Investigating the Relationship between Dietary Sodium Intake and Severity Levels of Fluid Overload Symptoms in Patients with Heart Failure

Aim: This study aimed to investigate dietary sodium intake levels and to explore the relationship between those levels and the severity of fluid overload symptoms.Background: The management of dietary sodium is an important nursing intervention in the care of patients with heart failure stemming from fluid overload. Recommendations for the intake of dietary sodium among heart failure patients were discussed. If a heart failure patient’s dietary sodium intake habits are understood, then the relationship between this intake and fluid overload can be elucidated. This knowledge would be beneficial for nursing intervention in cases of heart failure.Methods: A total of 98 patients selected from cardiology wards who had a diagnosis of heart failure were enrolled in this study. Their dietary sodium intake level was estimated from a 24-hour urinary sodium excretion analysis. The severity of fluid overload symptoms was assessed using the fluid volume overload symptoms scale. Results: This study showed that the mean dietary sodium intake for patients with heart failure was 2.49 g/day and that this intake had no correlation with the severity levels of fluid overload symptoms. Conclusions: Using the patients’ own perceptions of the severity of fluid overload symptoms as a reference, adopting more relaxed sodium dietary intake restrictions may lead patients to have better food consumption habits

A Unified Framework for Mutual Improvement of SLAM and Semantic Segmentation

This paper presents a novel framework for simultaneously implementing localization and segmentation, which are two of the most important vision-based tasks for robotics. While the goals and techniques used for them were considered to be different previously, we show that by making use of the intermediate results of the two modules, their performance can be enhanced at the same time. Our framework is able to handle both the instantaneous motion and long-term changes of instances in localization with the help of the segmentation result, which also benefits from the refined 3D pose information. We conduct experiments on various datasets, and prove that our framework works effectively on improving the precision and robustness of the two tasks and outperforms existing localization and segmentation algorithms.Comment: 7 pages, 5 figures.This work has been accepted by ICRA 2019. The demo video can be found at https://youtu.be/Bkt53dAehj

Poly[diaqua­bis(μ3-1H-benzimidazole-5,6-dicarboxyl­ato-κ4 N 3:O 5,O 5′:O 6)bis­(μ2-1H,3H-benzimidazolium-5,6-dicarboxyl­ato-κ3 O 5,O 5′:O 6)digadolinium(III)]

In the title complex, [Gd2(C9H4N2O4)2(C9H5N2O4)2(H2O)2]n, two of the benzimidazole-5,6-dicarboxyl­ate ligands are pro­ton­ated at the imidazole groups. Each GdIII ion is coordinated by six O atoms and one N atom from five ligands and one water mol­ecule, displaying a distorted bicapped trigonal-prismatic geometry. The GdIII ions are linked by the carboxyl­ate groups and imidazole N atoms, forming a layer parallel to (001). These layers are further connected by O—H⋯O and N—H⋯O hydrogen bonds into a three-dimensional supra­molecular network

Poly[[aqua­(μ2-oxalato)(μ2-2-oxido­pyridinium-3-carboxylato)dysprosium(III)] monohydrate]

In the title complex, {[Dy(C6H4NO3)(C2O4)(H2O)]·H2O}n, the DyIII ion is coordinated by seven O atoms from two 2-oxidopyridinium-3-carboxylate ligands, two oxalate ligands and one water mol­ecule, displaying a distorted bicapped trigonal-prismatic geometry. The carboxyl­ate groups of the 2-oxidopyridinium-3-carboxylate and oxalate ligands link dysprosium metal centres, forming layers parallel to (100). These layers are further connected by inter­molecular O—H⋯O hydrogen-bonding inter­actions involving the coordin­ated water mol­ecules, forming a three-dimensional supra­molecular network. The uncoordinated water mol­ecule is involved in N—H⋯O and O—H⋯O hydrogen-bonding inter­actions within the layer

Brown Fat Paucity Due to Impaired BMP Signaling Induces Compensatory Browning of White Fat

Summary Maintenance of body temperature is essential for survival of homeotherms. Brown adipose tissue (BAT) is a specialized fat tissue that is dedicated to thermoregulation1. Due to its remarkable capacity to dissipate stored energy and its demonstrated presence in adult humans2-5, BAT holds great promise for the treatment of obesity and metabolic syndrome1. Rodent data suggest the existence of two types of brown fat cells: the constitutive BAT (cBAT), which is of embryonic origin and anatomically located in the interscapular region of mice, and the recruitable BAT (rBAT) that resides within white adipose tissue (WAT)6 and skeletal muscle7, that has alternatively been called beige8, brite9, or inducible BAT10. Bone morphogenetic proteins (BMPs) regulate the formation and thermogenic activity of BAT10-12. We here provide evidence for a systemically active regulatory mechanism that serves to control whole body BAT-activity for thermoregulation and energy homeostasis. Genetic ablation of type 1A BMP-receptor (Bmpr1A) in brown adipogenic progenitor cells leads to a severe paucity of cBAT. This in turn increases sympathetic input to WAT, thereby promoting the formation of rBAT within white fat depots. This previously unknown compensatory mechanism, aimed at restoring total brown fat-mediated thermogenic capacity in the body, is sufficient to maintain normal temperature homeostasis and resistance to diet-induced obesity. These data suggest an important physiological cross-talk between the constitutive and recruitable brown fat cells. This sophisticated regulatory mechanism of body temperature may participate in the control of energy balance and metabolic disease

Hierarchical TiO2/C nanocomposite monoliths with a robust scaffolding architecture, mesopore-macropore network and TiO2-C heterostructure for high-performance lithium ion batteries.

Engineering hierarchical structures of electrode materials is a powerful strategy for optimizing the electrochemical performance of an anode material for lithium-ion batteries (LIBs). Herein, we report the fabrication of hierarchical TiO2/C nanocomposite monoliths by mediated mineralization and carbonization using bacterial cellulose (BC) as a scaffolding template as well as a carbon source. TiO2/C has a robust scaffolding architecture, a mesopore-macropore network and TiO2-C heterostructure. TiO2/C-500, obtained by calcination at 500 °C in nitrogen, contains an anatase TiO2-C heterostructure with a specific surface area of 66.5 m(2) g(-1). When evaluated as an anode material at 0.5 C, TiO2/C-500 exhibits a high and reversible lithium storage capacity of 188 mA h g(-1), an excellent initial capacity of 283 mA h g(-1), a long cycle life with a 94% coulombic efficiency preserved after 200 cycles, and a very low charge transfer resistance. The superior electrochemical performance of TiO2/C-500 is attributed to the synergistic effect of high electrical conductivity, anatase TiO2-C heterostructure, mesopore-macropore network and robust scaffolding architecture. The current material strategy affords a general approach for the design of complex inorganic nanocomposites with structural stability, and tunable and interconnected hierarchical porosity that may lead to the next generation of electrochemical supercapacitors with high energy efficiency and superior power density.Sincere gratitude goes to funding agencies for financially support: Y. Xu to NNSF China (2117 1067, 21373100), Jilin Provincial Talent Fund (802110000412) and Tang Aoqing Professor Fund of Jilin University (450091105161). T. Hasan to the Royal Academy of Engineering Research Fellowship. B.L. Su to the Thousand Talents Program of China (“Expert of the State” position), Clare Hall Life Membership at the Clare Hall College and the financial support of the Department of Chemistry, University of Cambridge, L.H. Chen and Y. Li to the Department of Education of Hubei Province for “Chutian Scholar” program, NNSF China (21301133), Hubei Natural Science Foundation (2014CFB1 60, 2015CFB428) and the financial support of SRF for ROCS (SEM [2015]311).This is the author accepted manuscript. The final version is available from the Royal Society of Chemistry via https://doi.org/10.1039/C5NR09149

Rapid Identification of Asteraceae

Plants from Asteraceae family are widely used as herbal medicines and food ingredients, especially in Asian area. Therefore, authentication and quality control of these different Asteraceae plants are important for ensuring consumers’ safety and efficacy. In recent decades, electronic nose (E-nose) has been studied as an alternative approach. In this paper, we aim to develop a novel discriminative model by improving radial basis function artificial neural network (RBF-ANN) classification model. Feature selection algorithms, including principal component analysis (PCA) and BestFirst + CfsSubsetEval (BC), were applied in the improvement of RBF-ANN models. Results illustrate that in the improved RBF-ANN models with lower dimension data classification accuracies (100%) remained the same as in the original model with higher-dimension data. It is the first time to introduce feature selection methods to get valuable information on how to attribute more relevant MOS sensors; namely, in this case, S1, S3, S4, S6, and S7 show better capability to distinguish these Asteraceae plants. This paper also gives insights to further research in this area, for instance, sensor array optimization and performance improvement of classification model