Fabrication and Characterization of Konjac Glucomannan/Oat ß-Glucan Composite Hydrogel: Microstructure, Physicochemical Properties and Gelation Mechanism Studies.

The aim of this study was to evaluate the effect of oat ß-glucan on the formation mechanism, microstructure and physicochemical properties of konjac glucomannan (KGM) composite hydrogel. The dynamic rheology results suggested that the addition of oat ß-glucan increased the viscoelastic modulus of the composite hydrogel, which was conducive to the formation of a stronger gel network. Gelling force experiments showed that hydrogen bonds and hydrophobic interactions participated in the formation of the gel network. Textural profile analysis results found that the amount of oat ß-glucan was positively correlated with the elasticity, cohesiveness and chewiness of the composite hydrogel. The water-holding capacity of the composite hydrogel was enhanced significantly after the addition of oat ß-glucan (p < 0.05), which was 18.3 times that of the KGM gel. The thermal stability of KGM gel was enhanced after the addition of oat ß-glucan with the increase in Tmax being approximately 30 °C. Consequently, a composite hydrogel based on KGM and oat ß-glucan was a strategy to overcome pure KGM gel shortcomings.

Risk Factors and Safety Analyses for Intrapartum Fever in Pregnant Women Receiving Epidural Analgesia During Labor.

BACKGROUND We aimed to explore the factors leading to epidural-related maternal fever and the influence of intrapartum fever on neonates. MATERIAL AND METHODS A retrospective analysis was performed on data from pregnant women who received epidural analgesia during labor. The primary aim was to determine the influence of epidural labor analgesia on the incidence of intrapartum fever in pregnant women. The secondary aim was to determine the influence of intrapartum fever on neonates. RESULTS Logistic regression analysis showed that premature rupture of membranes (OR=2.008, 95% CI: 1.551-2.600), vaginal examination performed more than 6 times (OR=1.681, 95% CI: 1.286-2.197), long duration of labor (OR=1.090, 95% CI: 1.063-1.118), and long time from rupture of membranes to delivery (OR=1.048, 95% CI: 1.010-1.087) were all risk factors for intrapartum fever in pregnant women with epidural labor analgesia. Regarding the secondary research outcome, the incidence of intrapartum fever was significantly associated with the number of neonates with Apgar score of 10 delivered from pregnant women with epidural labor analgesia (P<0.05). There was no statistically significant difference in the transfer rate of newborns to the Neonatal Intensive Care Unit (NICU) (P>0.05). CONCLUSIONS Premature rupture of membranes, vaginal examination performed more than 6 times, long duration of labor, and long time from rupture of membranes to delivery are all factors raising the risk of fever during epidural labor analgesia. Although intrapartum fever in the mothers had a significant influence on the number of neonates with Apgar score of 10, it did not affect the outcome of neonates in terms of NICU transfer rate.

Structural Characteristics and Immunomodulatory Effects of Melanoidins from Black Garlic.

Melanoidins are considered to have several biological activities. In this study, black garlic melanoidins (MLDs) were collected using ethanol solution extraction; 0%, 20%, and 40% ethanol solutions were used for chromatography. Three kinds of melanoidins were produced by macroporous resin, named MLD-0, MLD-20, and MLD-40. The molecular weight was determined, and the infrared and microscopic structures were studied. In addition, Balb/c mice were induced with cyclophosphamide (CTX) to establish an immune deficiency model to evaluate the immune efficacy of black garlic melanoidins (MLDs). The results showed that MLDs restored the proliferation and phagocytosis ability of macrophages, and the proliferation activity of B lymphocytes in the MD group was 63.32% (♀) and 58.11% (♂) higher than that in the CTX group, respectively. In addition, MLDs alleviated the abnormal expression of serum factors such as IFN-γ, IL-10, and TNF-α. 16SrDNA sequencing of intestinal fecal samples of mice showed that MLDs changed the structure and quantity of intestinal flora, and especially that the relative abundance of Bacteroidaceae was significantly increased. The relative abundance of Staphylococcaceae was significantly reduced. These results showed that MLDs improved the diversity of intestinal flora in mice, and improved the adverse state of immune organs and immune cells. The experiments confirm that black garlic melanoidins have potential value in immune activity, which provides an important basis for the development and utilization of melioidosis.

Quality characteristics and gastrointestinal fate of low fat emulsified sausage formulated with konjac glucomannan/oat ß-glucan composite hydrogel.

The objective of present study was to evaluate the utilization of konjac glucomannan/oat ß-glucan composite hydrogel as partial or complete fat replacer on the quality characteristics and gastrointestinal fate of emulsified sausages. The obtained results indicated that in comparison to control emulsified sausage sample, the incorporation of composite hydrogel at a 75 % fat replacement level could not only enhance emulsion stability, water holding capacity (WHC), and compact structure of formulated emulsified sausage, but also decrease their total fat content, cooking loss, hardness, and chewiness. The in vitro digestion results suggested the addition of konjac glucomannan/oat ß-glucan composite hydrogel reduced the protein digestibility of emulsified sausage, while it did not change the molecular weight of digestive products. The confocal laser scanning microscopy(CLSM) image showed the addition of composite hydrogel changed the size of fat and protein aggregate of emulsified sausage during digestion. Based on these findings, the fabrication of composite hydrogel containing konjac glucomannan and oat ß-glucan was a promising strategy as fat replacer. Furthermore, this study provided a theoretic basis for designing composite hydrogel based fat replacers.

The Efficacy and Safety of Celecoxib for Pain Management After Total Knee Arthroplasty: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: This study aimed to determine the efficacy and safety of celecoxib for pain management after total knee arthroplasty (TKA). METHODS: PubMed, EMBASE, Web of Science, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched to identify eligible randomized controlled trials (RCTs) that compared celecoxib with a placebo in term of pain control efficacy after TKA. Primary outcomes included pain scores at 24, 48, and 72 h after TKA. Secondary outcomes included the active range of motion (ROM) at 24, 48,72 h, and 7 days postoperatively, morphine consumption over 72 h after TKA, incidence of postoperative nausea and vomiting (PONV), and total blood loss after surgery. Data analysis was conducted using RevMan version 5.3. RESULTS: Five RCTs involving 593 participants were included in the study. Compared with a placebo, celecoxib significantly reduced visual analog scale (VAS) scores at rest at 24 h [mean difference (MD) = -0.72; 95% confidence interval (CI), -1.27 to -0.17; I 2 = 82%; P = 0.01], 48 h (MD = -1.51; 95% CI, -2.07 to -0.95; I 2 = 0%; P < 0.00001), and 72 h (MD = -1.30; 95% CI, -2.07 to -0.54; I 2 = 82%; P = 0.0009) after TKA, decreased morphine consumption over postoperative 72 h (MD = -0.73; 95% CI, -0.96 to -0.51; I 2 = 96%; P < 0.00001), and increased active ROM at 48 h (MD = 13.23; 95% CI, 7.79 to 18.67; I 2 = 0%; P < 0.00001), 72 h (MD = 6.52; 95% CI, 4.95 to 8.10; I 2 = 68%; P < 0.00001), and 7 days (MD = 7.98; 95% CI, 3.64 to 12.31; I 2 = 68%; P = 0.0003) after the operation. No significant difference was found in the active ROM at 24 h (MD = 7.60; 95% CI, -6.14 to 21.34; I 2 = 94%; P = 0.28) and the incidence of PONV after surgery [risk ratio (RR) = 0.66; 95% CI, 0.40 to 1.09; I 2 = 0%; P = 0.11]. CONCLUSION: The administration of celecoxib is an effective and safe strategy for postoperative analgesia after TKA.

Effect of water sorption on glass transition and microstructural variation of dextran & sugar mixtures.

Dextran is widely used as a model polysaccharide to study the interactions between polysaccharides and small molecule sugars. This study examined water sorption isotherms and glass transition temperatures (Tg) of mixtures of dextran with trehalose, lactose and sucrose for understanding how different disaccharides affect dextran's processing adaptation and storage performance relevant to water sorption. At the same chemical composition, monolayer water (m0) was dextran & sucrose (dex&suc) > dextran & trehalose (dex&tre) > dextran & lactose (dex&lac). The higher ratios of dextran, the higher was the Guggenheim constant (C) value of the mixtures. The compatibility of dextran and disaccharides was dex&tre > dex&lac > dex&suc. Gordon-Taylor model showed dex&tre (2:1) best inhibited water plasticization. Furthermore, trehalose and lactose were more effective in preventing morphological changes of hydrous matrices in the mixtures. The crystallinities of samples at 43% relative humidity (RH) were slightly lower than that at 11% RH.

Fabrication optimization and application of 3D hybrid SERS substrates.

Three-dimensional (3D) plasmonic nanostructures with nanoparticles that can be tuned have got a lot of attention in surface-enhanced Raman scattering (SERS) due to the unique 3D plasmonic coupling. Here, two nanoparticles, gold nanosphere (AuNS) and gold nanooctahedra (AuNO), were used to construct 3D hybrid SERS substrates to investigate the effect of nanoparticle spatial position on the SERS performance of the 3D nanostructure and to obtain 3D substrates with high SERS activity. And more hybrid combination possibilities were tested to explore the variation trend of hot spots generated when the nanoparticles were near. First, two-dimensional (2D) planar substrates were prepared using the air-liquid interface-assisted self-assembly method, to examine the effect of nanoparticle size on SERS performance. Then, 3D hybrid SERS substrates were further prepared layer by layer to discuss the effect of different combination methods within three layers on SERS performance. The optimized 3D hybrid substrate with the sandwich structure of AuNS/AuNO/AuNS performed the strongest SERS enhancement effect, whose intensity was 4.1 and 1.9 times that of AuNS/AuNS/AuNS and AuNO/AuNO/AuNO, respectively, and had good reproducibility (relative standard deviation (RSD) of 1.08%). Furthermore, the thiram molecular result showed that the prepared AuNS/AuNO/AuNS had good linear relationship (R 2 of 0.991) and good molecule detection sensitivity (the minimum detection volume of thiram is 100 ppb), which demonstrated the great potential of the 3D hybrid SERS substrates in practical analysis.

SoilGrids250m: Global gridded soil information based on machine learning.

This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methods-random forest and gradient boosting and/or multinomial logistic regression-as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10-fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resolution) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License.

Quantifying spatial variability of selected soil trace elements and their scaling relationships using multifractal techniques.

Multifractal techniques were utilized to quantify the spatial variability of selected soil trace elements and their scaling relationships in a 10.24-ha agricultural field in northeast China. 1024 soil samples were collected from the field and available Fe, Mn, Cu and Zn were measured in each sample. Descriptive results showed that Mn deficiencies were widespread throughout the field while Fe and Zn deficiencies tended to occur in patches. By estimating single multifractal spectra, we found that available Fe, Cu and Zn in the study soils exhibited high spatial variability and the existence of anomalies ([α(q)max-α(q)min]≥0.54), whereas available Mn had a relatively uniform distribution ([α(q)max-α(q)min]≈0.10). The joint multifractal spectra revealed that the strong positive relationships (r≥0.86, P<0.001) among available Fe, Cu and Zn were all valid across a wider range of scales and over the full range of data values, whereas available Mn was weakly related to available Fe and Zn (r≥0.18, P<0.01) but not related to available Cu (r = -0.03, P = 0.40). These results show that the variability and singularities of selected soil trace elements as well as their scaling relationships can be characterized by single and joint multifractal parameters. The findings presented in this study could be extended to predict selected soil trace elements at larger regional scales with the aid of geographic information systems.