Impact of dietary manganese on intestinal barrier and inflammatory response in broilers challenged with Salmonella Typhimurium

Growing concern for public health and food safety has prompted a special interest in developing nutritional strategies for removing waterborne and foodborne pathogens, including Salmonella. Strong links between manganese (Mn) and intestinal barrier or immune function hint that dietary Mn supplementation is likely to be a promising approach to limit the loads of pathogens in broilers. Here, we provide evidence that Salmonella Typhimurium (S. Typhimurium, 4 × 108 CFUs) challenge-induced intestinal injury along with systemic Mn redistribution in broilers. Further examining of the effect of dietary Mn treatments (a basal diet plus additional 0, 40, or 100 mg Mn/kg for corresponding to Mn-deficient, control, or Mn-surfeit diet, respectively) on intestinal barrier and inflammation status of broilers infected with S. Typhimurium revealed that birds fed the control and Mn-surfeit diets exhibited improved intestinal tight junctions and microbiota composition. Even without Salmonella infection, dietary Mn deficiency alone increased intestinal permeability by impairing intestinal tight junctions. In addition, when fed the control and Mn-surfeit diets, birds showed decreased Salmonella burdens in cecal content and spleen, with a concomitant increase in inflammatory cytokine levels in spleen. Furthermore, the dietary Mn-supplementation-mediated induction of cytokine production was probably associated with the nuclear factor kappa-B (NF-κB)/hydrogen peroxide (H2O2) pathway, as judged by the enhanced manganese superoxide dismutase activity and the increased H2O2 level in mitochondria, together with the increased mRNA level of NF-κB in spleen. Ingenuity-pathway analysis indicated that acute-phase response pathways, T helper type 1 pathway, and dendritic cell maturation were significantly activated by the dietary Mn supplementation. Our data suggest that dietary Mn supplementation could enhance intestinal barrier and splenic inflammatory response to fight against Salmonella infection in broilers

The FilZ protein contains a single PilZ domain and facilitates the swarming motility of pseudoalteromonas sp. SM9913

Swarming regulation is complicated in flagellated bacteria, especially those possessing dual flagellar systems. It remains unclear whether and how the movement of the constitutive polar flagellum is regulated during swarming motility of these bacteria. Here, we report the downregulation of polar flagellar motility by the c-di-GMP effector FilZ in the marine sedimentary bacterium Pseudoalteromonas sp. SM9913. Strain SM9913 possesses two flagellar systems, and filZ is located in the lateral flagellar gene cluster. The function of FilZ is negatively controlled by intracellular c-di-GMP. Swarming in strain SM9913 consists of three periods. Deletion and overexpression of filZ revealed that, during the period when strain SM9913 expands quickly, FilZ facilitates swarming. In vitro pull-down and bacterial two-hybrid assays suggested that, in the absence of c-di-GMP, FilZ interacts with the CheW homolog A2230, which may be involved in the chemotactic signal transduction pathway to the polar flagellar motor protein FliMp, to interfere with polar flagellar motility. When bound to c-di-GMP, FilZ loses its ability to interact with A2230. Bioinformatic investigation indicated that filZ-like genes are present in many bacteria with dual flagellar systems. Our findings demonstrate a novel mode of regulation of bacterial swarming motility

Significance and challenges of stereoselectivity assessing methods in drug metabolism

Stereoselectivity in drug metabolism can not only influence the pharmacological activities, tolerability, safety, and bioavailability of drugs directly, but also cause different kinds of drug–drug interactions. Thus, assessing stereoselectivity in drug metabolism is of great significance for pharmaceutical research and development (R&D) and rational use in clinic. Although there are various methods available for assessing stereoselectivity in drug metabolism, many of them have shortcomings. The indirect method of chromatographic methods can only be applicable to specific samples with functional groups to be derivatized or form complex with a chiral selector, while the direct method achieved by chiral stationary phases (CSPs) is expensive. As a detector of chromatographic methods, mass spectrometry (MS) is highly sensitive and specific, whereas the matrix interference is still a challenge to overcome. In addition, the use of nuclear magnetic resonance (NMR) and immunoassay in chiral analysis are worth noting. This review presents several typical examples of drug stereoselective metabolism and provides a literature-based evaluation on current chiral analytical techniques to show the significance and challenges of stereoselectivity assessing methods in drug metabolism

Effects of essential oils on performance, egg quality, nutrient digestibility and yolk fatty acid profile in laying hens

The study was conducted to investigate the effect of essential oils on performance, egg quality, nutrient digestibility and yolk fatty acid profile in laying hens. A total of 960 Lohmann laying hens aged 53 weeks were enrolled, under 4 different treatment diets supplemented with 0, 50, 100 and 150 mg/kg essential oils (Enviva EO, Dupont Nutrition Biosciences ApS, Denmark), respectively. Each treatment was replicated 8 times with 30 birds each. Birds were fed dietary treatment diets for 12 weeks (54 to 65 weeks). For data recording and analysis, a 12-week period was divided into 3 periods of 4 weeks' duration each: period 1 (54 to 57 weeks), period 2 (58 to 61 weeks), and period 3 (62 to 65 weeks). For the diet supplemented with Enviva EO, hen-day egg production and the feed conversion ratio (FCR) were significantly improved (P < 0.05) at weeks 58 to 61, and the eggshell thickness was significantly increased (P < 0.05) at week 65. However, egg production, egg weight, feed intake, FCR and other egg quality parameters (albumen height, Haugh unit, egg yolk color and eggshell strength) were not affected by the dietary treatment. In addition, compared with the control diet, protein digestibility in the 100 mg/kg Enviva EO treatment group was significantly increased (P < 0.05), and fat digestibility in the 100 and 150 mg/kg Enviva EO treatment groups was significantly decreased (P < 0.05), but Enviva EO had no effect on energy apparent digestibility. Saturated fatty acid (SFA) and monounsaturated fatty acid (MUFA) gradually decreased and polyunsaturated fatty acid (PUFA) increased with Enviva EO supplementation, but the difference was not significant. The data suggested that the supplementation of essential oils (Enviva EO) in laying hen diet did not show a significant positive effect on performance and yolk fatty acid composition but it tended to increase eggshell thickness and protein digestibility, especially at the dose of 50 mg/kg

Sugarcane Biomass Prediction with Multi-Mode Remote Sensing Data Using Deep Archetypal Analysis and Integrated Learning

The use of multi-mode remote sensing data for biomass prediction is of potential value to aid planting management and yield maximization. In this study, an advanced biomass estimation approach for sugarcane fields is proposed based on multi-source remote sensing data. Since feature interpretability in agricultural data mining is significant, a feature extraction method of deep archetypal analysis (DAA) that has good model interpretability is introduced and aided by principal component analysis (PCA) for feature mining from the multi-mode multispectral and light detection and ranging (LiDAR) remote sensing data pertaining to sugarcane. In addition, an integrated regression model integrating random forest regression, support vector regression, K-nearest neighbor regression and deep network regression is developed after feature extraction by DAA to precisely predict biomass of sugarcane. In this study, the biomass prediction performance achieved using the proposed integrated learning approach is found to be predominantly better than that achieved by using conventional linear methods in all the time periods of plant growth. Of more significance, according to model interpretability of DAA, only a small set of informative features maintaining their physical meanings (four informative spectral indices and four key LiDAR metrics) can be extracted which eliminates the redundancy of multi-mode data and plays a vital role in accurate biomass prediction. Therefore, the findings in this study provide hands-on experience to planters with indications of the key or informative spectral or LiDAR metrics relevant to the biomass to adjust the corresponding planting management design

SB216763, a selective small molecule inhibitor of glycogen synthase kinase-3, improves bleomycin-induced pulmonary fibrosis via activating autophagy

An excessive accumulation of extracellular matrix composed by insoluble collagen is the core pathogenic change of fibroproliferative diseases including pulmonary fibrosis. We recently found that autophagy, a self-catabolic process that maintains intracellular homeostasis, participates critically in the regulation of collagen degradation in the fibrotic tissues. Here we report that treatment of mice with SB216763, a potent and selective inhibitor of glycogen synthase kinase-3 (GSK3), significantly decreased the bleomycin (BLM)-induced acute inflammation, attenuated pulmonary fibrosis, improved the lung function and increased animal survival through activating autophagy. Indeed, we found that treatment of mice or cultured cells with SB216763 restored the autophagy in vivo and in vitro through increasing the expression of autophagy related proteins and decreasing the physical interaction of Bcl-2 and Beclin-1. Additionally, SB216763 stimulated the binding of Bcl-2 and GSK3, which reduces the interaction of Bcl-2 and Beclin-1. We conclude that the GSK3 inhibitor SB216763 improves the BLM-induced pulmonary fibrosis through stimulating autophagy core complex to restore the activity of autophagy in fibrotic lung tissue. Our work suggests that using a moderate autophagic agonist, such as SB216763, is a promising therapeutic strategy for the treatment of devastating fibroproliferative diseases such as idiopathic pulmonary fibrosis

Growth and Characterization of Ce-Doped Luag Single Crystal Fibers from Transparent Ceramics by Laser-Heated Pedestal Method

Scintillation single crystal fibers (SCFs) have great potential applications in the new generation of high-energy ray and particle detectors due to their morphological advantages. In this work; Ce:LuAG SCFs with a diameter of 1 mm were grown along the direction of [111] by laser-heated pedestal growth (LHPG) method using a transparent ceramic as the source rod; and a doping concentration was 0.1 at%, 0.3 at%, 1 at%, respectively. The effects of growth rate and annealing in air on the scintillation and optical properties of SCF are discussed in detail. The results of analyzing the absorption spectra; radioluminescence (RL) spectra; pulse-height spectra and fluorescence lifetime of SCFs show that the SCF maintains excellent scintillation performance while having a fiber structure. Therefore; Ce:LuAG SCF is a potential candidate material for detector

Modeling and Validation of a Diesel Engine with Turbocharger for Hardware-in-the-Loop Applications

This paper presents a simulator model of a diesel engine with a turbocharger for hardware-in-the-loop (HIL) applications, which is used to obtain engine performance data to study the engine performance under faulty conditions, to assist engineers in diagnosis and estimation, and to assist engineers in model-based calibration (MBC). The whole diesel engine system is divided into several functional blocks: air block, injection block, cylinder block, crankshaft block, cooling block, lubrication block, and accessory block. The diesel engine model is based on physical level, semi-physical level and mathematical level concepts, and developed by Matlab/Simulink. All the model parameters are estimated using weighted least-squares optimization and the tuning process details are presented. Since the sub-model coupling may cause errors, the validation process is then given to make the model more accurate. The results show that the tuning process is important for the functional blocks and the validation process is useful for the accuracy of the whole engine model. Subsequently, this program could be used as a plant model for MBC, to develop and test engine control units (ECUs) on HIL equipment for the purpose of improving ECU performance

Calcium supplementation in low nutrient density diet for meat ducks improves breast meat tenderness associated with myocyte apoptosis and proteolytic changes

To define the relationship between dietary nutrient density, calcium (Ca), and meat quality in meat ducks. A total of 288 male Cherry Valley SM3 medium ducklings were fed a common standard starter diet until d 14. At 15 d of age, ducks were randomly divided into 2 treatment groups and fed either a conventional diet or a low nutrient density (LND) diet. Compared with the conventional diet, the energy was reduced in the LND diet by 8.6% and 16.8% in grower (15 to 35 d) and finisher (36 to 56 d) phases, respectively, while other essential nutrients were kept proportionate to energy. The LND diet decreased the shear force (P < 0.05) and increased the lightness values of the pectoralis muscle when compared to the conventional diet, suggesting that LND diet exerted a beneficial role in meat quality. Subsequently, the effects of grated Ca in the LND diet on meat quality of pectoralis muscle were evaluated. A total of 576 male ducklings were fed a common starter diet until d 14, followed by feeding 4 LND diets with 0.5%, 0.7%, 0.9%, and 1.1% Ca. The results show that LND diets with 0.7% or more Ca decreased the shear force of pectoralis major muscle in 42-d-old meat ducks (P < 0.05). To explore the mechanism underlying Ca and tenderness, data from birds fed either 0.5% or 1.1% Ca in the LND diet indicated that birds fed 1.1% Ca exhibited lower shear force, upregulated calpains 1 expression, and higher calpains activity compared to those fed the LND diet with 0.5% Ca (P < 0.05). Moreover, the 1.1% Ca LND diet induced a higher myocyte apoptosis (P = 0.06) and upregulated mRNA expression of caspase-3 (P = 0.07) in breast muscle. Our data suggest that LND diets with 0.9% or 1.1% Ca had a positive role in the tenderness of breast meat, particularly the enhancing effect of 1.1% Ca LND diet on tenderness seems to be associated with proteolytic changes of myofibrillar proteins and myocyte apoptosis in meat ducks. (c) 2022 Chinese Association of Animal Science and Veterinary Medicine. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

MHPCG:Multi-modal Hyperspectral Point Cloud Generation Based on Single RGB Image

Multimodal hyperspectral point cloud which has both spectral features and three-dimensional spatial features, has presented great potential in various remote sensing applications. However, direct acquisition of this multimodal data is expensive and difficult as for the rareness of this type of imaging equipment. Moreover, acquisition through heterogeneous fusion of independently collected hyperspectral image and point cloud data brings great challenges. In this study, a multimodal hyperspectral point cloud data generation method is proposed using data-driven learning based deep learning approach with only a single RGB image. The whole network unifies spectral super-resolution reconstruction, monocular 3D reconstruction and data fusion to generate hyperspectral point cloud. The quality of the generated data is testified through experiments on practical plants. Both single modality and multi-modality data quality are evaluated by estimation of the growth status of plants. In this paper, hyperspectral point cloud obtained though low-cost RGB imaging not only avoids the independent acquisition of single modality data using expensive professional equipment, and also gets rid of challenging fusion of the multi-source heterogeneous data. Of more importance, it renders simultaneous acquisition of multidimensional data of high resolution with respect to both spectral and spatial information of the target. The synchronous acquisition of rich spectral and physical geometry information throws light on the comprehensive understanding of the physical and biochemical information of the target object