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Microsphere with sphere-in-capsule structure is a multi-drugs delivery system to achieve the purpose of combination therapy. In this paper, we have prepared gelatin/alginate-based microspheres with sphere-in-capsule structure by a relatively fast, simple, and easily large-scale industrialized emulsification method for spatiotemporal manipulative drug release in gastrointestinal tract. Calcium alginate microspheres encapsulated with bovine serum albumin (BSA) were first prepared as inner microspheres, and then inner microspheres and ranitidine hydrochloride (RH) were co-encapsulated by gelatin microspheres to form double-layer microspheres with sphere-in-capsule structure. The size and distribution of microspheres can be easily controlled by emulsifying conditions. The microspheres with sphere-in-capsule structure displayed desirable encapsulation efficiency of BSA (61.52 %) and RH (56.07 %). The in vitro simulated drug release showed the spatiotemporal release feature of microspheres with sphere-in-capsule structure. In the specific simulated fluid, the release behavior and cumulative release of RH (sustainedly released 95 % in simulated gastric fluid) and BSA (rapidly released 73 % in simulated intestinal fluid) were different. The drug release mechanisms were analyzed to determine RH and BSA's release behavior. Overall, the microspheres with sphere-in-capsule structure have the potential application of spatiotemporal manipulative drug delivery in the gastrointestinal tract.

In orthopedics, developing functionalized biomaterials to enhance osteogenesis and bacterial resistance is crucial. Although poly(ether ether ketone) (PEEK) is regarded as an important engineering plastic for biomedical material with excellent mechanical properties and biocompatibility, its biological inertness has greatly compromised its application in biomedical engineering. Inspired by the catecholamine chemistry of mussels, we propose a universal and versatile approach for enhancing the osteogenesis and antibacterial performances of PEEK based on surface functionalization of polydopamine-modified nanohydroxyapatite and lysozyme simultaneously. The characterizations of surface morphology and elemental composition revealed that the composite coating was successfully added to the PEEK surface. Additionally, the

RNase H1s are associated with growth and development in both plants and animals, while the roles of RNase H1s in bryophytes have been rarely reported. Our previous data found that PpRNH1A, a member of the RNase H1 family, could regulate the development of Physcomitrium (Physcomitrella) patens by regulating the auxin. In this study, we further investigated the biological functions of PpRNH1A and found PpRNH1A may participate in response to heat stress by affecting the numbers and the mobilization of lipid droplets and regulating the expression of heat-related genes. The expression level of PpRNH1A was induced by heat stress (HS), and we found that the PpRNH1A overexpression plants (A-OE) were more sensitive to HS. At the same time, A-OE plants have a higher number of lipid droplets but with less mobility in cells. Consistent with the HS sensitivity phenotype in A-OE plants, transcriptomic analysis results indicated that PpRNH1A is involved in the regulation of expression of heat-related genes such as DNAJ and DNAJC. Taken together, these results provide novel insight into the functions of RNase H1s.

Selenium (Se) is a nutritionally important micronutrient for humans. The use of Se fertilizers is often the most feasible approach to precisely increase Se contents in rice grains, but the effects of common commercial Se fertilizers on producing Se-rich rice remain to be investigated. In this study, we compared the effects of liquid and granular Se fertilizers on the accumulation of Se and heavy metals in rice grains of four different varieties in field. Results showed that Se accumulation in rice grains was affected by the form of fertilizers, applied concentrations of Se fertilizers, and rice varieties. Liquid fertilizer displayed significantly higher Se transfer efficiency than granular fertilizer, whereas the granular fertilizer had a slightly higher effect on organic Se accumulation. More than 95.5% Se in grains were organic Se, with selenomethionine (SeMet) being the dominant one. The proportion of organic selenocysteine (SeCys2) in grains was significantly higher in treatments with liquid fertilizer. Both forms of fertilizers significantly reduced the accumulation of cadmium, lead, and arsenic. Collectively, our study provides a reference for producing Se-rich rice in a more competitive manner in practice.

Rice is one of the staple foods for the majority of the global population that depends directly or indirectly on it. The yield of this important crop is constantly challenged by various biotic stresses. Rice blast, caused by Magnaporthe oryzae (M. oryzae), is a devastating rice disease causing severe yield losses annually and threatening rice production globally. The development of a resistant variety is one of the most effective and economical approaches to control rice blast. Researchers in the past few decades have witnessed the characterization of several qualitative resistance (R) and quantitative resistance (qR) genes to blast disease as well as several avirulence (Avr) genes from the pathogen. These provide great help for either breeders to develop a resistant variety or pathologists to monitor the dynamics of pathogenic isolates, and ultimately to control the disease. Here, we summarize the current status of the isolation of R, qR and Avr genes in the rice–M. oryzae interaction system, and review the progresses and problems of these genes utilized in practice for reducing rice blast disease. Research perspectives towards better managing blast disease by developing a broad-spectrum and durable blast resistance variety and new fungicides are also discussed.

Rice blast, caused by the Magnaporthe oryzae fungus, is one of the most devastating rice diseases worldwide. Developing resistant varieties by pyramiding different blast resistance (R) genes is an effective approach to control the disease. However, due to complex interactions among R genes and crop genetic backgrounds, different R-gene combinations may have varying effects on resistance. Here, we report the identification of two core R-gene combinations that will benefit the improvement of Geng (Japonica) rice blast resistance. We first evaluated 68 Geng rice cultivars at seedling stage by challenging with 58 M. oryzae isolates. To evaluate panicle blast resistance, we inoculated 190 Geng rice cultivars at boosting stage with five groups of mixed conidial suspensions (MCSs), with each containing 5–6 isolates. More than 60% cultivars displayed moderate or lower levels of susceptibility to panicle blast against the five MCSs. Most cultivars contained two to six R genes detected by the functional markers corresponding to 18 known R genes. Through multinomial logistics regression analysis, we found that Pi-zt, Pita, Pi3/5/I, and Pikh loci contributed significantly to seedling blast resistance, and Pita, Pi3/5/i, Pia, and Pit contributed significantly to panicle blast resistance. For gene combinations, Pita+Pi3/5/i and Pita+Pia yielded more stable pyramiding effects on panicle blast resistance against all five MCSs and were designated as core R-gene combinations. Up to 51.6% Geng cultivars in the Jiangsu area contained Pita, but less than 30% harbored either Pia or Pi3/5/i, leading to less cultivars containing Pita+Pia (15.8%) or Pita+Pi3/5/i (5.8%). Only a few varieties simultaneously contained Pia and Pi3/5/i, implying the opportunity to use hybrid breeding procedures to efficiently generate varieties with either Pita+Pia or Pita+Pi3/5/i. This study provides valuable information for breeders to develop Geng rice cultivars with high resistance to blast, especially panicle blast.

Salinity is one of the main adverse environmental factors severely inhibiting rice growth and decreasing grain productivity. Developing rice varieties with salt tolerance (ST) is one of the most economical approaches to cope with salinity stress. In this study, the salt tolerance of 220 rice accessions from rice diversity panel l (RDP1), representing five subpopulations, were evaluated based on 16 ST indices at both seedling and reproductive stages under salt stress. An apparent inconsistency was found for ST between the two stages. Through a gene-based/tightly linked genome-wide association study with 201,332 single nucleotide polymorphisms (SNPs) located within genes and their flanking regions were used, a total of 214 SNPs related to 251 genes, significantly associated with 16 ST-related indices, were detected at both stages. Eighty-two SNPs with low frequency favorable (LFF) alleles in the population were proposed to hold high breeding potential in improving rice ST. Fifty-four rice accessions collectively containing all these LFF alleles were identified as donors of these alleles. Through the integration of meta-quantitative trait locus (QTL) for ST and the response patterns of differential expression genes to salt stress, thirty-eight candidate genes were suggested to be involved in the regulation of rice ST. In total, the present study provides valuable information for further characterizing ST-related genes and for breeding ST varieties across whole developmental stages through marker-assisted selection (MAS).

Summary Necrotrophic fungus Rhizoctonia solani Kühn (R. solani) causes serious diseases in many crops worldwide, including rice and maize sheath blight (ShB). Crop resistance to the fungus is a quantitative trait and resistance mechanism remains largely unknown, severely hindering the progress on developing resistant varieties. In this study, we found that resistant variety YSBR1 has apparently stronger ability to suppress the expansion of R. solani than susceptible Lemont in both field and growth chamber conditions. Comparison of transcriptomic profiles shows that the photosynthetic system including chlorophyll biosynthesis is highly suppressed by R. solani in Lemont but weakly in YSBR1. YSBR1 shows higher chlorophyll content than that of Lemont, and inducing chlorophyll degradation by dark treatment significantly reduces its resistance. Furthermore, three rice mutants and one maize mutant that carry impaired chlorophyll biosynthesis all display enhanced susceptibility to R. solani. Overexpression of OsNYC3, a chlorophyll degradation gene apparently induced expression by R. solani infection, significantly enhanced ShB susceptibility in a high‐yield ShB‐susceptible variety ‘9522’. However, silencing its transcription apparently improves ShB resistance without compromising agronomic traits or yield in field tests. Interestingly, altering chlorophyll content does not affect rice resistance to blight and blast diseases, caused by biotrophic and hemi‐biotrophic pathogens, respectively. Our study reveals that chlorophyll plays an important role in ShB resistance and suppressing chlorophyll degradation induced by R. solani infection apparently improves rice ShB resistance. This discovery provides a novel target for developing resistant crop to necrotrophic fungus R. solani.

Chloroplasts play essential roles in plant metabolic processes and stress responses by functioning as environmental sensors. Understanding chloroplast responses to drought stress and subsequent recovery will help the ability to improve stress tolerance in plants. Here, a combined proteomic and physiological approach was used to investigate the response mechanisms of Nicotiana benthamiana chloroplasts to drought stress and subsequent recovery. Early in the stress response, changes in stomatal movement were accompanied by immediate changes in protein synthesis to sustain the photosynthetic process. Thereafter, increasing drought stress seriously affected photosynthetic efficiency and led to altered expression of photosynthesis- and carbon-fixation-related proteins to protect the plants against photo-oxidative damage. Additional repair mechanisms were activated at the early stage of recovery to restore physiological functions and repair drought-induced damages, even while the negative effects of drought stress were still ongoing. Prolonging the re-watering period led to the gradual recovery of photosynthesis at both physiological and protein levels, indicating that a long repair process is required to restore plant function. Our findings provide a precise view of drought and recovery response mechanisms in N. benthamiana and serve as a reference for further investigation into the physiological and molecular mechanisms underlying plant drought tolerance.

Background Salinity is one of the main adverse environmental factors severely inhibiting rice growth and decreasing grain productivity. Developing rice varieties with salt tolerance (ST) is one of the most economical approaches to cope with salinity stress. However, the valuable resources for rice breeding towards ST remain to be identified. In this study, the salt tolerance of 220 rice accessions from RDP1, representing five subpopulations, were evaluated at both seedling and reproductive stages. Results An apparent inconsistency was found for ST between the two stages. Through a gene-based / tightly linked genome-wide association study, a total of 214 single nucleotide polymorphisms (SNPs) related to 251 genes, significantly associated with 16 ST-related indices, were detected at both stages. Eighty-two SNPs with low frequency favorable (LFF) alleles in the population were proposed to hold high breeding potential in improving rice ST. Fifty-four rice accessions collectively containing all these LFF alleles were identified as donors of these alleles. Through the integration of meta-QTL for ST and the response patterns of differential expression genes to salt stress, thirty-one candidate genes were suggested to be involved in the regulation of rice ST. Conclusions In total, the present study provides valuable information for further characterizing ST-related genes and for breeding ST varieties across whole developmental stages through marker-assisted selection (MAS).

ObjectivesTo clarify non-alcoholic fatty liver disease (NAFLD) prevalence, risk factors and clinical outcome in an exemplary Chinese population, a cohort of company employees was followed up for 11 years.DesignRetrospective cohort study.SettingBetween 2006 and 2016 in Ning bo, China.Participants13 032 company employees.ResultsOver 11 years, the prevalence of NAFLD increased from 17.2% to 32.4% (men 20.5%–37% vs women 9.8%–22.2%). Male peak prevalence was between 40 and 60 years of age, whereas highest prevalence in women was at an age of 60 years and older. Logistic and Cox regression revealed 16 risk factors, including body mass index (BMI), albumin, white blood cell, triglycerides (TG), high-density lipoprotein, glutamyl transpeptidase, alanine transaminase, creatinine, urea acid, glucose, systolic blood pressure, diastolic blood pressure, blood sedimentation, haemoglobin, platelet and apolipoprotein B2 (pConclusionDiabetes, hypertension and hyperuricaemia are the main clinical outcomes of NAFLD. Eleven years of NAFLD are not sufficient to cause severe liver disease. Age and obesity are direct risk factors for NAFLD. BMI, gender and TG are three parameters directly reflecting the occurrence of NAFLD.

To overcome the limitations of narrow light-response range and rapid electron–hole recombination in the TiO2 photocatalytic treatment of dye wastewater, we prepared and systematically studied the Bi-doped TiO2/montmorillonite composite using the sol–gel method. Results showed that Bi enters the crystal lattice of anatase TiO2 in the +3 valence state. The highest photocatalytic activity was achieved when the molar ratio of Bi:Ti was 7%. During the photocatalytic treatment, the degradation extent of rhodamine B reached 90.60% under visible-light irradiation. This high photocatalytic activity results from the doping with Bi3+ ions, which makes the band gap lie between the Ti4+ 3d and Bi3+ 6s bands and inhibits the recombination of electrons and holes.

Compared with traditional single-beam side-scan sonar device, current side-scan sonar have greatly improved the stability, resolution and definition of sonar image, which leads to a large increase in the amount of data, so it is impossible to completely identify target artificially. During the side-scanning sonar operation, sonar equipment is affected by ocean currents, wind waves, etc., resulting in posture instability and image distortion. The complex underwater environment and the interference of its own will also cause a lot of noise in the collected sonar image. The problems above have brought great difficulties for target recognition. This paper utilizes LeNet5 convolutional neural network (CNN) to perform automatic rough recognition of side-scan sonar images, and then uses scale-invariant feature transform (SIFT) feature matching for further recognition. The processing of experimental data shows that the accuracy and efficiency of target recognition are good using these two algorithms.

The paper presents an historical perspective on the design, construction, failure and rehabilitation of the west breakwater of the Portuguese harbour of Sines, as well as on the overtopping physical model studies performed to check the effectiveness of the different proposed solutions for its rehabilitation. Studies are now being conducted for Sines Port Authority for the final rehabilitation of the breakwater, with the primary objective of reactivating berth 1 but also to generally improve the shelter and operating conditions within the port. The paper presents the three proposed solutions for the west breakwater and their two-dimensional physical model tests of stability and overtopping carried out in 2008 at Laboratório Nacional de Engenharia Civil (LNEC), Portugal. The paper also illustrates the application of a new version of the non-linear shallow water numerical model, Amazon, and of the methodologies recommended in the EurOtop overtopping manual to study the mean overtopping discharge over the breakwater. The Clash neural network was the only tool applicable to the three proposed solutions, although it tended to underpredict the physical model discharges, mainly for the selected solution 3. There was good agreement between the physical model data and the Amazon results for solutions 1 and 2, although Amazon tended to slightly overpredict the discharges, especially for solution 2. The empirical methods overpredicted these discharges to a great extent, warning of the fact that direct application of these methods is limited to particular structural configurations and wave conditions.

This paper compares the output from four methods used to predict the mean overtopping discharge at the root of the South Breakwater of Povoa de Varzim Harbour (Portugal): two numerical models AMAZON, based on solving the nonlinear shallow-water equations, and COBRAS-UC, based on the Reynolds averaged Navier–Stokes equations, Pedersen’s empirical formula, and the neural network tool NN_Overtopping. Output from the methods is considered alongside data from two-dimensional (2D) physical model tests. The results show that rather accurate predictions can be obtained with COBRAS-UC. Agreement between the data and the AMAZON output depends principally on the impact of porosity on overtopping: agreement is very good when the impact is limited (for high overtopping discharges) and it worsens as porosity plays a more important role (for small discharges). NN_Overtopping estimates the mean discharges with a degree of accuracy similar to AMAZON. Pedersen’s results are those which deviate more from the data, substanti...

Output is compared from four methods used to estimate the overtopping rate at seawalls subject to random wave action: two empirical models, a semiempirical model, and a numerical model. The empirical models were developed by fitting dimensionless groups to data derived from physical model tests. The semiempirical model was derived from consideration of the unsteady flow of water over a weir. However, like the empirical models, it was calibrated with the results of physical model tests. In contrast, the numerical model AMAZON is a high-resolution two-dimensional finite volume model based on the nonlinear shallow-water equations. In this study, we calculated the mean overtopping discharge for a range of seawalls with front slopes from 1 : 1 to 1 : 20 and for incident wave steepnesses from 0.01 to 0.03. The results are considered alongside four sets of data from physical model tests. They show general agreement between the output from the numerical and semiempirical models and the data. Agreement wi...

A one-dimensional high-resolution finite volume model capable of simulating storm waves propagating in the coastal surf zone and overtopping a sea wall is presented. The model (AMAZON) is based on solving the non-linear shallow water (NLSW) equations. A modern upwind scheme of the Godunov-type using an HLL approximate Riemann solver is described which captures bore waves in both transcritical and supercritical flows. By employing a finite volume formulation, the method can be implemented on an irregular, structured, boundary-fitted computational mesh. The use of the NLSW equations to model wave overtopping is computationally efficient and practically flexible, though the detailed structure of wave breaking is of course ignored. It is shown that wave overtopping at a vertical wall may also be approximately modelled by representing the wall as a steep bed slope. The AMAZON model solutions have been compared with analytical solutions and laboratory data for wave overtopping at sloping and vertical seawalls and good agreement has been found. The model requires more verification tests for irregular waves before its application as a generic design tool.

This paper reviews the current practice of coastal flood forecasting and warning in England and Wales. The basis of the coastal flood forecasting and warning and recent advances in relevant numerical modelling technology are reviewed and explained. The paper discusses the benefits and opportunities these new technologies can bring and the practical problems, dilemmas and challenges that the service providers and consultants face at present and in the future

new mesh-patching model is presented for shallow water flow described by the 2D non-linear shallow water (NLSW) equations. The mesh-patching model is based on AMAZON, a high-resolution NLSW engine with an improved HLLC approximate Riemann solver. A new patching algorithm has been developed, which not only provides improved spatial resolution of flow features in particular parts of the mesh, but also simplifies and speeds up the (structured) grid generation process for an area with complicated geometry. The new patching technique is also compatible with increasingly popular parallel computing and adaptive grid techniques. The patching algorithm has been tested with moving bores, and results of test problems are presented and compared to previous work.

Developments in computational modelling of storm waves propagating in the coastal surf zone and overtopping at sea walls and related structures is reported. The AMAZON suite of 1D and 2D Plan shallow water models are used for the calculations. The models employ a modern Riemann-based upwind scheme in a finite volume form for use on boundary-conforming meshes. Sea wall structures are approximately represented using a steep bed slope. Breaking waves are modelled as steep moving fronts represented by bore waves. Comparisons with measured data show good agreement for sloping sea walls. Results are presented for the effects of wave obliquity on overtopping discharges including cases involving Mach stem formation. For vertical and recurved sea walls, an accurate model of wave breaking is required.

A high-resolution finite volume hydrodynamic solver is presented for open-channel flows based on the 2D shallow water equations. This Godunov-type upwind scheme uses an efficient Harten-Lax-van Leer (HLL) approximate Riemann solver capable of capturing bore waves and simulating supercritical flows. Second-order accuracy is achieved by means of MUSCL reconstruction in conjunction with a Hancock two-stage scheme for the time integration. By using a finite volume approach, the computational grid can be irregular which allows for easy boundary fitting. The method can be applied directly to model 1D flows in an open channel with a rectangular cross-section without the need to modify the scheme. Such a modification is normally required for solving the 1D St Venant equations to take account of the variation of channel width. The numerical scheme and results of three test problems are presented in this paper.