Silvaconley0819

Eating outside the three main meals - in other words, snacking - is a part of the dietary pattern of individuals in all stages of life. The quality and pattern of snacking have an impact on health during the life span. Thus, the aim of this review was to evaluate various patterns and health outcomes of the snacking habits of different demographical groups, from children to the elderly, throughout their life span. check details We discuss the snacking pattern among children and adolescents, which is characterized by consuming high energy foods with low nutrient value, and which is associated with increased risk of obesity. During university years, study stress and lack of time were obstacles to a healthy dietary pattern involving nutritious snacks, although awareness of the importance of healthy snacks was higher in this group than among younger age groups. Employment status and skipping regular meals were important factors affecting snacking quality and patterns in adulthood. Unhealthy snacks, high in energy, sugar, and salt and low in nutrients, were demonstrated to have a negative impact on individuals' health, such as oral health, blood pressure, obesity, and diabetes. In conclusion, encouraging individuals to consume healthy snacks that are high in nutrients through education to help them plan for their snacks is important to enhance health and reduce disease risk.

To assess the diagnostic performance and reader confidence in determining the resectability of pancreatic cancer at computed tomography (CT) using a new deep learning image reconstruction (DLIR) algorithm.

A retrospective review was conduct of on forty-seven patients with pathologically confirmed pancreatic cancers who underwent baseline multiphasic contrast-enhanced CT scan. Image data sets were reconstructed using filtered back projection (FBP), hybrid model-based adaptive statistical iterative reconstruction (ASiR-V) 60 %, and DLIR "TrueFidelity" at low(L), medium(M), and high strength levels(H). Four board-certified abdominal radiologists reviewed the CT images and classified cancers as resectable, borderline resectable, or unresectable. Diagnostic performance and reader confidence for categorizing the resectability of pancreatic cancer were evaluated based on the reference standards, and the interreader agreement was assessed using Fleiss k statistics.

For prediction of margin-negative resections(ie, R0), the average area under the receiver operating characteristic curve was significantly higher with DLIR-H (0.91; 95 % confidence interval [CI] 0.79, 0.98) than FBP (0.75; 95 % CI0.60, 0.86) and ASiR-V (0.81; 95 % CI0.67, 0.91) (p = 0.030 and 0.023 respectively). Reader confidence scores were significantly better using DLIR compared to FBP and ASiR-V 60 % and increased linearly with the increase of DLIR strength level (all p < 0.001). Among the image reconstructions, DLIR-H showed the highest interreader agreement in the resectability classification and lowest subject variability in the reader confidence.

The DLIR-H algorithm may improve the diagnostic performance and reader confidence in the CT assignment of the local resectability of pancreatic cancer while reducing the interreader variability.

The DLIR-H algorithm may improve the diagnostic performance and reader confidence in the CT assignment of the local resectability of pancreatic cancer while reducing the interreader variability.

To fully automatically derive quantitative parameters from late gadolinium enhancement (LGE) cardiac MR (CMR) in patients with myocardial infarction and to investigate if phase sensitive or magnitude reconstructions or a combination of both results in best segmentation accuracy.

In this retrospective single center study, a convolutional neural network with a U-Net architecture with a self-configuring framework ("nnU-net") was trained for segmentation of left ventricular myocardium and infarct zone in LGE-CMR. A database of 170 examinations from 78 patients with history of myocardial infarction was assembled. Separate fitting of the model was performed, using phase sensitive inversion recovery, the magnitude reconstruction or both contrasts as input channels. Manual labelling served as ground truth. In a subset of 10 patients, the performance of the trained models was evaluated and quantitatively compared by determination of the Sørensen-Dice similarity coefficient (DSC) and volumes of the infarct zone compared with the manual ground truth using Pearson's r correlation and Bland-Altman analysis.

The model achieved high similarity coefficients for myocardium and scar tissue. No significant difference was observed between using PSIR, magnitude reconstruction or both contrasts as input (PSIR and MAG; mean DSC 0.83 ± 0.03 for myocardium and 0.72 ± 0.08 for scars). A strong correlation for volumes of infarct zone was observed between manual and model-based approach (r = 0.96), with a significant underestimation of the volumes obtained from the neural network.

The self-configuring nnU-net achieves predictions with strong agreement compared to manual segmentation, proving the potential as a promising tool to provide fully automatic quantitative evaluation of LGE-CMR.

The self-configuring nnU-net achieves predictions with strong agreement compared to manual segmentation, proving the potential as a promising tool to provide fully automatic quantitative evaluation of LGE-CMR.Solar photocatalysis is the key to resolve many environmental challenges but is usually hard to achieve over a metal oxide semiconductor. Therefore, assembling π-conjugated molecules onto semiconductors becomes an efficient approach to solar conversion via ligand-to-metal charge transfer. Here, a rational design of ligands for titanium dioxide (TiO2) is presented to produce robust visible light photocatalysts. Three hydroxynaphthoic acids (HNAs) were selected as ligands by extending an extra benzene ring of salicylic acid (SA) at 3,4 or 4,5 or 5,6 positions. These ligands could regulate the performance of TiO2 in which 2-hydroxy-1-naphthoic acid (2H1NA) endows the best outcome. In detail, blue light-powered cooperative photocatalysis of 2H1NA-TiO2 with 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO, 5 mol%) inaugurates the expeditious formation of imines by oxidation of amines with atmospheric oxygen (O2). Interestingly, the increase of the O2 pressure from 1 atm to 0.4 MPa promoted the selective oxidation of benzylamine but thereafter declined with a further boost to 0.6 MPa. Notably, an electron transfer between the oxidatively quenched 2H1NA-TiO2 and TEMPO is established, offering a new pathway for environmental applications. This work presents a strategy in designing cutting-edge visible light photocatalysts via altering semiconductors with surface ligands.Molybdenum carbides are promising electrocatalysts for the hydrogen evolution reaction (HER). Rational design of morphology, composition and interfacial structure in Mo2C materials is essential to enhance their HER performance. Herein, an acid-base molecular assembly strategy is demonstrated for the synthesis of novel N-doped Mo2C@C core-shell nanowires (NWs) composed of mesoporous Mo2C cores with interconnected crystalline walls and ultrathin carbon shells. The strong interactions between the two precursors, adenine (Ade) and phosphomolybdic acid (PMA), lead to the formation of inter-molecular hybrid NWs during a hydrothermal process. The subsequent pyrolysis leads to confined growth of crystalline Mo2C NWs with inter-crystal mesopores (5 ~ 10 nm), formation of ultrathin carbon shells (~1.5 nm in thickness), and effective N doping. Such a structure architecture can provide abundant active sites, fast and diverse mass and electron transport paths, as well as stable reaction interfaces. The typical N-doped Mo2C@C NWs exhibit high HER performance with a low overpotential of 136 mV at 10 mA cm-2, a small Tafel slop of 58 mV dec-1, excellent durability and outstanding anti-poisoning performance against CO and H2S gases. Furthermore, the influences of several important factors, including the pyrolysis temperature, hydrothermal temperature and precursor mass ratio, on the morphology, composition and structural configuration of the resulted materials are elucidated and correlated with their HER performance. This work may provide a general strategy for the synthesis of other nanoscale metal carbides for various catalytic applications.A multifunctional metal-organic framework (MOF) hybrid Zr-FeTCPP-MOF is fabricated with 2-aminoterephthalic acid (NH2-BDC) and Fe (III) meso-Tetra (4-carboxyphenyl) porphine chloride (FeTCPPCl) participating in the coordination to Zr6 clusters via one-pot hydrothermal method. The adsorption of phosphoproteins on the surface of Zr-FeTCPP-MOF hybrid cause the chances on the absorbance (Abs), fluorescence (FL) and resonance light scattering (RLS) signals of Zr-FeTCPP-MOF/3,3',5,5'-Tetramethylbenzidine (TMB) system, and an array sensing platform is successfully built for sensitive identification of protein phosphorylation based on the three-dimensional spectral changes of MOF/TMB sensing system induced by the variations on the structure, size, and phosphorylation site of phosphoproteins. This array sensing system is robust in recognizing different phosphoprotein species, and shows high sensitivity in discriminating similar phosphoproteins of different phosphorylation distribution, i.e., caseins (α-, β- and κ-cas). The detection limit of this array sensing platform to individual phosphoprotein is low down to 5 nM. The practical application of this MOF/TMB-base sensing system is substantially demonstrated by identifying tau peptides with different phosphorylation distribution, and distinguishing cancer cells of abnormal phosphorylations from normal cells. This work proves the reliability, sensitivity, and practicality of the MOF/TMB-base sensing system platform for the diagnosis of phosphorylation-related diseases in clinical trials.Developing effective and robust novel electrocatalysts for direct alcohol fuel cells has been gaining much attention. However, the widely used Pt catalyst suffers from limitations including the sluggish kinetics, severe CO poisoning, and catalyst lost caused by aggregation and Ostwald ripening during alcohol oxidation reaction. Herein, dendritic intermetallic PtSnBi nanoalloys were synthesized via a facile hydrothermal approach with high electrocatalytic performance and enhanced CO resistance for methanol oxidation reaction (MOR) and ethanol oxidation reaction (EOR) owing to the synergism of the chosen three elements and unique three-dimensional morphology. Specifically, the PtSnBi nanoalloys display 4.6 and 6.7 times higher of mass activity (7.02 A mg-1Pt) and specific activity (16.65 mA cm-2) toward MOR than those of commercial Pt/C, respectively. The mass activity of PtSnBi nanoalloys still retains 75.7% of the initial value after 800 cycles of stability test, superior to Pt/C (38.0%). The dual-functional effect of Sn, optimized electronic structure by the ligand effect, and unique atomic arrangement are responsible for the enhanced MOR activity and stability of PtSnBi nanoalloys. Furthermore, the PtSnBi nanoalloys with highlighted anti-CO poisoning capacity also improve the electrocatalytic performance toward EOR, indicating their great promise as broad energy electrocatalysts.