In the present study, an effort has been made to understand the interaction mode of propolis, a natural substance produced by honey bees, with gram-positive and gram-negative bacterial cells by measuring alterations in cell surface physico-chemical properties following the incubation of the cells with different sub-inhibitory concentrations of this antimicrobial agent. Electrophoretic mobility and surface hydrophobicity measurements revealed for the first time that propolis induced substantial changes in the volumetric charge density, electrophoretic softness and degree of hydrophobicity characterizing the outermost surface layer of cells. These changes, which appear to be dose-dependent, seem to be consistent with the increasing accumulation and penetration of the propolis antimicrobial components through the cells extracellular layer. Moreover, electron microscopy observation and the determination of the cell constituents' release demonstrated that propolis at sub-bactericidal concentrations already provoked (at least localized) cell wall damage and/or perturbations. These findings thus suggest that the initial mechanism of action of propolis is most likely structural, resulting from sufficient interaction between the different propolis components and bacterial cell wall structures.
  Research on prenatal cannabis use and adverse infant outcomes is inconsistent, and findings vary by frequency of use or cigarette use. We assess (1) the prevalence of high frequency (≥once/week), low frequency (<once/week), and any cannabis use during pregnancy by maternal characteristics and adverse infant outcomes; (2) the prevalence of infant outcomes by cannabis use frequency, stratified by cigarette smoking; and (3) the association between cannabis use frequency and infant outcomes, stratified by cigarette smoking.
 
  Cross-sectional data from 8 states' 2017 Pregnancy Risk Assessment Monitoring System (n = 5548) were analyzed. We calculated adjusted prevalence ratios (aPR) between cannabis use frequency and infant outcomes with Modified Poisson regression.
 
  Approximately 1.7 % and 2.6 % of women reported low and high frequency prenatal cannabis use, respectively. Prevalence of use was higher among women with small-for-gestational age (SGA) (10.2 %) and low birthweight (9.7 %) deliveries, and cigaret counseling and cessation services to help pregnant women avoid tobacco and cannabis use.Lupine (Lupinus sp.) is a valuable source of plant proteins. There is little knowledge on the impact of food processing on composition and sensory properties of lupine products. In this research, we investigated the impact of fermentation with five starters of lactic acid bacteria on the sensory quality and flavor-active compounds in dairy analogues prepared from sweet lupine (Lupinus angustifolius L.). The sensory qualities of unfermented and fermented products were studied with generic descriptive analysis and affective tests. Acids and sugars were analyzed with GC-FID and volatiles with HS-SPME-GC-MS and GC-O. Fermentation increased sourness and 'vinegar' odor and reduced the 'beany' odor and flavor as well as the unpleasantness of flavor. Formation of volatiles during the fermentation was dependent on the starters. However, all fermentations increased the contents of lactic, acetic, and hexanoic acids, while reducing the contents of hexanal, described as 'grassy' in the unfermented lupine sample.Highland barley (HB) was subjected to three thermal treatments (heat fluidization, microwave, and baking) and assessed for physicochemical, ultrastructural and nutritional properties. After thermal treatments, the hardness, bulk density, thousand kernel weight, length/breadth ratio, and color difference decreased significantly, while puffing index increased. Meanwhile, the formation of fissure was observed in the appearance. Microstructure images illustrated that numerous micropores were evenly distributed in the endosperm structure, and aleurone layer cells were deformed by compression. Furthermore, a dramatically disruption of endosperm cell walls and slightly deformation of outer layers were observed by confocal laser scanning microscopy. Moreover, a notably decrease in total phenolics (14.02%-36.91%), total flavonoids (25.28%-44.94%), and bound phenolics (8.99%-27.53%) was detected, while free phenolics (8.81%-43.40%), β-glucan extractability (4.71%-43.66%), antioxidant activity (71.87%-349.77%), and reducing power (3.05%-56.13%) increased significantly. Greatest increase in nutritional values was caused by heat fluidization, which possessed the potential for development of ready-to-eat functional foods.This study was aimed to investigate the effect of incubation temperature on the binding of hexanal, octanal and 3-methylbutyraldehyde to myosin. Fluorescence quenching, Fourier transform infrared spectroscopy, surface plasmon resonance (SPR), isothermal titration calorimetry (ITC) and gas chromatography-mass spectrometry (GC-MS) were employed. An increase in aldehyde concentration led to a reduction in fluorescence intensity in myosin.  https://www.selleckchem.com/products/iso-1.html  SPR revealed that the interactions were involved in a rapid combination and dissociation, and the dissociation constants significantly decreased from 25 to 37 °C. ITC showed that the values of entropy, enthalpy and Gibbs free energy were negative. The interactions were driven by hydrogen bonds and van der Waals forces. GC-MS further demonstrated that the highest binding capacity occurred at 37 °C between myosin and aldehydes. The findings provide a new insight into the mechanism on controlling or maintaining meat flavor.Data sparsity is a common issue to train machine learning tools such as neural networks for engineering and scientific applications, where experiments and simulations are expensive. Recently physics-constrained neural networks (PCNNs) were developed to reduce the required amount of training data. However, the weights of different losses from data and physical constraints are adjusted empirically in PCNNs. In this paper, a new physics-constrained neural network with the minimax architecture (PCNN-MM) is proposed so that the weights of different losses can be adjusted systematically. The training of the PCNN-MM is searching the high-order saddle points of the objective function. A novel saddle point search algorithm called Dual-Dimer method is developed. It is demonstrated that the Dual-Dimer method is computationally more efficient than the gradient descent ascent method for nonconvex-nonconcave functions and provides additional eigenvalue information to verify search results. A heat transfer example also shows that the convergence of PCNN-MMs is faster than that of traditional PCNNs.