Effect of pH, protein/polysaccharide ratio and preparation method on the stability of lactoferrin-polysaccharide complexes.

In this study, carrageenan (CG), xanthan gum (XG) and locust bean gum (LBG), which can be used in infant formulas in China national standards, were selected to prepare LF-polysaccharide complexes to improve the stability of lactoferrin. The results showed that LF interacted more strongly with polysaccharides and did not affect the LF structure to a large extent when the pH and protein/polysaccharide mass ratio were 7 and 10:1 for LF-CG, 8 and 5:1 for LF-XG, 7 and 15:1 for LF-LBG. The zeta potential and fluorescence intensity of the LF-polysaccharide complexes displayed a decreasing trend with the increase in pH. When pH < 6, LF-CG and LF-XG exhibited precipitation and increased UV absorbance. Complexation between LF and CG/XG mainly attributed to electrostatic interactions, while LF and LBG form complexes based on hydrogen bonding or hydrophobic interactions. This study could provide a reference for the practical application of LF in infant formula.

Deep Probabilistic Principal Component Analysis for Process Monitoring.

Probabilistic latent variable models (PLVMs), such as probabilistic principal component analysis (PPCA), are widely employed in process monitoring and fault detection of industrial processes. This article proposes a novel deep PPCA (DePPCA) model, which has the advantages of both probabilistic modeling and deep learning. The construction of DePPCA includes a greedy layer-wise pretraining phase and a unified end-to-end fine-tuning phase. The former establishes a hierarchical deep structure based on cascading multiple layers of the PPCA module to extract high-level features. The latter builds an end-to-end connection between the raw inputs and the final outputs to further improve the representation of the model to high-level features. After constructing the model structure of DePPCA, we first present the detailed training processes of the pretraining and fine-tuning stages, then clarify the theoretical merits of the proposed model from the perspective of variational inference. For process monitoring purposes, we develop two statistics based on the established DePPCA. The monitoring performance of these two statistics can remain superior even if the features extracted by DePPCA are significantly compressed to univariate. This makes the feature extraction process and online monitoring procedure of DePPCA quite fast. In other words, the proposed DePPCA can achieve accurate and efficient process monitoring by only extracting one feature for each sample. Finally, the effectiveness of DePPCA is evaluated on the Tennessee Eastman (TE) process and the multiphase flow (MPF) facility.

Biocontrol potential of endophytic Pseudomonas strain IALR1619 against two Pythium species in cucumber and hydroponic lettuce.

The use of fungicides to manage disease has led to multiple environmental externalities, including resistance development, pollution, and non-target mortality. Growers have limited options as legacy chemistry is withdrawn from the market. Moreover, fungicides are generally labeled for traditional soil-based production, and not for liquid culture systems. Biocontrol agents for disease management are a more sustainable and environmentally friendly alternative to conventional agroprotectants. Pythium ultimum is a soil borne oomycete plant pathogen with a broad taxonomic host range exceeding 300 plants. Cucumber seedlings exposed to P. ultimum 1 day after a protective inoculation with bacterial endophyte accession IALR1619 (Pseudomonas sp.) recorded 59% survival; with the control assessed at 18%. When the pathogen was added 5 days post endophyte inoculation, 74% of the seedlings treated survived, compared to 36% of the control, indicating a longer-term effect of IALR1619. Under hydroponic conditions, IALR1619 treated leaf type lettuce cv. 'Cristabel' and Romaine cv. 'Red Rosie' showed 29% and 42% higher shoot fresh weight compared to their controls, respectively. Similar results with less growth decline were observed for a repeat experiment with IALR1619. Additionally, an experiment on hydroponic lettuce in pots with perlite was carried out with a mixture of P. ultimum and P. dissotocum after IALR1619 inoculation. The endophyte treated 'Cristabel' showed fresh weight gain, but the second cultivar 'Pensacola' yielded no increase. In summary, the endophyte IALR1619 provided short term as well as medium-term protection against Pythium blight in cucumber seedlings and may be used as an alternative to conventional fungicides in a greenhouse setting. This study also demonstrated the potential of ALR1619 as a biocontrol agent against Pythium blight in hydroponic lettuce.

The impact of network externalities and altruistic preferences on carbon emission reduction of low carbon supply chain.

This paper explores the manufacturer's carbon emission reduction in the presence of network externalities and altruistic preferences. Existing literature mainly analyzes the impact of government regulations and firms' behavior characteristics on manufacturers' decisions, while little literature investigates the role of network externalities and altruistic preferences in promoting carbon emission reduction of manufacturers. Our results show that network externalities and altruistic preferences are conducive to improving manufacturers' profits and carbon emission reduction levels. However, we find that manufacturers' carbon emission reductions are more likely to be optimal without network externalities and altruistic preferences when the cost of low-carbon technologies is low, and consumer preferences are high. Interestingly, when the low-carbon technologies cost is high, the combined effect of network externalities and altruistic preferences is more favorable for manufacturers to implement carbon emission reductions. However, when the cost of low-carbon technologies is moderate, we find that the combined effect of network externalities and retailers' altruistic preferences does not always increase the level of carbon emission reductions. In addition, we also find that network externalities or altruistic preferences enhance manufacturers' ability to afford the costs of low-carbon technologies, which implies that manufacturers are more inclined to reduce carbon emissions compared to scenarios without network externalities and altruistic preferences.

Characterization of Phosphate Solubilizing Bacterial Endophytes and Plant Growth Promotion In Vitro and in Greenhouse.

Phosphate is one of the most important nutrients for plant growth and development, and only 0.1% of the phosphate in soils is available to plants. Currently, the use of excess phosphate fertilizer has caused surface and ground water pollution and water eutrophication, resulting in algal blooms in lakes and oceans. Therefore, it is imperative to explore alternative ways to solve these problems for sustainable agricultural production and improvement of soil fertility, while protecting the environment. Microorganisms from the rhizosphere and within plants are able to solubilize insoluble soil phosphate, making it available to plants. Five high phosphate solubilizing bacteria from our bacterial endophyte library were chosen for this study and identified as Pantoea vagans IALR611, Pseudomonas psychrotolerans IALR632, Bacillus subtilis IALR1033, Bacillus safensis IALR1035 and Pantoea agglomerans IALR1325. All five bacteria significantly promoted tall fescue growth in vitro. Greenhouse experiments showed that IALR1325 significantly promoted pepper and tomato growth, and IALR632 was the best in promoting tomato growth. In addition, all these bacteria had extracellular acid phosphatase and phytase activities. One of the mechanisms for phosphate solubilization by bacteria is pH reduction caused by gluconic acid production. Our results indicate that P. agglomerans IALR1325 is a promising bacterium for future applications.

The role of volumetric ADC histogram analysis in preoperatively evaluating the tumour subtype and grade of endometrial cancer.

PURPOSE: To assess the value of volumetric ADC histogram metrics in evaluating the histological subtype and grade of endometrial cancer. METHOD: Preoperative MRI datasets of 317 patients with endometrial cancer were used to obtain volumetric ADC histogram metrics (tumour volume; minADC, maxADC and meanADC; 10th, 25th, 50th, 75th and 90th percentiles of ADC; skewness; and kurtosis). The Mann-Whitney test or Student's t-test was used to compare the difference in ADC histogram metrics between endometrioid adenocarcinomas (EACs) and serous endometrial cancers (SECs) and between different tumour grades (G1, G2, G3). The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate the performance of ADC histogram metrics or combined models in predicting the tumour subtype and grade. RESULTS: SECs showed a significantly larger tumour volume (P < 0.001) and lower meanADC, 50th, 75th and 90th percentiles of ADC than EACs (all P < 0.05). MinADC, maxADC, meanADC, 10th, 25th, 50th, 75th, 90th percentiles of ADC were significantly higher in G1 than in G2 and G3 EACs (all P < 0.05), while were not significantly different between G2 and G3 EACs (all P > 0.05). A tumour volume ≥ 7.752 cm3 allowed for the prediction of SECs, with an AUC of 0.765 (0.714-0.810). A meanADC ≥ 0.892 × 10-3  mm2/s enabled to discriminate G1 from G2 and G3 EACs, with an AUC of 0.818 (0.769-0.861). CONCLUSION: Volumetric ADC histogram analysis is helpful for non-invasive preoperatively predicting the subtype of endometrial cancer and differentiating G1 from G2 and G3 EACs.

An inverse approach to determine solute and solvent permeability parameters in artificial tissues.

This study presents a generic numerical model to simulate the coupled solute and solvent transport in tissue sections during addition and removal of chemical additives or cryoprotective agents (CPA; dimethylsulfoxide or DMSO). Osmotic responses of various tissue cells within the artificial tissue are predicted by the numerical model with three model parameters: Permeability of the tissue cell membrane to water (Lp), permeability of the tissue cell membrane to the solute or CPA (omega), and the diffusion coefficient of the solute or CPA in the extracellular space (D). By fitting the model results with published experimental data on solute/water concentrations at various locations within an artificial tissue, we were able to determine the permeability parameters of artificial tissue cells in the presence of 1.538 M DMSO. Lp and omega were determined at three different locations within the artificial tissue assuming a constant value of solute diffusivity (D = 1.0 x 10(-9) m2/s). The best fit values of Lp ranged from 0.59 x 10(-14) to 4.22 x 10(-14) m3/N-s while omega ranged from 0 to 6.6 x 10(-13) mol/N-s. Based on these values of Lp and omega, the solute reflection coefficient, sigma = 1 - omegav(-)CPA/Lp, ranged from 0.9923 to 1.0. The relative values of omega and sigma suggest that the artificial tissue cells are relatively impermeable to DMSO (or omega approximately 0 and sigma approximately 1.0). This observation was used to modify our model to predict the values of Lp and D assuming omega = 0 and sigma = 1.0. The best fit values of Lp ranged from 640 x 10(-14) to 2.1 x 10(-14) m3/N-s while D ranged from 0.63 x 10(-9) to 1.52 x 10(-9) m2/s. The permeability parameters obtained in the present study represent the first such effort for artificial tissues.

Variation in the membrane transport properties and predicted optimal rates of freezing for spermatozoa of diploid and tetraploid Pacific oyster, Crassostrea gigas.

In the present study, a shape-independent differential scanning calorimeter (DSC) technique was used to measure the dehydration response during freezing of sperm cells from diploid and tetraploid Pacific oysters, Crassostrea gigas. This represents the first application of the DSC technique to sperm cells from nonmammalian species. Volumetric shrinkage during freezing of oyster sperm cell suspensions was obtained at cooling rates of 5 and 20 degrees C/min in the presence of extracellular ice and 8% (v/v) concentration of dimethyl sulfoxide (DMSO), a commonly used cryoprotective agent (CPA). Using previously published data, sperm cells from diploid oysters were modeled as a two-compartment "ball-on-stick" model with a "ball" 1.66 microm in diameter and a "stick" 41 microm in length and 0.14 microm wide. Similarly, sperm cells of tetraploid oysters were modeled with a "ball" 2.14 microm in diameter and a "stick" 53 microm in length and 0.17 microm wide. Sperm cells of both ploidy levels were assumed to have an osmotically inactive cell volume, Vb, of 0.6 Vo, where Vo is the isotonic (or initial) cell volume. By fitting a model of water transport to the experimentally obtained volumetric shrinkage data, the best-fit membrane permeability parameters (Lpg and ELp) were determined. The combined-best-fit membrane permeability parameters at 5 and 20 degrees C/min for haploid sperm cells (or cells from diploid Pacific oysters) in the absence of CPAs were: Lpg = 0.30 x 10(-15) m(3)/Ns (0.0017 microm/min-atm) and ELp = 41.0 kJ/mole (9.8 kcal/mole). The corresponding parameters in the presence of 8% DMSO were: Lpg[cpa] = 0.27 x 10(-15) m(3)/Ns (0.0015 microm/min-atm) and ELp[cpa] = 38.0 kJ/mole (9.1 kcal/mole). Similarly, the combined-best-fit membrane permeability parameters at 5 and 20 degrees C/min for diploid sperm cells (or cells from tetraploid Pacific oysters) in the absence of CPAs were: Lpg = 0.34 x 10(-15) m(3)/Ns (0.0019 microm/min-atm) and ELp = 29.7 kJ/mole (7.1 kcal/mole). The corresponding parameters in the presence of 8% DMSO were: Lpg[cpa] = 0.34 x 10(-15) m(3)/Ns (0.0019 microm/min-atm) and ELp[cpa] = 37.6 kJ/mole (9.0 kcal/mole). The parameters obtained in this study suggest that optimal rates of cooling for Pacific oyster sperm cells range from 40 to 70 degrees C/min. These theoretical cooling rates are in close conformity with empirically determined optimal rates of cooling sperm cells from Pacific oysters, C. gigas.