) enhances hippocampal synaptic plasticity, with one of the significant mechanistic pathways being activation of ß2-adrenergic receptor (ß2-AR) signaling, thereby mitigating the synaptotoxic effects of soluble oligomers of amyloid ß-protein (oAß). However, the detailed mechanism remained elusive. In this work, we recorded field excitatory postsynaptic potentials (fEPSP) in the CA1 region of mouse hippocampal slices treated with or without toxic Aß-species. We found that pharmacological activation of ß2-AR, but not ß1-AR, selectively mimicked the effects of EE in enhancing LTP and preventing oAß-induced synaptic dysfunction. Mechanistic analyses showed that certain histone deacetylase (HDAC) inhibitors mimicked the benefits of EE, but this was not seen in ß2-AR knockout mice, suggesting that activating ß2-AR prevents oAß-mediated synaptic dysfunction via changes in histone acetylation. EE or activation of ß-ARs each decreased HDAC2, whereas Aß oligomers increased HDAC2 levels in the hippocampus. Further, oAß-induced inflammatory effects and neurite degeneration were prevented by either ß2-AR agonists or certain specific HDAC inhibitors. These preclinical results suggest that activation of ß2-AR is a novel potential therapeutic strategy to mitigate oAß-mediated features of AD.

Optimization method for Microcystis bloom mitigation by hydrogen peroxide and its stimulative effects on growth of chlorophytes.

Hydrogen peroxide (HP) is a feasible algicide to control cyanobacterial blooms, but its application in the waters with strong reductive power is still a problem. The rapid decomposition rate of HP results in a short residence time in the waters, which renders the failure of bloom mitigation. In this study, the damage of Microcystis aeruginosa (M. aeruginosa) by HP, the optimization method for Microcystis bloom control and its field effects were investigated. Results of microcosm experiments indicated M. aeruginosa was vulnerable to HP. The HP-induced damage was mainly attributed to the impairments of HP detoxification pathways and photosystem. Repetitive additions of HP, which could prolong the residence time, were conducted in the mesocosm experiments. HP concentration ranged from 96 µM to 165 µM for 2 h could successfully mitigate Microcystis bloom, even though HP decomposition rate reached 109 µM per h. Besides the removal of M. aeruginosa, contents of total dissolved nitrogen, total dissolved phosphate, dissolved organic carbon and chromophoric dissolved organic matter in water column increased significantly (p < 0.05). The enrichment of nutrients promoted the growth of chlorophytes but the growth of M. aeruginosa couldn't be observed. The dominant species thrived in the HP-treated waters was Chlamydomonas sp. Results in this study confirmed that HP was a promising algicide for cyanobacterial blooms control. The optimization method further demonstrated that repetitive additions of HP could favor the mitigation of cyanobacterial blooms.

An Intelligent Computing Method for Contact Plan Design in the Multi-Layer Spatial Node-Based Internet of Things.

Computational Intelligence (CI) has been addressed as a great challenge in recent years, particularly the aspects of routing, task scheduling, and other high-complexity issues. Especially for the Contact Plan Design (CPD) that schedules contacts in dynamic and resource-constrained networks, a suitable CI algorithm can be exchanged for a high-quality Contact Plan (CP) with the appropriate computational overhead. Previous works on CPD mainly focused on the optimization of satellite network connectivity, but most of them ignored network topology characteristics. In this paper, we study the CPD issue in the spatial node based Internet of Things (IoT), which enables the spatial nodes to deliver data cooperatively via intelligent networking. Specifically, we first introduce a Multi-Layer Space Communication Network (MLSCN) model consisting of satellites, High Altitude Platforms (HAPs), Unmanned Aerial Vehicles (UAVs), and ground stations, on which a Time-Evolving Graph (TEG) is used to illustrate the CPD process. Then, according to the characteristics of each layer in the MLSCN, we design the corresponding CPs for the inter-layer contacts and intra-layer contacts. After that, a CI algorithm named as Multidirectional Particle Swarm Optimization (MPSO) is proposed for inter-layer CPD, which utilizes a grid-based initialization strategy to expand the diversity of individuals, in which a quaternary search method and quaternary optimization are introduced to improve efficiency of particle swarms in iterations and to ensure the continuous search ability, respectively. Furthermore, an optimized scheme is implemented for the intra-layer CPD to reduce congestion and improve transmission efficiency. Simulation results show that the proposed CPD scheme can realize massive data transmission with high efficiency in the multi-layer spatial node-based IoT.